Science vs Finance

“I can calculate the motion of heavenly bodies, but not the madness of people.”- Sir Isaac Newton

These were the words of one of the most revered physicist of all time after the South Sea Company bubble. Indeed, Newton described the intricacies in modeling the psychology of people. As compared to the sciences such as physics, chemistry or mathematics, finance is fundamentally different, for several reasons.

Firstly, in sciences, objects do not react as humans do towards information. Neither the three laws of motion governing our macro world nor the speed of light will change due to our investigation into those areas. Hence, the laws in the sciences that are established through experiments and theoretical argument truly describe the very nature of the phenomenon. For that very reason, these laws can stand the test of time.
On the contrary, for finance, people are extremely reactive to information. If a piece of research work shows that are opportunities to exploit the market in a certain way, you can be sure that such exploitations will not work soon enough as such opportunities will vanish under the laws of supply and demand. This is also the core basic of finance, the principle of “No Free Lunch” or formally, the No Arbitrage principle which indeed holds in the markets. Therefore, financial modelling is relatively challenging and there is more dynamics in the process.

Secondly, in finance, the so-called “laws” are fundamentally weak as they may not hold for every instant. Despite that we are trying to quantify finance and economics and provide a more mathematical treatment on those subjects, we fail to observe that some of the laws in those fields are meaningless. Not matter how technical or bombastic mathematics we use, some of theorems and laws we arrive at will not hold for long. In fact, I would suggest an extreme and not to call those findings as theorem but rather an observation. Holding on to those laws when they are not relevant may result in adverse impact on your portfolio or understanding of the markets. Instead, I propose that we adopt a more dynamic view in describing the phenomenon in the markets by constantly adjusting our interpretations and methodologies. Not only are we able to adopt the ever dynamic market environment, we will be able to devise new ways to solve the related problems in finance and economics.

Although the above two arguments hold true in my perspective, they do not mean that application of scientific methods to finance and economics are valueless. In fact, that is probably the best we can do given the tools that are at our disposal. For instance, opponents of quantitative finance would argue that stock prices are not normally distributed. However, here a challenge I would throw to them, find a tool that is as convenient as Brownian motion with all the established known mathematical laws to model stock price evolution. I doubt they will able to achieve anything in facing such a challenge. Mandelbrot suggested using chaos theory to build financial models, however, the mathematics in that area are not developed to be applied conveniently to financial data. To that end, we see that financial modelers and economists are already putting the best of tools they have to explain the crazy world of economics and finance.

In spite of that, we as modelers in finance and economics, should take into account that the models and the tools we have are not perfect. There are always information in the data that we are unable to capture with our current knowledge and tools. Rather than defending the models we developed, I propose that we have an open mind and understand what are the shortcomings and deficiencies of the models and theories we developed. To a certain extent, the field of quantitative finance are full of so called “players” and people who are not willing to work with data. Foregoing the information of the data and focusing too much on the mathematics of the models, in my opinion, are completely a waste of time as the models developed cannot be applied! This is probably what the finance academics and economists will have to address.

While we compare science and finance, we observe that their paths crossed at the tools that are used in modeling and understanding the phenomenon in each respective fields. However, we also see that finance are not like the sciences as the mathematical laws in finance may not hold true to eternity.