Search Results (7)

This paper analyzes the control strategy for urban battery-swapping stations by optimizing the charging policy based on real-time battery demand and the time required for a full charge. The energy stored in available batteries serves as an electricity buffer, allowing energy to be drawn from the grid when costs or equivalent ${\mathrm{CO}}_2$ emissions are low. An optimized charging policy is derived using dynamic programming (DP), assuming average battery demand and accounting for both the costs and emissions associated with electricity consumption. The proposed algorithm uses a prediction of the expected traffic in the area as well as the expected cost of electricity on the net. Battery tests were conducted to assess charging time variability, and traffic density measurements were collected in the city of Valencia across multiple days to provide a realistic scenario, while real-time data of the electricity cost is integrated into the control proposal. The results show that incorporating traffic and electricity price forecasts into the control algorithm can reduce electricity costs by up to 11% and decrease associated ${\mathrm{CO}}_2$ emissions by more than 26%. Full article

In this paper, we consider the problem of pricing variance, volatility, covariance and correlation swaps for financial markets with semi-Markov volatilities. The paper’s motivation derives from the fact that in many financial markets, the inter-arrival times between book events are not independent or exponentially distributed but instead have an arbitrary distribution, which means they can be accurately modelled using a semi-Markov process. Through the results of the paper, we hope to answer the following question: Is it possible to calculate averaged swap prices for financial markets with semi-Markov volatilities? This question has not been considered in the existing literature, which makes the paper’s results novel and significant, especially when one considers the increasing popularity of derivative securities such as swaps, futures and options written on the volatility index VIX. Within this paper, we model financial markets featuring semi-Markov volatilities and price-averaged variance, volatility, covariance and correlation swaps for these markets. Formulas used for the numerical evaluation of averaged variance, volatility, covariance and correlation swaps with semi-Markov volatilities are presented as well. The formulas that are detailed within the paper are innovative because they provide a new, simplified method to price averaged swaps, which has not been presented in the existing literature. A numerical example involving the pricing of averaged variance, volatility, covariance and correlation swaps in a market with a two-state semi-Markov process is presented, providing a detailed overview of how the model developed in the paper can be used with real-life data. The novelty of the paper lies in the closed-form formulas provided for the pricing of variance, volatility, covariance and correlation swaps with semi-Markov volatilities, as they can be directly applied by derivative practitioners and others in the financial industry to price variance, volatility, covariance and correlation swaps. Full article

In this paper, we examine whether jumps matter in both equity market returns and integrated volatility. For this purpose, we use the swap variance (SwV) approach to identify monthly jumps and estimated realized volatility in prices for both developed and emerging markets from February 2001 to February 2020. We find that jumps arise in all equity markets; however, emerging markets have more jumps relative to developed markets, and positive jumps are more frequent than negative jumps. In emerging markets, the markets with average volatility earn higher returns during jump periods; however, highly volatile markets earn higher returns during jump periods in developed markets. Furthermore, markets with low continuous returns and high volatility are more adversely affected during periods of negative jumps. The average ratio of jump variations to total variation shows considerable variations due to jumps. Integrated volatility is high during periods of negative jumps, and this pattern is consistent in both developed and emerging markets. Moreover, the peak volatility of stock markets is observed during periods of crises. The implication of this study is useful in the asset pricing model, risk management, and for individual investors and portfolio managers for both developed and emerging markets. Full article

This study discovered market determinants of credit default swap (CDS) spreads in the North American oil and gas industry. Due to the limited theoretical background on market sources of CDS price fluctuations, we chose to alleviate model uncertainty and possible misspecification issues using Bayesian model averaging. This robust framework allowed us to aggregate results from a vast number of linear panel models estimated over the 2017–2020 period. We identified oil price volatility, major shifts in the OPEC+ supply policy, natural gas prices and industrial metal prices as the most robust determinants of CDS spreads. We show that following the onset of the COVID-19 pandemic, oil prices ceased to be a notably important determinant of credit risk, as factors indirectly related to oil prices, such as global and sectoral uncertainty, financial conditions and the macroeconomic stance became more influential. Additionally, we show that the CDS spreads of shale companies are determined by similar common factors, but they are more sensitive to the OPEC+ decisions on the global supply and are less affected by the domestic activity. Finally, we also prove that our modelling approach may help investors and risk officers to identify robust determinants behind the dynamics of credit risk. Full article

This study examines the short- and long-run effects of corporate social responsibility (CSR) activities on the credit risk implied in credit derivative prices. Measuring the different term effects on credit risk by the slope of credit default swap (CDS) spreads with different maturities, we investigate how CSR activities affect credit risk differently in the short and long run. Fama-MacBeth regressions reveal that firms with higher CSR scores tend to have more gently decreasing CDS slopes because, on average, CSR activities reduce credit risk in the long run more than in the short run. An analysis of individual CSR categories shows that while community, diversity and employee relations lead to a lower CDS slope, human rights and product characteristics increase the CDS slope. This finding suggests that not all CSR activities affect short-term and long-term credit risks in the same direction. Therefore, even though CSR activities can reduce credit risk in the long-run, some CSR activities may increase the short-term credit risk and hence increase short-term borrowing costs. Full article

This study examines whether systematic default risks affect a cross section of credit risk premiums. Using a structural framework, I derive a theoretical cross-sectional relationship, develop a testable hypothesis, and provide a method to estimate the systematic default risk. The empirical results of US corporate credit default swap data are consistent with my hypothesis. The findings show that, while credit market factors have positive effects on a cross section of credit risk premiums, stock market factors have a negative impact. Regression analyses reveal that the market’s average default probability and the value factor have a significant effect on the credit risk premium. In addition, credit market factors are more influential than equity market factors as systematic default risk factors. The results suggest that systematic and idiosyncratic default risks are priced differently in a cross section of credit risk premiums. Full article

This paper draws on network theory to investigate European banks’ sovereign debt exposures. Banks’ holdings of sovereign debt build a network of financial linkages with European countries that exhibits a long-tail distribution of node degrees. A highly connected network core of 15 banks is identified. These banks accounted for the majority of sovereign debt investments between December 2010 and December 2013 but exhibited only average and sometimes even below average capitalizations. Consequently, they constituted a potential source and transmission channel of systemic risk, especially due to their proneness to portfolio contagion. In a complementary regression analysis, the effect of counterparty risk on Credit Default Swap (CDS) spreads of 15 EU sovereigns is investigated. Among the banks exposed to the debt of a particular issuer, the biggest institutions in terms of their own asset sizes are identified and some of their balance sheet characteristics included into the regression. The analysis finds that the banks’ implied volatilities had a significant and increasing effect on CDS spreads during the recent crisis years, providing evidence of the presence of counterparty risk and its effect on EU sovereign debt pricing. Furthermore, the role of the domestic financial sectors is assessed and found to have affected the CDS spreads. Full article