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We comprehensively analyze the predictive power of several option-implied variables for monthly S&P 500 excess returns and realized variance. The correlation risk premium (CRP) and the variance risk premium (VRP) emerge as strong predictors of both excess returns and realized variance. This is true both in- and out-of-sample. Our results also reveal that statistical evidence of predictability does not necessarily lead to economic gains. However, a timing strategy based on the CRP leads to utility gains of more than 5.03% per annum. Forecast combinations provide stable forecasts for both excess returns and realized variance, and add economic value. [ABSTRACT FROM AUTHOR]

Understanding the mechanisms that drive extreme negative and positive prices in day-ahead electricity prices is crucial for managing risk and market design. In this paper, we consider the problem of understanding how fundamental drivers impact the probability of extreme price occurrences in the German day-ahead electricity market. We develop models using fundamental variables to predict the probability of extreme prices. The dynamics of negative prices and positive price spikes differ greatly. Positive spikes are related to high demand, low supply and high prices the previous days, and mainly occur during the morning and afternoon peak hours. Negative prices occur mainly during the night and are closely related to low demand combined with high wind production levels. Furthermore, we do a closer analysis of how renewable energy sources, hereby photovoltaic and wind power, impact the probability of negative prices and positive spikes. The models confirm that extremely high and negative prices have different drivers, and that wind power is particularly important in relation to negative price occurrences. The models capture the main drivers of both positive and negative extreme price occurrences and perform well with respect to accurately forecasting the probability with high levels of confidence. Our results suggest that probability models are well suited to aid in risk management for market participants in day-ahead electricity markets. [ABSTRACT FROM AUTHOR]

The price of a European option can be computed as the expected value of the payoff function under the risk-neutral measure. For American options and path-dependent options in general, this principle cannot be applied. In this paper, we derive a model-free analytical formula for the implied risk-neutral density based on the implied moments of the implicit European contract under which the expected value will be the price of the equivalent payoff with the American exercise condition. The risk-neutral density is semi-parametric as it is the result of applying the multivariate generalized Edgeworth expansion, where the moments of the American density are obtained by a reverse engineering application of the least-squares method. The theory of multivariate truncated moments is employed for approximating the option price, with important consequences for the hedging of variance, skewness and kurtosis swaps. [ABSTRACT FROM PUBLISHER]

In this paper we study the stochastic behavior of the prices and volatilities of a sample of six of the most important commodity markets and we compare these properties with those of the equity market. we observe a substantial degree of heterogeneity in the behavior of the series. Our findings show that it is inappropriate to treat different kinds of commodities as a single asset class as is frequently the case in the academic literature and in the industry. We demonstrate that commodities can be a useful diversifier of equity volatility as well as equity returns. Options pricing and hedging applications exemplify the economic impacts of the differences across commodities and between model specifications. [ABSTRACT FROM AUTHOR]

This article empirically investigates whether continuous time pricing models are able to help reveal mispriced commodity futures contracts. Mispricings are identified based on the difference between model and observed prices, using four different pricing models for four different commodity markets, namely crude oil, copper, silver, and gold. Pricing errors are found to carry informational content for future price movements in excess of the overall market. Investment strategies based on these pricing errors yield significant excess returns, particularly for the relatively small copper and silver markets. [ABSTRACT FROM PUBLISHER]

In this article we investigate whether contagion is present in the banking sector by analysing how banks are affected by negative earnings surprises from their competitors. The banking sector is of crucial importance for the economy and, thus, highly regulated on an individual bank level. However, a high degree of contagion risk should call for a regulation of the financial network rather than solely regulating on an individual level. To be able to make a judgement about the magnitude of possible contagion effects we compare the results of the banking sector with the results of the nonbanking industries. We find that earnings surprises cause significant contagion in the banking sector. In contrast, we do not find this effect in the nonbanking sectors, including the insurance sector. The magnitude of contagion in the banking sector is positively related with the size of the bank reporting an earnings surprise, as well as the size of the affected banks. [ABSTRACT FROM AUTHOR]