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Commodity Indices Risk and Return Analysis Against Libor Benchmark

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This study analyze the risk and return characteristics of commodity index investments against the LIBOR benchmark. Commodity-based asset allocation strategies can be optimized by benchmarking the risk and return characteristics of commodity indices with LIBOR index rate. In this study, we have considered agriculture, energy, and precious metals commodity indices and LIBOR index to determine the risk and return characteristics using estimation techniques in terms of expected return, standard deviation, and geometric mean. We analyzed the publicly available daily market data from 10/9/2001 to 12/30/2016 for benchmarking commodity indices against LIBOR. S&P GSCI Agriculture Index (SGK), S&P GSCI Energy Index (SGJ), and S&P GSCI Precious Metals Index (SGP) are taken to represent each category of widely traded commodities in the regression analysis. Our study uses time series data based on daily prices. Alternative forecasting methodologies for time series analysis are used to cross-check the results. The forecasting techniques used are Holt-Winters Exponential Smoothing and ARIMA. This methodology predicts forecasts using smoothening parameters. The empirical research has shown that the risk of each of the commodity index that represents agriculture, energy, and precious metals sector is smaller compared to its return, whereas LIBOR based interest rate benchmark shows higher risk compared to its return in recession, non-recession and overall periods. JEL Classification: C43, G13, G15
University of Debrecen/ Debreceni Egyetem
Title: Commodity Indices Risk and Return Analysis Against Libor Benchmark
Description:
This study analyze the risk and return characteristics of commodity index investments against the LIBOR benchmark.
Commodity-based asset allocation strategies can be optimized by benchmarking the risk and return characteristics of commodity indices with LIBOR index rate.
In this study, we have considered agriculture, energy, and precious metals commodity indices and LIBOR index to determine the risk and return characteristics using estimation techniques in terms of expected return, standard deviation, and geometric mean.
We analyzed the publicly available daily market data from 10/9/2001 to 12/30/2016 for benchmarking commodity indices against LIBOR.
S&P GSCI Agriculture Index (SGK), S&P GSCI Energy Index (SGJ), and S&P GSCI Precious Metals Index (SGP) are taken to represent each category of widely traded commodities in the regression analysis.
Our study uses time series data based on daily prices.
Alternative forecasting methodologies for time series analysis are used to cross-check the results.
The forecasting techniques used are Holt-Winters Exponential Smoothing and ARIMA.
This methodology predicts forecasts using smoothening parameters.
The empirical research has shown that the risk of each of the commodity index that represents agriculture, energy, and precious metals sector is smaller compared to its return, whereas LIBOR based interest rate benchmark shows higher risk compared to its return in recession, non-recession and overall periods.
JEL Classification: C43, G13, G15.

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