In the investment world, the market is a leading indicator that reflects the expectations of the economy. However, the economic-financial models that serve as support to try to anticipate these movements have recently witnessed an increase in criticism about the divergence they show when trying to explain the empirical reality. For this reason, it is necessary to innovate by empiricizing the financial economy to generate higher returns.
The economic-financial models are representations that generalize the interactions between economic agents in order to study them, and in the case of stock market finance, use them as support to anticipate the movement of the market. An example is the law of supply and demand, where by analyzing its factors, it is sought to identify the phase of the economic cycle that is about to happen and position the optimal portfolio in this scenario. Based on this, there are two challenges that investors face: 1) the market is a leading indicator of economic expectations and 2) the models fail to explain the real behavior of the market.
Regarding the first point, although the economic-financial variables are analyzed to form an investment thesis, the reality is that the market anticipates with great speed before any economic expectation. The economic crisis of last year was characterized by having been induced due to global lockdowns, to later begin the recovery by gradually increasing mobility in the countries. This transition was gradually reflected in the economic indicators throughout the past year and the current one; However, the stock indices digested it in an accelerated way, showing the fall and the fastest recovery in history. In the case of the S & P500, in less than 25 business days the index fell to its local minimum, while in less than 15 business days, it had recovered 50% of the drop. With this, it is observed that the monitoring of the economic-financial variables may be irrelevant due to the lag that exists in their publication, while the market anticipates these events.
On the other hand, an area of opportunity for economic-financial models is the disconnection with the real behavior of economic agents. Charlie Munger, businessman, investor and colleague of Warren Buffett, mentioned that these types of models do not consider the psychology of the human; Therefore, because the theory is based on a rational context, any divergence from reality is considered an anomaly. Frank Fabozzi, famous scholar, researcher, author, and editor, has commented that an empirical science must fit its models to real data; contextualized to Charlie Munger’s observation, human psychology needs to be treated as normal behavior and not as an anomaly.
This does not mean that the models are not useful to generate returns, an innovation is simply needed in an environment where the evolution of the market and the economy has been faster than that of the study. Frank Fabozzi comments that it is necessary to combine sophisticated mathematical tools and empirical techniques, recognizing the limitations when trying to analyze an environment with constant evolution. The first step has been taken; New tools such as alternative data, data science, big data, machine learning, among others are being used every time. An example of this has been the mobility indices of various platforms or massive data to identify whether recent inflation is temporary or structural.
In conclusion, the empiricization of the financial economy is a necessary innovation to adapt to the complexities that previously did not exist in the market and that will allow generating higher returns. It is a complicated path, since it requires moving away from the security of a completely rational model, to enter the insecurity of understanding and trying to model reality effectively.
The author is Executive Director of Quantitative Models – BBVA Asset Management *
Reference-www.eleconomista.com.mx