Stochastic Volatility and Seasonality in Commodity Futures and Options PDF Download
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Author: Martin Christian Richter
Publisher:
ISBN:
Category :
Languages : en
Pages : 45
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Author: Martin Christian Richter
Publisher:
ISBN:
Category :
Languages : en
Pages : 45
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Author: Juan Arismendi-Zambrano
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ISBN:
Category :
Languages : en
Pages : 53
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Book Description
Many commodity markets contain a strong seasonal component not only at the price level, but also in volatility. In this paper, the importance of seasonal behavior in the volatility for the pricing of commodity options is analyzed. We propose a seasonally varying long-run mean variance process that is capable of capturing empirically observed patterns. Semi-closed form option valuation formulas are derived. We then empirically study the impact of the proposed seasonal stochastic volatility model on the pricing accuracy of natural gas futures options traded at the New York Mercantile Exchange (NYMEX) and corn futures options traded at the Chicago Board of Trade (CBOT). Our results demonstrate that allowing stochastic volatility to fluctuate seasonally significantly reduces pricing errors for these contracts.
Author: Nazibrola Lordkipanidze
Publisher:
ISBN:
Category :
Languages : en
Pages : 296
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Author: Jilong Chen
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Category :
Languages : en
Pages : 23
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In this paper we investigate the applicability of the asymptotic approach developed in Fouque et al. (2000) for pricing commodity futures options in a Schwartz (1997) multi factor model, featuring both stochastic convenience yield and stochastic volatility. We show that the zero order term in the expansion coincides with the Schwartz (1997) two factor term, with expected long-term volatility replacing the constant volatility term, and provide an explicit expression for the first order correction term. Using empirical data from the natural gas futures market, we demonstrate that a significantly better calibration can be achieved by involving the correction term as compared to the standard Schwartz (1997) two factor expression. This improvement comes at virtually no extra effort.
Author: Gonzalo Cortazar
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ISBN:
Category :
Languages : en
Pages : 60
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We propose a novel representation of commodity spot prices in which the cost-of-carry and the spot price volatility are both driven by an arbitrary number of risk factors, nesting many existing specifications. The model exhibits unspanned stochastic volatility, provides simple closed-form expressions of commodity futures, and yields analytic formulas of European options on futures. We estimate the model using oil futures and options data, and find that the pricing of traded contracts is accurate for a wide range of maturities and strike prices. The results suggest that at least three risk factors in the spot price volatility are needed to accurately fit the volatility surface of options on oil futures, highlighting the importance of using general multifactor models in pricing commodity contingent claims.
Author: Nasibrola Lordkipanidze
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ISBN:
Category :
Languages : en
Pages :
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The empirical evidence in this paper supports the existence of seasonality, time-to-maturity, and long-memory effects in the volatility of prices, but not in the returns themselves, in corn and soybean futures markets. This volatility is modeled as an Orenstein-Ulenbeck process driven by fractional Brownian motion. The inclusion of long-memory stochastic volatility is found to have a significant impact upon the term structure of implied volatilities, and should be able to provide better estimates of in- and out-of-the money options Ěprices.
Author: Michael Jamel Osei
Publisher:
ISBN:
Category : Options (Finance)
Languages : en
Pages : 128
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Author: Anders B. Trolle
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Category : Petroleum industry and trade
Languages : en
Pages : 50
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We conduct a comprehensive analysis of unspanned stochastic volatility in commodity markets in general and the crude-oil market in particular. We present model-free results that strongly suggest the presence of unspanned stochastic volatility in the crude-oil market. We then develop a tractable model for pricing commodity derivatives in the presence of unspanned stochastic volatility. The model features correlations between innovations to futures prices and volatility, quasi-analytical prices of options on futures and futures curve dynamics in terms of a low-dimensional affine state vector. The model performs well when estimated on an extensive panel data set of crude-oil futures and options.
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: Gareth Peters
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Category :
Languages : en
Pages :
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Book Description
We construct a general multi-factor model for estimation and calibration of commodity spot prices and futures valuation. This extends the multi-factor long-short model in Schwartz and Smith (2000) and Yan (2002) in two important aspects: firstly we allow for both the long and short term dynamic factors to be mean reverting incorporating stochastic volatility factors and secondly we develop an additive structural seasonality model. In developing this non-linear continuous time stochastic model we maintain desirable model properties such as being arbitrage free and exponentially affine, thereby allowing us to derive closed form futures prices. In addition the models provide an improved capability to capture dynamics of the futures curve calibration in different commodities market conditions such as backwardation and contango. A Milstein scheme is used to provide an accurate discretized representation of the s.d.e.model. This results in a challenging non-linear non-Gaussian state-space model. To carry out inference, we develop an adaptive particle Markov chain Monte Carlo method. This methodology allows us to jointly calibrate and filter the latent processes for the long-short and volatility dynamics. This methodology is general and can be applied to the estimation and calibration of many of the other multi-factor stochastic commodity models proposed in the literature. We demonstrate the performance of our model and algorithm on both synthetic data and real data for futures contracts on crude oil.
