Dec 16, 2011

Financial Risk Management

On Volatility versus Risk I commented on Risk and Volatility, without however mentioning practical activities related to the direct use of metrics for risk. 

risk management 

Market risk, which is the possibility of financial loss due to the typical ups and downs of the market, should, as the intuition suggests, reflect the degree of oscillation that the asset provides.

The simplest metric, known and used for this purpose is the standard deviation. The standard deviation has inaccuracies in quantifying the risk, because strictly financial returns do not follow a normal distribution, which is the necessary premise to calculate the standard deviation. The metric of the standard deviation necessarily produce a bias, always deviated from the true value.

The biggest problem with the standard deviation, however, is not the premise that it performs when considering the normal data. The standard deviation by itself does not present the risk management of an efficient way, because it still lacks the statistical scenario was considered.


The methodology Value-at-Risk (VaR) fills this gap. It was developed in order to produce management reports more objective and intuitive. His metric is well established in statistical terms and reflects exactly what one would expect from a market risk measure. The VaR results in a net asset value, or a possibility of financial loss. This possibility of financial loss is tied to a time interval and statistical significance. So we say: The portfolio has the possibility of losing $X on Y days (or hours) with a statistical significance of Z%. 

Financial processes, however, do not follow a behavior said homoscedastic or constant over time but heteroscedastic. The volatility can undergo dramatic changes as in times of crisis. These phenomena can cause a sharp drop in equity of a particular institution leading to bankruptcy in many cases. 


An analysis complementary to VaR, called Stress analysis is used to simulate situations of panic and financial crises. These simulations analyze the tails of the distributions of returns and evaluate the portfolio in more extreme scenarios. It is possible to simulate historical crises, specific situations and scenarios to highly pessimistic and uncorrelated. 

It is necessary to understand the main feature of the market is the strong stochastic process which asset prices are submitted. Unexpected situations are possible and even expected, and it is impossible to predict turbulence and crisis situations with sufficient precision. The Financial Risk Management, however, has enough tools to evaluate and quantify the risks and fluctuations to which the portfolio is submitted.

Rodrigo Sucupira Rodrigo Sucupira
Rodrigo is a Automation and Control Engineer - Escola Politécnica / USP. Interested on Financial Engineering, writes articles about Finance and Technology.
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