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Financial Risk Management

Posted on the 19 December 2011 by Rodrigosucupira @rodrigosucupira
On Volatility versus Risk I commented on Risk and Volatility, withouthowever mentioning practical activities related to the direct use of metricsfor risk. risk management 
Market risk, which is the possibility of financial loss dueto 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 thestandard deviation. The standard deviation has inaccuracies in quantifyingthe risk, because strictly financial returns do not follow a normaldistribution, which is the necessary premise to calculate the standard deviation. Themetric of the standard deviation necessarily produce a bias, always deviatedfrom the true value.
The biggest problem with the standard deviation, however, isnot the premise that it performs when considering the normal data. The standard deviation by itself does not present the riskmanagement of an efficient way, because it still lacks the statistical scenariowas considered.

The methodology Value-at-Risk (VaR) fills this gap. Itwas developed in order to produce management reports more objective andintuitive. His metric is well established in statistical terms andreflects exactly what one would expect from a market risk measure. The VaRresults in a net asset value, or a possibility of financial loss. Thispossibility of financial loss is tied to a time interval and statisticalsignificance. So we say: The portfolio has the possibility of losing $X onY days (or hours) with a statistical significance of Z%. 
Financial Risk Management 
Financial processes, however, do not follow a behavior saidhomoscedastic or constant over time but heteroscedastic. The volatilitycan undergo dramatic changes as in times of crisis. These phenomena can cause a sharp drop in equity of aparticular institution leading to bankruptcy in many cases. 

An analysis complementary to VaR, called Stress analysis isused to simulate situations of panic and financial crises. Thesesimulations analyze the tails of the distributions of returns and evaluate theportfolio in more extreme scenarios. It is possible to simulate historicalcrises, specific situations and scenarios to highly pessimistic anduncorrelated. 
It is necessary to understand the main feature of the marketis the strong stochastic process which asset prices are submitted. Unexpected situations are possible and even expected, and itis impossible to predict turbulence and crisis situations with sufficientprecision. The Financial Risk Management, however, has enough tools toevaluate and quantify the risks and fluctuations to which the portfolio issubmitted.

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