by Don Alexander, MBA
Associate, RSD Solutions Inc.
Financial volatility is a crucial input for risk management, asset pricing and portfolio management and has important economic repercussions as evidenced in the recent financial crisis. It is important to understand from a risk management standpoint the key drivers of volatility.
A recent working paper (March 2012) at the BIS, "A Comprehensive Look at Financial Volatility Prediction by Economic Variables", by Charlotte Christiansen, Malik Schmeling & Andreas Schrimpf looks at the use economic and financial variables as a predictor of volatility. Christiansen et al investigate if asset return volatility is predictable by macroeconomic and financial variables. The main goal of the study is to shed light on the economic sources of financial volatility.
Their approach is distinct due to its comprehensiveness and extends recent research in several directions: First, they employ a long-term sample period and use forecast methodology to handle a large set of potential predictors, Second, they include multiple asset classes (equities, foreign exchange, bonds, and commodities), Third, they employ a comprehensive set of predictive variables which goes beyond existing studies in the literature on the economic drivers of volatility, and Fourth, the authors use comprehensive model selection and forecast combination procedures to assess whether economic variables are useful and robust predictors of financial volatility.
The authors find that there is significant information contained in economic variables that helps in predicting future volatility for all four asset classes under study. Importantly, this predictive content by economic variables goes beyond the information contained in the history of the time series of realized volatility.
The results are also supportive of financial volatility predictability by macroeconomic and financial variables in a realistic out-of-sample setting. The variables that are the most robust predictors of volatility are those that have sensible economic interpretations. In particular, variables that proxy for credit risk and funding liquidity (illiquidity) consistently show up significant forecast variable of volatility across several asset classes. Variables capturing time-varying risk premia (such as valuation ratios for equities, or interest rate differentials in foreign exchange) also perform well as significant indicators of volatility.
In contrast to these financial predictors, variables that proxy for macroeconomic conditions, are much less informative about future volatility. Thus, the results suggest that channels that emphasize the effects of leverage, credit risk and funding illiquidity as well as time-variation of risk premia are the most promising candidates for understanding the economic drivers of financial volatility.
A key requirement for risk management is the understanding of volatility, but it also provides other information. This may include uncovering linkages between price movements in financial markets and underlying risk factors or business cycle variables. There is growing evidence showing that risks associated with volatility are priced into most asset and derivative markets.
For more on this, follow the link: www.bis.org/index.htm?ht=Research
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