Alternative Data is growing as a necessary weapon for traders and quantitative investors. Yet there are many barriers to alternative data success. (Includes python code)
CloudQuant’s portfolio managers and quantitative algo traders look back on their starts in Algorithmic Trading. This candid overview allows everyone to see the “Things We Wish We Knew When We Started AlgoTrading”. This is a short collection of the interviews with some of our amazing coders here in the office
On February 8th Trevor Trinkino presented Machine Learning with FXCM in a webinar.
During this presentation, he promised to make available his machine learning Python Notebook and the supporting data file. These are available on our Google drive at:
The first book I got was “Hello World”. The book intimidated me, because I saw programming as a superpower, something only my dad was capable enough to do. I tried to learn it, but I just got bored very quickly. My dad, still persistent, decided it was time to try programming something we loved.
If you knew your trading strategy would work 50% of the time, would you commit your scarce savings to trade it? What if it worked 75% of the time? Backtesting gives one the confidence to know that your trading strategy will work.
IBM, the 100-year-old company, is wedging into a tight trade, but it looks like the Bulls are gearing to press a move higher. Just before year-end, the stock set a Three Inside Up Japanese candlestick pattern setting the stage for a rally.
Source code using TA-LIB and Python included.
December 19, 2017 Monday Google pressed new highs, but Tuesday closed out the day with a Harami Sell signal. Watch out for today. A negative close today boosts the negative outlook with the emergence of a Three Inside Down pattern. In this event, it will most likely mean that there will be a “little coal in Google stockholders stockings for Christmas”.
Anyone who has ever worked on developing a trading strategy from scratch knows the huge amount of difficulty that is required to get your logic right. … TA-LIB Turbo-Charges Your Research Loop: TA-Lib is widely used by quantitative researchers and software engineers developing automated trading systems and charts. This freely available tool allows you to gather information on over 200 stock market indicators.
In this video, we introduce you to Candlestick Bars, a store of Historic Market Data, how to access that data via Pythons Lists and how pointers work in lists.
A suggested a Zig-Zag trading strategy that bounces back and forth on the stock market to make small profits. Testing shows the strategy wouldn’t work.