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Former investment bank FX trader: Risk management part II

Former investment bank FX trader: Risk management part II
Firstly, thanks for the overwhelming comments and feedback. Genuinely really appreciated. I am pleased 500+ of you find it useful.
If you didn't read the first post you can do so here: risk management part I. You'll need to do so in order to make sense of the topic.
As ever please comment/reply below with questions or feedback and I'll do my best to get back to you.
Part II
  • Letting stops breathe
  • When to change a stop
  • Entering and exiting winning positions
  • Risk:reward ratios
  • Risk-adjusted returns

Letting stops breathe

We talked earlier about giving a position enough room to breathe so it is not stopped out in day-to-day noise.
Let’s consider the chart below and imagine you had a trailing stop. It would be super painful to miss out on the wider move just because you left a stop that was too tight.

Imagine being long and stopped out on a meaningless retracement ... ouch!
One simple technique is simply to look at your chosen chart - let’s say daily bars. And then look at previous trends and use the measuring tool. Those generally look something like this and then you just click and drag to measure.
For example if we wanted to bet on a downtrend on the chart above we might look at the biggest retracement on the previous uptrend. That max drawdown was about 100 pips or just under 1%. So you’d want your stop to be able to withstand at least that.
If market conditions have changed - for example if CVIX has risen - and daily ranges are now higher you should incorporate that. If you know a big event is coming up you might think about that, too. The human brain is a remarkable tool and the power of the eye-ball method is not to be dismissed. This is how most discretionary traders do it.
There are also more analytical approaches.
Some look at the Average True Range (ATR). This attempts to capture the volatility of a pair, typically averaged over a number of sessions. It looks at three separate measures and takes the largest reading. Think of this as a moving average of how much a pair moves.
For example, below shows the daily move in EURUSD was around 60 pips before spiking to 140 pips in March. Conditions were clearly far more volatile in March. Accordingly, you would need to leave your stop further away in March and take a correspondingly smaller position size.

ATR is available on pretty much all charting systems
Professional traders tend to use standard deviation as a measure of volatility instead of ATR. There are advantages and disadvantages to both. Averages are useful but can be misleading when regimes switch (see above chart).
Once you have chosen a measure of volatility, stop distance can then be back-tested and optimised. For example does 2x ATR work best or 5x ATR for a given style and time horizon?
Discretionary traders may still eye-ball the ATR or standard deviation to get a feeling for how it has changed over time and what ‘normal’ feels like for a chosen study period - daily, weekly, monthly etc.

Reasons to change a stop

As a general rule you should be disciplined and not change your stops. Remember - losers average losers. This is really hard at first and we’re going to look at that in more detail later.
There are some good reasons to modify stops but they are rare.
One reason is if another risk management process demands you stop trading and close positions. We’ll look at this later. In that case just close out your positions at market and take the loss/gains as they are.
Another is event risk. If you have some big upcoming data like Non Farm Payrolls that you know can move the market +/- 150 pips and you have no edge going into the release then many traders will take off or scale down their positions. They’ll go back into the positions when the data is out and the market has quietened down after fifteen minutes or so. This is a matter of some debate - many traders consider it a coin toss and argue you win some and lose some and it all averages out.
Trailing stops can also be used to ‘lock in’ profits. We looked at those before. As the trade moves in your favour (say up if you are long) the stop loss ratchets with it. This means you may well end up ‘stopping out’ at a profit - as per the below example.

The mighty trailing stop loss order
It is perfectly reasonable to have your stop loss move in the direction of PNL. This is not exposing you to more risk than you originally were comfortable with. It is taking less and less risk as the trade moves in your favour. Trend-followers in particular love trailing stops.
One final question traders ask is what they should do if they get stopped out but still like the trade. Should they try the same trade again a day later for the same reasons? Nope. Look for a different trade rather than getting emotionally wed to the original idea.
Let’s say a particular stock looked cheap based on valuation metrics yesterday, you bought, it went down and you got stopped out. Well, it is going to look even better on those same metrics today. Maybe the market just doesn’t respect value at the moment and is driven by momentum. Wait it out.
Otherwise, why even have a stop in the first place?

Entering and exiting winning positions

Take profits are the opposite of stop losses. They are also resting orders, left with the broker, to automatically close your position if it reaches a certain price.
Imagine I’m long EURUSD at 1.1250. If it hits a previous high of 1.1400 (150 pips higher) I will leave a sell order to take profit and close the position.
The rookie mistake on take profits is to take profit too early. One should start from the assumption that you will win on no more than half of your trades. Therefore you will need to ensure that you win more on the ones that work than you lose on those that don’t.

Sad to say but incredibly common: retail traders often take profits way too early
This is going to be the exact opposite of what your emotions want you to do. We are going to look at that in the Psychology of Trading chapter.
Remember: let winners run. Just like stops you need to know in advance the level where you will close out at a profit. Then let the trade happen. Don’t override yourself and let emotions force you to take a small profit. A classic mistake to avoid.
The trader puts on a trade and it almost stops out before rebounding. As soon as it is slightly in the money they spook and cut out, instead of letting it run to their original take profit. Do not do this.

Entering positions with limit orders

That covers exiting a position but how about getting into one?
Take profits can also be left speculatively to enter a position. Sometimes referred to as “bids” (buy orders) or “offers” (sell orders). Imagine the price is 1.1250 and the recent low is 1.1205.
You might wish to leave a bid around 1.2010 to enter a long position, if the market reaches that price. This way you don’t need to sit at the computer and wait.
Again, typically traders will use tech analysis to identify attractive levels. Again - other traders will cluster with your orders. Just like the stop loss we need to bake that in.
So this time if we know everyone is going to buy around the recent low of 1.1205 we might leave the take profit bit a little bit above there at 1.1210 to ensure it gets done. Sure it costs 5 more pips but how mad would you be if the low was 1.1207 and then it rallied a hundred points and you didn’t have the trade on?!
There are two more methods that traders often use for entering a position.
Scaling in is one such technique. Let’s imagine that you think we are in a long-term bulltrend for AUDUSD but experiencing a brief retracement. You want to take a total position of 500,000 AUD and don’t have a strong view on the current price action.
You might therefore leave a series of five bids of 100,000. As the price moves lower each one gets hit. The nice thing about scaling in is it reduces pressure on you to pick the perfect level. Of course the risk is that not all your orders get hit before the price moves higher and you have to trade at-market.
Pyramiding is the second technique. Pyramiding is for take profits what a trailing stop loss is to regular stops. It is especially common for momentum traders.

Pyramiding into a position means buying more as it goes in your favour
Again let’s imagine we’re bullish AUDUSD and want to take a position of 500,000 AUD.
Here we add 100,000 when our first signal is reached. Then we add subsequent clips of 100,000 when the trade moves in our favour. We are waiting for confirmation that the move is correct.
Obviously this is quite nice as we humans love trading when it goes in our direction. However, the drawback is obvious: we haven’t had the full amount of risk on from the start of the trend.
You can see the attractions and drawbacks of both approaches. It is best to experiment and choose techniques that work for your own personal psychology as these will be the easiest for you to stick with and build a disciplined process around.

Risk:reward and win ratios

Be extremely skeptical of people who claim to win on 80% of trades. Most traders will win on roughly 50% of trades and lose on 50% of trades. This is why risk management is so important!
Once you start keeping a trading journal you’ll be able to see how the win/loss ratio looks for you. Until then, assume you’re typical and that every other trade will lose money.
If that is the case then you need to be sure you make more on the wins than you lose on the losses. You can see the effect of this below.

A combination of win % and risk:reward ratio determine if you are profitable
A typical rule of thumb is that a ratio of 1:3 works well for most traders.
That is, if you are prepared to risk 100 pips on your stop you should be setting a take profit at a level that would return you 300 pips.
One needn’t be religious about these numbers - 11 pips and 28 pips would be perfectly fine - but they are a guideline.
Again - you should still use technical analysis to find meaningful chart levels for both the stop and take profit. Don’t just blindly take your stop distance and do 3x the pips on the other side as your take profit. Use the ratio to set approximate targets and then look for a relevant resistance or support level in that kind of region.

Risk-adjusted returns

Not all returns are equal. Suppose you are examining the track record of two traders. Now, both have produced a return of 14% over the year. Not bad!
The first trader, however, made hundreds of small bets throughout the year and his cumulative PNL looked like the left image below.
The second trader made just one bet — he sold CADJPY at the start of the year — and his PNL looked like the right image below with lots of large drawdowns and volatility.
Would you rather have the first trading record or the second?
If you were investing money and betting on who would do well next year which would you choose? Of course all sensible people would choose the first trader. Yet if you look only at returns one cannot distinguish between the two. Both are up 14% at that point in time. This is where the Sharpe ratio helps .
A high Sharpe ratio indicates that a portfolio has better risk-adjusted performance. One cannot sensibly compare returns without considering the risk taken to earn that return.
If I can earn 80% of the return of another investor at only 50% of the risk then a rational investor should simply leverage me at 2x and enjoy 160% of the return at the same level of risk.
This is very important in the context of Execution Advisor algorithms (EAs) that are popular in the retail community. You must evaluate historic performance by its risk-adjusted return — not just the nominal return. Incidentally look at the Sharpe ratio of ones that have been live for a year or more ...
Otherwise an EA developer could produce two EAs: the first simply buys at 1000:1 leverage on January 1st ; and the second sells in the same manner. At the end of the year, one of them will be discarded and the other will look incredible. Its risk-adjusted return, however, would be abysmal and the odds of repeated success are similarly poor.

Sharpe ratio

The Sharpe ratio works like this:
  • It takes the average returns of your strategy;
  • It deducts from these the risk-free rate of return i.e. the rate anyone could have got by investing in US government bonds with very little risk;
  • It then divides this total return by its own volatility - the more smooth the return the higher and better the Sharpe, the more volatile the lower and worse the Sharpe.
For example, say the return last year was 15% with a volatility of 10% and US bonds are trading at 2%. That gives (15-2)/10 or a Sharpe ratio of 1.3. As a rule of thumb a Sharpe ratio of above 0.5 would be considered decent for a discretionary retail trader. Above 1 is excellent.
You don’t really need to know how to calculate Sharpe ratios. Good trading software will do this for you. It will either be available in the system by default or you can add a plug-in.

VAR

VAR is another useful measure to help with drawdowns. It stands for Value at Risk. Normally people will use 99% VAR (conservative) or 95% VAR (aggressive). Let’s say you’re long EURUSD and using 95% VAR. The system will look at the historic movement of EURUSD. It might spit out a number of -1.2%.

A 5% VAR of -1.2% tells you you should expect to lose 1.2% on 5% of days, whilst 95% of days should be better than that
This means it is expected that on 5 days out of 100 (hence the 95%) the portfolio will lose 1.2% or more. This can help you manage your capital by taking appropriately sized positions. Typically you would look at VAR across your portfolio of trades rather than trade by trade.
Sharpe ratios and VAR don’t give you the whole picture, though. Legendary fund manager, Howard Marks of Oaktree, notes that, while tools like VAR and Sharpe ratios are helpful and absolutely necessary, the best investors will also overlay their own judgment.
Investors can calculate risk metrics like VaR and Sharpe ratios (we use them at Oaktree; they’re the best tools we have), but they shouldn’t put too much faith in them. The bottom line for me is that risk management should be the responsibility of every participant in the investment process, applying experience, judgment and knowledge of the underlying investments.Howard Marks of Oaktree Capital
What he’s saying is don’t misplace your common sense. Do use these tools as they are helpful. However, you cannot fully rely on them. Both assume a normal distribution of returns. Whereas in real life you get “black swans” - events that should supposedly happen only once every thousand years but which actually seem to happen fairly often.
These outlier events are often referred to as “tail risk”. Don’t make the mistake of saying “well, the model said…” - overlay what the model is telling you with your own common sense and good judgment.

Coming up in part III

Available here
Squeezes and other risks
Market positioning
Bet correlation
Crap trades, timeouts and monthly limits

***
Disclaimer:This content is not investment advice and you should not place any reliance on it. The views expressed are the author's own and should not be attributed to any other person, including their employer.
submitted by getmrmarket to Forex [link] [comments]

I used to trade only FOREX. I have since diversified into cryptocurrency for a less stressful approach. Anyone here interested in learning how to trade cryptocurrency and what steps you need to take?

