July 18, 2019
This article was written by Talia Shakhnovsky, a Financial Analyst at I Know First.
Executive SummaryIn this forecast evaluation report, we will examine the performance of the forecasts generated by the I Know First AI Algorithm for assets from the short term signals Options universe provided as part of the Options Package, which is sent to our customers on a daily basis. Our analysis covers the time period from 1 January 2019 to 14 July 2019. We cover samsung galaxy s6 edge will start with an introduction to our asset picking and benchmarking methods and then apply it to the short term signals Options universe covered by us in the Options Package. We will then compare returns based on our algorithm with the benchmark performance over the same period. Below, we present our key takeaways from applying signal and predictability filters.
Options Short Term Signals Highlights:Top 5 signals had better returns in all time horizons than the Benchmark Index. The following report provides extensive explanation on our methodology and detailed analysis of the performance metrics that we obtained during the evaluation. This report is a new I Know First evaluation series illustrating the ability to provide successful short term forecasting for the Options Universe.
About the I Know First Algorithm
The I Know First self learning algorithm analyzes, models, and predicts the capital market, including stocks, bonds, currencies, commodities and interest cover samsung bianca rates markets. 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 cover burlon iphone 6 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 custodia cover samsung s6 edge 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 custodia cover iphone x xs movement of the asset. This is measured frominf to +inf.
The predictability indicates our confidence in that result. It is a Pearson correlation coefficient between past algorithmic performance and actual market movement. This is measured from1 to 1.
You can find a detailed description of our heatmap here.
The Asset Picking MethodThe method in this evaluation is as follows:
To fully utilize information provided by our forecast, we filter out the top X most predictable assets and rank them according to their predictability value. Thereafter, from them, we pick the top Y highest signals and re adjust the rankings accordingly.
By doing so we focus on the most predictable assets on the one hand, while capturing the ones with the highest signal on the other.
For example, a top 30 predictability filter with a top 10 signal filter means that on each day we take only the 30 most predictable assets from our asset universe, and then we pick from them the top 10 assets with the highest absolute signals. On the other hand, a top 30 predictability filter with a top 30 signal filter would imply that we are solely filtering based on predictability, since we are selecting all assets in this particular set which have already been filtered by predictability.
We use absolute signals since these strategies are long and short ones. open long position and, if negative, we open short position on such asset. This is to help us to identify the assets with the maximum magnitude of change, which is indiscriminate as to whether one adopts custodia cover huawei y5 2018 a short or long position.
The Performance Evaluation MethodWe perform evaluations on the individual forecast level. This means that we calculate the return of each forecast we have issued for each horizon in the testing period. We then take the average of those results based on our positions on different assets and forecast horizon.
For example, to evaluate the performance of our 1 month forecasts, we calculate the return note 2 cover samsung of each trade by using this formula:
This simulates a client purchasing the asset on the day we issue our prediction and selling it exactly 1 month in the future from that day.
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 Hit Ratio CalculationThe hit ratio helps us to identify the accuracy of our algorithm’s predictions.
Using our asset filtering method based on predictability and signal, we predict the direction of movement of different assets. Our predictions are then compared custodia cover samsung note 8 against actual movements of these assets within the same time horizon.
The hit ratio is then calculated as follows:
For instance, a 90% hit ratio for a top 30 predictability filter with a top 10 signal filter would imply that the algorithm correctly predicted the price movements of 9 out of 10 assets within this particular set of assets.
The Benchmarking MethodThe S 500 index is used as a benchmark. Particular assets should be bought (or shorted) when they have been identified to have high signal strength and high predictability. We compare our rate of return based on purchasing (or shorting) the top X assets after applying both the predictability and signal filters with the rate of return of the S 500 index in the same time horizon. This helps us to determine the effectiveness of our methodology against the average investor…