Artificial Intelligence in Finance – Superior or Subordinate?

The article was written by Vladimir Zaslavsky, a Financial Analyst at I Know First.

Artificial Intelligence in Finance – Superior or Subordinate?

Finding good partners is the key to success in anything: in business, in marriage and, especially, in investing.” ~ Robert Kiyosaki 

Summary

  • Application of Artificial Intelligence in the Finance Sector
  • Is Artificial Intelligence Superior or Subordinate to Humans?
  • I Know First’s Artificial Intelligence Algorithm

Artificial Intelligence (AI) is fast encroaching into every area of our digital lives – it chooses the social media stories we see, provides recommendations for music and movies, identifies our friends in photos, predicts our online purchases, and ensures that we avoid accidents on the road.

AI is an area of computer science that emphasizes the creation of intelligent machines. It is a rapidly evolving part of the technology industry, that will ultimately set the foundation for the future.

Machines are programmed to “think” like humans and mimic the way a person acts. They are designed to rationalize and take actions to achieve specific goals, whilst simultaneously learning and self-improving.

The drivers pushing AI forward are common across industries – it eliminates the need for manual processes, and supplies insights in real-time for data-driven decision making. AI has liberated humans from trivial and repetitive work, and has the capacity to accomplish tasks that are otherwise unachievable due to physical or intellectual constraints.

Lately, AI has been adopted by a number of domains, financial institutions and companies moving fast, to keep pace. Finance and accounting departments are experiencing fundamental changes as AI evolves and continues to become more sophisticated. It influences financial markets and is used for a number of applications including: managing stock portfolios, conducting algorithmic trades and market analysis.

Whilst AI continues to become more sophisticated and complex, so do the markets. Indeed, the application of AI is controversial and widely debated – some consider it as a tool, valuable but subordinate, used to assist decision making. Others, however, foresee it controlling and making decisions, valuable and superior.

Application of AI in the Finance Sector

To some degree, AI has an advantage over humans in finance. It eliminates the emotional and psychological weaknesses that inevitably influence and hinder reasoning. Biases, incentives and emotions aren’t prevalent in an algorithm.

EquBot LLC is a technology company that is disrupting the investing space. Leveraging on AI, EquBot launched the world’s first AI-powered Exchange-Traded Fund (ETF) in the New York Stock Exchange in October. Powered by IBM Watson, the technology is a multi-staged process seeking to capitalize on mispriced stocks in the marketplace. The technology uses data to build financial models on over 6,000 publicly traded US companies to identify those whose values are not fully recognized by the market. It parses millions of articles and online news sources to uncover catalysts and events which may influence the probability of realizing those opportunities – simulating “the work of equity research analysts and work[ing] around the clock in an “almost fully automated” process” (Art Amador, a founder of EquBot). Ultimately, the analysis coupled with artificial intelligence determines the strategic entry and exit points. Typically, the fund will make one trade per day as it continues to fine-tune its stock picking methods.

To date, EquBot has not demonstrated a superior track record. Over the course of the 18th of October to the end of 2017, EquBot achieved returns of 3.1%, compared to a 5.1% gain achieved by the S&P 500 stock index. Nevertheless, this underperformance may be attributed to the early stages of learning and development. It is important to note that financial markets are run by humans which innately have flaws, emotions, complexity, motivations and unpredictability. Tim Clift, Chief Investment Strategist at Envestnet PMC, stated “we know the markets are irrational…but the machines aren’t going to know how to behave in that kind of environment.” Perhaps, AI will outperform the index over the long-term, whereby it can process immense amounts of data – focusing on the broader landscape and avoiding the short-term volatility.

Moreover, Wells Fargo research analysts have developed a bot using artificial intelligence and machine learning, named Aiera, to perform research and analysis. Aiera’s purpose is to track stocks and formulate a daily, weekly and overall view on the performance. However, Aiera is only six months old, and it is not picking stocks in the traditional sense. Ken Sena, the analyst that led the group to develop AIERA stated, “I would still say that my ability to lay out a fundamental idea to a client and look further over the horizon will continue to have an advantage over Aiera for some time.”

I Know First – a Strategic Partner

Whilst the irrationality of human psychology is not entirely predictable, there are underlying economic principles and assumptions that reveal how people will likely react to market change.

I Know First, combines the unique intelligence of humans with the incomprehensible capabilities of machines. Every day, the self-learning and self-adjusting algorithm produces market forecasts with trends of stocks, commodities, and indices over 6 different time horizons ranging between a few days and a year. Through a mixture of chaotic system and efficient patterns found in the market, the algorithm is able to successfully detect trends to enable investors to understand entry and exit points in investing.

With over 15 years of historical market data, I Know First forecasts a growing range of over 7,000 securities for the short, medium and long-term horizons daily, by applying AI and Machine Learning techniques to search for patterns and relationships. Through its self-learning ability and flexible multi-layered neural networks structure, the algorithm is able to learn from, adapt to, and evolve together with continuously changing markets. It offers an independent, objective and unique perspective on the financial markets and does not rely on any human derived assumptions or traditional theories and models.

The results of intense learning and prediction cycles are aggregated into two indicators per time frame: signal and predictability. While predictability indicator helps to identify and focus on the most predictable assets, the signal is used to define and rank the trades and is related to the magnitude of expected return.

The scalability of the algorithmic predictive system allows I Know First to offer custom forecasting solutions to financial institutions or private investors. Further, the solution can be used as a decision support system in form of an algorithmic screen integrated into client’s investment process in order to confirm or reject investment ideas before execution.

Conclusion

With time, development and self-learning, we will see the performance and application of AI in the financial space. At this stage, I believe humans are crucial in investing and AI should serve as a powerful partner used to complement decision making (DSS)  – valuable, but subordinate.


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