As the title says, I used to only trade on FOREX. I have since diversified into cryptocurrency because FOREX was so stressful for me and I needed to have something that was a bit less news-job-report intensive to level it all out. You can't get away from charts and candles in crypto, but I feel like there are more long-term hold opportunities in the crypto space and I feel like longer-term investments are less stressful for me. I know this isn't 100% FOREX related, but since I do trade on FOREX, I feel like it has relevance in terms of the ways the spaces are similar.
First, the reasons I diversified. The main one that frustrates me is I feel like the cards are stacked against me in ways I have no control over. Exchanges can sell information about customer buy and sell points to bigger fish than me. The whales have way more information about what the public is doing than I do. Next, trading firms have access to news much faster than me. They can process announcements in microseconds. And lastly, countries do crazy things with their currencies and I just wasn't great at interpreting all the signs. I don't like my fortunes being tied to job reports and the decisions of a treasury secretary that doesn't take any input from me.
The above reasons pushed me to start trading longer term in FOREX. That's fine, there are plenty of long-term strategies that work. Most people will tell you that longer-term is safer, and so the shift didn't bug me that much. But over time, I felt like there were more currencies I was missing out on, so I started adding cryptocurrency into my portfolio.
For those of you that don't know much about cryptocurrency, it's basically a currency that is not controlled by any one person or government (or shouldn't be). It's money free from political corruption, free from bailouts, and free from big banks. It is also highly more volatile than FOREX. Gains and losses are measured in the 10% or 20% range per day. There's actually lots of money to be made day trading it, just like FOREX. But I chose to take a longer term approach for my peace of mind.
One of the things that I looked for when trading FOREX was to trade pairs where I could earn interest while holding it. Then when the pair appreciated, I could sell it for a gain plus the interest. Win win.
Right now, I feel like I found that in ADA (Cardano) crypto. ADA just opened staking (mining) capability last week, meaning that just by holding it you can earn 4.5%-5.5% on your coins (paid in coins, not in dollars). It's the most undervalued crypto in the market (in my opinion), and the fundamentals on it look really strong. It is doing everything I was hoping a FOREX pair would do and I think it's the best crypto investment right now, so I'm just filing it away as a 5-year investment. It's now 50% of my "overall" currency investments, including FOREX.
Anyway, that's my story. I wanted to share it in case anyone here was curious about Cardano in particular, and how it related to fiat currencies. I was super intimidated about crypto at first, but I am also a software developer with a lot of experience, and so I was able to make the transition quite well. I even started my own mining pool to earn more.
submitted by WiddleWhiskers to Forex [link] [comments]

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submitted by ViralMedia007 to FREECoursesEveryday [link] [comments]

Seeking advice on platforms (or not) for integrated Algo development.

Starting at ground-zero as an Algo Trading developer, I am hoping for some advice on platforms for operationalizing strategies—i.e. would like to ultimately only build things 2 to 3 times before actually getting a clue of what I should have done to begin with. ; )
I have 20+ years of professional software development experience, mainly writing backend services in Perl, Java, Python, JavaScript or Go. Finance was my Major as an Undergrad. Instruments of interest are Options, Futures and maybe Forex.
First question; should I even seriously choose an integrated environment, or—like everything else I do for a paycheck—build something from 'scratch' because of bad fills or high commissions? Normally, for a question like this, in some order, I'll do exhaustive feature comparisons, correspond/talk with vendors, kick some tires and talk to peers to make sure nothing has been missed, however, nobody I know has ever done anything like what people here are doing or trying to do, so...
Has anyone had experience with Quantower? Quantower looks impressive and allows for writing strategies in C#.
Noted also that cTrader Automate (formerly known as cAlgo), MultiCharts .NET and NinjaTrader (via NinjaScript) also have integrated C# or C#-ish software language strategy development and IB allows C# as well as other languages via the Trader Workstation API.
C# seems like a good choice (nowish) for the sake of portability as it looks like more platforms run on Windows than Mac or Linux and most support integrated strategy development using the C or C++ or C# languages, or scripts based thereon.
People mention a lot of interest in using R and Python, two languages I like, though their support for integrated strategy development seems to be only slowly catching up to the other languages. Is this accurate?
submitted by whimpy_dalek to algotrading [link] [comments]

Has anyone tried Forex robot trading?

What Is a Forex Robot?
These days, it is becoming more and more common for traders to utilize modern methods of technology in their trading and there are many advantages to doing so.
Traders are increasingly likely to use trading systems or software that allows them to automate the trading process — thus reducing the problems of emotional attachment to a trade or a lack of trading discipline. A Forex robot does exactly that and one of the most popular ways to use one is via the MetaTrader 4 platform.
The MetaTrader 4 platform offers a complete solution to a trader’s needs, consisting of charts, news feeds, and more. And, by coding in the native MQL4 programming language, it is also possible to write custom built indicators or even trading strategies — also known as expert advisors.
Free Ex4 to Mq4 decompiler!! Top EA List: https://best-forex-trading-robots.com/
Expert Advisors
An expert advisor (EA) is another name for a Forex robot, one that has been developed to be used on the MetaTrader 4 platform. Since it can be custom built, an expert advisor can be designed to implement any trading strategy or risk management system so long as the designer knows how to code it into the program.
For example, a trader may design an EA to open positions in the market at a certain size after a moving average crossover.
Has anyone tried Forex robot trading? Best-forex-robots
Benefits
The main advantage of using a Forex robot is that it takes the emotion out of trading, which if not addressed, can be a big barrier to many traders. Fear, greed, and stress can build up in manual trading all too easily, leading a trader to lose money and get frustrated with the game.
A robot on the other hand, will implement the chosen strategy flawlessly every time and with a high degree of accuracy. It will also make difficult risk management calculations in the blink of an eye, much faster than a human trader. Not only that, but robots can be designed to trade around the clock and on different markets at once, meaning that you need not have to sit in front of your screen all day and all night.
In short, a Forex robot can take much of the hard work out of trading — that hard work is done beforehand — developing and testing the trading idea.
Limitations
Of course, there are no shortcuts to making money on the Forex markets and working with a Forex robot brings with it its own inherent limitations.
For one thing, Forex markets are fiercely competitive and coming up with a robot that is able to beat the market is a notoriously difficult thing to do.
Indeed, it is not enough to design a robot that works over a couple of weeks data, the robot must work over several months, if not years, of historical data and undergo rigorous statistical testing to prove that it works. Because if a trader cannot be confident that the robot works, they will more than likely abandon it when times get tough.
submitted by Rongpure1 to u/Rongpure1 [link] [comments]

Acute Growth of Algorithm Trading Market Opportunity Assessments 2019-2023

Acute Growth of Algorithm Trading Market Opportunity Assessments 2019-2023
Algorithm Trading Market
Research report comes up with the size of the global Algorithm Trading Market for the base year 2019 and the forecast between 2019 and 2023. Market value has been estimated considering the application and regional segments, market share, and size, while the forecast for each product type and application segment has been provided for the global and local markets.
The Algorithm Trading report offers detailed profiles of the key players to bring out a clear view of the competitive landscape of the Algorithm Trading Outlook. It also comprehends market new product analysis, financial overview, strategies and marketing trends.
Major Manufacturer Detail: Thomson Reuters, 63 moons, InfoReach, Argo SE, MetaQuotes Software, Automated Trading SoftTech, Tethys, Trading Technologies, Tata Consulting Services, Vela, Virtu Financial, Symphony Fintech, Kuberre Systems, iRageCapital, QuantCore Capital Management
Get a Free PDF Sample Copy! Click Here: https://www.acquiremarketresearch.com/sample-request/205792/
The report reckons a complete view of the world Algorithm Trading market by classifying it in terms of application and region. These segments are examined by current and future trends. Regional segmentation incorporates current and future demand for them in North America, Asia Pacific, Europe, and the Middle East. The report collectively covers specific application segments of the market in each region.
Types of Algorithm Trading covered are: Forex Algorithm Trading, Stock Algorithm Trading, Fund Algorithm Trading, Bond Algorithm Trading, Cryptographic Algorithm Trading
Applications of Algorithm Trading covered are: large Enterprise, SME
Use Corporate ID to avail Discount on this Algorithm Trading Market Report report: https://www.acquiremarketresearch.com/discount-request/205792/
Regional Analysis For Algorithm Trading Market
North America (The United States, Canada, and Mexico) Europe (Germany, France, UK, Russia, and Italy) Asia-Pacific (China, Japan, Korea, India, and Southeast Asia) South America (Brazil, Argentina, Colombia, etc.) The Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria, and South Africa)
Table of Contents:
Study Coverage: It includes key manufacturers covered, key market segments, the scope of products offered in the global Algorithm Trading market, years considered, and study objectives. Additionally, it touches the segmentation study provided in the report on the basis of the type of product and application. Executive summary: It gives a summary of key studies, market growth rate, competitive landscape, market drivers, trends, and issues, and macroscopic indicators. Production by Region: Here, the report provides information related to import and export, production, revenue, and key players of all regional markets studied. Profile of Manufacturers: Each player profiled in this section is studied on the basis of SWOT analysis, their products, production, value, capacity, and other vital factors.
Reasons to buy:
• In-depth analysis of the market on the global and regional level. • Major changes in market dynamics and competitive landscape. • Segmentation on the basis of type, application, geography, and others. • Historical and future market research in terms of size, share, growth, volume & sales. • Major changes and assessment in market dynamics & developments. • Industry size & share analysis with industry growth and trends. • Emerging key segments and regions. • Key business strategies by major market players and their key methods. • The research report covers size, share, trends and growth analysis of the Algorithm Trading Market on the global and regional level.
Get Full Report Description, TOC, Table of Figures, Chart, etc. @ https://www.acquiremarketresearch.com/industry-reports/algorithm-trading-market/205792/
In conclusion, the Algorithm Trading Market report is a reliable source for accessing the Market data that will exponentially accelerate your business. The report provides the principle locale, economic scenarios with the item value, benefit, supply, limit, generation, request, Market development rate, and figure and so on. Besides, the report presents a new task SWOT analysis, speculation attainability investigation, and venture return investigation.
submitted by hannah_jack to TechInsightreports [link] [comments]

trading of all kinds with no charts

Hi, community: I am trying to determine if someone is able to trade and make profit with no charts or visuals at all: first, because I am myself legally blind and I traded forex and other instruments -intraday mostly- and I make profit, however my results are inconsistent. the second reason, I'd like to help others if I could stablish some guidelines to start with, ib it's a possibility. I'd like to hear your opinions: do you think it's possible? If so, what strategies or trading stiles you thing could work better? What instruments etc? Any thoughts are welcome. Any tip would be appreciated, even identifying the difficulties is a starting point for developing tools, software or anything useful. Thanks for your time and excuse my english. ,
submitted by AlanSoulchild to Trading [link] [comments]

Crypto exchange trade. Remember psychology!

