Sector Rotation Based Algorithmic Trading Strategies for Stocks and ETFs

In the following we present an analysis of Sector Rotation based Algorithmic Trading Strategies which rely upon quantitative equity sector predictions computed by aggregating our AI forecasting algorithm’s daily signals for S&P 500 stocks. We show that these aggregated predictions result in high performing trading strategies with:
  • Sharpe ratios reaching 1.48
  • Returns of up to 70.5% in a 2-year time period
  • The possibility of trading up to 195 million US dollars

Stock Market Forecast: Chaos Theory Revealing How the Market Works

I Know First Research | May 8th 2014

How Can We Predict the Financial Markets by Using Algorithms? Common fallacies about markets claim markets are unpredictable. However, chaos theory together with powerful algorithms proves such statements are wrong. Markets are chaotic systems with complex dynamics, yet to a certain extent we can make valid stock market forecasts. Using these forecasts generated by cutting-edge predictive algorithms together with a careful risk management strategy may give a trader a significant competitive advantage.

Markets Are Complex Systems

Looking at the common fallacies about stock markets, we can see two major groups. The first group is connected to the classical economic theory, which claims that markets are 100% efficient, and as such unpredictable. However, trying to make predictions regarding the markets is useless anyway, as no stock can be possibly be a better deal than another. Both of them are efficient and everybody in the market has perfect information available to them. From our daily lives it is obvious that this does not truly reflect reality. There are people who actually profit trading stocks, which should not be possible in this idealistic market of economy theories.

Day Trading Strategy: An In-depth Analysis of Realistic Back-Tests

Daniel Tal is a Quantitative Analyst at I Know First. He is currently a candidate for his bachelor's degree in Computer Science and Business Management at Columbia University.

  • Implementation of IKF strategy in intraday trading environment
  • Quantopian slippage and commissions models used to simulate real-time trading
  • Data and statistical Analysis of the methods used to gain day trading returns
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I Know First Live Forecast Evaluation: Based On New Global Volatility Adjusted Approach

Top S&P 500 Stocks

Executive Summary

As of December 2018, I Know First finished a performance evaluation of the live AI-based predictive forecasts for the new S&P 500 stock strategy sent to customers. This evaluation clearly demonstrates the consistent out-performance of I Know First’s forecasts vs the S&P 500 index and previous stock picking methods. This evaluation is part of our continuous studies of live I Know First’s AI predictive algorithm performance.

S&P 500 Highlights:

  • Selecting the S&P 500 stocks with only the top 5 adjusted signal strength provides the highest return consistently beating other filters for each time horizon.
  • There is a clear correlation between the length of the time horizon and the return as the length increases the accuracy and performance of the I Know First algorithm dramatically improves.
  • For the three-month time horizon all signal filters outperform the benchmark with the top 5 signal providing a return of 42% more than the benchmark.

Read The Evaluation Report

Evaluation Report For The Nikkei 225 Stock Universe – Consistently Outperforming Benchmarks

Executive Summary

In this Live Forecast Evaluation Report, we will examine the performance of the forecasts generated by the I Know First AI Algorithm for the Japanese stock market and sent to our customers on a daily basis. Our analysis covers the time period from January 1, 2018 – November 31, 2018. The following results were observed when signal and predictability filters were applied in order to pick the best performing stocks out of the most predictable ones. The main findings for the returns distribution of stock filters (stocks subsets) for the Nikkei 225 universe are outlined below:

Nikkei 225 Highlights:

  • Signal indicator filter applied to Top 30 most predictable stocks provides the highest return of 3.80% for Top 10 stocks on 3-months’ investment horizon.
  • We observe clear increasing trend on returns improving with the increase of forecast time horizon – the change in returns from 1 month to 3 months is more than 1361.5% for Top 10 stocks.
  • Top 10 stocks significantly out-perform both benchmarks, including Nikkei 225 actual performance recorded over the time under consideration, by over 475%.
The common pattern between the forecasts’ performance for the above stock universe is that systematic filtering by both signal and predictability provides the most benefit for long term investments, hence are more suited for private and institutional investors whose primary goal is to systematically identify assets which will provide the most gains of its value going forward in time.

Read The Evaluation Report

Evaluation Report For The Currencies Market

Executive Summary

In this Live Forecast Evaluation Report, we will examine the performance of the forecasts generated by the I Know First AI Algorithm for the Currency market which were delivered to our customers on a daily basis. Our analysis covers the time period from January 1, 2018 – November 31, 2018. We present below the key observations when signal and predictability filters were applied in order to pick the best performing currency pairs out of the most predictable ones:    

Currencies Universe Highlights:

  • The Top 10 most predictable currency pairs on 3-months’ investment horizon provided the highest return of 2.02% and beat the benchmark by 0.11%.
  • We monitor an improving return with the increase of the forecast time horizon¬- the difference in return from 1 month to 3 months for the Top 10 currency pairs is 1.42%.
  • Top 10 currency pairs outperform the benchmark, whereas Top 20 currency pairs outperform the benchmark in 3 out of 5 cases.

I Know First Live Evaluation Report For The Singaporean Stock Universe: Top 5 Stock Signals Return 2.30% in A 3-Month Investment Horizon

Executive Summary

The purpose of this report is to present the results of live forecast performance evaluation for I Know First AI Algorithm, specifically for Singaporean stock market. The following results were observed when signal and predictability filters were applied in order to pick the best performing stocks out of the most predictable ones. The period under evaluation is from January 1st,2018 to November 30th, 2018. The corresponding returns distribution of stock filters (stocks subsets) for both Singaporean stock market universe and the main findings are below:

Singaporean Stock Market Universe Highlights:

  • Signal indicator filter applied to Top 30 stocks by predictability provides the highest return of 2.30% for a 3-months’ investment horizon at Top 5 signals level
  • There is a clear increasing trend for returns’ improvement with the time horizon increase
  • Top 5 stocks by signal significantly out-perform the benchmark, in every time-horizon
The above results were obtained based on forecasts’ evaluation over the specific time period using  consecutive filtering approach – by predictability, then by signal, to give general overview of the forecasting capabilities of the algorithm for specific stock universe.

Read The Evaluation Report

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