Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

Commodity Indices Risk and Return Analysis Against Libor Benchmark

View through CrossRef
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.

Related Results

A Practitioner's Guide to Pricing and Hedging Callable Libor Exotics in Forward Libor Models
A Practitioner's Guide to Pricing and Hedging Callable Libor Exotics in Forward Libor Models
Callable Libor exotics is a class of single-currency interest-rate contracts that are Bermuda-style exercisable into underlying contracts consisting of fixed-rate, floating-rate an...
Commodity trading advisors (CTAs) for the Indian commodity market
Commodity trading advisors (CTAs) for the Indian commodity market
PurposeThe Indian commodity market requires large investments and enhanced trading activity both in the national as well as the regional commodity markets. The participation of non...
The LIBOR Reader
The LIBOR Reader
Short articles on the LIBOR scandal looking for a deeper understanding of the crisis<br><br>At the end of June 2012, news of a further scandal in the banking industry b...
Tiny datablock in saving Hadoop distributed file system wasted memory
Tiny datablock in saving Hadoop distributed file system wasted memory
<p>Hadoop distributed file system (HDFS) is the file system whereby Hadoop is use it to store all the upcoming data inside it. Since it been declared, HDFS is consuming a hug...
LIBOR Manipulation?
LIBOR Manipulation?
On May 29, 2008, the Wall Street Journal (the Journal) printed an article that alleged that several global banks were reporting unjustifiably low borrowing costs for the calculatio...
The Rise and Fall of LIBOR and Its Alternatives
The Rise and Fall of LIBOR and Its Alternatives
For forty years, LIBOR was the dominant benchmark interest rate for various financial products, playing a central role in global financial markets. LIBOR was available in 10 curren...
Is LIBOR Still Being Manipulated?: Identifying Colluders with Methods of Detecting LIBOR Tampering
Is LIBOR Still Being Manipulated?: Identifying Colluders with Methods of Detecting LIBOR Tampering
We analyze the one-month U.S. Dollar London Interbank Offer Rate (LIBOR) between January 1987 and February 2015 to determine whether there are signs of manipulation based on a prev...
Technical Analysis in Financial Markets
Technical Analysis in Financial Markets
The efficient markets hypothesis states that in highly competitive and developed markets it is impossible to derive a trading strategy that can generate persistent excess profits a...

Back to Top