https://medium.com/@sergiygolubyev/crypto-exchange-trade-remember-psychology-6d4433569d9d
Crypto Exchange is a high-tech platform in which all trade transactions are conducted using modern software created based on the latest IT solutions. The emergence of new types of currencies, in particular cryptocurrencies, gives a chance for the rapid development of the world economy as a whole. In turn, structural changes in the international economic system gave impetus to the emergence and development of new types of exchange technologies. Thus, crypto exchanges appeared which allowed its participants anywhere in the world to buy, sell and exchange one cryptocurrency for others, or for fiat of other countries. Each crypto exchange tries to offer customers convenient ways to convert financial instruments, and provides the ability to conduct transactions on its own terms. The high rates of development and distribution of cryptocurrencies, which are based on Blockchain, as well as the gradual wide recognition by the world community and leading economists, ensure the further improvement of exchange technologies. This means that in an effort to provide the most comfortable conditions for its customers, each crypto exchange will take them to an ever-higher quality level of service with innovative nuances. But at the same time, within the framework of the technological process of stock trading, which is available to users (from professional traders to amateurs), the question of psychology and its role in the decision making has not been canceled. Successful trading depends on 70% primarily on the psychology of a trader and only 30% on the trading scheme/strategy.
Trading on the exchange, it is necessary to develop discipline, self-control and be able to respond quickly to changing stock charts. All this will allow you to earn and minimize your losses more effectively. Everyone should remember, from the amateur to the professional, that in the financial markets you can not only earn money, but also lose money. Cryptocurrency rates are still subject to political and regulatory influences; their value is influenced by the reputation of the company's founders, informational insertions about blockchain projects and plans for their further development, scandals and disclosures. Nevertheless, there are simple rules for successful trading from the field of psychology, which will reduce the risks when trying to make money on cryptocurrency and not only. There are a number of problems that always hinder every beginner - amateur:
· Excitement
· Fear
· Greed
· Unwillingness to learn new things
· Imaginary visualization of results
All these problems have psychological aspects. Emotions, feelings and desires significantly influence the trading decisions made by the trader. This happens all the time, not only on traditional exchanges, but also in the cryptocurrency sphere as well. Excitement is an emotional state when it seems to a person that he is lucky, and as the series of successful transactions continues, he performs larger by volume financial transactions. Often, the excitement motivates to turn away from long-term transactions and trends, and look towards short-term operations. After all, it seems that the more often you successfully complete operations, the more capital you earn. Not at all! The more often you make mistakes, leading to a default on your account. Money only is earned on long-term trends and operations. Traders are often worried, fearing an unsuccessful deal closing.
Of course, a loss is bad, but sometimes it is better to close a position in minus than to lose a large amount only because of the hope of a quick price reversal. Therefore, fear often pushes for the wrong strategic decisions. Fear of loss as a result becomes a sentence for your positioning in profit. On the same face with fear, if not strange, is the factor of greed. Having essentially a different source of inspiration, greed, like fear, leads to a generally pitiable result — to the default of your trading account. The reluctance to learn new strategies, technologies, and denial of forecasting also leads to failure. Successful is who always strives to learn new things, and perceives the fact and necessity of continuous learning. Since learning is a process of striving for the progress of its results and professional qualities. Another scourge - Wish list or visualization. Everyone wants to see the price move in the right direction. This is pretty dangerous. By visualizing the price jump in the right direction, you can dream and invest too much in cryptocurrency. This will lead to losses. Here you should always remember to diversify your investments. Remember your psychological portrait even when you program your trading strategies, algorithms and bots. After all, your algorithm is essentially your psychological portrait. Finally, the above-mentioned flaws, especially in the strategy can dominate and damage your deposit and reputation. The main signs of competent crypto-trade are the same as on other exchanges (such as FOREX). This is a kind of algorithm for a sustainable profit strategy:
· Risk no more than 10% of the deposit
· Use risk per trade of 5% or less
· Do not close profitable deals too early
· Do not accumulate losing trades
· Fix quick speculative profit
· Respect the trend
· Pay more attention to liquid assets (cryptocurrency)
· Set your personal entry and exit rules for trades and stick to them
· Long-term trading strategy gives you maximum steady profits
· Do not use the principles of Martingale tactics if there is no experience. You cannot double the volume of the transaction, if it closed in the red zone. If a loss was incurred, then the cryptocurrency market situation was predicted incorrectly and it was necessary to work on improving the analytical skills, and not to conclude a larger deal, which probably also closes in the negative
It is obvious that the psychology of trading significantly affects the performance of stock speculation both in the traditional market and in the field of cryptocurrency. It is important to remember that the success of a person in any field of activity depends on the emotional component, namely the internal balance. Exchange trading is a nervous activity, and if you do not learn to take emotions under control, the results can be disastrous. The basis for achieving success in stock trading, in my opinion, are two fundamental factors. The first factor relates to the field of formulation of the trading idea, and the second - to the area of ​​its implementation.
To formulate a trading idea, on the one hand, methods of technical and fundamental analysis are used to select an exchange instrument and determine the moment of opening and closing a position on it. On the other hand, capital management methods are used to determine the optimal size of the position being opened. As you know, without these two crucial moments it is impossible to achieve stable success in stock trading. As experience shows, for the most part, people have enough intelligence to master all the necessary theoretical knowledge of technical and fundamental analysis in a few months of intensive training. There are no special intellectual difficulties. But, as the same experience shows, this is clearly not enough for successful exchange trading, since all knowledge may turn out to be a useless load if the second success factor is not sufficiently present - the practical implementation of trading ideas, which is no longer based on the intellectual sphere, and psycho-emotional. It is within this area that the main problem arises for many traders, which prevents the receipt of stable profits. As a rule, this is due to the psycho-emotional profile of a person. It depends on how the trader will behave in the psychologically stressful situations that the exchange trading is full of. Inherent in all human emotions and feelings - fear, greed, excitement, envy, hope, etc. very often have a decisive influence on the behavior of traders, not allowing them to follow strictly the trading strategy and plan, even if they have one. From a psychological point of view, the process of stock exchange activity can be divided into stages, after which the trader can return to the starting point. The above scenarios and risk factors are one of the options for the behavior of an exchange speculator; however, it often happens exactly the opposite. Having suffered losses from his first transactions in the market, the trader loses interest in exchange trading, he gives up and he falls into despair. In this case, the first step to victory is the admission of defeat. It would seem silly and ridiculous, but it works. After that, there are two options: either the trader leaves the exchange forever, or returns to the battlefield. Such “returns” may occur more than once. In addition, at some other time, after repeated analysis of his actions, mistakes made and their consequences, a person from a beginner begins to turn into an experienced trader, which is marked by the stability of his activity and, perhaps, by slow, but surely growth of his deposit and profit. The psychological basis for success in trading, which leads to victory and the absence of which is equivalent to defeat, are as follows:
· It is not only the lack of self-control, discipline and focus on the process that causes the defeat
· Self-control, discipline and ability to concentrate is not enough to achieve success
· To achieve success, it is equally important to be able to adapt to changes
In principle, one can consider the idea that traditional approaches to the psychology of trading are limited. In the majority of benefits for traders, the key qualities necessary for successful exchange trading are only self-control and discipline. Of course, these qualities are necessary in any field of business activities. Trading is not an exception, especially considering that it is in the risk zone. But self-control and discipline are not enough to achieve success. Trading is a business. Moreover, any business does not stand still. You cannot find a formula for success and use it forever. You will need to monitor trends and constantly look for new successful solutions.
The main feature of a successful trader is adaptability to changes. The lack of development leads to defeat, large monetary losses. Many technology companies continued to produce stationary computers when laptops became popular. The same companies continued to produce laptops when tablets appeared and became popular. The products of these companies were of high quality, and their employees organized pre-set tasks in an organized manner. But they lost large sums due to the fact that they could not adapt to changes in demand. If we draw a parallel with the sphere of investment, the similarities will become noticeable. The stock market, like any other subject to change. One period is replaced by another. Those methods that allowed achieving success in the previous period can lead to failure in the current. The key concept in stock trading is volatility. The change in this indicates the onset of a new period. When volatility increases, trade becomes more risky. Accordingly, with a decrease in this indicator, the degree of risk during trading operations decreases. With a high level of volatility, trends most often unfold. Strong and weak positions can be swapped out. With a high level of volatility, trends continue for some time. From the foregoing, it should be concluded that market processes and methods during periods of high and low volatility differ strongly. You cannot use the same methods during changing market trends. Often it is the adherence to the previous methods, excessive discipline leads to collapse as well. The fact that the investor was defeated does not mean that he suddenly became morally unstable, unorganized. Trading is trading.
Therefore, we have every right to assert that under the psychology of trade in the markets is meant human preparedness for the risks that inevitably accompany any activity. Trading on the stock exchange is based on the interaction of the three most important components: capital management, analysis, and the psychology of trading (which cannot be considered in conjunction with the other aspects of trading). The psychology of human behavior is a source for understanding what is happening in financial markets. The source for understanding the events occurring in the financial markets and the behavior of traders during exchange trading is the psychology of the human person. Emotions — greed, fear, doubt, hope, a sense of self-preservation — are peculiar to any person in life — are clearly manifested in the hard rhythm of decision-making during the dynamic course of exchange trading (which was partially considered above). Knowledge of the human psychology and their behavioral characteristics must be used to achieve success. The psychology of a trader is formed from a multitude of grains - it is a belief in what one does in the stock market, in one’s actions, in own system of one’s decisions, in trading method. In addition, the psychology of a trader is that one can unload oneself emotionally, one does not accept the intellectual challenge that the stock market carries. On the contrary, becomes restrained, calm when making decisions on operations in the stock market. There are many situations where a trader expresses his attention and focus; he does not disperse it on the tracking of news factors or on the receipt of stimuli from the news agencies. Consequently, the crowd psychology is the factor that makes prices move, therefore, in addition to assessing one's own psychological state, one must be sensitive to changes in the mood of other market participants, move in the flow, not against it, and then success will not take long.
Of course, you can argue that why do I need this psychology? After all, besides creating your own strategies and individual work, some exchanges (including crypto exchanges) allow minimizing risks by following the strategies of experienced traders; this service is called a PAMM account. PAMM provides an opportunity for clients (Subscribers) to follow the trading strategy of experienced and professional traders (Providers). Provider's trading results are publicly available. With the help of the rating of accounts, graphs of profitability and reviews of other traders, you can choose the most suitable Provider and begin to follow his strategy. Again, in this case, the provider is a human with all the ensuing consequences. And psychological aspects are not foreign to professionals as well, including victories and mistakes. The financial market attracts people the possibility of obtaining independence, including financial. A successful trader can live and work in any country in the world without having either a boss or subordinates. The motivation of people on the exchanges can be different: from getting a higher percentage than from a bank to making several thousand dollars a day. At the same time, there are two main categories of people in the financial market (including cryptocurrencies): investors who acquire assets or currency for a relatively long period, and speculators who profit from changes in the prices of certain assets for short periods. Many believe, an easy way to make money is not for everybody. First, the skillful use and manipulation of the psychological aspects of a human make it possible to become a speculator. And this, of course, in addition to knowledge and analytical skills. Experience shows that successful speculation is the right state of mind. It would seem that this is the simplest thing that can be acquired by human. But in fact, this self-tuning is available to very few. It is also necessary to distinguish the psychology of the market and the personal psychology of the trader. The behavior of the market as a whole depends on people, since it is the stock market crowd that determines its direction. However, quite often traders lose sight of the most important component of victory - managing their personal emotions, that is, their psychology. Without control over oneself, there can be no control over one’s trading capital. If a trader is not tuned to the trend range of the stock crowd, if he does not pay attention to changes in her psychology, then he will also not achieve significant success in trading. To succeed on the exchange, one needs to take a sober look at exchange trading, recognize its trends and their changes, and not waste time on dreams or lamenting about failures.
Any price of a financial instrument is a momentary agreement on its value, reached by a market crowd and expressed in the fact of a transaction, i.e. it is the equilibrium point between the players for a rise and a fall, or the "equilibrium" price. Crowds of traders create asset prices: buyers, sellers and fluctuating market watchers. Charts of prices and trading volumes reflect the psychology of the exchange. In addition, this is always worth remembering! After all, the main purpose of the presence of the analysis of psychology in stock trading is not the quantity, but the quality of transactions. A person striving to become a good trader needs to remember the words of DiNapoli, a well-known stock exchange trader: “The most important trading tool is not a computer, not a service for supplying information, or even methods developed by a trader. It is he himself! If a trader is not suitable for this - he should not trade at all”! Therefore, before pushing orders on the trading platform, think about whether you are suitable for this role.
Join chat — https://t.me/joinchat/AAAAAE84vCXg5PK-VpHADg
Sergiy Golubyev (Сергей Голубев)
EU structural funds, ICO projects, NGO & investment projects, project management, comprehensive support of business
submitted by Golubyev_Sergiy to u/Golubyev_Sergiy [link] [comments]

The Bloomberg Finance Lab

The Bloomberg Terminal (aka Bloomberg Professional Services) connects finance professionals to a dynamic network of information, people, and ideas. At the core of this network is the ability to deliver real-time data to finance professionals around the world.
The main value added services provided by Bloomberg Terminal are:
  1. Data
  2. News
  3. Analytics
These services are provided through innovative, proprietary technology, that quickly and accurately provides financial information to individuals and across enterprises around the world.
A world leader in providing market data information across the globe through its websites, apps and dedicated feeds and software products, Bloomberg offers a variety of tools available on free and paid basis, allowing finance professionals to use them in their research, analysis and related trading activities. Bloomberg’s coverage includes all possible financial securities ranging from equities, fixed income, derivatives, commodities, forex and OTC products, across the globe.

Bloomberg website:

The official Bloomberg website offers a wealth of free and subscription based tools and utilities, most offering customized views as per regions/markets.

Symbol Lookup Service:

Introduced couple of years back, Bloomberg Open Symbology tool offers Symbol lookup service and mapping of different symbols (SEDOL, CUSIP, ISIN, Stock exchange ticker, etc.) at global level. Individual traders as well as large investment firms having a need to consolidate data sourced from multiple sources with different symbols use this service. For e.g. a mutual fund company may take 2 different data feeds – one from Bloomberg containing Bloomberg symbol and other from Stock exchange containing local ticker. Symbology service enables cross referencing to validate data across two sources with different tickers.
Apart from the generic Open Symbology service, the widely followed Bloomberg symbols can be accessed through its dedicated symbol search tool.

