Forecasting crude oil volatility with geopolitical risk: Do time-varying switching probabilities play a role?

This study examines whether geopolitical risk (GPR) exhibits an ability to forecast crude oil volatility from a time-varying transitional dynamics perspective. Unlike previous studies that assume an oversimplification of the fixed transition probabilities for crude oil volatility, we develop an asymmetric time-varying transition probability Markov regime switching (AS-TVTP-MS) GARCH model. In-sample estimated results show that GPR yields strong evidence of regime switching behavior on crude oil volatility and that the negative shocks of GPR result in greater effects on switching probabilities than positive shocks. Out-of-sample results indicate that the AS-TVTP-MS GARCH model containing the GPR index outperforms other models, suggesting that the consideration of GPR information and time-varying regime switching together results in superior predictive performance. Moreover, the predictability of oil volatility is further verified to be economically significant in the framework of portfolio allocation. In addition, our results are robust to various settings.     

Do precious metals hedge crude oil volatility jumps?

In this study, we investigate the impacts of contemporaneous and lagged implied oil volatility (OVX) jumps on precious metals (gold, palladium, platinum, and silver) with the focus on hedging property of precious metals. Additionally, the impacts of OVX jumps on precious metals is investigated in returns and volatility. The results show that gold returns are relatively less responsive against contemporaneous and lagged OVX jumps, thus, gold acts as a weak hedge against OVX jumps. However, other metals (copper, palladium, platinum, and silver) do not serve as a hedge against contemporaneous OVX jumps. Nevertheless, these metals takeover the traditional hedging favourite ‘gold’ in the case of lagged OVX jumps and offers a strong hedge. It suggests that ignoring past information could severely undermine the investigation of OVX and the precious metal relationship. OVX jumps result in an increased volatility in precious metals, thereby indicating that all precious metals behave as a single asset class in terms of volatility transmissions. Moreover, gold is the contemporaneous metal of choice when risk perception is high or investors are averse to risk. Nevertheless, as information is diffused, other metals yield better performance as a hedge.     

Do China's macro-financial factors determine the Shanghai crude oil futures market?

Existing studies have investigated the Chinese Shanghai crude oil futures (INE) from price efficiency, cross-futures transmission, etc., but neglected the potential links with China. This paper is committed to filling this gap by conducting an initial discussion from the perspective of macro-financial factors. Applying the dynamic model averaging (DMA) approach, we examine the time-varying importance of the six potential factors that drive the INE prices. The results based on the overall conditions of all determinants and based on individual predictors both support the crucial roles of some Chinese macro-financial factors. The pricing effects of these factors almost display upward features within 6 months since the INE establishment. Thereafter, it maintains an overall stable trend, though some abnormal turmoil is found after the COVID-19 outbreak. According to the multi-scale analysis, the importance of China's macro-financial factors mainly reveals the INE market at the low-frequency components. To confirm the robustness of the estimation and the uniqueness of such effects on the INE, we utilize an alternative forecast accuracy criterion to confirm stability, accommodate the DMA estimation on the WTI and Brent oil futures prices as comparisons, and discuss the frequency domain through another decomposition procedure. These all mirror our findings.     

Forecasting EUR–USD implied volatility: The case of intraday data

This study models and forecasts the evolution of intraday implied volatility on an underlying EUR–USD exchange rate for a number of maturities. To our knowledge we are the first to employ high frequency data in this context. This allows the construction of forecasting models that can attempt to exploit intraday seasonalities such as overnight effects. Results show that implied volatility is predictable at shorter horizons, within a given day and across the term structure. Moreover, at the conventional daily frequency, intraday seasonality effects can be used to augment the forecasting power of models. The type of inefficiency revealed suggests potentially profitable trading models.     

Do the crude oil futures of the Shanghai International Energy Exchange improve asset allocation of Chinese petrochemical-related stocks?

The Shanghai International Energy Exchange (INE) facilitates both local and international investment in Chinese petrochemical-related stocks through local crude oil futures. This study investigates whether the Chinese emerging market can better aid investors' risk hedging and asset allocation compared to two major international developed markets–the Brent and West Texas Intermediate (WTI) crude oil futures markets—and examines the pairwise risk hedging effects and multi-asset allocation performance of INE and petrochemical-related stocks. The results show that INE has higher hedge effectiveness than Brent and WTI under pairwise hedging. Further, in multi-asset allocation, the portfolios containing INE outperform other portfolios. Overall, INE results in a better diversification effect and volatility reduction than the use of WTI crude oil futures to construct multi-asset allocation with Chinese petrochemical-related stocks. However, INE performance is inferior to Brent's in terms of constructing portfolios with oil or energy stocks. Finally, our results are robust to the five factors proposed by Fama and French (2015) in asset pricing.     

