The Return-Volatility Relation in Commodity Futures Markets PDF Download
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Author: Carl Chiarella
Publisher:
ISBN:
Category :
Languages : en
Pages : 30
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Book Description
By employing a continuous time stochastic volatility model, the dynamic relation between price returns and volatility changes in the commodity futures markets is analysed. An extensive daily database of gold and crude oil futures and futures options is used to estimate the model that is well suited to assess the return-volatility relation for the entire term structure of futures prices. The empirical results indicate a positive relation in the gold futures market and a negative relation in the crude oil futures market, especially over periods of high volatility principally driven by market-wide shocks. However, the opposite reaction occurs over quiet volatility periods when typically commodity-specific effects dominate. As leverage effect, volatility feedback effect and inventory effect do not adequately explain this reaction especially for the crude oil futures, the convenience yield effect is proposed. Accordingly, commodity futures markets in backwardation entail a positive relation, while futures markets in contango entail a negative relation.
Author: Carl Chiarella
Publisher:
ISBN:
Category :
Languages : en
Pages : 30
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Book Description
By employing a continuous time stochastic volatility model, the dynamic relation between price returns and volatility changes in the commodity futures markets is analysed. An extensive daily database of gold and crude oil futures and futures options is used to estimate the model that is well suited to assess the return-volatility relation for the entire term structure of futures prices. The empirical results indicate a positive relation in the gold futures market and a negative relation in the crude oil futures market, especially over periods of high volatility principally driven by market-wide shocks. However, the opposite reaction occurs over quiet volatility periods when typically commodity-specific effects dominate. As leverage effect, volatility feedback effect and inventory effect do not adequately explain this reaction especially for the crude oil futures, the convenience yield effect is proposed. Accordingly, commodity futures markets in backwardation entail a positive relation, while futures markets in contango entail a negative relation.
Author: Sang-Hak Lee
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Author: Hendrik Bessembinder
Publisher:
ISBN:
Category : Futures
Languages : en
Pages : 36
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Book Description
Author: Daniel Giamouridis
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
The relationship between stock market returns and volatilities has been extensively investigated in the academic literature. In this paper the relationship between Commodity Returns and volatility is investigated for the first time. We shared the feeling that the relationship between return and volatility in the commodity markets is the inverse of that observed in the stock markets. If that hypothesis proves to be true and if commodity markets returns are negatively correlated with the returns of traditional financial assets, the introduction of commodities in investment portfolios would result in the diversification of the volatility exposure. This will allow Fund Managers to hedge investment portfolios with commodities, thus avoiding the use of more complicated instruments, such as options. We carry out the exploratory tests of Black [1976], to test the hypothesis with the unconditional variance, as well as the tests of Nelson [1991], Zakoian [1990] and Glosten, Jagannathan, and Runkle [1993], to test the hypothesis on the conditional variance. The estimation of the models yields statistically significant asymmetric terms only for the conditional variance and the initial hypothesis that the conditional variance responds asymmetrically to past information is not rejected.
Author: Peter Christoffersen
Publisher:
ISBN:
Category :
Languages : en
Pages : 64
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Book Description
We uncover stylized facts of commodity futures price and volatility dynamics in the post-financialization period and find a factor structure in daily commodity volatility that is much stronger than the factor structure in returns. The common factor in commodity volatility relates to stock market volatility as well as to the business cycle. Model-free realized commodity betas with the stock market were high during 2008-2010 but have since returned to the pre-crisis level close to zero. We conclude that, while commodity markets appear segmented from the equity market when considering only returns, commodity volatility indicates a nontrivial degree of market integration.
Author: Lin Gao
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
The detrended implied volatility of commodity options (VOL) forecasts the cross section of the commodity futures returns significantly. A zero-cost strategy that is long in low VOL and short in high VOL commodities yields an annualized return of 12.66% and a Sharpe ratio of 0.69. Notably, the excess returns based on the volatility strategy emanate mainly from its forecasting power for the future spot component, different from the other commodity strategies examined so far in the literature which are all driven by roll returns. This strategy demonstrates low correlations (below 10%) with the other strategies such as momentum or basis and performs especially well in recessions. Our results are robust after controlling for illiquidity, other commodity pricing factors, and exposure to the aggregate commodity market volatility. The VOL measure is associated with hedging pressure on the futures and especially on the options market. News media also helps amplify the uncertainty impact. Variables related to investors' lottery preferences and market frictions are able to explain part of the predictive relationship.