Bloomberg Professional Products & Services:

The paid professional products and tools available from Bloomberg offer coverage across 360+ exchanges, 24000+ companies, global currency markets, and includes recently launched bitcoin coverage. These products and tools today are used by more than 315,000 subscribers across 175 countries, demonstrating the depth and variety of offerings from Bloomberg.
Bloomberg Market data terminal remains the most saleable product for both individual and enterprise use. A good 2 pager Getting Started Guide is available for introduction to financial analysis tools available within the Bloomberg Terminal. Apart from usual charts, graphs, technical indicators and market data coverage, one of the key selling points of Bloomberg Terminals is its instant messaging feature which enables easy communication across individuals, dedicated workgroups and even Bloomberg representatives for assistance.
Bloomberg Briefs: A dedicated service in the form of digital newsletters for the global financial markets, Bloomberg Brief offers insights into sector or region specific areas in PDF format.
Briefs for following categories are published daily – Bankruptcy & Restructuring, Economics, Economics Asia, Economics Europe, London, Municipal Market and Oil. Publication for other categories is weekly – China, Clean Energy & Carbon, Financial Regulation, Hedge Funds Europe, Hedge Funds, Leveraged Finance, Mergers, Private Equity, Structured Notes and Technical Strategies.
Such wide varieties of tools offered by Bloomberg come with lots of portability. All website based functionality can be accessed through standard browsers on mobiles and tablets, and even professional products offer portability for mobile and remote access through desktops, laptops, tablets and smartphones.

Bloomberg Enterprise Solutions

At the enterprise level, Bloomberg offers dedicated data feeds, pricing, reference and market data, news and information services to meet the needs of large financial enterprises employing financial analysts, traders and researchers. The Bloomberg trading solutions, offer connectivity and integration for buy side and sell side institutional clients. These find usage in complementing the OMS (Order management system), and recent EMS (Execution management system), for trade execution.
N L Dalmia has set up Mumbai’s first Bloomberg Finance Lab with 12 Bloomberg terminals, offering students extremely focused and high end knowledge programs with a high degree of practical learning and on-the-job applicability. Learning mba in mumbai from N L Dalmia is a step towards boosting one's career.
submitted by dipika20 to MBAinIndiaExplained [link] [comments]

The Bloomberg Finance Lab Launched at N L Dalmia Campus Mumbai

The Bloomberg Terminal (aka Bloomberg Professional Services) connects finance professionals to a dynamic network of information, people, and ideas. At the core of this network is the ability to deliver real-time data to finance professionals around the world.
The main value added services provided by Bloomberg Terminal are:
  1. Data
  2. News
  3. Analytics
These services are provided through innovative, proprietary technology, that quickly and accurately provides financial information to individuals and across enterprises around the world.
A world leader in providing market data information across the globe through its websites, apps and dedicated feeds and software products, Bloomberg offers a variety of tools available on free and paid basis, allowing finance professionals to use them in their research, analysis and related trading activities. Bloomberg’s coverage includes all possible financial securities ranging from equities, fixed income, derivatives, commodities, forex and OTC products, across the globe.

Bloomberg website:

The official Bloomberg website offers a wealth of free and subscription based tools and utilities, most offering customized views as per regions/markets.

Symbol Lookup Service:

Introduced couple of years back, Bloomberg Open Symbology tool offers Symbol lookup service and mapping of different symbols (SEDOL, CUSIP, ISIN, Stock exchange ticker, etc.) at global level. Individual traders as well as large investment firms having a need to consolidate data sourced from multiple sources with different symbols use this service. For e.g. a mutual fund company may take 2 different data feeds – one from Bloomberg containing Bloomberg symbol and other from Stock exchange containing local ticker. Symbology service enables cross referencing to validate data across two sources with different tickers.
Apart from the generic Open Symbology service, the widely followed Bloomberg symbols can be accessed through its dedicated symbol search tool.

Bloomberg Professional Products & Services:

The paid professional products and tools available from Bloomberg offer coverage across 360+ exchanges, 24000+ companies, global currency markets, and includes recently launched bitcoin coverage. These products and tools today are used by more than 315,000 subscribers across 175 countries, demonstrating the depth and variety of offerings from Bloomberg.
Bloomberg Market data terminal remains the most saleable product for both individual and enterprise use. A good 2 pager Getting Started Guide is available for introduction to financial analysis tools available within the Bloomberg Terminal. Apart from usual charts, graphs, technical indicators and market data coverage, one of the key selling points of Bloomberg Terminals is its instant messaging feature which enables easy communication across individuals, dedicated workgroups and even Bloomberg representatives for assistance.
Bloomberg Briefs: A dedicated service in the form of digital newsletters for the global financial markets, Bloomberg Brief offers insights into sector or region specific areas in PDF format.
Briefs for following categories are published daily – Bankruptcy & Restructuring, Economics, Economics Asia, Economics Europe, London, Municipal Market and Oil. Publication for other categories is weekly – China, Clean Energy & Carbon, Financial Regulation, Hedge Funds Europe, Hedge Funds, Leveraged Finance, Mergers, Private Equity, Structured Notes and Technical Strategies.
Such wide varieties of tools offered by Bloomberg come with lots of portability. All website based functionality can be accessed through standard browsers on mobiles and tablets, and even professional products offer portability for mobile and remote access through desktops, laptops, tablets and smartphones.

Bloomberg Enterprise Solutions

At the enterprise level, Bloomberg offers dedicated data feeds, pricing, reference and market data, news and information services to meet the needs of large financial enterprises employing financial analysts, traders and researchers. The Bloomberg trading solutions, offer connectivity and integration for buy side and sell side institutional clients. These find usage in complementing the OMS (Order management system), and recent EMS (Execution management system), for trade execution.
NLDIMSR has set up Mumbai’s first Bloomberg Finance Lab with 12 Bloomberg terminals, offering students extremely focused and high end knowledge programs with a high degree of practical learning and on-the-job applicability.
submitted by dipika20 to MBAIndia [link] [comments]

General info and list of exchanges for X8X Token (X8X)

Ultimate crypto safe haven! Finally, Securing Value in Crypto is simple. X8X Token holders are granted a 0% fee for issuing X8Currency, a 100% fiat & gold backed Token.
Token holders are the gatekeepers!
YouTube Video Preview X8X token is also trading on:
Latest X-FEED
ARE CRYPTOCURRENCIES LEAVING LONG-TERM BEAR TERRITORY? On 17 July Bitcoin broke past the $7000 mark. The influx of …
X8 PROJECT ROADMAP UPDATE As promised we are now ready with an updated roadmap which will …
FACEBOOK’S POLICY REVERSAL LEADS TO WIDESPREAD SPECULATION After an explosive year for ICOs and cryptocurrency in 2017, some regulators …
STOCK AND COMMODITY MARKETS REACT PREDICTABLY TO THE LOOMING TRADE WARS – WITH THE EXCEPTION OF GOLD The G7 Summit in Canada in June was marked by uneasiness and …
Media YouTube Video Preview Global Leaders Forum panel 1
YouTube Video Preview Global Leaders Forum panel 2
YouTube Video Preview Global Leaders Forum panel 3
YouTube Video Preview Dubai Blockchain Summit 2018
Upcoming Events
Asean Blockchain Summit 3rd – 4th September 2018
Kuala Lumpur, Malaysia
More info
World Blockchain Summit 2018 1st – 5th October 2018
Mumbai, India
More info
Salon International des Femmes Entrepreneures 13th – 15th February 2019
Paris, France
More info
Past Events
KBS2018 in Seoul 12th – 13th July 2018
Seoul, Korea
More info
Bloomberg Global Leaders Forum 3rd April 2018
Dubai, UAE
More info
Dubai Blockchain Summit 2018 28th – 29th March 2018
Dubai, UAE
More info
Blockchain in Finance 14th – 15th March 2018
Rome, Italy
More info
Ideal for
TGEs / TGE contributors
Private individuals – traditional savers
Crypto contributors
Financial institutions
Merchants
Speculators & traders
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What is X8X? X8X is an Ethereum pure utility Token, functioning as a Key for issuing X8Currency. To exchange X8Currency for fiat ($/€) with 0% fee you will need to hold a corresponding amount of X8X.
X8X TOKEN SPECIFICATION Address: 0x910Dfc18D6EA3D6a7124A6F8B5458F281060fa4c Token Symbol: X8X Decimals: 18
YouTube Video Preview
Utility Token Token is used as a key to access services of issuing or exchanging the X8Currency at the Issuer.
Limited Cap There will be only 100.000.000 Tokens issued in the TGE, later mining is not supported.
Opportunity X8X holders will be able to obtain their own X8Currency or distribute this right to others on Online Exchanges.
Legislation compliant The X8X Token is issued by a Swiss-based company, approved by the Swiss Regulatory Authorities.
X8 Project - Dual Token Model A revolutionary new store of value for the distributed and traditional economy brought to you by the ultimate currency. The X8 Project developed two Ethereum based Tokens: X8Currency that is fully backed with 8 fiat (cash) currencies + gold and X8X Utility Token that functions as a key to the issuance and exchange process of X8C with 0% fee.
What is X8Currency (X8C)? X8Currency is an Ethereum Token, 100% backed in 8 fiat (Cash) Currencies & Gold. Each Token is represented with assets deposited on bank accounts. Assets are actively managed by the propriety software, Automatic Reserve Management AI. X8C can only be issued or exchanged for fiat with X8X Utility Tokens.
fiat-gold X8Currency Facts:
100% backed with Cash & Gold assets are actively managed by proved and tested AI risk management platform ARM the most stable Crypto Currency 100% exchangeable for 8 fiat Currencies (Cash) at the Issuer for 0% fee with X8X Tokens PROVEN PROVEN Risk management AI developed over 10 years for traditional FinTech, $1B in transactions since 2015.
SAFE SAFE Non-leveraged reserves in top 8 fiat currencies and gold provide unparalleled safety.
LIQUID LIQUID Fiat currency foundation enables daily volume in billions without affecting the price.
SECURE SECURE Triple-redundant Swiss architecture and gold reserves fully utilise the advantages of the Swiss financial ecosystem.
verified Our business partner verifies that this chart represents the holdings of a live account where all trades were executed by ARM AI. View reference here.
The ARM Portfolio risk management AI, which operates the reserves of the X8 currency, was developed over 10 years. It has been operational since 2015 and has generated a transaction volume of over $1 Billion for clients in the traditional financial industry.
8-Currencies-ARM-AI Fiat in X8 brings vast liquidity which can support speedy large transactions with little to no price impact. That means that X8 can scale globally and provide a sustainable solution as a financial system for more than 3,5bn people.
Together with friendly nature of X8 market operations, all participants in the value chain benefit from this constructive system.
X8 leverages the benefits of the Swiss financial ecosystem. Fiat funds deposited in the Swiss UBS AG, will be insured by SwissRE AG and audited daily by JP Fund Services. A store of gold currency in the safest certified storages outside the banking system serves as additional reserve for X8 currency.
Swiss-setup Road map
Team The team behind the X8 Currency blockchain product.
Gregor is behind some of the main design features of ioNectar platform. Gregor combined natural investment perspective with advanced technology capabilities of today into a winning philosophy match. His accumulated experience comes from working as portfolio manager in institutional environment, advising funds, HNWIs and specialists in foreign exchange and other markets.
GREGOR KOŽELJ CEO / Founder Tomaz with his long-term experience in business is responsible for executing the Sales strategy and tactics. The focus is to drive the business forward in creating stronger relationships, converting more prospects in gaining potential clients, increasing sales, creating operational efficiency, and lastly creating a fun and motivational environment.
TOMAŽ LEPOŠA CSO His experience with entrepreneurship, business organization and sales management has given him a valuable insight into business processes and development. His approach to team management and integration makes business operation a smooth and exciting experience.
ALY KULAUZOVIĆ Business development Rudolf Ströbl is a financial expert and program-developer with over 20 years of experience in various projects involving precious metals, options, equities and digital currencies. He has also developed models and algorithms in the Forex Markets. Currently he is the Managing Director of FX & Project Management GMBH in Switzerland. RUDOLF P. STRÖBL Infrastructure Francesca Greco has been a board member of several Private Equity Funds. Her focus are projects related to energy and telecommunications. She has been following closely the development of cutting-edge technologies of great potential. She is currently part of Green Brain Technologies team, where she is in charge of Government Relations and Regulatory Affairs.
FRANCESCA GRECO Legal Lenart manages and supervises legal aspects of the company's business. With experience at law office, he finds working in the area of finance an opportunity to expand his skills and understanding of legal dimensions of finance.
LENART KMETIČ Communications & Legal support Phil is an expert problem solver with a background in finance and communications. He has been a most welcome addition to the team, especially in terms of strategy and sharpening message clarity. He has more than 20 years of active experience in bringing together businesses from Western, Central and Eastern Europe by means of eliminating cultural differentiation.
PHIL LAWRENCE Communications An IT expert with years of participation in the world of cryptocurrencies. His experience in computer programming and knowledge of IT is a valuable contribution to the company. The products of ioNectar gave him an opportunity to employ his skills in a new and exciting way. He is also responsible for ICO communication.
ALEN OBERSTAR Communications With background in social sciences and focus on collapse of complex systems, he welcomed the opportunity to explore issues of financial stability. His passion for research led him to become one of the main contributors to the company's xfeed. He is also in charge of TGE communication.
DAVID PREŽELJ Communications Urban is a long-time cryptocurrency enthusiast with a passion for ICO/TGE research. With his expertise in developing and leading teams he has developed a strategic plan to achieve the successful launch of the X8 TGE project. His strategic vision has assisted in bringing together the existing talents of the X8 team in a coherent manner.
URBAN ALJANČIČ TGE / ICO project manager Simon is a seasoned computer expert with an extensive range of programing skills in different computer languages. As the CTO of ioNectar he knows the area of the platform client and manages technological releases of the product. He is creativity driven with insight in new products development and is behind different original aspects of the platform.
SIMON HOHLER CTO Ervin is a specialist in IT. He brings together his broad technical proficiency from computer science and manages all main IT administration perspectives of ioNectar. Work in specialized software and electronics product solutions is his passion which he has been following. Through persistent expansion of his ability Ervin proved many times he is an IT authority.
ERVIN MARGUČ CIO A computer programmer proficient in several computer languages. He is involved in developing the key components of the ioNectar technology. He is eager to use his knowledge to build bridges between blokchain technology and the world of traditional finance.
ERGIM RAMADAN IT Sofia is in charge of visual presentations and design strategies at ioNectar. The dedicated and enthusiastic team around her created the right environment for her to express her artistic sensibilities and passion for aesthetics in every aspect of the company's presentations.
SOFIA KULAUZOVIĆ Corporate look & design Advisory Board The team behind the X8 Currency blockchain product.
Peter Kristensen is the CEO of JP Integra LLC US, an international finance service group providing administrative and management services to owners and managers of international private capital. PETER KRISTENSEN Financial specialist Olaf Chalmer is a financial advisor with decades of experience in the banking sector who, among other things, offers guidance to investors in financial sector. Currently he is the president of the Swiss Management, Ltd, a consulting company oriented towards clients from Eastern Europe. OLAF CHALMER B2B placement A progressive investment professional with more than 2 decades of experience in top level banks. Mikkel is advising globally on interest rate and FX risk and manages alpha driven G10 portfolios. He is running independent trading & advisory business, is also a specialist in market making and sits on several investment management boards. MIKKEL THORUP Foreign exchange field Marcus von Goetz is a seasoned bondspecialist and trader. During his career he held key bondstrading positions at several prominent financial institutions. He is also a financial advisor for larger market participants. Currently his expertise is available to institutional clients and venture capital entrepreneurs through VG&S Business Development. MARCUS VON GOETZ Business development With a background in finance and an enthusiasm for blockchain technology attorney Peter Merc PhD is the ideal legal consultant for TGEs. He is a member of the supervisory board of Slovenian systemic bank and cofounder of Lemur Legal, a legal company promoting digital transformation. He helps transform TGEs in legally compliant enterprises. PETER MERC, PH.D. Legal advice Simon Cocking is a seasoned business mentor to TGEs and a senior editor at Irish Tech News. He is also an experienced public speaker at events including TEDx and Web Summit. He is a crypto connoisseur and has to date successfully advised and mentored 18 TGEs. He has also founded six prosperous companies. SIMON COCKING Digital Marketing Branko Drobnak is a former investment banker with more than 25 years of experience in finance and entrepreneurship. This background combined with his enthusiasm for ICO research and investment provides valuable insights to the X8 project. BRANKO DROBNAK Strategic advice
EXCHANGE LIST
Binance
Huobi
Kucoin
Bibox
Qryptos
Satoexchange
BIGone
Bitrue
Bilaxy
Bit-Z
Linkcoin
SECURE WALLET
Ledgerwallet
Trezor
submitted by icoinformation to X8XToken [link] [comments]

