Stock Market Predictions Executive Summary

In this forecast evaluation report, we examine the performance of the stock market predictions generated by the I Know First AI Algorithm for the S&P 500 and Nasdaq indices with time horizons ranging from 3 days to 1 year, which were delivered daily to our clients. Our analysis covers the time period from the 26^thNovember 2018 to 26^thJanuary 2020. Below, we present our key takeaways for checking hit ratios of our stock market predictions.

Stock Market Predictions Highlights:

• The best Hit Ratio is 82% for the 90 day-time horizon of Nasdaq ETF (QQQ) 
• Almost all forecasts are more than 70% accurate for the longest time horizons

Note that the above results were obtained as a result of an evaluation conducted over the specific time period to give a presentation for the S&P 500 and Nasdaq movements. The following report provides an extensive explanation of our methodology and a 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 forecasting on the Nasdaq and S&P 500 indices.

Stock Forecast Algorithm

The system is a predictive stock forecast algorithm based on Artificial Intelligence and Machine Learning with elements of Artificial Neural Networks and Genetic Algorithms incorporated in it.

This means the algorithm is able to create, modify, and delete relationships between different financial assets. Based on the relationships and the latest market data, the algorithm calculates its forecasts. Since the algorithm learns from its previous forecasts and is continuously adapting the relationships, it adapts quickly to changing market situations.

The I Know First Market Prediction System models and predicts the flow of money between the markets. It separates the predictable information from any “random noise”. It then creates a model that projects the future trajectory of the given market in the multidimensional space of other markets.

The system outputs the predicted trend as a number, positive or negative, along with the wave chart that predicts how the waves will overlap the trend. This helps the trader decide which direction to trade, at what point to enter the trade, and when to exit.

The model is 100% empirical, meaning it is based on historical data and not on any human derived assumptions. The human factor is only involved in building the mathematical framework and initially presenting to the system the “starting set” of inputs and outputs.

From that point onward, the computer algorithms take over, constantly proposing “theories”, testing them on years of market data, then validating them on the most recent data, which prevents over-fitting. If an input does not improve the model, it is “rejected” and another input can be substituted.

This bootstrapping system is self-learning, and thus live. The resulting formula is constantly evolving, as new daily data is added and a better machine-proposed “theory” is found.

Some stocks are members of several separate modules. Thus, multiple predictions can be obtained based on different data sets. Also, each module consists of a number of sub-modules, each giving an independent prediction. If sub-modules give contradictory predictions, this should be a warning sign. Six different filters are also employed to refine the predictions.

Learn How To Strategize With The Algorithm To Optimize Gains And Mitigate Risk

The Hit Ratio Calculation

The hit ratio helps us to identify the accuracy of our algorithm’s predictions.

We predict the direction of the movement of the S&P 500 and Nasdaq Indices using our algorithm. Our predictions are then compared against actual movements of the S&P 500 and Nasdaq benchmarks respectively within the same time horizon.

The hit ratio is then calculated as follows:  

S&P 500 Index and SPY ETF

When thinking of index funds as benchmarks for the whole economy, many experts tend to gravitate towards checking the S&P 500. This prominent index, followed by millions throughout the globe, has historically shined a light on the movements in the stock market. What the index does, in essence, is to choose the 500 largest publicly traded companies by order of market capitalization and produces a list of corporations to be tracked. It is clear that any preemptive indication of how those shares appreciate or depreciate could be a powerful and highly profitable tool for investors.

At the same time SPY is the best-recognized and oldest ETF and typically tops rankings for largest AUM and greatest trading volume. The fund tracks the massively popular US index, the S&P 500. Few realize that S&P’s index committee chooses 500 securities to represent the US large-cap space—not necessarily the 500 largest by market cap, which can lead to some omissions of single names. Still, the index offers outstanding exposure to the US large-cap space. SPY is a unit investment trust, an older but entirely viable structure. It can’t reinvest portfolio dividends between distributions; the resulting cash drag will slightly hurt performance in up markets and help in downtrends. SPY is extremely cheap to hold and SPY’s phenomenal trading volume makes it the perfect vehicle for tactical traders and mom and pop investors alike.

NASDAQ Index and QQQ ETF

On the other hand, when looking towards the health of growth-oriented stocks, a majority within the world of investing points toward the Nasdaq as the strongest indicator. The index focuses on mostly technology and internet-related firms, but also contains many financial, consumer, biotech, and industrial companies. The Nasdaq Composite, the leading index for the group, tracks over 3,300 stocks including Apple (AAPL), Intel (INTC), Facebook (FB), and Microsoft (MSFT).

Finally, QQQ is one of the best established and most traded ETFs in the world. It’s also one of the most unusual. Per the rules of its index, the fund only invests in non-financial stocks listed on NASDAQ, and effectively ignores other sectors too, causing it to skew massively away from a broad-based large-cap portfolio. QQQ has huge tech exposure, but it is not a ‘tech fund’ in the pure sense either. The fund’s arcane weighting rules further distance it from anything close to plain vanilla large-cap or pure-play tech coverage. The ETF is much more concentrated in its top holdings and is relatively volatile. Still, it is extremely large and liquid, and has huge name recognition for the underlying index, the NASDAQ-100.

High Volatility of Stock Indexes Between November 2018 and January 2020

Over the considered period the major world markets experienced significant volatility across all the sectors, so both S&P 500 and NASDAQ, as well as the above-mentioned ETFs, prices were hardly predictable almost on any horizons. As a result, the demand for the reliable and consistent prediction algorithm has spiked from investors and analysts community. Meanwhile, I Know First predictive algorithm provided daily forecasts for these assets and the following sections are going to present the results of these forecasts in terms of hit ratio on different time horizons. The below charts illustrate the volatility experienced by the analysed indexes and ETFs over the last year:

Evaluating the Stock Market Predictions Hit Ratio

Through the table above, we can see that I Know First has developed an algorithm that is able to consistently predict the S&P 500 and Nasdaq throughout various time periods. The best hit ratio reached by the algorithm was 82% for 90-day time horizons for the Nasdaq ETF. We can notice that the performances were more than 70% for 14-day time horizon and later. Regarding the table, algorithm effectiveness was better according to the length of the time horizon: the longer the time horizon was, the more efficient the algorithm was. This allows our investors to have a safer outlook when investing despite these volatile time periods.

Conclusion

This evaluation report presented the performance of I Know Frist’s algorithm showing the hit ratio for several time horizons. We have achieved good results particularly by forecasting the Nasdaq ETF with a hit ratio of 82%. These indicate that our services were able to predict the movement of these indexes correctly more than 8 out of 10 times. We can also notice that each index had almost the same hit ratio as its ETF. Thanks to our abilities to predict the S&P 500 and Nasdaq indices and related ETFs through our Artificial Intelligence system, we provide services to our clients in order to their investment is safer and more profitable. I Know First’s research team will continue to monitor the algorithm’s performance and derive relevant insights that will help provide the best algorithmic trading solutions to our clients.