Written by Jun Wu.
Every year since I worked on wall street, traditional trading-is-an-art-form traders are leaving and retiring.
Their jobs are replaced by a new breed of experts who are savvy with numbers, systems, and the market. These experts don’t sleep, eat or drink. They are the AI Systems that can run on a thousand machines to analyze information from markets, social media, corporate filings, and economic conditions to quickly decipher which trades to make at any given moment in time.
Problems Arising from the Use of AI for Trading Purposes
- The “Black Box” of algorithms, particularly deep learning algorithms make grasping how decisions are made virtually impossible. These include trading decisions, investment decisions, and risk management decisions. The communication mechanisms inside the AI System is not transparent. When money is lost, it’s difficult for the hedge fund or the regulatory body to reconcile that loss to any foul-play. If the AI System is at the center, then it is the AI System that is responsible. But, who is responsible for the AI System? If a third party AI system is used, is it the financial management firm that’s responsible or the company that created the AI System that’s responsible?
- The problem is further complicated when multiple intermediaries experience rapid loss in a short span of time. Then, it leads to a new kind of systematic risk. Volatility in the market begets more volatility in the AI world. As volatility inputs are fed into AI systems, it accounts for that volatility by making new trading decisions that can potentially increase volatility.
Read the full article here.
