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

Analysis of model implied volatility for jump diffusion models: Empirical evidence from the Nordpool market

In this paper we examine the importance of mean reversion and spikes in the stochastic behaviour of the underlying asset when pricing options on power. We propose a model that is flexible in its formulation and captures the stylized features of power prices in a parsimonious way. The main feature of the model is that it incorporates two different speeds of mean reversion to capture the differences in price behaviour between normal and spiky periods. We derive semi-closed form solutions for European option prices using transform analysis and then examine the properties of the implied volatilities that the model generates. We find that the presence of jumps generates prominent volatility skews which depend on the sign of the mean jump size. We also show that mean reversion reduces the volatility smile as time to maturity increases. In addition, mean reversion induces volatility skews particularly for ITM options, even in the absence of jumps. Finally, jump size volatility and jump intensity mainly affect the kurtosis and thus the curvature of the smile with the former having a more important role in making the volatility smile more pronounced and thus increasing the kurtosis of the underlying price distribution

Economic significance of market timing rules in the Forward Freight Agreement markets

Quantitative market timing strategies have been traditionally tested in liquid commodity and financial futures, often with mixed results with respect to their performance. We extend this methodology to a non-storable commodity, freight, where hitherto this analysis has not been carried out. The freight futures market is mature and increasingly liquid, making it a good case for diversification and trading opportunities. We carry out a comprehensive study of quantitative trading strategies in the FFA (Forward Freight Agreements) market on a wide variety of contracts and maturities with a number of trading rules. We find that in spite of robustness checks, trading rules do outperform the buy-and-hold benchmark in general. We also explore the possibility that illiquidity and a small sample size may impact the results of the tests and therefore offer an intuitive approach to mitigate their effects. A procedure that augments the Hansen (2005) SPA (Superior Predictive Ability) methodology and allows us to use it for smaller sample sizes with increased confidence is also proposed

Corporate Cash Holdings in the Shipping Industry

We examine the corporate cash holdings of listed shipping companies and show that shipping firms hold more cash than similar firms in other asset-heavy industries. Higher cash holdings in the shipping industry are not attributable to firm- or country-level characteristics, but rather to the higher marginal value of cash. Shipping firms value an additional dollar of cash higher than matched manufacturing firms, regardless of their financial constraints status, but depending on their cultural background and the cyclicality of their expansion opportunities. Less procyclical shipping firms have a higher marginal value of cash, and this valuation effect is most pronounced in bad times of the business cycle when external capital supply tends to becomescarce.Overall, it appears that shipping companies are more conservative than their peers in managing their cash positions

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

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

Container trade and the U.S. recovery

Since the 1970s, exports and imports of manufactured goods have been the engine of international trade and much of that trade relies on container shipping. This paper introduces a new monthly index of the volume of container trade to and from North America. Incorporating this index into a structural macroeconomic VAR model facilitates the identification of shocks to domestic U.S. demand as well as foreign demand for U.S. manufactured goods. We show that, unlike in the Great Recession, the primary determinant of the U.S. economic contraction in early 2020 was a sharp drop in domestic demand. Although detrended data for personal consumption expenditures and manufacturing output suggest that the U.S. economy has recovered to near 90% of pre-pandemic levels as of March 2021, our structural VAR model shows that the component of manufacturing output driven by domestic demand had only recovered to 59% of pre-pandemic levels and that of real personal consumption only to 76%. The difference is mainly accounted for by unexpected reductions in frictions in the container shipping market

Modelling short and long-term risks in power markets: Empirical evidence from Nord Pool

In this paper we propose a three-factor spike model that accounts for different speeds of mean reversion between normal and spiky shocks in the Scandinavian power market. In this model both short and long-run factors are unobservable and are hence estimated as latent variables using the Kalman filter. The proposed model has several advantages. First, it seems to capture in a parsimonious way the most important risks that practitioners face in the market, such as spike risk, short-term risk and long-term risk. Second, it explains the seasonal risk premium observed in the market and improves the fit between theoretical and observed forward prices, particularly for long-dated forward contracts. Finally, closed-form solutions for forward contracts, derived from the model, are consistent with the fact that the correlation between contracts of different maturities is imperfect. The resulting model is very promising, providing a very useful policy analysis and financial engineering tool to market participants for risk management and derivative pricing particularly for long-dated contracts.Electricity derivatives Kalman filter Affine jump diffusion models

Cost of carry, causality and arbitrage between oil futures and tanker freight markets

This paper investigates the dynamic relationship between oil futures and spot markets and tanker freight rates across two major tanker routes. In particular, we examine the validity of the cost of carry relationship in the WTI futures market, which suggests that the difference between physical and futures crude oil prices should reflect the transportation costs. We also examine whether the futures-physical oil differential contains information regarding tanker freight rate formation. Using physical crude oil prices for the Brent and Bonny markets, WTI futures prices and freight rates we find no evidence to support the existence of a relationship between tanker freight rates and physical-futures differentials in the crude oil market. This is mainly attributed to regional supply and demand imbalances and suggests that arbitrage opportunities between oil derivatives and tanker freight markets exist. Simulated trading strategies reveal the existence of excess profits, which are robust to variations in transaction costs, pipeline charges and timing of initiation of arbitrage.G13

Analysis of model implied volatility for jump diffusion models: Empirical evidence from the Nordpool market

In this paper we examine the importance of mean reversion and spikes in the stochastic behaviour of the underlying asset when pricing options on power. We propose a model that is flexible in its formulation and captures the stylized features of power prices in a parsimonious way. The main feature of the model is that it incorporates two different speeds of mean reversion to capture the differences in price behaviour between normal and spiky periods. We derive semi-closed form solutions for European option prices using transform analysis and then examine the properties of the implied volatilities that the model generates. We find that the presence of jumps generates prominent volatility skews which depend on the sign of the mean jump size. We also show that mean reversion reduces the volatility smile as time to maturity increases. In addition, mean reversion induces volatility skews particularly for ITM options, even in the absence of jumps. Finally, jump size volatility and jump intensity mainly affect the kurtosis and thus the curvature of the smile with the former having a more important role in making the volatility smile more pronounced and thus increasing the kurtosis of the underlying price distribution.Affine jump diffusion models Implied volatility Volatility skew Electricity derivatives Risk management