Spectral Risk Measures: Properties and Limitations

Dowd, Kevin; Cotter, John; Sorwar, Ghulam

doi:10.2139/ssrn.1517148

Cited by 28 publications

(40 citation statements)

References 11 publications

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“…An alternative SRM is a power SRM based on the assumption that the coefficient of relative risk aversion is constant. The properties of these various SRMs are examined in more detail by Dowd et al (2008). 9 The measurement of risk aversion has figured significantly in the agricultural literature including inter alia Lagerkvist (2005) and Lence (2000).…”

Section: Estimation Methodsmentioning

confidence: 99%

Extreme Measures of Agricultural Financial Risk

Morgan¹,

Cotter²,

Dowd³

2011

J Agricultural Economics

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Risk is an inherent feature of agricultural production and marketing and accurate measurement of it helps inform more efficient use of resources. This paper examines three tail quantile-based risk measures applied to the estimation of extreme agricultural financial risk for corn and soybean production in the US: Value at Risk (VaR), Expected Shortfall (ES) and Spectral Risk Measures (SRMs). We use Extreme Value Theory (EVT) to model the tail returns and present results for these three different risk measures using agricultural futures market data. We compare the estimated risk measures in terms of their size and precision, and find that they are all considerably higher than normal estimates; they are also quite uncertain, and become more uncertain as the risks involved become more extreme.

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Section: Estimation Methodsmentioning

confidence: 99%

Extreme Measures of Agricultural Financial Risk

Morgan¹,

Cotter²,

Dowd³

2011

J Agricultural Economics

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“…Following Dowd et al. (), we introduce an exponential weighting function, where R represents the absolute risk aversion coefficient, with

R > 0

θ (p) = \frac{R \cdot e^{R \cdot p}}{e^{R} - 1} .

…”

Section: Conceptual Framework and Analysismentioning

confidence: 99%

“…For the SRM, we applied a R value of 0.5 following Dowd et al. (). In order to receive consistent results, we repeated the out‐of‐sample procedure 10,000 times, whereas we set

T = 20

and

j = 11 .

…”

Section: Case Study and Datamentioning

confidence: 99%

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Tailored to the extremes: Quantile regression for index‐based insurance contract design

Conradt

Finger

Bokusheva

2015

Agricultural Economics

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A new approach for weather index-based insurance design based on Quantile Regression (QR) to condition the yield-index dependency is developed and compared to standard regression technique. Three conceptual different risk measures, i.e., Expected Utility, Expected Shortfall and a Spectral Risk Measure, are used to evaluate the risk reducing properties of these contracts. Our findings show that QR is much more powerful in establishing the yield-index dependency and lead for all risk measures to a higher risk reduction than the standard technique ordinary least squares (OLS). Thus, QR leads to a more efficient contract design, which is beneficial for both, the insurer (smaller remaining risk) and the insured (higher demand and willingness to pay). Our empirical application is based on a 31 years long time series of wheat yield data from Northern Kazakhstan.JEL classifications: C21, G22, Q14

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“…Also, since Equation (3) provides all the quantiles of the hedged portfolio returns, we may employ any general QRM. As an example, we choose the exponential risk measure, which is probably the most studied SRM in the literature (Cotter & Dowd, 2006;Dowd, Cotter, & Sorwar, 2008).…”

Section: Special Casesmentioning

confidence: 99%

A Copula‐Based Quantile Risk Measure Approach to Estimate the Optimal Hedge Ratio

Barbi

Romagnoli

2013

Journal of Futures Markets

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We propose an innovative theoretical model to determine the optimal hedge ratio (OHR) with futures contracts as the minimizer of a quantile risk measure. This class of measures is very large and allows to recover the minimum‐VaR and the minimum‐expected shortfall hedge ratios as special cases. The copula representation of quantiles yields an accurate and flexible estimation of the dependence structure between the spot and the futures position. Employing data for the main UK and US indices, and EUR/USD and EUR/GBP exchange rates, we investigate the hedging effectiveness of our model compared to that of existing approaches. We document that our model improves upon the hedging performance of minimum‐VaR and minimum‐expected shortfall hedge ratios, provided that the copula shows an acceptable fit to the data. © 2013 Wiley Periodicals, Inc. Jrl Fut Mark 34:658–675, 2014

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Spectral Risk Measures: Properties and Limitations

Cited by 28 publications

References 11 publications

Extreme Measures of Agricultural Financial Risk

Extreme Measures of Agricultural Financial Risk

Tailored to the extremes: Quantile regression for index‐based insurance contract design

A Copula‐Based Quantile Risk Measure Approach to Estimate the Optimal Hedge Ratio

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