We have written on the pros and cons of financial modelling. Today, we ponder about the role and importance of Financial Modelling in the financial landscape of today and tomorrow.

A financial model is more than mere lines of codes. It is a marriage of 3 disciplines – finance, mathematics and information technology. A good financial model is one which combines the 3 disciplines with sufficient adequacy. As business students, mathematics and information technology are admittedly our shortfalls. In the interest of time, detailed explanations of assumptions and derivations are often omitted. Consequently, there is a tendency to take them for granted and we fail to grasp their full implications. For example, the argument that beta is an appropriate proxy for a firm’s underlying business risk is centered on the efficient market hypothesis. Under the efficient market hypothesis, changes in fundamental business risk are reflected accurately in price changes. Financial markets in general are often thought to abide by the semi-strong form of the hypothesis. However, individual securities exhibit a range of efficiency and it is the weak form that allows for portfolio outperformance – alpha. Therefore, the quest for undervalued stocks by nature inherently assumes that they have been inefficiently priced by the market, contravening the efficient market hypothesis. By that virtue, an undervalued stock’s beta will not be an accurate reflection of fundamental business risk.

This represents a divergence between soft business acumen and hard mathematical rigour. It would be ingenuous of us to believe that this is the only instance of divergence. We also recognise this to be dangerous as it can result in significant mispricing. At an industry level, this may exacerbate volatility and contribute to the formation of bubbles.

As such, we believe that the role of financial models is to bridge this gap between the soft side of finance and hard mathematics. As the financial landscape evolves, it is likely to become more complex, rather than simpler. The importance of financial models will rise as they will help institutes and investors alike navigate the complex landscape. Unfortunately, the increased complexity will also pose a greater challenge in achieving accurate financial modelling. A financial model by itself is dead, with numerous assumptions in place. The rigour of mathematics should always be cross-checked with business intuition and vice versa. When financial modelling is done without either component, the results can be disastrous.

In 2002, when banks and financial institutions were loading up on financial derivatives (no doubt acting on the output of financial models), Warren Buffett, through Berkshire Hathaway’s annual report, denounced them as ‘financial weapons of mass destruction’. A few years later, the global financial crisis hit. When business acumen and mathematics meet, they do not always agree. As mentioned earlier, we believe the ideal role of financial models is to bridge the divergence. However, it is clear that this is not always the case in reality. It is highly possible for financial models to exacerbate the divergence as well. If one ever needs further proof, simply look up on Long Term Capital Management.

It is detrimental for financial models to adequately combine the 3 disciplines of finance, mathematics and information technology. We believe economies will pay the price if it has finance people blindly making investment decisions based on a model developed by mathematicians/developers who have little finance knowledge. Therefore, one of the challenges of Financial Modelling in the future would be the obvious difficulty in mastering and incorporating all 3 disciplines.

Unfortunately, we believe that it is the second challenge that will seriously impede the rising prominence of Financial Modelling. As a discipline on a whole, by bridging the gap between the soft side of finance and hard mathematics, the benefit of Financial Modelling is increased market pricing efficiency. However, at a micro level, the incentive of Financial Modelling is profit-making. A perfect financial model, if it ever exists, ceases to be useful to its proprietors once it becomes public knowledge. It is this conflict of interest that leads us to believe Financial Modelling, as a discipline, faces serious headwinds in truly filling the gap between soft side of finance and hard mathematics.

To conclude, we cannot deny that Financial Modelling will become increasingly important as the financial landscape grows more complex. With the potential to either reduce or exacerbate the divergence between soft business acumen and hard mathematics rigour, it does not seem overboard to regard Financial Modelling as a gatekeeper. However, there are serious challenges in place and the outcome is fraught with uncertainty.

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Financial Modelling For Value Investors In An Increasingly Complex World
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