SPECTACULAR NUMBERS

Watching Wall Street boast its best start to a year in over a decade, investors are turning their focus to the fourth quarter earnings season, with results beginning to trickle in this week. Traders are focusing on the recent U.S. tax overhaul, which could provide breathtaking numbers, but it will not affect stock prices much.
ECONOMIES
German factory orders in Europe's biggest economy slipped by 0.4% in November after three months of gains. The dip was largely due to fluctuations in bulk orders but the overall trend remains positive. China's forex reserves posted an eleventh straight monthly increase in December, $20.7B, taking the full-year increase of the world's largest foreign-currency stockpile to $129B.
The FED should raise interest rates three times this year, given the already strong economy will get a boost from tax cuts.
ARAMCO’s 5% IS FOR SALE
Aligning its strategy with peers, Exxon Mobil (XOM) and Chevron (CVX), CEO Ben van Beurden said that growth of competitor Shell's (RDS.A) oil and gas operations in the next decade will depend on shale production. On what else?! Candies? What a discovery! Saudi Aramco and some of the kingdom's biggest companies said they'll pay Saudi staff more money, matching a royal order amid rising prices. Saudi Arabia seeks to sell as much as 5% of Aramco.
CRYPTO
The SEC has received a request to allow five bitcoin-related ETFs to be listed on Arca, a secondary marketplace on the NYSE. The instruments, are not tied to the price of the cryptocurrency itself, but would track bitcoin futures.
AT&T BACKS DOWN
AT&T (T) is backing away from a plan to sell phones made by Chinese handset giant Huawei, on the eve of a big announcement of the deal. The deal that Huawei was set to announce tomorrow would have been its first partnership with a major U.S. carrier, but AT&T has changed its mind. So far it is not clear why AT&T backed down, but there are two issues occur. Are Huawei's phones carry spyware? Is it because the US wants to have domestic competition? At one point we’ll have the answer.
THERE ARE NO JEDIS IN CHINA
$36 million in third-week grosses, Jumanji: Welcome to the Jungle (Sony) finally toppled Star Wars: The Last Jedi (Disney) from the top of the box-office charts. Disney made an impressive $1.2 billion, but it is far from the estimated $2 billion. It seems that China has no Jedis, the movie made only 26% of expectations in the country. The Force is weak in China.
NVIDIA, VOLKSWAGEN, UBER, AI
Making further gains in the autonomous vehicle industry, Nvidia (NVDA) is partnering with Uber and Volkswagen on AI platforms. So far, 320 companies involved in self-driving cars - whether software developers, automakers, or sensor and mapping companies - are using Nvidia Drive, formerly branded as the Drive PX2, proven that there is more than cryptomining to the company!
WHIRLPOOL KICKS OFF CES2018
Apple (AAPL) Watch users will soon have the ability to control Whirlpool (WHR) appliances through the wearable. Whirlpool announced the development at CES and said the compatibility would come later this year to 20 connected appliances. Whirlpool says Amazon (AMZN) Alexa and Google (GOOGC) Assistant voice controls will also arrive in 2018.
SPACEX - THE FIRST LAUNCH OF 2018
SpaceX successfully launched a secret U.S. government payload called Zuma on Sunday and landed its rocket back on Earth. The Falcon 9 powered a spacecraft made by Northrop Grumman, which was sent into low-Earth orbit. SpaceX is now looking towards its next challenge, launching the Falcon Heavy - its largest rocket to date - at the end of January, meanwhile Tesla’s stock price soared higher.
#DAILY PICK
Amazon (AMZN) Alexa Onboard was introduced yesterday. Another green day.
Electronic Arts (EA) is upgraded to Buy, new PT is $130.
Applied Materials (AMAT) also got an upgrade, double bottom formed, ready to rock!
Johnson & Johnson (JNJ) had great presentation at JPM Healthcare conference. Climbing steady.
PayPal (PYPL) one day transfer, instant debit card transfer. Smells like blockchain integration. But who cares?! $86 on the way. Tight stop people!
FX WORLD
Not a lot happened on Monday, mostly momentum trading was possible. It doesn’t seem to be busy today either, still look for the correct entry points! The EURUSD initially took off to the upside, then broke down to the 1.20 area. 1.19 offers support, where the pair can find buyers and clear the 1.21 level. The GBPUSD didn’t do a lot, which is a sign that it is trying to break out. 1.365 offers resistance, if we break above, the pair will aim higher. 1.3333 is supportive underneath. The USDJPY did a lot of back and forth move during Monday, but couldn’t clear 113.5. Expect pull backs, which will offer good entry points, the pair eventually will break out on top! 112 is kind of an absolut floor.
TODAY’s MARKET
In Asia ASX200 +0.13% (6,130.3) HANG SHENG +0.11% (30,869) NIKKEI +0.99% (23,849.5) SHANGHAI +0.52% (4,178.5) In Europe DAX30 +0.36% (13,367.78) FTSE100 -0.36% (7,696.5) BUX +0.27% (40,1.4) CAC40 +0.30% (5,487.4) In US Dow -0.05% (25,283) S&P500 +0.17% (2,747.7) NASDAQ +0.29% (7,157.4) Crude +0.12% ($62.21) Gold -0.10% ($1,319.05) Today's Economic Calendar CHF - Unemployment rate EUR - German trade balance EUR - French trade balance EUR - Unemployment rate USD - JOLTS job openings
Check our blog for more information: https://www.gtc.news/single-post/DT18009EN

GTC #GTCnews #daily #dailynews #GTCdailythread #followus #dailypick #forexworld

submitted by GTCnews to InvestmentBanking123 [link] [comments]

