6 research outputs found
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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
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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
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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
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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
Factors affecting the dynamics of yield premia on shipping seasoned high yield bonds
This paper investigates factors that can explain the dynamics of yield premia on seasoned high yield bonds of shipping companies. Our analysis utilises 40 seasoned high yield bonds offered by 32 shipping companies between April 1998 and December 2002 and a set of microeconomic, macroeconomic and, industry related factors. Our model suggests that the dynamics of credit premia of seasoned shipping high yield bonds can be explained by: credit rating; term-to-maturity; changes in earnings in the shipping market, as well as in the yield on 10-year Treasury bonds; and the yield on the Merrill Lynch single-B index.High yield bonds Yield spread Shipping market Panel data