AI Stock Market Forecast – How to Spot Great Market Opportunities in The New Market Realm?

motek 1The stock prediction article was written by Tianyue Yu, Analyst at I Know First, Master’s candidate at Brandeis University.


  • AI technology is gaining attention in the stock market
  • Quantitative trading supported by machine learning fits the features of the post-pandemic market well
  • I Know First’s AI predictive algorithm can provide investors with timely forecasts across various asset classes and regions

What Can AI Stock Market Forecast Technology Bring to the Table?

The financial market is never stationary, especially after COVID-19 outbroke globally. The US stock market has been extremely volatile in the last twelve months, bringing big challenges to the stock market forecast. This trend also accelerated the application of artificial intelligence and machine learning techniques in algorithmic trading.

stock market forecast
(Source: Yahoo Finance)

After each trading day, investors get random news mostly through mass media. The information that comes in this way is usually full of noise and is influenced by stock market volatility. Artificial intelligence can use a large amount of market information, rule out the noise, and find patterns. While machine learning is the cornerstone for AI application in finance, by using the deep-learning technique, analysts’ time and energy can be saved by the computer’s self-learning and analysis ability. Specifically, deep-learning allows AI to prove to be a useful tool to help investors learn and spot market trends from the past and put the market data to the decision-making process in accordance with the speed demanded by the financial market.

stock market forecast
(Source: Investment Magazine)

Although machine learning techniques don’t start in the financial area, more companies are using those to guide investment. Popular applications include pattern discovery, sentimental analysis, and quantitative trade in the security market, and credit analysis in the banking system.

One of the sectors covered by artificial intelligence that is going largely unnoticed is wealth management. People are always eager to seek the most advanced technology to generate wealth. This new “wealth technology” now allows wealth managers to offer financial advice through artificial intelligence and use AI-driven solutions to conduct risk-assessment services and backtesting.

(Source: Zoidpay)

New Opportunities in the Post-Pandemic Market

The new market environment under the pandemic adds more color to the advantages of AI and machine learning techniques – pattern recognition and productivity improvement. Investors witnessed high volatility and trading frequency under the epidemic. For example, according to Morgan Stanley, the pandemic triggered broad selling across the market in the first quarter. The machine learning technique is good at dealing with this situation. Enhanced by AI technology, algorithmic trading models can analyze thousands of trades in a day to conduct high-frequency trading strategies in the most efficient way possible. The self-learning feature helps the models adapt to the changing market. Once experienced traders have defined the operation rules, machines will execute thousands or millions of trades each day, trying to take advantage of market inefficiencies that only exist over brief periods.

(Source: Google)

The next question is – how will the machine identify and pick the best stocks to maximize the returns for investors? Will it be robust in its recommendations over time and how to trust the machine which may see the market purely quantitatively? The answers to these questions are not simple, but the algorithms can do all the heavy-lifting and provide the users with the output that is designed to simplify the stock-picking process. Let us consider and example of the AI-driven stock market forecast from I Know First:

I Know First AI Forecast Structure

The key questions for investors are which assets should be invested in and what should be the weight should have an asset in my portfolio? These questions could be addressed with a simple heatmap that features asset attractiveness ranking and the sentiment regarding the future stock price movement. Therefore, the first question regarding which assets represent the best market opportunities is addressed with the position of each asset in the ranking. However, things get more complex when someone needs to decide how much weight needs to be put in a portfolio for a specific asset. Technically, the decision-making process remains the same – each investor distributes the weights in accordance with his risk-appetite and required return prospects. This is the moment when AI can provide numerical input for investors or their trading algorithms – signal and predictability pair. The signal represents the predicted movement and direction, be it an increase or decrease, for each particular asset; not a percentage or specific target price. In other words, the signal strength indicates how much the current price deviates from what the system considers an equilibrium or “fair” price. The predictability is the historical correlation between the past algorithmic predictions and the actual market movement for each particular asset.

long stock market forecast
Example of top S&P 500 stocks for long position forecast
long stock market forecast
Example of top Aggressive stocks for long positions forecast
short stock market forecast
Example of top Aggressive stocks for short positions forecast

Therefore, an investor can build an investment strategy based on his risk-return preferences and define rules for investment and trading using the signal-predictability value pairs. For instance, one can invest in S&P 500 index stocks and rely more on signal for shorter investment horizons, while for long-term positions to provide more weight on the most predictable assets. Another option may also be to trust the predictive algorithm, invest in aggressive stocks which could be more volatile but having a higher potential for return, and distribute weights equally among the top 10 stock picks identified by AI. This is a simple investment strategy, but sometimes paying out, even amid unstable coronavirus times both for long and short positions. As we see from the above, such an “equal-weights” approach can provide impressive returns and accuracy even within short periods.

AI Can Give Stock Market Forecast Amid New Market Realm

Artificial intelligence can help with investment opportunities research using its predictive power and machine learning capabilities utilizing various data. As such a recent paper found the relation between stock price and the sentiment in the news using the machine learning method. Essentially, machine learning techniques can give predictions based on sentiment analysis of news, social media comments, and other resources, besides quantitative data. For example, if an analyst believes that successful vaccine development is a positive signal for the market and set this as a rule for the algorithm model, the model will suggest a good investment opportunity when it “read” about the news that Pfizer announced a vaccine candidate against COVID-19 has achieved success in the first interim analysis of the final 3rd stage clinical study. However, such an approach relies heavily on the data quality and the ability of the algorithm to identify the relevant data for continuous analysis. We at I Know First, believe that the stock market, even though it is affected in many ways by politics and news, can be robustly and continuously predicted using purely quantitative market data. Below we present our AI-driven predictive algorithm concept:

stock market forecast
(Source: I know First)

The system is a predictive stock market 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 can 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.

This said I Know First forecasts cover a broad variety of assets (more than 10,500 items) for periods ranging from three-days to a one-year horizon to help investors capture the short-term momentum and long-term signals representing the best stock market opportunities. Another important feature of the algorithm is that it provides predictions for the market volatility indicators that provide insight into the overall market stability in the future.

volatility stock market forecast
Example of volatility indexes stock market forecast

Such volatility forecasts include the predictions for the major volatility indexes which coupled with our stocks predictions provide a solid market outlook that investors can integrate into their strategic investment decisions.

Secondly, given all the uncertainties that we are facing, it is important to capture comprehensive information from different markets and assets. 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.

Finally, 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. This results in the purely statistical and numbers-based forecasting approach that could be benchmarked against the regular analysts’ fundamental estimates, but used daily for continuous monitoring of investment portfolio.


Nowadays, investment is a business involving large amounts of data, absolute accuracy, and strong analysis ability. These features are where the advantages of AI and algorithm technology dominate. The quantitative models do not make decisions based on sentiments like hope, luck, and superstitions. They stick to the facts and objectives and they act fast.

The successful prediction of market volatility trend under the pandemic by the I Know First algorithm proves the adaptability of artificial intelligence and machine learning to uncertainties and even extreme market fluctuations. Therefore, AI sets up a new frontier that could stretch across every application in the investment business.

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Please note-for trading decisions use the most recent stock market forecast