Estimating financial risk measures for futures positions: a non-parametric approach

TL;DR

This paper introduces a non-parametric method to estimate spectral risk measures for equity futures, compares them with VaR and ES, and analyzes how their accuracy varies with risk aversion and confidence levels.

Contribution

It provides a novel non-parametric approach to spectral risk measures and compares their performance with traditional risk metrics in futures trading.

Findings

All risk measures increase with higher risk aversion and confidence levels.

Estimator precision deteriorates as the conditioning parameters increase.

Spectral risk measures are comparable in magnitude and precision to traditional measures.

Abstract

This paper presents non-parametric estimates of spectral risk measures applied to long and short positions in 5 prominent equity futures contracts. It also compares these to estimates of two popular alternative measures, the Value-at-Risk (VaR) and Expected Shortfall (ES). The spectral risk measures are conditioned on the coefficient of absolute risk aversion, and the latter two are conditioned on the confidence level. Our findings indicate that all risk measures increase dramatically and their estimators deteriorate in precision when their respective conditioning parameter increases. Results also suggest that estimates of spectral risk measures and their precision levels are of comparable orders of magnitude as those of more conventional risk measures. Running head: financial risk measures for futures positions