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In this paper we model the dynamics of the Chinese crude oil futures returns by using a skew‐geometric Brownian motion correlated with the market volatility, which is taken as a square‐root stochastic process. We use the OVX index data as proxy for market volatility. We validate the proposed model in terms of accuracy of its calibrations through an in‐sample simulation. Instead, out‐of‐sample simulations are used to show that a correlated skew‐geometric Brownian motion is more appropriate for modelling the Chinese returns compared to a single skew‐geometric Brownian motion in terms of forecasts. Furthermore, we price an American call option on the Chinese futures by using a recursively scheme based on a closed‐form formula, and an alternative Monte Carlo approach, for the related European call option. We show that our call price estimates are very close to market values and our model generally outperforms many benchmarks in literature, such as the Barone‐Adesi and Whaley formula and its generalizations. [ABSTRACT FROM AUTHOR]

In this paper, we introduce the concept of statistical arbitrage through the definition of a mean-reverting trading strategy that captures persistent anomalies in long-run relationships among assets. We model the statistical arbitrage proceeding in three steps: (1) to identify mispricings in the chosen market, (2) to test mean-reverting statistical arbitrage, and (3) to develop statistical arbitrage trading strategies. We empirically investigate the existence of statistical arbitrage opportunities in crude oil markets. In particular, we focus on long-term pricing relationships between the West Texas Intermediate crude oil futures and a so-called statistical portfolio, composed by other two crude oils, Brent and Dubai. Firstly, the cointegration regression is used to track the persistent pricing equilibrium between the West Texas Intermediate crude oil price and the statistical portfolio value, and to identify mispricings between the two. Secondly, we verify that mispricing dynamics revert back to equilibrium with a predictable behaviour, and we exploit this stylized fact by applying the trading rules commonly used in equity markets to the crude oil market. The trading performance is then measured by three specific profit indicators on out-of-sample data. [ABSTRACT FROM AUTHOR]

Taking the greatest socially responsible sovereign wealth fund in the world, namely, the Norwegian Government Pension Fund‐Global (GPF‐G), as a proxy for the world market portfolio, and collecting investment data from 2006 to 2021, our research studies how the attitude of environmentally concerned investors has changed, on different markets, over time, particularly before and after the 2015 Paris Climate Agreement. We investigate, with an event study methodology, what happens to stock prices when companies are excluded from the GPF‐G portfolio for serious environmental violations, unacceptable level of greenhouse gas emissions, or for their involvement in thermal coal processing. In line with previous studies, our results show that Paris Agreement has acted as a catalyst for environmentally conscious behavior by international investors, and this is particularly true in Anglo‐Saxon countries. Especially US, Japanese, Chilean, Indian, and Canadian investors care about the environmental issues that have led to the exclusion from the fund investment portfolio. To the contrary, investors in China, Germany, Australia, and UK seem to have an opposite reaction, as the prices of the excluded stocks increase. [ABSTRACT FROM AUTHOR]

The correction notice addresses an error in Equation (12) of the original publication by Fanelli on mean-reverting statistical arbitrage strategies in crude oil markets. The correction involves substituting the term St with Zt in Equation (12) and the subsequent row. The author assures that the scientific conclusions remain unchanged, and the correction has been approved by the Academic Editor. [Extracted from the article]

In this paper, we evaluate a swing option contract embedded in a real world gas sales agreement. Under special conditions, contracts of this kind can be seen as a strip of American spread options, where the spread is the difference between a calculated contract price and the market price for the reference commodity. The reference commodity is the natural gas traded on the NetConnect Germany. The contract price has four underlying assets, which leads to a multifactor valuation problem for the pricing. Correlated mean-reverting models are chosen for all of the underlying assets. The Monte Carlo approach is used to estimate the fair value of the swing option with one year maturity. The model gives an accurate short -term forecast of the actual company values. [ABSTRACT FROM AUTHOR]

In this paper we propose a model to evaluate the performance of a Constant Proportion Debt Obligation (CPDO) and assess its rating. We model credit spread evolution in a HJM framework and default events for CPDO are generated by using a reduced form approach. Implementing a numerical algorithm that simulates the strategy of a CPDO, we obtain a rating for a CPDO by using Monte Carlo simulations. We find a rating inferior to the one assigned by rating agencies. Using our model for credit spread dynamics, the revealed default probability for CPDO could have been predicted. [ABSTRACT FROM AUTHOR]