I Know First Weekly Review Algorithmic Performance: November 16th, 2020
I Know First Weekly Newsletter
Investment Selection Using AI Predictive Algorithm
November 16, 2020
I Know First Evaluation Report for Highest Implied Volatility Options
Executive Summary
In this stock market forecast evaluation report, we will examine the performance of the forecasts generated by the I Know First AI Algorithm for Highest Implied Volatility Options for long and short positions which were sent daily to our customers. Our analysis covers the period from May 15th, 2020, to October 7th, 2020.
Top Implied Volatility Options Highlights
- All the signal groups' returns on the short-term horizon outperformed the S&P 500 Index, especially the ones for the 7 and 14 days time horizons.
- The Top 10 and Top 5 signal groups outperformed the S&P 500 Index by over 5% and 15%, respectively, for the 3 months time horizon.
- Higher signals had higher returns for every time horizons except for the 3 days time horizon.
I Know First Evaluation Report For Undervalued Stocks
Executive Summary
In this Know First forecast evaluation report, we will examine the performance of the forecasts generated by the I Know First AI Algorithm for the Low P/E Stocks, a subpackage of the Fundamental package, for short and long positions that were sent daily to our customers. Our Analysis covers the period from May 17, 2020, until September 9, 2020. We will start with an introduction to our asset picking for undervalued stocks and benchmarking methods. In this case, it apply to the universe covered by us in the Low PE subpackage.
Top Undervalued Stocks Highlights
- The Top 10 and Top 5 signal groups consistently outperformed the S&P 500 Index.
- All the group returns had a good performance, especially the ones for the 14 days and 1-month time horizon. Every group on those time horizons registered a significant higher return than the S&P 500 Index.
- The Top 5 signal group significantly outperformed the S&P 500 for all time horizons.
I Know First Evaluation Report For Interest Rates Assets Universe
Executive Summary
- Top 5 signals provided the most predictable stocks with a return of 4.85% in a 3-month investment horizon, beating the benchmark by 4.29%.
- There is a clear positive correlation between increasing time horizons and heightened investment returns.
- The benchmark was over-performed in the top 20, 10 and 5 signal classes for every time horizon - from 3 days all the way up to 3 months.
Read The Evaluation Report
I Know First Live Forecast Evaluation Report For Under 10 Dollars Stocks Package
This performance evaluation for the Under 10 Dollars stocks package was written by Diana Na Kyoung Lee, an Applied Math-Computer Science student at Brown University.
Executive Summary
In this forecast evaluation report, we will examine the performance of the forecasts generated by the I Know First AI Algorithm for stocks from the Stocks Under 10 Dollars Package, which is sent to our customers on a daily basis. Our analysis covers the time period from 1 April 2018 to 31 May 2019. We will start with an introduction to our asset picking and benchmarking methods and then apply it to the stock universe of all of the stocks covered by us in the Under 10 Dollars Package. We will then compare returns based on our algorithm with the benchmark performance over the same period.
Stock Forecast Evaluation Report For US Stock Market – Significantly Beating S&P 500 Index
Executive Summary
In this stock forecast evaluation report, we will examine the performance of the forecasts generated by the I Know First AI Algorithm for the US stock market and sent to our customers on a daily basis. Our analysis covers time period from January 1, 2019 to May 23, 2019.
- Top 5 signals provided the most predictable stocks with a return of 10.42% in a 3-month investment horizon, beating the benchmark by 1.61%.
- There is a clear correlation between increasing time horizons and investment return.
- The benchmark was over-performed in the top 10 and 5 signal classes.
The above results were obtained based on the stock forecast 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. The following sections of this study will develop
I Know First Live Forecast Evaluation for Western Markets Based On New Global Volatility Adjusted Approach
Executive Summary
As of December 2018, I Know First finished a performance evaluation of the live AI-based predictive forecasts for the new West stock strategy sent to customers. This evaluation clearly demonstrates the consistent out-performance of I Know First’s forecasts vs. the entirety of stocks within the West Market. The West Market is comprised of stocks in Western countries such as the U.S., UK, Canada, and Brazil. This evaluation is part of our continuous studies of live I Know First’s AI predictive algorithm performance.
