Man vs machine in the investment world - the rise of the algorithmic model and its implications
AI showed that it has decisively reared its head in the investment arena.
Would you trust a machine to manage your wealth, or do you feel more comfortable with a person? After all, it is a fact that, last year, BlackRock - the world's largest asset manager with around $5.7 trillion under management - announced that it was moving away from having humans selecting and selling its stocks, at least in part, and was turning to automated systems for certain of its stock picks.
Datacentrix is fostering discussions on the possibilities that the digital age brings to South Africa, and how disruptive technologies are reshaping traditional business models. Dr Dennis Mwansa, an expert with both local and international experience in the field of stock traders and their related technologies, has contributed to the theme, 'Trading billions in nanoseconds - how artificial intelligence is used to achieve this'. Mwansa is the chairman of Dot Com Zambia, and holds the position of Technology Strategist and Head of Technology Research & Development at one of the largest exchanges in Africa.
In the financial services and insurance sectors, artificial intelligence (AI) has already become a force to be reckoned with, taking on certain functions that are based on parameters and inputs that humans provide. This includes 'robo-advisors' in the investment world, and the use of AI in the insurance arena for claims processing. Robo-advisers rely on automation and mathematical rules (algorithms) to offer low-cost financial planning advice on the Internet. They'll typically ask a few questions designed to understand your attitude towards taking financial risks, and how long you have to save and invest your money (for example, as compared to when you will reach your retirement age). Once the platform has received some input, it will be able to suggest a personalised portfolio to help you achieve your investment goals.
But the use of algorithms in the financial arena goes much further than the use of a relatively simple robo-adviser platform giving advice to individuals in their quests to improve their personal wealth. In the world of stock exchanges, algorithms can be used to trade billions of dollars in nanoseconds, and also to make decisions on where to invest a pool of funds instead of using a team of human beings.
Mwansa says: "We are seeing the rise of artificially intelligent investment funds in the world's markets. On 17 March 2017, many in the financial world were stunned to learn that BlackRock had cut more than 40 jobs, replacing a number of its human portfolio managers with artificially intelligent, computerised stock-trading algorithms, in order to create a fund that makes decisions on where and how much to invest using machines rather than people."
This isn't the only case of Wall Street investors laying off human stock-pickers and replacing them with robots, but it has arguably made people sit up and take notice. While all is not necessarily lost for the human trader, however, it does seem as though algorithmic trading is here to stay - and, in turn, this is bound to bring potential job losses in certain financial spheres going forward.
Mwansa further clarifies how AI, as used in the world's capital markets, can today allow traders to buy and sell stock in moments on global stock exchanges. He says: "It's a style to execute certain strategies, allowing traders to take advantage of buying and selling price differences in stock on offer in a tiny timeframe. Trading securities has increasingly become an information-intensive decision-making process. Today, more risk controls are taking place before the trade, driven by regulation and a desire to minimise risk exposure.
"The information that needs to be processed includes details about price, liquidity and even sentiment, coming through from sources such as social media, blogs, news feeds and analysts' reports. When you think about big data that needs to be factored in, it's useful to have a system that can vacuum up all the information available and process this data at lightning speed in order to make the billion-dollar decision on whether to trade or not."
These decisions are facilitated by algorithmic trading, which uses mathematical models to determine decision-making on the financial markets. Computer-based algorithmic trading is most commonly used by large institutional investors (for example, those who are responsible for running retirement funds on behalf of fund members) because of the large number of shares they buy every day. Complex algorithms allow these investors to obtain the best possible price without significantly affecting the stock's price and increasing purchasing costs.
Fans of algorithmic trading say the use of automation to trade takes the human bias out of the equation. It is a known fact in investment circles that human emotions can lead to financial losses, because people make the wrong investment decisions based on their emotions - buying or selling at the wrong time in an investment cycle because of emotions such as fear or greed.
Speed is also becoming increasingly important in the exchange industry of the 21st Century as a way to attract and keep clients. Those exchanges that have trading systems with the lowest latency, which is the time between when an order is received and processed, and acknowledgement sent, will be seen as more desirable to investors, especially those investors in the big leagues with huge funds at their disposal.
Mwansa concludes: "The open outcry floor system has been replaced by digital trading for 21 years. The open outcry system was how professionals on a stock exchange traded floor communicated, and as per its name, it involved shouting and the use of hand signals to transfer information about buy and sell orders. The introduction of electronic trading immediately made this process dramatically faster, and allowed for anonymity of selling the stocks. Today's ongoing evolutionary use of AI in global stock exchanges has made trading its fastest yet. It is another example of how AI is taking over skilled professions and disrupting business as we know it."