Stay Ahead Of The Curve: AI Weekly

Algorithmic Trading Strategy Video: Understanding I Know First's Signal Strength (Part 2) Last week, we introduced a tutorial that explained how to trade using Dr. Rotiman's cutting-edge signal strategy and I Know First's "Top 10 Stock Picks" chart. Click this link to see part two of the tutorial that dives into using Excel to trade. Watch here! Top S&P 500 Stocks: Daily Forecast and Global Model Performance Evaluation Report Evaluation highlights: Stock market forecasts that were generated by our Daily Forecast model obtained positive returns for all time horizons and outperformed the S&P 500 for all time horizons (3-days to 1-year).

We observed a consistent positive effect of signal-based filtering, besides one exception in the 90 days time horizon, additional screening by signal always resulted in higher performance.

The Global Model improved the performance even further – our algorithm’s forecast according to this new model enabled a more flexible trading strategy that generated robust returns compared to both the S&P 500 Benchmark and the traditional model performance on longer horizons.

The highest return of 6.86% was obtained by applying the Global Model on the 90-days time stock market forecast horizon. Read more. Stock Filtering by the I Know First Signal and Predictability Indicators In the following we explore a very simple analysis of these predictions: for each trading day from January to June 2016 we filter stocks from the S&P500 universe by their short-term I Know First predictabilities and signals and compute their average close-to-close returns per trade. In this analysis the predictabilities are filtered by fixed levels and the signals by daily quantiles. Mean returns per trade consistently increase along both I Know First prediction measures, peaking for the highest predictabilities and signals. Thus the two indicators are informative at all levels and, on average, higher indicators imply higher returns. The highest average return per trade achieved in this analysis (corresponding to the highest predictabilities and signals) equals 0.27% for the considered time frame versus a daily close-to-close mean return per trade of 0.08% for the S&P500 constituents in the same time period. Overall the analysis shows that the mean returns per trade and the mean return per trade to standard deviation ratio consistently grow with the I Know First indicators. Read more. Deep Learning Algorithms: The Future of Financial Investment The market for deep learning and AI is definitely an exciting one. It is becoming increasingly important, and I Know First Research and Development team is strongly involved into pioneering new methods, models and technology to predict financial markets. We see that the investors' demand for new quantitative trading solutions annually grows and the trend is to automate as much as possible while maintaining transparency and control over such systems. Although it is not a completely new trend for the market, it is the one which is going to be developing with more momentum as market data is becoming available to a wider public.



The article presents multiple insights into the workflow with the AI-powered predictions that are daily sent to our subscribers. The article covers fundamental topics, such as deep learning and its applications nowadays with special emphasis being put on financial markets. It also provides a perspective on the developments in these fields with explanation of the I Know First’s role in the machine learning community and our contributions into it. Read more. I Know First Algorithmic Trading Strategies This article presents a study conducted on a several algorithmic trading strategies that investors can apply when they want to elaborate I Know First’s AI algorithm as a tool for their investment analysis to reduce risk and maximize returns. The research elaborates on how one can build and apply sample of algorithmic trading strategies to a sample of daily forecasts.



The article presents a detailed overview of the forecast heatmap with explanations on its usage and links to additional resources that could benefit the beginner users. Next, the article proceeds to interpretation of the heatmap and various considerations on how to apply the signal and predictability value within algorithmic trading strategies using a few examples. Tactics, possible considerations and best practices are finalizing the article, making it the great tab-to-bookmark for any investor or analyst who is working on his or her algorithmic strategy based on I Know First stock predictions and wants to have easy and ready-to-go reference source. Read more. Want to learn more? ETF Trading Strategies Based on I Know First's Aggregated Algorithmic Forecasts

i24 News Channel Report: Uncovering the Best Investment Opportunities Using AI

MarketWatch Press Release: AI-Powered Stock Market Predictive Algorithm Successfully Outperforming Live on TV