AI Stock Picker: Quantitative Revolution

Sergey Okun  This AI Stock Picker article was written by Sergey Okun – Senior Financial Analyst at I Know First, Ph.D. in Economics.

  • Quantitative methods have undergone a long and successful path of development.
  • Renaissance’s Medallion fund earned over $100 billion with average annual returns of 66% before fees.
  • I Know First provides daily investment forecasts based on an advanced self-learning algorithm.

The Legacy of a Pioneer in Quantitative Market Analysis

Jim Simons, a mathematician who rose to become one of the most successful investors in contemporary financial history, passed away at the age of 86. A pioneer in cryptography and geometry, Simons revolutionized trading by implementing a computer-based quantitative approach in the 1980s, well ahead of its widespread adoption on Wall Street. He and his team leveraged trading algorithms and artificial intelligence to consistently beat the market.

At that time, many competitors were “fundamental” investors who interacted with corporate managers, closely examined balance sheets, and depended on their judgment and intuition to forecast the rises and falls of investments. While others perceived chaos in the market’s fluctuations, Simons, with his training in analyzing large data sets, believed that financial markets had more structure than most assumed. He believed that markets are not random and are somewhat predictable. He thought that there were statistical anomalies that could be taken advantage of. He set the task to develop an automated trading system that could detect fleeting and unnoticed patterns in prices and be free from human interference.

By 1990, Simons and his team had developed methods to profit from various markets, including currency and commodities, by leveraging short-term patterns. Renaissance Technologies uncovered a strategy to generate billions from stock trading. Their successful approach involved holding investments for brief intervals, often minutes, delegating trading decisions to computers, and maintaining unparalleled secrecy. From 1988 to 2018, Renaissance’s Medallion fund earned over $100 billion with average annual returns of 66% before high fees. Despite these fees, annual returns reached 39%.

Continuous Quantitative Traditions

In contemporary finance, an increasing number of investors are embracing a mathematical, computer-driven approach. Approximately one-third of total funds are overseen by quant firms, while businesses across different sectors depend on algorithms. I Know First, Ltd. provides daily investment forecasts based on an advanced self-learning algorithm. I Know First’s algorithm is based on decades of research into the nature of chaotic systems, self-similarity, fractals, and machine learning algorithms. The algorithm uses artificial neural networks to process large amounts of data from various sources, such as historical prices, volumes, and indicators. The algorithm then generates forecasts for over 13 500 assets and growing, covering stocks, ETFs, commodities, futures, currencies, cryptocurrencies, interest rates, and world indices. The algorithm also provides a predictability indicator, which allows users to identify and focus on the most predictable assets. I Know First’s algorithm is self-learning, adaptable, and evolving, meaning that it constantly updates and improves its forecasts based on new data and feedback. The algorithm also takes a holistic approach, modeling the market as one whole complex system using data from all markets to make its predictions.

I Know First provides investment solutions for both individual and institutional investors, utilizing an advanced AI self-learning algorithm to gain a competitive advantage. We offer a personalized approach to our institutional clients, assisting them in their investment process based on their specific needs and preferences (Find more information here).

We offer two tiers of solutions:

  • Tier 1 – the daily AI-powered predictions
  • Tier 2 – AI-powered systematic strategies

In the context of tier 1, we provide daily forecasts for long and short trading across six time horizons, as outlined in our forecast packages (you can access them here). Before the stock market opened on May 19th, 2024, we had sent recommendations to our clients where we had identified the most promising stocks from the S&P 500 stocks package to buy on a 14-day horizon.

For this 7 Days stock forecast the algorithm has successfully predicted 9 out of 10 movements. CLSK was our best stock pick with a return of 85.07%. Other notable stocks were CELH and ALGN with a return of 9.73% and 8.79%. With these notable trade returns, the package itself registered an average return of 11.55% compared to the S&P 500’s return of 0.69% for the same period.

In Tier 2, we offer advanced investment strategies tailored to the specific needs and preferences of institutional clients. We provide various strategies depending on strategy volatility, drawdown, short/long positions, and offer strategies not only on a stock level but also on an industry level through industry ETF trading. Below, we can observe the performance of one of the sector rotation strategies based on level 2 ETFs for the period from January 1st, 2020, to April 12th, 2024.

The strategy involves trading GICS level 2 ETFs based on the majority direction. While, the Level 1 Sectors include broad segments of the economy, such as technology, healthcare, finance, and consumer goods to provide a high-level view of the market. Level 2 Industries goes deep into specific industries. For example, within the technology sector (Level 1), you might find industries like semiconductors, software, and hardware. These industries offer a more detailed perspective on the market. The strategy provides a positive return of 613.64% which exceeded the S&P 500 return by 551.70%. Below we can notice the strategy behavior for each year.


Analysis of financial markets using quantitative methods has proven its effectiveness and is actively used to generate positive returns. I Know First offers its algorithmic solutions to both private and institutional investors, who can access them through web or mobile platforms. Users can select from various packages and plans based on their needs and objectives. Additionally, users have the option to customize their quant trading solutions by choosing the assets, markets, time frames, and strategies they prefer.

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Please note-for trading decisions use the most recent forecast.