Whitepaper Symetrics: Drivers of Risk

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The arrangements of the International Monetary and Financial System (IFMS) have brought unprecedented levels of wealth. Yet at the same time, it also has led to financial excess and instability. The scope and scale of the Great Financial Crisis (GFC) made clear that not all arrangements of the IMFS were perfect. To mitigate financial excess and systemic instability, national and international regulatory bodies have responded to limit and contain repercussions. Still, the altered financial and monetary conditions result in a market dynamic wherein incentives favor short term gains over long-term stability.

The financial system is changing rapidly, not only by the brute force of monetary and fiscal stimulus or the changing regulatory environment, but also due to technological advancements that allow people to challenge the ways in which their financial interests are handled. In a way, the monetary, fiscal and financial paradigms have entered a phase of a transitory shift. Irrespective of the exact structure and arrangements that will shape the 21st century monetary and financial system, three key elements will drive the evolution of Big Finance whether it is liked or not. In our view these elements are financial risk, market behavior and reward.

As we all see interest rates falling, moving to the lower zero bound, and even into negative territory, we are confronted by an ever greater need to question our assumptions about financial markets. At Symetrics, we believe markets are all about imperfections. There is a simple reason for this: nothing is without risk. However you look at it, risks and rewards are key elements in all financial contracts. In this respect, regulatory scrutiny has become much more stringent. It has left the financial industry with the familiar questions of what must and what can be done.

As model builders, we like to take issue with sentiments that econometric models cannot predict financial crises. Not because we think models in theory or practice have predictive capabilities, but because also before 2008 everybody should have known models cannot predict future crises.

The role of mathematics is not found with its predictive capabilities, statistical correlation will never equate to causation. So why use models then? We think that mathematics can put forward brilliant tools. Whether these tools become mandatory or are strictly voluntary, mathematics – properly understood and applied – allows us to better understand and measure financial risks in different macro-economic circumstances. And since risks are inseparably tied to returns, models can be used to evaluate asset valuations, calculate asset mix optimizations, prices and even stress-test asset portfolios or balance sheets.

Utilizing what if scenarios is the next best thing to predicting. Even if models cannot predict future crises, an econometric model capable of integrating a range of economic scenarios in a meaningful way can increase your understanding of financial and economic risks, and the impact of these risks most relevant to you. There is thus an important difference between relying solely on black-box model output and increasing your risk-awareness by using next generation models as a tool for a clearer understanding.

We believe that models should allow a far better understanding of financial risk, especially in our time. The technological advancements in econometric modelling already provide the tools that meet the financial challenges of today. Macro-economic analysis, asset mix optimization, ALM, and mortgage & loan portfolio valuation can be done through a range of realistic what if scenarios. The time has come for an integrated approach.

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