105 research outputs found
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Herd behavior in the drybulk market: An empirical analysis of the decision to invest in new and retire existing fleet capacity
We examine whether investors herd in their decision to order or scrap vessels in the drybulk market. We decompose herding into unintentional and intentional, and test for herd behavior under asymmetric effects with respect to freight market states, cycle phases, risk-return and valuation profiles, and ownership of the vessel. We detect unintentional herd behavior during down freight markets and contractions. Furthermore, we find evidence of spill-over unintentional herding effects from the newbuilding to the scrap market. Finally, asymmetric herd effects are evident between traditional and liberal philosophy towards the ownership of the vessel, and during extreme risk-return and valuation periods
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Freight Derivatives Pricing for Decoupled Mean-Reverting Diffusion and Jumps
We develop an accurate valuation setup for freight options, featuring an exponential meanreverting model for the freight rate with distinct reversion scales for its jump and diffusion components. We calibrate to Baltic option prices and analyze the freight rate dynamics. More specifically, we observe that jumps dissipate faster than the diffusive deviations about the equilibrium level. We benchmark against practitioners’ model of choice, i.e., the lognormal model and variants, and find that our approach reduces the pricing error while preserving analytical tractability and computational competence. We also find that neglecting fast mean-reverting jumps leads to nontrivial option mispricings
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Freight options: Price modelling and empirical analysis
This paper discusses an extension of the traditional lognormal representation for the risk neutral spot freight rate dynamics to a diffusion model overlaid with jumps of random magnitude and arrival. Then, we develop a valuation framework for options on the average spot freight rate, which are commonly traded in the freight derivatives market. By exploiting the computational efficiency of the proposed pricing scheme, we calibrate the jump diffusion model using market quotes of options on the trip-charter route average Baltic Capesize, Panamax and Supramax Indices. We show that the jump-extended setting yields important model improvements over the basic lognormal setting
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Shipping equity risk behavior and portfolio management
This paper investigates the dynamics of stock price volatility for different vessel-type segments of the U. S, water transportation industry . We measure market exposure by a portfolio of tanker, dry bulk, container, and gas stocks to examine tail behavior and tail risk dependence. The role of mixture distributions in predicting future volatility is studied from both statistical and economic perspectives. We further test for predictability in co-movements in the tails of sectors returns . Findings indicate that large losses are strongly correlated, supporting asymmetric transmission processes for financial contagion. Finally, using a non-parametric approach, we extend the model to the multivariate case and assess the value of volatility and correlation timing in optimal portfolio selection. The results can help to improve the understanding of time-varying volatility, correlation and tail systemic risk of shipping stock markets, and consequently, have implications for risk management and asset allocation practices, as well as regulatory policies
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Shipping Investor Sentiment and International Stock Return Predictability
Stock return predictability by investor sentiment has been subject to constant updating, but reaching a decisive conclusion seems rather challenging as academic research relies heavily on US data. We provide fresh evidence on stock return predictability in an international setting and show that shipping investor sentiment is a common leading indicator for financial markets. We establish out-of-sample predictability and demonstrate that investor sentiment is also economically significant in providing utility gains to a mean-variance investor. Finally, we find evidence that the predictive power of sentiment works best when negative forecasts are also taken into account
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Affine-Structure Models and the Pricing of Energy Commodity Derivatives
We consider a seasonal mean-reverting model for energy commodity prices with jumps and Heston-type stochastic volatility, and three nested models for comparison. By exploiting the affine form of the log-spot models, we develop a general valuation framework for futures and discrete arithmetic Asian options. We investigate five major petroleum commodities from Europe (Brent crude oil, gasoil) and US (light sweet crude oil, gasoline, heating oil) and analyse the effects of the competing fitted spot models in futures pricing, Asian options pricing and hedging. We find evidence that price jumps and stochastic volatility are important features of the petroleum price dynamics
Downstream separation and purification of succinic acid from fermentation broths using spent sulphite liquor as feedstock
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Analysis of Volatility and Correlation for CME Steel Products
Correlation and volatility between commodity prices is a very important factor to consider when designing risk management and investment strategies. The efficiency of hedging strategies for instance, depends on the existence of strong and stable correlation between spot and futures commodity prices; the absence of correlation on the other hand, or even sudden changes in the level of correlations may have detrimental implications not only for hedging and risk management but also in shaping the efficiency of a country’s energy, manufacturing and food policies. In general,co-movements between commodity markets may be attributed to common macroeconomic shocks on world markets, and the complementarity or substitutability in the production or consumption of related commodities. It is also an established fact that although the prices for related commodities are correlated, correlation changes over time and, in particular, correlation changes have become more erratic over the last five years. Recent research by Buyuksahin et. al (2010) and Silvennoinen and Thorp (2010) has found that returns correlation between commodities has increased substantially during the recent financial crisis. Tang and Xiong (2011) also highlight that the increase in the correlations between the returns of different commodity futures started long before the crisis and cannot be simply attributed to the onset of the crisis. In this report we attempt to identify whether the co-movement of HRC CRU, which is the underlying asset for the CME contract, and a basket of related steel commodities is strong enough
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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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