A Wake-up Call for Risk Managers

Exposure to market risk is part and parcel of doing business for financial institutions as, ultimately, the four standard market risk factors of stock prices, interest rates, foreign exchange (FX) rates and commodity prices cannot be controlled. However, the market turmoil of the past 24 months has undoubtedly acted as a wake-up call for the industry, resulting in a wave of new regulatory requirements aimed at providing greater supervision and enforcement of financial institutions’ risk management. In 2009/10, the UK’s Financial Services Authority (FSA) issued a record number of fines, eclipsing the levels of the previous year by 21%, according to city law firm Reynolds Porter Chamberlain. In total, the report suggests that the regulator handed out penalties totalling £33.1m over the course of the year. Risk management and regulation has clearly entered a new era, but what does this mean for those tasked with trying to measure market risk in the post financial crisis world?

For financial institutions’ risk managers, the new wave of market regulation is cause for concern at a time when the financial meltdown has left them questioning the very essence of risk modelling. Since the 1990s, investment firms have relied on highly complex mathematical models for measuring the associated risk in their various portfolios, primarily to reassure investors that all is well. While risk managers use a variety of mathematical models to measure market risk, the most widely used has been Value at Risk (VaR).

Improving VaR Management

VaR is built around statistical ideas and probability theories that have been around for centuries. It describes the probability of losing more than a given amount of assets, based on a current portfolio. Alongside its ability to express risk as a single number, it is the only commonly used risk measure that can be applied to just about any asset class. VaR allows banks and investment firms to make quick and simple predictions on the potential losses of trading. However, since the worldwide financial crisis, VaR has been criticised for underestimating tail risk. While its application has been extended in many ways to reflect liquidity risk and take into account operational risk and basic stop losses, it is still backward looking and can fall short if there is an extreme change in price.

While there is no doubt that risk modelling, as we know it, needs to evolve to better cope with market risk, one could argue that it is more banks’ and traders’ approach to, and use of VaR, that needs to change, rather than the actual model itself.

First, VaR needs to be broken down and analysed by traders. Instead of relying on a single number, traders need to look beyond the top line and delve into the complex mathematical calculations to gain a better understanding of the type of risk they’re taking and how it can best be mitigated. By taking this approach VaR will become a valuable management tool, alongside other factors, such as the profit and loss (P&L) sheet.

Second, as well as better analysis, traders need to receive VaR calculations in a timely manner. When used simply as a reporting tool, receiving VaR calculations within 24 or 48 hours is adequate. However, if traders are to have the ability to act on the information provided within the VaR calculation, they require the information as lot more quickly. While real-time VaR might not be necessary, to have it within the trading day is crucial. A firm’s ability to understand its risk position in near real-time can allow it to undertake more and/or greater positions and trade across complex products with more confidence.

Technology to Answer Regulatory Questions

In light of the recession, many of these considerations are being mandated by the regulators. It is expected that the emerging regulations will not only require a change of culture but also a review of banks’ systems. As it stands, many financial institutions simply do not have the right technology in place to deliver in-depth VaR analysis in a timely fashion.

The general lack of sophisticated technology within banks sits at the heart of the risk management problem. Broadly speaking, banks are no better prepared now for another financial meltdown than they were prior to the recent recession. This is not necessarily down to complacency but more due to the fact that financial institutions have not had long enough to implement new risk management methods and make the necessary changes to their IT infrastructure. Faced with pressure from the regulators, IT projects are underway, but the overall results and improvements are still a few years off.

The FSA has put in place a firmer stress testing regime by requiring firms to improve their stress testing capability, enhance their capital planning stress testing and introduce a reverse stress testing requirement. The Basel committee is also modifying its Internal Model Approach to assessing regulatory capital for market risk by introducing a ‘Stressed VaR charge’ and an increasing proportion of financial institutions are supplementing the use of VaR results with stress tests when reviewing their allocation of economic capital.

These new rules will take time for financial institutions to digest and respond to. However, once banks do have enhanced risk management systems in place, they should pay dividends. For example, when VaR is supplemented by well-designed stress tests, the resulting risk estimates incorporate traditional market risk and the outcomes of stress tests, as well as the probabilities of each. They therefore give risk managers a single, integrated set of risk estimates to work with.

As investment firms get to grips with the new regulatory requirements, it’s clear that an overhaul of technology is on the cards as financial institutions start to implement more sophisticated risk mitigation solutions and approaches. Ultimately, the widespread institutional reliance on VaR as an accurate indicator of market risk is only a gamble if traders do not have the right technology solutions in place to help them analyse and break down VaR in near real-time.


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