SPECTACULAR NUMBERS

Watching Wall Street boast its best start to a year in over a decade, investors are turning their focus to the fourth quarter earnings season, with results beginning to trickle in this week. Traders are focusing on the recent U.S. tax overhaul, which could provide breathtaking numbers, but it will not affect stock prices much.
ECONOMIES
German factory orders in Europe's biggest economy slipped by 0.4% in November after three months of gains. The dip was largely due to fluctuations in bulk orders but the overall trend remains positive. China's forex reserves posted an eleventh straight monthly increase in December, $20.7B, taking the full-year increase of the world's largest foreign-currency stockpile to $129B.
The FED should raise interest rates three times this year, given the already strong economy will get a boost from tax cuts.
ARAMCO’s 5% IS FOR SALE
Aligning its strategy with peers, Exxon Mobil (XOM) and Chevron (CVX), CEO Ben van Beurden said that growth of competitor Shell's (RDS.A) oil and gas operations in the next decade will depend on shale production. On what else?! Candies? What a discovery! Saudi Aramco and some of the kingdom's biggest companies said they'll pay Saudi staff more money, matching a royal order amid rising prices. Saudi Arabia seeks to sell as much as 5% of Aramco.
CRYPTO
The SEC has received a request to allow five bitcoin-related ETFs to be listed on Arca, a secondary marketplace on the NYSE. The instruments, are not tied to the price of the cryptocurrency itself, but would track bitcoin futures.
AT&T BACKS DOWN
AT&T (T) is backing away from a plan to sell phones made by Chinese handset giant Huawei, on the eve of a big announcement of the deal. The deal that Huawei was set to announce tomorrow would have been its first partnership with a major U.S. carrier, but AT&T has changed its mind. So far it is not clear why AT&T backed down, but there are two issues occur. Are Huawei's phones carry spyware? Is it because the US wants to have domestic competition? At one point we’ll have the answer.
THERE ARE NO JEDIS IN CHINA
$36 million in third-week grosses, Jumanji: Welcome to the Jungle (Sony) finally toppled Star Wars: The Last Jedi (Disney) from the top of the box-office charts. Disney made an impressive $1.2 billion, but it is far from the estimated $2 billion. It seems that China has no Jedis, the movie made only 26% of expectations in the country. The Force is weak in China.
NVIDIA, VOLKSWAGEN, UBER, AI
Making further gains in the autonomous vehicle industry, Nvidia (NVDA) is partnering with Uber and Volkswagen on AI platforms. So far, 320 companies involved in self-driving cars - whether software developers, automakers, or sensor and mapping companies - are using Nvidia Drive, formerly branded as the Drive PX2, proven that there is more than cryptomining to the company!
WHIRLPOOL KICKS OFF CES2018
Apple (AAPL) Watch users will soon have the ability to control Whirlpool (WHR) appliances through the wearable. Whirlpool announced the development at CES and said the compatibility would come later this year to 20 connected appliances. Whirlpool says Amazon (AMZN) Alexa and Google (GOOGC) Assistant voice controls will also arrive in 2018.
SPACEX - THE FIRST LAUNCH OF 2018
SpaceX successfully launched a secret U.S. government payload called Zuma on Sunday and landed its rocket back on Earth. The Falcon 9 powered a spacecraft made by Northrop Grumman, which was sent into low-Earth orbit. SpaceX is now looking towards its next challenge, launching the Falcon Heavy - its largest rocket to date - at the end of January, meanwhile Tesla’s stock price soared higher.
#DAILY PICK
Amazon (AMZN) Alexa Onboard was introduced yesterday. Another green day.
Electronic Arts (EA) is upgraded to Buy, new PT is $130.
Applied Materials (AMAT) also got an upgrade, double bottom formed, ready to rock!
Johnson & Johnson (JNJ) had great presentation at JPM Healthcare conference. Climbing steady.
PayPal (PYPL) one day transfer, instant debit card transfer. Smells like blockchain integration. But who cares?! $86 on the way. Tight stop people!
FX WORLD
Not a lot happened on Monday, mostly momentum trading was possible. It doesn’t seem to be busy today either, still look for the correct entry points! The EURUSD initially took off to the upside, then broke down to the 1.20 area. 1.19 offers support, where the pair can find buyers and clear the 1.21 level. The GBPUSD didn’t do a lot, which is a sign that it is trying to break out. 1.365 offers resistance, if we break above, the pair will aim higher. 1.3333 is supportive underneath. The USDJPY did a lot of back and forth move during Monday, but couldn’t clear 113.5. Expect pull backs, which will offer good entry points, the pair eventually will break out on top! 112 is kind of an absolut floor.
TODAY’s MARKET
In Asia ASX200 +0.13% (6,130.3) HANG SHENG +0.11% (30,869) NIKKEI +0.99% (23,849.5) SHANGHAI +0.52% (4,178.5) In Europe DAX30 +0.36% (13,367.78) FTSE100 -0.36% (7,696.5) BUX +0.27% (40,1.4) CAC40 +0.30% (5,487.4) In US Dow -0.05% (25,283) S&P500 +0.17% (2,747.7) NASDAQ +0.29% (7,157.4) Crude +0.12% ($62.21) Gold -0.10% ($1,319.05) Today's Economic Calendar CHF - Unemployment rate EUR - German trade balance EUR - French trade balance EUR - Unemployment rate USD - JOLTS job openings
Check our blog for more information: https://www.gtc.news/single-post/DT18009EN

GTC #GTCnews #daily #dailynews #GTCdailythread #followus #dailypick #forexworld

submitted by GTCnews to InvestCrypto [link] [comments]

Tips For Choosing The Best Forex Company In Malaysia


It is recommended to take not less than six months to learn and understand how the Forex Online Income System Review trading market works before you start trading using a live account. During this period, you should learn which strategies to use over shorter periods of time and which ones to use over longer periods. You will also need to learn the importance of money management, self-discipline and restraint when you are trading in the Forex market. Otherwise, you may end up losing a lot of money if you trade based on assumptions or instinct.
Before you start working with a Forex training company, you need to make sure that it is a reputable company. It should be able to teach you about the best trading style as well as strategies that you can use in order to be successful in this business. The company should have software, charting and trading tools that are highly reliable. They should allow you to trade with different currency pairs with ease.
When you are looking for a company on the internet, you will need to be careful not to get yourself into tricks of fraudsters and scam artists that are only interested in extorting money from you. It is important to take your time to carry out a detailed review of different Forex training companies in this country so as to find out which one among them has the right qualifications. You should crosscheck the credentials of the companies that you are considering hiring with regulatory boards and make sure they can meet your needs. You can also choose to work with an offshore company, but you will need to do it with great care.
If you want to become a successful Forex trader, you should be in it for the long haul. Trying for a few weeks or months will not get you anywhere. This is because Forex is a volatile market where new tricks are constantly being developed. So you will need to be learning them constantly and augmenting them to your system so as to adapt to the current market conditions. It will be easier to adapt to these changes once you develop a solid system or trading strategy that works well for you over the years.Exkash is a name of easy money facility offering magnificent facility of E-currency cash out.

https://optimusforexreview.com/online-income-system-review/
submitted by steffandevin1 to u/steffandevin1 [link] [comments]

Subreddit Stats: cs7646_fall2017 top posts from 2017-08-23 to 2017-12-10 22:43 PDT

Period: 108.98 days
Submissions Comments
Total 999 10425
Rate (per day) 9.17 95.73
Unique Redditors 361 695
Combined Score 4162 17424

