Enterprise-level risk assessment of geographically diversified commercial farms: a copula approach

As agriculture becomes more industrialized, the role of risk measures such as value-at-risk (VaR) will become more utilized. In this case it was applied to geographical diversification and also modifying the traditional VaR estimation by incorporating a copula dependence parameter into the VaR estimation. In addition, an alternative risk measure was also calculated, CVaR. The CVaR, unlike VaR, is a coherent risk measure. Thus it does not suffer from many of the shortcomings of the VaR. The land portfolio consisted of Dryland wheat production acres in Texas, Colorado, and Montana. Three series of net returns were calculated for each region. Based on the VaR and the CVaR, the portfolio was optimized based on minimizing the expected loss based on historical net revenues. The results showed that diversification could be reduced by producing in all three areas.Copula, CVaR, Risk-Management, Geographical Diversification, Agribusiness, Farm Management, Risk and Uncertainty,

Geographical Diversification: An Application of Copula Based CVaR

Risk and Uncertainty,

Credit Risk, Systemic Uncertainties and Economic Capital Requirements for an Artificial Bank Loan Portfolio

This paper analyses the impact of different credit risk-based capital requirement implementations on banks' need for capital. The capital requirements for an artificially constructed risky loan portfolio are calculated by applying the BIS approach, the two widespread commercial risk-measurement models, CreditMetrics and CreditRisk+, and, finally, an original synthetic model similar to KMV. In the first three cases we closely follow the methodologies proposed by the regulatory or credit risk models. Economic capital requirements for the latter are obtained by means of Monte Carlo simulations. In the context of CreditMetrics, we additionally perform a Monte Carlo-based stress testing of the monetary policy changes reflected in the term structure of interest rates. Our model of KMV type combines the elements of the structural and the reduced-form methods of risky debt pricing, and the possibilities of its numerical solution are outlined.credit risk, economic capital, market risk, New Basel Capital Accord, systemic uncertainty.

WARNING: Physics Envy May Be Hazardous To Your Wealth!

The quantitative aspirations of economists and financial analysts have for many years been based on the belief that it should be possible to build models of economic systems - and financial markets in particular - that are as predictive as those in physics. While this perspective has led to a number of important breakthroughs in economics, "physics envy" has also created a false sense of mathematical precision in some cases. We speculate on the origins of physics envy, and then describe an alternate perspective of economic behavior based on a new taxonomy of uncertainty. We illustrate the relevance of this taxonomy with two concrete examples: the classical harmonic oscillator with some new twists that make physics look more like economics, and a quantitative equity market-neutral strategy. We conclude by offering a new interpretation of tail events, proposing an "uncertainty checklist" with which our taxonomy can be implemented, and considering the role that quants played in the current financial crisis.Comment: v3 adds 2 reference

Time-Varying Market, Interest Rate and Exchange Rate Risk in Australian Bank Portfolio Stock Returns: A Garch-M Approach

This study employs an extended version of the Generalised Autoregressive Conditional Heteroskedasticity in Mean (GARCH-M) model to consider the time-series sensitivity of Australian bank stock returns to market, interest rate and foreign exchange rate risks. Daily Australian bank portfolio returns, a market wide accumulation index, short, medium and long-term interest rates, and a trade-weighted foreign exchange index are used to model these risks over the period 1996 to 2001. The results suggest that market risk is an important determinant of bank stock returns, along with short and medium term interest rate levels and their volatility. However, long-term interest rates and the foreign exchange rate do not appear to be significant to the Australian bank return generating process over the period considered.Bank stock returns; GARCH; market risk; interest rate risk; foreign exchange risk

CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles

Value at Risk has become the standard measure of market risk employed by financial institutions for both internal and regulatory purposes. Despite its conceptual simplicity, its measurement is a very challenging statistical problem and none of the methodologies developed so far give satisfactory solutions. Interpreting Value at Risk as a quantile of future portfolio values conditional on current information, we propose a new approach to quantile estimation that does not require any of the extreme assumptions invoked by existing methodologies (such as normality or i.i.d. returns). The Conditional Value at Risk or CAViaR model moves the focus of attention from the distribution of returns directly to the behavior of the quantile. Utilizing the criterion from Regression Quantiles, and postulating a variety of dynamic updating processes we propose methods based on a Genetic Algorithm to estimate the unknown parameters of CAViaR models. We propose a Dynamic Quantile Test of model adequacy that tests the hypothesis that in each period the probability of exceeding the VaR must be independent of all the past information. Applications to simulated and real data provide empirical support to our methodology and illustrate the ability of these algorithms to adapt to new risk environments.