West Market Highlights:
- Selecting the West Market stocks with the top 5 signal adjusted strength provides the highest return consistently beating other filters for the 2-week and 3-month horizons
- Selecting the All signals indicator yielded the best results for the 3-day time horizon
- There is a positive 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 3-day, 1-week, 2-week, 1-month, and 3-month time horizons all signal filters outperform the benchmark with the top 10 signal on the 3-month horizon providing the largest return of 2.11%
Evaluation Period and Universe
In this Live Forecast Evaluation Report, we will examine the performance of the forecasts generated by the I Know First AI Algorithm for the West Market stock universe. Our analysis covers the time period from January 1, 2018 – December 1, 2018. We present below the optimal stock picking strategy for this period. This period was chosen since this was a milestone in which I Know First introduced a major new version of the stock picking method for West Market investment universe. It includes analysis of all the predictions generated by the algorithm and sent daily to I Know First’s clients over this time period. The results of this study illustrate the significant positive effects of the algorithm’s continuous improvement utilizing advanced machine learning and AI capabilities.
The asset universe under consideration is the full 10,200 set of assets that I Know First forecasts. These assets include stocks, commodities and currency pairs. Each daily forecast sent to I Know First’s clients includes predictions for the following time horizons: 3 days, 7 days, 14 days, 1 month, 3 month and 1 year.
About the I Know First Algorithm
The I Know First self-learning algorithm analyses, models, and predicts the stock market. The algorithm is based on Artificial Intelligence (AI) and Machine Learning (ML) and incorporates elements of Artificial Neural Networks and Genetic Algorithms.
The system outputs the predicted trend as a number, positive or negative, along with a wave chart that predicts how the waves will overlap the trend. This helps the trader to decide which direction to trade, at what point to enter the trade, and when to exit. Since the model is 100% empirical, the results are based only on factual data, thereby avoiding any biases or emotions that may accompany human derived assumptions. The human factor is only involved in building the mathematical framework and providing the initial set of inputs and outputs to the system. The algorithm produces a forecast with a signal and a predictability indicator. The signal is the number in the middle of the box. The predictability is the number at the bottom of the box. At the top, a specific asset is identified. This format is consistent across all predictions.
Our algorithm provides two independent indicators for each asset – Signal and Predictability.
The Signal is the predicted strength and direction of movement of the asset. Measured from -inf to +inf.
The predictability indicates our confidence in that result. It is a Pearson correlation coefficient between past algorithmic performance and actual market movement. Measured from -1 to 1.
Here is the detailed description of the heatmap.
Our New Stock
I Know First Live Forecast Evaluation for Eastern Markets Based On New Global Volatility Adjusted Approach
Executive Summary
As of December 2018, I Know First finished a performance evaluation of the live AI-based predictive forecasts for the new East stock strategy sent to customers. This evaluation clearly demonstrates the consistent out-performance of I Know First’s forecasts vs. the entirety of stocks within the East Market. The East Market is comprised of stocks in Eastern countries such as China, Japan, Australia, and New Zealand. This evaluation is part of our continuous studies of live I Know First’s AI predictive algorithm performance.