Top Submitters' Top Submissions

  1. 296 points, 24 submissions: tuckerbalch
    1. Project 2 Megathread (optimize_something) (33 points, 475 comments)
    2. project 3 megathread (assess_learners) (27 points, 1130 comments)
    3. For online students: Participation check #2 (23 points, 47 comments)
    4. ML / Data Scientist internship and full time job opportunities (20 points, 36 comments)
    5. Advance information on Project 3 (19 points, 22 comments)
    6. participation check #3 (19 points, 29 comments)
    7. manual_strategy project megathread (17 points, 825 comments)
    8. project 4 megathread (defeat_learners) (15 points, 209 comments)
    9. project 5 megathread (marketsim) (15 points, 484 comments)
    10. QLearning Robot project megathread (12 points, 691 comments)
  2. 278 points, 17 submissions: davebyrd
    1. A little more on Pandas indexing/slicing ([] vs ix vs iloc vs loc) and numpy shapes (37 points, 10 comments)
    2. Project 1 Megathread (assess_portfolio) (34 points, 466 comments)
    3. marketsim grades are up (25 points, 28 comments)
    4. Midterm stats (24 points, 32 comments)
    5. Welcome to CS 7646 MLT! (23 points, 132 comments)
    6. How to interact with TAs, discuss grades, performance, request exceptions... (18 points, 31 comments)
    7. assess_portfolio grades have been released (18 points, 34 comments)
    8. Midterm grades posted to T-Square (15 points, 30 comments)
    9. Removed posts (15 points, 2 comments)
    10. assess_portfolio IMPORTANT README: about sample frequency (13 points, 26 comments)
  3. 118 points, 17 submissions: yokh_cs7646
    1. Exam 2 Information (39 points, 40 comments)
    2. Reformat Assignment Pages? (14 points, 2 comments)
    3. What did the real-life Michael Burry have to say? (13 points, 2 comments)
    4. PSA: Read the Rubric carefully and ahead-of-time (8 points, 15 comments)
    5. How do I know that I'm correct and not just lucky? (7 points, 31 comments)
    6. ML Papers and News (7 points, 5 comments)
    7. What are "question pools"? (6 points, 4 comments)
    8. Explanation of "Regression" (5 points, 5 comments)
    9. GT Github taking FOREVER to push to..? (4 points, 14 comments)
    10. Dead links on the course wiki (3 points, 2 comments)
  4. 67 points, 13 submissions: harshsikka123
    1. To all those struggling, some words of courage! (20 points, 18 comments)
    2. Just got locked out of my apartment, am submitting from a stairwell (19 points, 12 comments)
    3. Thoroughly enjoying the lectures, some of the best I've seen! (13 points, 13 comments)
    4. Just for reference, how long did Assignment 1 take you all to implement? (3 points, 31 comments)
    5. Grade_Learners Taking about 7 seconds on Buffet vs 5 on Local, is this acceptable if all tests are passing? (2 points, 2 comments)
    6. Is anyone running into the Runtime Error, Invalid DISPLAY variable when trying to save the figures as pdfs to the Buffet servers? (2 points, 9 comments)
    7. Still not seeing an ML4T onboarding test on ProctorTrack (2 points, 10 comments)
    8. Any news on when Optimize_Something grades will be released? (1 point, 1 comment)
    9. Baglearner RMSE and leaf size? (1 point, 2 comments)
    10. My results are oh so slightly off, any thoughts? (1 point, 11 comments)
  5. 63 points, 10 submissions: htrajan
    1. Sample test case: missing data (22 points, 36 comments)
    2. Optimize_something test cases (13 points, 22 comments)
    3. Met Burt Malkiel today (6 points, 1 comment)
    4. Heads up: Dataframe.std != np.std (5 points, 5 comments)
    5. optimize_something: graph (5 points, 29 comments)
    6. Schedule still reflecting shortened summer timeframe? (4 points, 3 comments)
    7. Quick clarification about InsaneLearner (3 points, 8 comments)
    8. Test cases using rfr? (3 points, 5 comments)
    9. Input format of rfr (2 points, 1 comment)
    10. [Shameless recruiting post] Wealthfront is hiring! (0 points, 9 comments)
  6. 62 points, 7 submissions: swamijay
    1. defeat_learner test case (34 points, 38 comments)
    2. Project 3 test cases (15 points, 27 comments)
    3. Defeat_Learner - related questions (6 points, 9 comments)
    4. Options risk/reward (2 points, 0 comments)
    5. manual strategy - you must remain in the position for 21 trading days. (2 points, 9 comments)
    6. standardizing values (2 points, 0 comments)
    7. technical indicators - period for moving averages, or anything that looks past n days (1 point, 3 comments)
  7. 61 points, 9 submissions: gatech-raleighite
    1. Protip: Better reddit search (22 points, 9 comments)
    2. Helpful numpy array cheat sheet (16 points, 10 comments)
    3. In your experience Professor, Mr. Byrd, which strategy is "best" for trading ? (12 points, 10 comments)
    4. Industrial strength or mature versions of the assignments ? (4 points, 2 comments)
    5. What is the correct (faster) way of doing this bit of pandas code (updating multiple slice values) (2 points, 10 comments)
    6. What is the correct (pythonesque?) way to select 60% of rows ? (2 points, 11 comments)
    7. How to get adjusted close price for funds not publicly traded (TSP) ? (1 point, 2 comments)
    8. Is there a way to only test one or 2 of the learners using grade_learners.py ? (1 point, 10 comments)
    9. OMS CS Digital Career Seminar Series - Scott Leitstein recording available online? (1 point, 4 comments)
  8. 60 points, 2 submissions: reyallan
    1. [Project Questions] Unit Tests for assess_portfolio assignment (58 points, 52 comments)
    2. Financial data, technical indicators and live trading (2 points, 8 comments)
  9. 59 points, 12 submissions: dyllll
    1. Please upvote helpful posts and other advice. (26 points, 1 comment)
    2. Books to further study in trading with machine learning? (14 points, 9 comments)
    3. Is Q-Learning the best reinforcement learning method for stock trading? (4 points, 4 comments)
    4. Any way to download the lessons? (3 points, 4 comments)
    5. Can a TA please contact me? (2 points, 7 comments)
    6. Is the vectorization code from the youtube video available to us? (2 points, 2 comments)
    7. Position of webcam (2 points, 15 comments)
    8. Question about assignment one (2 points, 5 comments)
    9. Are udacity quizzes recorded? (1 point, 2 comments)
    10. Does normalization of indicators matter in a Q-Learner? (1 point, 7 comments)
  10. 56 points, 2 submissions: jan-laszlo
    1. Proper git workflow (43 points, 19 comments)
    2. Adding you SSH key for password-less access to remote hosts (13 points, 7 comments)
  11. 53 points, 1 submission: agifft3_omscs
    1. [Project Questions] Unit Tests for optimize_something assignment (53 points, 94 comments)
  12. 50 points, 16 submissions: BNielson
    1. Regression Trees (7 points, 9 comments)
    2. Two Interpretations of RFR are leading to two different possible Sharpe Ratios -- Need Instructor clarification ASAP (5 points, 3 comments)
    3. PYTHONPATH=../:. python grade_analysis.py (4 points, 7 comments)
    4. Running on Windows and PyCharm (4 points, 4 comments)
    5. Studying for the midterm: python questions (4 points, 0 comments)
    6. Assess Learners Grader (3 points, 2 comments)
    7. Manual Strategy Grade (3 points, 2 comments)
    8. Rewards in Q Learning (3 points, 3 comments)
    9. SSH/Putty on Windows (3 points, 4 comments)
    10. Slight contradiction on ProctorTrack Exam (3 points, 4 comments)
  13. 49 points, 7 submissions: j0shj0nes
    1. QLearning Robot - Finalized and Released Soon? (18 points, 4 comments)
    2. Flash Boys, HFT, frontrunning... (10 points, 3 comments)
    3. Deprecations / errata (7 points, 5 comments)
    4. Udacity lectures via GT account, versus personal account (6 points, 2 comments)
    5. Python: console-driven development (5 points, 5 comments)
    6. Buffet pandas / numpy versions (2 points, 2 comments)
    7. Quant research on earnings calls (1 point, 0 comments)
  14. 45 points, 11 submissions: Zapurza
    1. Suggestion for Strategy learner mega thread. (14 points, 1 comment)
    2. Which lectures to watch for upcoming project q learning robot? (7 points, 5 comments)
    3. In schedule file, there is no link against 'voting ensemble strategy'? Scheduled for Nov 13-20 week (6 points, 3 comments)
    4. How to add questions to the question bank? I can see there is 2% credit for that. (4 points, 5 comments)
    5. Scratch paper use (3 points, 6 comments)
    6. The big short movie link on you tube says the video is not available in your country. (3 points, 9 comments)
    7. Distance between training data date and future forecast date (2 points, 2 comments)
    8. News affecting stock market and machine learning algorithms (2 points, 4 comments)
    9. pandas import in pydev (2 points, 0 comments)
    10. Assess learner server error (1 point, 2 comments)
  15. 43 points, 23 submissions: chvbs2000
    1. Is the Strategy Learner finalized? (10 points, 3 comments)
    2. Test extra 15 test cases for marketsim (3 points, 12 comments)
    3. Confusion between the term computing "back-in time" and "going forward" (2 points, 1 comment)
    4. How to define "each transaction"? (2 points, 4 comments)
    5. How to filling the assignment into Jupyter Notebook? (2 points, 4 comments)
    6. IOError: File ../data/SPY.csv does not exist (2 points, 4 comments)
    7. Issue in Access to machines at Georgia Tech via MacOS terminal (2 points, 5 comments)
    8. Reading data from Jupyter Notebook (2 points, 3 comments)
    9. benchmark vs manual strategy vs best possible strategy (2 points, 2 comments)
    10. global name 'pd' is not defined (2 points, 4 comments)
  16. 43 points, 15 submissions: shuang379
    1. How to test my code on buffet machine? (10 points, 15 comments)
    2. Can we get the ppt for "Decision Trees"? (8 points, 2 comments)
    3. python question pool question (5 points, 6 comments)
    4. set up problems (3 points, 4 comments)
    5. Do I need another camera for scanning? (2 points, 9 comments)
    6. Is chapter 9 covered by the midterm? (2 points, 2 comments)
    7. Why grade_analysis.py could run even if I rm analysis.py? (2 points, 5 comments)
    8. python question pool No.48 (2 points, 6 comments)
    9. where could we find old versions of the rest projects? (2 points, 2 comments)
    10. where to put ml4t-libraries to install those libraries? (2 points, 1 comment)
  17. 42 points, 14 submissions: larrva
    1. is there a mistake in How-to-learn-a-decision-tree.pdf (7 points, 7 comments)
    2. maximum recursion depth problem (6 points, 10 comments)
    3. [Urgent]Unable to use proctortrack in China (4 points, 21 comments)
    4. manual_strategynumber of indicators to use (3 points, 10 comments)
    5. Assignment 2: Got 63 points. (3 points, 3 comments)
    6. Software installation workshop (3 points, 7 comments)
    7. question regarding functools32 version (3 points, 3 comments)
    8. workshop on Aug 31 (3 points, 8 comments)
    9. Mount remote server to local machine (2 points, 2 comments)
    10. any suggestion on objective function (2 points, 3 comments)
  18. 41 points, 8 submissions: Ran__Ran
    1. Any resource will be available for final exam? (19 points, 6 comments)
    2. Need clarification on size of X, Y in defeat_learners (7 points, 10 comments)
    3. Get the same date format as in example chart (4 points, 3 comments)
    4. Cannot log in GitHub Desktop using GT account? (3 points, 3 comments)
    5. Do we have notes or ppt for Time Series Data? (3 points, 5 comments)
    6. Can we know the commission & market impact for short example? (2 points, 7 comments)
    7. Course schedule export issue (2 points, 15 comments)
    8. Buying/seeking beta v.s. buying/seeking alpha (1 point, 6 comments)
  19. 38 points, 4 submissions: ProudRamblinWreck
    1. Exam 2 Study topics (21 points, 5 comments)
    2. Reddit participation as part of grade? (13 points, 32 comments)
    3. Will birds chirping in the background flag me on Proctortrack? (3 points, 5 comments)
    4. Midterm Study Guide question pools (1 point, 2 comments)
  20. 37 points, 6 submissions: gatechben
    1. Submission page for strategy learner? (14 points, 10 comments)
    2. PSA: The grading script for strategy_learner changed on the 26th (10 points, 9 comments)
    3. Where is util.py supposed to be located? (8 points, 8 comments)
    4. PSA:. The default dates in the assignment 1 template are not the same as the examples on the assignment page. (2 points, 1 comment)
    5. Schedule: Discussion of upcoming trading projects? (2 points, 3 comments)
    6. [defeat_learners] More than one column for X? (1 point, 1 comment)
  21. 37 points, 3 submissions: jgeiger
    1. Please send/announce when changes are made to the project code (23 points, 7 comments)
    2. The Big Short on Netflix for OMSCS students (week of 10/16) (11 points, 6 comments)
    3. Typo(?) for Assess_portfolio wiki page (3 points, 2 comments)
  22. 35 points, 10 submissions: ltian35
    1. selecting row using .ix (8 points, 9 comments)
    2. Will the following 2 topics be included in the final exam(online student)? (7 points, 4 comments)
    3. udacity quiz (7 points, 4 comments)
    4. pdf of lecture (3 points, 4 comments)
    5. print friendly version of the course schedule (3 points, 9 comments)
    6. about learner regression vs classificaiton (2 points, 2 comments)
    7. is there a simple way to verify the correctness of our decision tree (2 points, 4 comments)
    8. about Building an ML-based forex strategy (1 point, 2 comments)
    9. about technical analysis (1 point, 6 comments)
    10. final exam online time period (1 point, 2 comments)
  23. 33 points, 2 submissions: bhrolenok
    1. Assess learners template and grading script is now available in the public repository (24 points, 0 comments)
    2. Tutorial for software setup on Windows (9 points, 35 comments)
  24. 31 points, 4 submissions: johannes_92
    1. Deadline extension? (26 points, 40 comments)
    2. Pandas date indexing issues (2 points, 5 comments)
    3. Why do we subtract 1 from SMA calculation? (2 points, 3 comments)
    4. Unexpected number of calls to query, sum=20 (should be 20), max=20 (should be 1), min=20 (should be 1) -bash: syntax error near unexpected token `(' (1 point, 3 comments)
  25. 30 points, 5 submissions: log_base_pi
    1. The Massive Hedge Fund Betting on AI [Article] (9 points, 1 comment)
    2. Useful Python tips and tricks (8 points, 10 comments)
    3. Video of overview of remaining projects with Tucker Balch (7 points, 1 comment)
    4. Will any material from the lecture by Goldman Sachs be covered on the exam? (5 points, 1 comment)
    5. What will the 2nd half of the course be like? (1 point, 8 comments)
  26. 30 points, 4 submissions: acschwabe
    1. Assignment and Exam Calendar (ICS File) (17 points, 6 comments)
    2. Please OMG give us any options for extra credit (8 points, 12 comments)
    3. Strategy learner question (3 points, 1 comment)
    4. Proctortrack: Do we need to schedule our test time? (2 points, 10 comments)
  27. 29 points, 9 submissions: _ant0n_
    1. Next assignment? (9 points, 6 comments)
    2. Proctortrack Onboarding test? (6 points, 11 comments)
    3. Manual strategy: Allowable positions (3 points, 7 comments)
    4. Anyone watched Black Scholes documentary? (2 points, 16 comments)
    5. Buffet machines hardware (2 points, 6 comments)
    6. Defeat learners: clarification (2 points, 4 comments)
    7. Is 'optimize_something' on the way to class GitHub repo? (2 points, 6 comments)
    8. assess_portfolio(... gen_plot=True) (2 points, 8 comments)
    9. remote job != remote + international? (1 point, 15 comments)
  28. 26 points, 10 submissions: umersaalis
    1. comments.txt (7 points, 6 comments)
    2. Assignment 2: report.pdf (6 points, 30 comments)
    3. Assignment 2: report.pdf sharing & plagiarism (3 points, 12 comments)
    4. Max Recursion Limit (3 points, 10 comments)
    5. Parametric vs Non-Parametric Model (3 points, 13 comments)
    6. Bag Learner Training (1 point, 2 comments)
    7. Decision Tree Issue: (1 point, 2 comments)
    8. Error in Running DTLearner and RTLearner (1 point, 12 comments)
    9. My Results for the four learners. Please check if you guys are getting values somewhat near to these. Exact match may not be there due to randomization. (1 point, 4 comments)
    10. Can we add the assignments and solutions to our public github profile? (0 points, 7 comments)
  29. 26 points, 6 submissions: abiele
    1. Recommended Reading? (13 points, 1 comment)
    2. Number of Indicators Used by Actual Trading Systems (7 points, 6 comments)
    3. Software Install Instructions From TA's Video Not Working (2 points, 2 comments)
    4. Suggest that TA/Instructor Contact Info Should be Added to the Syllabus (2 points, 2 comments)
    5. ML4T Software Setup (1 point, 3 comments)
    6. Where can I find the grading folder? (1 point, 4 comments)
  30. 26 points, 6 submissions: tomatonight
    1. Do we have all the information needed to finish the last project Strategy learner? (15 points, 3 comments)
    2. Does anyone interested in cryptocurrency trading/investing/others? (3 points, 6 comments)
    3. length of portfolio daily return (3 points, 2 comments)
    4. Did Michael Burry, Jamie&Charlie enter the short position too early? (2 points, 4 comments)
    5. where to check participation score (2 points, 1 comment)
    6. Where to collect the midterm exam? (forgot to take it last week) (1 point, 3 comments)
  31. 26 points, 3 submissions: hilo260
    1. Is there a template for optimize_something on GitHub? (14 points, 3 comments)
    2. Marketism project? (8 points, 6 comments)
    3. "Do not change the API" (4 points, 7 comments)
  32. 26 points, 3 submissions: niufen
    1. Windows Server Setup Guide (23 points, 16 comments)
    2. Strategy Learner Adding UserID as Comment (2 points, 2 comments)
    3. Connect to server via Python Error (1 point, 6 comments)
  33. 26 points, 3 submissions: whoyoung99
    1. How much time you spend on Assess Learner? (13 points, 47 comments)
    2. Git clone repository without fork (8 points, 2 comments)
    3. Just for fun (5 points, 1 comment)
  34. 25 points, 8 submissions: SharjeelHanif
    1. When can we discuss defeat learners methods? (10 points, 1 comment)
    2. Are the buffet servers really down? (3 points, 2 comments)
    3. Are the midterm results in proctortrack gone? (3 points, 3 comments)
    4. Will these finance topics be covered on the final? (3 points, 9 comments)
    5. Anyone get set up with Proctortrack? (2 points, 10 comments)
    6. Incentives Quiz Discussion (2-01, Lesson 11.8) (2 points, 3 comments)
    7. Anyone from Houston, TX (1 point, 1 comment)
    8. How can I trace my error back to a line of code? (assess learners) (1 point, 3 comments)
  35. 25 points, 5 submissions: jlamberts3
    1. Conda vs VirtualEnv (7 points, 8 comments)
    2. Cool Portfolio Backtesting Tool (6 points, 6 comments)
    3. Warren Buffett wins $1M bet made a decade ago that the S&P 500 stock index would outperform hedge funds (6 points, 12 comments)
    4. Windows Ubuntu Subsystem Putty Alternative (4 points, 0 comments)
    5. Algorithmic Trading Of Digital Assets (2 points, 0 comments)
  36. 25 points, 4 submissions: suman_paul
    1. Grade statistics (9 points, 3 comments)
    2. Machine Learning book by Mitchell (6 points, 11 comments)
    3. Thank You (6 points, 6 comments)
    4. Assignment1 ready to be cloned? (4 points, 4 comments)
  37. 25 points, 3 submissions: Spareo
    1. Submit Assignments Function (OS X/Linux) (15 points, 6 comments)
    2. Quantsoftware Site down? (8 points, 38 comments)
    3. ML4T_2017Spring folder on Buffet server?? (2 points, 5 comments)
  38. 24 points, 14 submissions: nelsongcg
    1. Is it realistic for us to try to build our own trading bot and profit? (6 points, 21 comments)
    2. Is the risk free rate zero for any country? (3 points, 7 comments)
    3. Models and black swans - discussion (3 points, 0 comments)
    4. Normal distribution assumption for options pricing (2 points, 3 comments)
    5. Technical analysis for cryptocurrency market? (2 points, 4 comments)
    6. A counter argument to models by Nassim Taleb (1 point, 0 comments)
    7. Are we demandas to use the sample for part 1? (1 point, 1 comment)
    8. Benchmark for "trusting" your trading algorithm (1 point, 5 comments)
    9. Don't these two statements on the project description contradict each other? (1 point, 2 comments)
    10. Forgot my TA (1 point, 6 comments)
  39. 24 points, 11 submissions: nurobezede
    1. Best way to obtain survivor bias free stock data (8 points, 1 comment)
    2. Please confirm Midterm is from October 13-16 online with proctortrack. (5 points, 2 comments)
    3. Are these DTlearner Corr values good? (2 points, 6 comments)
    4. Testing gen_data.py (2 points, 3 comments)
    5. BagLearner of Baglearners says 'Object is not callable' (1 point, 8 comments)
    6. DTlearner training RMSE none zero but almost there (1 point, 2 comments)
    7. How to submit analysis using git and confirm it? (1 point, 2 comments)
    8. Passing kwargs to learners in a BagLearner (1 point, 5 comments)
    9. Sampling for bagging tree (1 point, 8 comments)
    10. code failing the 18th test with grade_learners.py (1 point, 6 comments)
  40. 24 points, 4 submissions: AeroZach
    1. questions about how to build a machine learning system that's going to work well in a real market (12 points, 6 comments)
    2. Survivor Bias Free Data (7 points, 5 comments)
    3. Genetic Algorithms for Feature selection (3 points, 5 comments)
    4. How far back can you train? (2 points, 2 comments)
  41. 23 points, 9 submissions: vsrinath6
    1. Participation check #3 - Haven't seen it yet (5 points, 5 comments)
    2. What are the tasks for this week? (5 points, 12 comments)
    3. No projects until after the mid-term? (4 points, 5 comments)
    4. Format / Syllabus for the exams (2 points, 3 comments)
    5. Has there been a Participation check #4? (2 points, 8 comments)
    6. Project 3 not visible on T-Square (2 points, 3 comments)
    7. Assess learners - do we need to check is method implemented for BagLearner? (1 point, 4 comments)
    8. Correct number of days reported in the dataframe (should be the number of trading days between the start date and end date, inclusive). (1 point, 0 comments)
    9. RuntimeError: Invalid DISPLAY variable (1 point, 2 comments)
  42. 23 points, 8 submissions: nick_algorithm
    1. Help with getting Average Daily Return Right (6 points, 7 comments)
    2. Hint for args argument in scipy minimize (5 points, 2 comments)
    3. How do you make money off of highly volatile (high SDDR) stocks? (4 points, 5 comments)
    4. Can We Use Code Obtained from Class To Make Money without Fear of Being Sued (3 points, 6 comments)
    5. Is the Std for Bollinger Bands calculated over the same timespan of the Moving Average? (2 points, 2 comments)
    6. Can't run grade_learners.py but I'm not doing anything different from the last assignment (?) (1 point, 5 comments)
    7. How to determine value at terminal node of tree? (1 point, 1 comment)
    8. Is there a way to get Reddit announcements piped to email (or have a subsequent T-Square announcement published simultaneously) (1 point, 2 comments)
  43. 23 points, 1 submission: gong6
    1. Is manual strategy ready? (23 points, 6 comments)
  44. 21 points, 6 submissions: amchang87
    1. Reason for public reddit? (6 points, 4 comments)
    2. Manual Strategy - 21 day holding Period (4 points, 12 comments)
    3. Sharpe Ratio (4 points, 6 comments)
    4. Manual Strategy - No Position? (3 points, 3 comments)
    5. ML / Manual Trader Performance (2 points, 0 comments)
    6. T-Square Submission Missing? (2 points, 3 comments)
  45. 21 points, 6 submissions: fall2017_ml4t_cs_god
    1. PSA: When typing in code, please use 'formatting help' to see how to make the code read cleaner. (8 points, 2 comments)
    2. Why do Bollinger Bands use 2 standard deviations? (5 points, 20 comments)
    3. How do I log into the [email protected]? (3 points, 1 comment)
    4. Is midterm 2 cumulative? (2 points, 3 comments)
    5. Where can we learn about options? (2 points, 2 comments)
    6. How do you calculate the analysis statistics for bps and manual strategy? (1 point, 1 comment)
  46. 21 points, 5 submissions: Jmitchell83
    1. Manual Strategy Grades (12 points, 9 comments)
    2. two-factor (3 points, 6 comments)
    3. Free to use volume? (2 points, 1 comment)
    4. Is MC1-Project-1 different than assess_portfolio? (2 points, 2 comments)
    5. Online Participation Checks (2 points, 4 comments)
  47. 21 points, 5 submissions: Sergei_B
    1. Do we need to worry about missing data for Asset Portfolio? (14 points, 13 comments)
    2. How do you get data from yahoo in panda? the sample old code is below: (2 points, 3 comments)
    3. How to fix import pandas as pd ImportError: No module named pandas? (2 points, 4 comments)
    4. Python Practice exam Question 48 (2 points, 2 comments)
    5. Mac: "virtualenv : command not found" (1 point, 2 comments)
  48. 21 points, 3 submissions: mharrow3
    1. First time reddit user .. (17 points, 37 comments)
    2. Course errors/types (2 points, 2 comments)
    3. Install course software on macOS using Vagrant .. (2 points, 0 comments)
  49. 20 points, 9 submissions: iceguyvn
    1. Manual strategy implementation for future projects (4 points, 15 comments)
    2. Help with correlation calculation (3 points, 15 comments)
    3. Help! maximum recursion depth exceeded (3 points, 10 comments)
    4. Help: how to index by date? (2 points, 4 comments)
    5. How to attach a 1D array to a 2D array? (2 points, 2 comments)
    6. How to set a single cell in a 2D DataFrame? (2 points, 4 comments)
    7. Next assignment after marketsim? (2 points, 4 comments)
    8. Pythonic way to detect the first row? (1 point, 6 comments)
    9. Questions regarding seed (1 point, 1 comment)
  50. 20 points, 3 submissions: JetsonDavis
    1. Push back assignment 3? (10 points, 14 comments)
    2. Final project (9 points, 3 comments)
    3. Numpy versions (1 point, 2 comments)
  51. 20 points, 2 submissions: pharmerino
    1. assess_portfolio test cases (16 points, 88 comments)
    2. ML4T Assignments (4 points, 6 comments)

