AI Stock Forecast: Fighting the Irrational Crowd by Investing Through AI
Dr. Lipa Roitman, Co-Founder & CTO at I Know First, Ph.D from the Weizmann Institute of Science.
Sergey Okun – Senior Financial Analyst at I Know First, Ph.D. in Economics.
Highlights:
- Why do investors tend to irrational decisions?
- Improving decisions making with AI.
- Investing with AI for everyone.
Traps for Rational Investment
We are human and like any human we have biases that do not allow us to make rational decisions. Deviation from rational thinking creates direct losses or opportunity costs in financial investment activity. Investors could be biased by confirmation when they seek out information that supports their existing views and ignore or dispute information that does not support their existing views. Also, in the process of making investment decisions, investors can attach their views to irrelevant, outdated, or incomplete information. Moreover, keep in mind that people tend to herd behavior. One of the famous experiments for detecting herding behavior is Asch’s experiment. Asch had groups of eight participants assess the length of three lines in relation to a target line. One of the lines was identical to the target line, while the other two were unambiguously longer or shorter. Of the groups of eight participants, however, seven were in on the experiment. Asch had them pretend to think that one of the longer or shorter lines was the same length as the target. The purpose of the study was to determine whether the “real” participants would change their correct answer to conform to the group’s incorrect answer. Incredibly, roughly 37% of responses conformed to the incorrect group response, despite the error rate being less than 1% when people were asked to assess the lines on their own.
The investment area is not an exception to herding behavior. Despite the fact that an investor should stay with a cold mind he is also subject to the influence of other people’s decisions. Often, investors will gravitate towards a set of similar assets, to which they are attracted solely by the fact that others are doing the same. To make a rational investment decision in a crowd a person’s opinion should remain independent of those around them, and individuals must make their own opinions based on their knowledge. Unfortunately, it has become quite common knowledge that the frenetic floors of a stock exchange will not often benefit from such serene cool-headedness. Therefore, investment decisions become biased base on decisions on the consensus of a larger group, rather than on what makes the most logical sense.
Way Out of the Crowd
Despite that rational theory says that investors should be risk neutral (perceive benefits and risks are equal way) there is a documented effect of loss aversion in the real world. There is a natural tendency among investors to prefer avoiding a loss, to realizing a gain. To avoid this effect people may try to formulate trading rules, but there is always a desire to deviate from them, and these rules might not be adaptive to the current market situation that in total can generate additional losses or miss promising investment opportunities.
Human is naturally restricted by different kinds of biases that limited them to make rational decisions, especially in a finance area where a mistake can lead to irreparable losses and bankruptcy. We must perform our functions “with objectivity and with awareness of our assumptions and risks. Therefore, we are interested in a tool that helps us to reset our limitations and fully use existing investment opportunities. Ensuring objectivity is a defining characteristic of analysis and it is where an artificial intelligence algorithm can help.
The outcome of our decisions depends on how good is our model. The faulty risk model relies too much on historical data and neglects the possibilities that are not present there. Human failings, the combination of over-confidence, short-sightedness, and complacency could spell disaster. The once in a hundred years pandemic or war is a risk that few people considered. Investors often allow emotions and biases to control their decisions, sometimes resulting in catastrophic failure. Emotions are running high in the market today. Most humans, when making trading and investment decisions, are driven by emotions like fear, greed, and prejudice.
AI can capture our biases and feelings, and also uncover the knowledge that is covered for a general investor. It should be noted that complex investment models make it possible to partially reveal the asymmetry of the capital market, which cannot be revealed by experts. AI can account for and test a plethora of potential investment scenarios. Its deep machine-learning abilities can paint a full picture of the investment landscape and uncover risks and rewards in ways that a human brain cannot.
The AI seeks to find the factors and trends that may go deeper than traditional stock-picking methods. Since traditional factors are already incorporated into many portfolios, it could be harder to find alpha through those traditional means. Once more people use the same strategy, it often becomes built into the price, and price discovery erodes. This does not mean that current strategies are no longer valid. However, since many of these strategies use only a few input values and trust in traditional methods, this may not be optimal. This makes it possible to find new investment opportunities that may seem invisible to humans. With input from multiple data sources, AI seeks to find greater prediction accuracy, while staying adaptable to new information. This is how AI seeks to find the invisible investment opportunities that humans cannot see and manage risk by positioning the weights of the portfolio to reduce drawdowns.
AI Stock Forecast: The Hope for AI
AI can be designed to spot patterns that help improve data mining and analysis. By technical analysis, we try to estimate current behavior in prices. In the fundamental analysis, we try to evaluate an asset value and distance ourselves from irrational behavior aspects that are dominant in the current stock market price. However, an analyst must do projections of variables and provide his outlook on an object under study thus the subjective aspect still stays in fundamental analysis. AI helps not only make investment decisions but, through analyzing price behavior, makes irrational decisions that are rational in a current irrational market environment. Such an approach enables IKF AI to provide valuable investment advice to our clients from short-term horizons where an irrational environment is dominant to long-term horizons which are a home for rational investments. AI is expensive to develop and computationally expensive. Learning and forecasting consume electricity 24/7. Today smaller investors do not have the resources to invest in AI. Thus, I Know First provides a way for private investors to take advantage of AI.
The I Know First predictive algorithm is a successful attempt to discover the rules of the market that enable us to make accurate stock market forecasts. Taking advantage of artificial intelligence and machine learning and using insights into chaos theory and self-similarity (the fractals), the algorithmic system is able to predict the behavior of over 13,500 markets. The key principle of the algorithm lays in the fact that a stock’s price is a function of many factors interacting non-linearly. Therefore, it is advantageous to use elements of artificial neural networks and genetic algorithms.
We use hundreds or thousands of independent predictors and calculate the weighted average of the signal according to past performance of each predictor. The predictability is the indicator of how good is the prediction. We are aware that there are hidden variables that we don’t know about. They limit the precision of our forecasts. Updates: our system is based on data being updated daily. Some important inputs are updated monthly or quarterly and can’t be directly used. When possible, we use daily updated proxies to approximate the effects of such data.
Below you can see the investment result of our World Indices package which was recommended to our clients for the period from November 24th, 2020 to December 6th, 2022 (you can access our forecast packages here).
The investment strategy that was recommended by I Know First accumulated a return of 524.30%, which exceeded the S&P 500 return by 512.53%.
AI Stock Forecast: Conclusion
Deviation from rational thinking creates direct losses or opportunity costs in investing activity. AI can capture our biases and feelings, and uncover the knowledge that is covered for a general investor. Its deep machine-learning abilities can paint a full picture of the investment landscape and uncover risks and rewards in ways that a human brain cannot. With input from multiple data sources, AI seeks to find greater prediction accuracy, while staying adaptable to new information. This is how AI seeks to find the invisible investment opportunities that humans cannot see and manage risk by positioning the weights of the portfolio to reduce drawdowns. The I Know First predictive algorithm is a successful attempt to discover the rules of the market that enable us to make accurate stock market forecasts.
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Please note-for trading decisions use the most recent forecast.