East Market Highlights:
- Selecting the East Market stocks with the top 5 signal adjusted strength provides the highest return consistently beating other filters for each time horizon with the exception of the top 10 signal, which provide the highest return for the 3-month 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 3-day, 1-week, 2-week, 1-month, and 3-month time horizons all signal filters outperform the benchmark with the top 10 signal on the 3-month horizon providing the largest return of 13.88%
Evaluation Period and Universe
In this Live Forecast Evaluation Report, we will examine the performance of the forecasts generated by the I Know First AI Algorithm for the East Market stock universe. Our analysis covers the time period from January 1, 2018 – December 1, 2018. We present below the optimal stock picking strategy for this period. This period was chosen since this was a milestone in which I Know First introduced a major new version of the stock picking method for East Market investment universe. It includes analysis of all the predictions generated by the algorithm and sent daily to I Know First’s clients over this time period. The results of this study illustrate the significant positive effects of the algorithm’s continuous improvement utilizing advanced machine learning and AI capabilities.
The asset universe under consideration is the full 10,200 set of assets that I Know First forecasts. These assets include stocks, commodities and currency pairs. Each daily forecast sent to I Know First’s clients includes predictions for the following time horizons: 3 days, 7 days, 14 days, 1 month, 3 month and 1 year.
About the I Know First Algorithm
The I Know First self-learning algorithm analyses, models, and predicts the stock market. The algorithm is based on Artificial Intelligence (AI) and Machine Learning (ML) and incorporates elements of Artificial Neural Networks and Genetic Algorithms.
The system outputs the predicted trend as a number, positive or negative, along with a wave chart that predicts how the waves will overlap the trend. This helps the trader to decide which direction to trade, at what point to enter the trade, and when to exit. Since the model is 100% empirical, the results are based only on factual data, thereby avoiding any biases or emotions that may accompany human derived assumptions. The human factor is only involved in building the mathematical framework and providing the initial set of inputs and outputs to the system. The algorithm produces a forecast with a signal and a predictability indicator. The signal is the number in the middle of the box. The predictability is the number at the bottom of the box. At the top, a specific asset is identified. This format is consistent across all predictions.
Our algorithm provides two independent indicators for each asset – Signal and Predictability.
The Signal is the predicted strength and direction of movement of the asset. Measured from -inf to +inf.
The predictability indicates our confidence in that result. It is a Pearson correlation coefficient between past algorithmic performance and actual market movement. Measured from -1 to 1.
Here is the detailed description of the heatmap.
Our New Stock Picking Method
The new stock picking method takes all 10,200 assets, the global set, that are forecasted by I Know First. The assets are then filtered by predictability and the top 30 most predictable assets are selected. A volatility measurement is then conducted. These top 30 assets are then adjusted for this volatility measurement. The East Market stocks are then selected from this final set of top 30 global most predictable assets with volatility adjusted signal.
As mentioned before, the asset universe under consideration is the full 10,200 set of assets covered by I Know First forecast and includes stocks, commodities and currency pairs. By implementing this new stock picking method, we are selecting only the most predictable assets and the ones with the highest signals. However, there could be occasions where no East Market stocks fall in this final set of 30 assets. If this was the case, a stock selection will not take place on such occasion.
The Performance Evaluation Method
We perform evaluations on the individual forecast level. It means that we calculate what would be the return of each forecast we have issued for each horizon in the testing period. Then, we take the average of those results by strategy and forecast horizon.
For example, to evaluate the performance of our 1-month forecasts, we calculate the return of each trade by using this formula:
This simulates a client purchasing the asset based on our prediction and selling it exactly 1 month in the future.
We iterate this calculation for all trading days in the analyzed period and average the results.
Note that this evaluation does not take a set portfolio and follow it. This is a different evaluation method at the individual forecast level.
The Benchmarking Method
The theory behind our benchmarking method is the “Null hypothesis“, meaning buying every stock in the particular asset universe regardless of our I Know First indicators.
In comparison, only when our signals are of high signal strength and high predictability for a specific stock, then it should be bought (or shorted).
The ratio of our signal’s trading results to benchmark results indicates the quality of the system and our indicators.
Example: A benchmark for the 3 days horizon means buy on each day and sell exactly 3 business days afterwards. We then average the results to get the benchmark. This is to get an “apples to apples” comparison.
Performance
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