Author: Adrian Fernandez-Perez
Publisher:
ISBN:
Category :
Languages : en
Pages : 30
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Book Description
This article investigates the relationship between expected returns and past idiosyncratic volatility in commodity futures markets. Measuring the idiosyncratic volatility of 27 commodity futures contracts with traditional pricing models that fail to account for backwardation and contango leads to the puzzling finding that idiosyncratic volatility is significantly negatively priced cross-sectionally. However, idiosyncratic volatility is not priced when the phases of backwardation and contango are suitably factored in the pricing model. A time-series portfolio analysis similarly suggests that failing to recognize the fundamental risk associated with the inexorable phases of backwardation and contango leads to overstated profitability of the idiosyncratic volatility mimicking portfolios.
Author: Vivek Rajvanshi
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
We use tick-by-tick data for one energy futures (crude oil) and four metal futures (gold, silver, copper, and zinc) traded at Multi-Commodity Exchange India Limited (MCX) for the period of four years from January 1, 2009 to December 31, 2012. We test and find support for the Mixture of-Distribution Hypothesis (MDH), which suggests a positive simultaneous relationship between trading volume and price volatility, and the Sequential Information Arrival Hypothesis (SIAH), which argues that information arrives sequentially in the market and there would be a lead-lag relationship between volatility and volume. Further, in order to test the dispersed belief and asymmetrical information hypothesis, we test the impact of the net effect of trading numbers and order imbalance on volatility. We find that trading numbers explain the volume-volatility relationship better than the order imbalance and mainly drive the return volatility in the Indian commodity futures market. Our results find strong support for the above hypotheses and suggest that the four theories -- MDH, SIAH, dispersed belief, and asymmetrical information hypothesis -- complement each other.
Author: Xuemei Xiao
Publisher:
ISBN:
Category :
Languages : en
Pages : 74
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Book Description
This thesis investigates the relationship between speculation in futures markets and expected and unexpected volatility in the spot markets for 21 different commodities. I use the index of adequate speculation, INDADSP, and the index of excess speculation, INDEXSP, developed and estimated by Shanker (2017), to capture the degree of speculation required to meet hedging demand, and the degree of speculation in excess of hedging demand, respectively. For comparison, I also use Working's (1960) speculative index T, as a measure of speculation. I estimate the expected volatility (EV) and unexpected volatility (UEV) of the spot market using a GARCH model. The empirical results indicate that the GJR-GARCH model with a Student's t distribution for the error term is the most appropriate model, among the GARCH-family of models, to capture the volatility of 17 of the 21 spot commodity returns. However, the results of feeder cattle indicate the exists of serial correlation of the residuals for all three GARCH model I used, so I drop it and do the further analysis for the rest of 20 commodities and financial contracts. For each commodity, I create time series of matched weekly indices of speculation, expected volatility and unexpected volatility. Next, I investigate the long-run and short-run relationships between volatilities and speculation using an autoregressive distributed lag model. The results indicate that there is a long term relationship between expected and unexpected volatility and the speculative indices, for all commodities, except the Euro, Eurodollar, and U.S. T-bond, and a short term relationship between volatilities and speculation for all commodities. Finally, I apply the Toda-Yamamoto test to investigate the causal relationship between speculation in futures markets and volatility in spot markets. I find that speculation tends to lead expected volatility more than unexpected volatility for the majority of commodities/financial assets. Expected volatility, rather than unexpected volatility, tends to lead speculation for a majority of commodities/financial assets. There is a bidirectional causality between expected volatility and INDADSP, INDEXSP, and T and between unexpected volatility and INDEXSP for several different commodities and financial assets. However, there is no bidirectional causality between unexpected volatility and the speculative indices INDADSP and T for all 20 commodities/financial assets.
Author: Thomas Hoehl
Publisher: GRIN Verlag
ISBN: 3656047715
Category : Business & Economics
Languages : en
Pages : 89
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Book Description
Master's Thesis from the year 2011 in the subject Economics - Finance, grade: 8,0, Maastricht University (School of Business and Economics), language: English, abstract: This study finds that while a large part of the variation in crude oil futures prices is driven by fundamental factors, financial investment and speculation has the potential to aggravate reactions to changing fundamental variables and furthermore move prices on its own. The evidence is gathered by performing linear regressions and Granger Causality tests on futures returns, position data of different categories of futures traders on the New York Mercantile Exchange and proxies for relevant fundamental factors such as equity and exchange rate returns gathered from August 2006 to December 2010. While higher prices for crude oil naturally come along with increasing physical demand and finite world supply, future regulation might temper market volatility and guarantee that prices reflect a sustainable physical market equilibrium. The study also gives an overview of commodity market regulation and position limits on futures markets.