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  30. ybai67 (96 points, 41 comments)
  31. JuanCarlosKuriPinto (95 points, 54 comments)
  32. acschwabe (93 points, 58 comments)
  33. pharmerino (92 points, 47 comments)
  34. jgeiger (91 points, 28 comments)
  35. Zapurza (88 points, 70 comments)
  36. jyoms (87 points, 55 comments)
  37. omscs_zenan (87 points, 44 comments)
  38. nurobezede (85 points, 64 comments)
  39. BelaZhu (83 points, 50 comments)
  40. jason_gt (82 points, 36 comments)
  41. shuang379 (81 points, 64 comments)
  42. ggatech (81 points, 51 comments)
  43. nitinkodial_gatech (78 points, 59 comments)
  44. harshsikka123 (77 points, 55 comments)
  45. bkeenan7 (76 points, 49 comments)
  46. moxyll (76 points, 32 comments)
  47. nelsongcg (75 points, 53 comments)
  48. nickzelei (75 points, 41 comments)
  49. hunter2omscs (74 points, 29 comments)
  50. pointblank41 (73 points, 36 comments)
  51. zheweisun (66 points, 48 comments)
  52. bs_123 (66 points, 36 comments)
  53. storytimeuva (66 points, 36 comments)
  54. sva6 (66 points, 31 comments)
  55. bhrolenok (66 points, 27 comments)
  56. lingkaizuo (63 points, 46 comments)
  57. Marvel_this (62 points, 36 comments)
  58. agifft3_omscs (62 points, 35 comments)
  59. ssung40 (61 points, 47 comments)
  60. amchang87 (61 points, 32 comments)
  61. joshuak_gatech (61 points, 30 comments)
  62. fall2017_ml4t_cs_god (60 points, 50 comments)
  63. ccrouch8 (60 points, 45 comments)
  64. nick_algorithm (60 points, 29 comments)
  65. JetsonDavis (59 points, 35 comments)
  66. yjacket103 (58 points, 36 comments)
  67. hilo260 (58 points, 29 comments)
  68. coolwhip1234 (58 points, 15 comments)
  69. chvbs2000 (57 points, 49 comments)
  70. suman_paul (57 points, 29 comments)
  71. masterm (57 points, 23 comments)
  72. RolfKwakkelaar (55 points, 32 comments)
  73. rpb3 (55 points, 23 comments)
  74. venkatesh8 (54 points, 30 comments)
  75. omscs_avik (53 points, 37 comments)
  76. bman8810 (52 points, 31 comments)
  77. snladak (51 points, 31 comments)
  78. dfihn3 (50 points, 43 comments)
  79. mlcrypto (50 points, 32 comments)
  80. omscs-student (49 points, 26 comments)
  81. NellVega (48 points, 32 comments)
  82. booglespace (48 points, 23 comments)
  83. ccortner3 (48 points, 23 comments)
  84. caa5042 (47 points, 34 comments)
  85. gcalma3 (47 points, 25 comments)
  86. krushnatmore (44 points, 32 comments)
  87. sn_48 (43 points, 22 comments)
  88. thenewprofessional (43 points, 16 comments)
  89. urider (42 points, 33 comments)
  90. gatech-raleighite (42 points, 30 comments)
  91. chrisong2017 (41 points, 26 comments)
  92. ProudRamblinWreck (41 points, 24 comments)
  93. kramey8 (41 points, 24 comments)
  94. coderafk (40 points, 28 comments)
  95. niufen (40 points, 23 comments)
  96. tholladay3 (40 points, 23 comments)
  97. SaberCrunch (40 points, 22 comments)
  98. gnr11 (40 points, 21 comments)
  99. nadav3 (40 points, 18 comments)
  100. gt7431a (40 points, 16 comments)

Top Submissions

  1. [Project Questions] Unit Tests for assess_portfolio assignment by reyallan (58 points, 52 comments)
  2. [Project Questions] Unit Tests for optimize_something assignment by agifft3_omscs (53 points, 94 comments)
  3. Proper git workflow by jan-laszlo (43 points, 19 comments)
  4. Exam 2 Information by yokh_cs7646 (39 points, 40 comments)
  5. A little more on Pandas indexing/slicing ([] vs ix vs iloc vs loc) and numpy shapes by davebyrd (37 points, 10 comments)
  6. Project 1 Megathread (assess_portfolio) by davebyrd (34 points, 466 comments)
  7. defeat_learner test case by swamijay (34 points, 38 comments)
  8. Project 2 Megathread (optimize_something) by tuckerbalch (33 points, 475 comments)
  9. project 3 megathread (assess_learners) by tuckerbalch (27 points, 1130 comments)
  10. Deadline extension? by johannes_92 (26 points, 40 comments)

Top Comments

  1. 34 points: jgeiger's comment in QLearning Robot project megathread
  2. 31 points: coolwhip1234's comment in QLearning Robot project megathread
  3. 30 points: tuckerbalch's comment in Why Professor is usually late for class?
  4. 23 points: davebyrd's comment in Deadline extension?
  5. 20 points: jason_gt's comment in What would be a good quiz question regarding The Big Short?
  6. 19 points: yokh_cs7646's comment in For online students: Participation check #2
  7. 17 points: i__want__piazza's comment in project 3 megathread (assess_learners)
  8. 17 points: nathakhanh2's comment in Project 2 Megathread (optimize_something)
  9. 17 points: pharmerino's comment in Midterm study Megathread
  10. 17 points: tuckerbalch's comment in Midterm grades posted to T-Square
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