Viewing Financial Markets as Complex Systems
This is the first time I am reading about complex systems and the field is quite interesting. I was struck by the thought that it is a study of a system as a whole and how individual elements are connected to each other, rather than studying the properties of the individual elements per se. As such, the study of complex systems provides a framework to understand any field if we view the field as a system where each element is connected to each other in different ways, and this interdependence and interaction among elements creates a complex system that can be greater or less than the sum of its parts. I am excited to learn more about this course as I believe there will be a lot of use cases for this.
I am particularly keen on applications in the field of business, economics, and finance, as I think these can be analyzed as complex systems consisting of different humans interacting together in a market, which ultimately affects supply and demand of any product, and therefore its price and market activity.
If we take the Philippine stock market for example, I can imagine that you and I, together with other individuals, can form a bigger system of retail traders. Meanwhile, banks like BDO and BPI, together with other firms, can form a bigger system of local institutional investors. Lastly, firms outside the Philippines that will be investing in our stock market can also form a bigger system of foreign investors. A combination of these systems of (1) retail traders, (2) local institutional investors, and (3) foreign investors can then form the bigger system which is the Philippine Stock Exchange (PSE), because essentially, the PSE and the value of all its stocks is just a result of the system of collective actions done by each of the parties.
The above three-element example is quite simplified. In reality, there are a lot more nuances to the underlying system. For example, there are investors who invest on a long-term basis (more than 1 year), and there are some who invest on a medium-term basis (around 3 months to 1 year). Meanwhile, there are those who invest on a shorter-term basis (less than 3 months), with some even day-trading and buy and sell stocks within 1 day to 1 week. It seems that by just considering these different investment time horizons, we can already form four sub-systems within each of the three systems that we have outlined above. To further complicate things, different investors usually have different strategies in determining their investments such as fundamental (looking at the business), technical (looking at price charts and patterns), or even just solely based on tips or rumors from friends or social media.
Thus, when we consider these nuances, the system of PSE stocks, or financial markets in general, can really turn quite complex, where all the parts of the system can practically do whatever they want based on what they think is best for themselves. The result is that it is not straightforward to predict what will happen to the price of any given stock, given all the factors that can happen (e.g., an institutional investor may suddenly decide to buy a huge amount of a stock due to proprietary analysis, but for no apparent reason from an outsider perspective).
Several groups in our cohort at the Asian Institute of Management’s Master of Science in Data Science program have already done some work in trying to crack the financial markets puzzle using machine learning or deep learning. But upon reading up on complex systems, it seems that financial markets can really be viewed as a complex system comprised of different types of investors, and it is exciting to see what new ideas and insights we can discover by modeling these markets as complex systems.
