A Markov regime switching approach for hedging energy commodities

Abstract This paper estimates constant and dynamic hedge ratios in the New York Mercantile Exchange oil futures markets and examines their hedging performance. We also introduce a Markov regime switching vector error correction model with GARCH error structure. This specification links the concept of disequilibrium with that of uncertainty (as measured by the conditional second moments) across high and low volatility regimes. Overall, in and out-of-sample tests indicate that state dependent hedge ratios are able to provide significant reduction in portfolio risk

Jumps and stochastic volatility in crude oil prices and advances in average option pricing

Crude oil derivatives form an important part of the global derivatives market. In this paper, we focus on Asian options which are favoured by risk managers being effective and cost-saving hedging instruments. The paper has both empirical and theoretical contributions: we conduct an empirical analysis of the crude oil price dynamics and develop an accurate pricing setup for arithmetic Asian options with discrete and continuous monitoring featuring stochastic volatility and discontinuous underlying asset price movements. Our theoretical contribution is applicable to various commodities exhibiting similar stylized properties. We here estimate the stochastic volatility model with price jumps as well as the nested model with omitted jumps to NYMEX WTI futures vanilla options. We find that price jumps and stochastic volatility are necessary to fit options. Despite the averaging effect, we show that Asian options remain sensitive to jump risk and that ignoring the discontinuities can lead to substantial mispricings

Investor Sentiment for Real Assets: The Case of Dry Bulk Shipping Market*

We investigate the role of sentiment and its implications for real assets. Using shipping sentiment proxies that capture market expectations, valuation, and liquidity, we construct sentiment indices for the dry bulk shipping market. Evidence suggests that sentiment affects the monthly returns of real assets. The empirical findings also show that market sentiment serves as a contrarian indicator for future cycle phases in all sectors. Furthermore, a sentiment-based trading simulation exercise on the sale and purchase of vessels shows that investors can benefit from higher returns compared to the buy-and-hold benchmark, while partially offsetting the highly volatile nature of the shipping industry

Portfolio optimization and index tracking for the shipping stock and freight markets using evolutionary algorithms

This paper reproduces the performance of an international market capitalization shipping stock index and two physical shipping indexes by investing only in US stock portfolios. The index-tracking problem is addressed using the differential evolution algorithm and the genetic algorithm. Portfolios are constructed by a subset of stocks picked from the shipping or the Dow Jones Composite Average indexes. To test the performance of the heuristics, three different trading scenarios are examined: annually, quarterly and monthly rebalancing, accounting for transaction costs where necessary. Competing portfolios are also assessed through predictive ability tests. Overall, the proposed investment strategies carry less risk compared to the tracked benchmark indexes while providing investors the opportunity to efficiently replic ate the performance of both the stock and physical shipping indexes in the most cost-effective way

Risk management of climate impact for tourism operators: An empirical analysis on ski resorts

The aim of this paper is to analyze the performance of hedging strategies based on snow andtemperature options developed by ski operators to protect their profitability under adversechanges in climatic conditions. The setup is based on a joint non-parametric model for snowand temperature aimed at providing a modelling support for the assessment of the impact ofthese weather variables on the number of visitors at the ski resort. The analysis is carried outconsidering the case of Austrian Alps, and examines: i) the ability of the proposed approach toprovide a realistic representation of the true data-generating process; ii) the variability reductionin the Profit and Loss of the ski operator offered by the suggested strategies; and iii) the tradeoffbetween the budget earmarked for hedging and profitability protection

Forecasting petroleum futures markets volatility: The role of regimes and market conditions

In this paper we employ regime volatility models to describe time dependency in petroleum markets. Using a sample of NYMEX and ICE futures contracts, we establish the existence of a regime process and link this process to market fundamentals. This formulation results in two distinct states: a highly persistent conditional volatility process, characterised by long memory and low sensitivity to market shocks, and a relatively short-lived nonstationary process with less memory but higher sensitivity to shocks. Moreover, to investigate the relationship between disequilibrium and volatility of oil futures across high and low volatility regimes we use augmented regime GARCH models to address in a realistic way the potential diverse response of volatility to forward curve shocks. The performance of these models is compared to benchmarks, using both statistical tests and risk management loss functions. To test the robustness of the forecasting strategies, we also perform a reality check employing the stationary bootstrap approach. The findings of this paper have important implications for decision making concerning trading and risk management, as well as energy market operations, such as refining and budget planning, by providing valuable information on the oil price volatility dynamics and the ability to predict risk.Petroleum markets Regime-dependent volatility Forecasting Reality check Value-at-risk