Volatility forecasting of crude oil futures market: Which structural change-based HAR models have better performance?

The paper focuses on the smooth and sharp structural changes in crude oil futures volatility and singles out the flexible Fourier form (FFF) and the modified ICSS algorithm to detect them, respectively, so as to explore whether different structural change-based HAR models exhibit significantly better performance for crude oil return volatility forecasting than traditional HAR-type models. The empirical results indicate that, on the one hand, crude oil market displays a strong evidence of breaks, and the incorporation of trigonometric terms can account for the structural changes in crude oil return volatility. On the other hand, the flexible Fourier form (FFF) based HAR-type models and the Structural Breakpoints (SB) based HAR-type models yield superior forecasting performance than traditional HAR-type models. Meanwhile, the forecasting results and economic performance of the former usually outperform the latter, particularly for the short- and medium-term forecasts.     

Does futures trading increase stock market volatility? The case of the Nikkei stock index futures markets

We propose new tests to examine whether stock index futures affect stock market volatility. These tests decompose spot portfolio volatility into the cross-sectional dispersion and the average volatility of returns on the portfolio's constituent securities. Our tests show that for Nikkei stocks spot portfolio volatility increased and cross-sectional dispersion decreased compared with average volatility when Nikkei futures began trading on the Osaka Securities Exchange, but not on the Singapore International Monetary Exchange. For non-Nikkei stocks, no shift occurred when futures trading began on either exchange. These findings are consistent with the hypotheses that futures trading increases spot portfolio volatility but that there is no volatility “spillover” to stocks against which futures are not traded. However, the increase in volatility attributable to futures trading is small compared with volatility shifts induced by changes in broad economic factors.     

Did crisis alter trading of two major oil futures markets?

The paper analyzes how traders in two major oil futures markets: New York Mercantile Exchange (NYMEX) and Intercontinental Exchange, reacted to the 2008 financial crisis, particularly whether they shifted their trading pattern and whether the relative information role of the two markets changed. Using trade-by-trade data, the paper analyzes several trading characteristics including trading volume, trade size, volatility, bid–ask spread, and relative information share. On average, NYMEX is characterized by greater volume, trade size and slightly greater spread. Before the crisis, NYMEX leads the process of price discovery, and volatility and trade size are significant factors explaining this leadership. However, following the financial crisis of 2008, the leadership role of NYMEX declines and trade size and volatility are no longer significant factors. Contrary to results of most equity market research, bid–ask spread is not a significant factor in information share and causality tests indicate that causality runs from spread to information share before the crisis but the opposite holds during the crisis period.     

Are commodity futures a hedge against inflation? A Markov-switching approach

This study examines the inflation hedging ability of various commodity futures using Markov-switching vector error correction models (MS-VECM). We find that total commodity futures fail to provide a hedge against inflation over the sample period between January 1983 and December 2021. However, industrial metals and precious metals are able to hedge against inflation. Other sub-indexes, including energy, agriculture, and livestock, do not have a significant inflation hedging ability. The inflation hedging capacity of industrial metals exhibits substantial variation over time, with most of the inflation hedging power occurring during the relatively longer and more common regimes covering the Great Moderation, the post-subprime crisis, and the periods after the outbreak of the COVID-19 pandemic. We further evaluate the inflation hedge ability of commodity futures by including stocks and bonds in the model. Our results suggest that industrial metals are more reliable inflation hedges.     

Pricing vulnerable options in a hybrid credit risk model driven by Heston–Nandi GARCH processes

Review of Derivatives Research - This paper proposes a hybrid credit risk model, in closed form, to price vulnerable options with stochastic volatility. The distinctive features of the model are...     

Pricing options under stochastic volatility: a power series approach

In this paper we present a new approach for solving the pricing equations (PDEs) of European call options for very general stochastic volatility models, including the Stein and Stein, the Hull and White, and the Heston models as particular cases. The main idea is to express the price in terms of a power series of the correlation parameter between the processes driving the dynamics of the price and of the volatility. The expansion is done around correlation zero and each term is identified via a probabilistic expression. It is shown that the power series converges with positive radius under some regularity conditions. Besides, we propose (as in Alós in Finance Stoch. 10:353–365, 2006) a further approximation to make the terms of the series easily computable and we estimate the error we commit. Finally we apply our methodology to some well-known financial models.      

Does country risks predict stock returns and volatility? Evidence from a nonparametric approach

We use the k-th order nonparametric causality test at monthly frequency over the period of 1984:1–2015:12 to analyze whether aggregate country risk, and its components (economic, financial and political) can predict movements in stock returns and volatility of eighty-three developed and developing economies. The nonparametric approach controls for the existing misspecification of a linear framework of causality, and hence, the weak evidence of causality obtained under the standard Granger tests cannot be relied upon. When we apply the nonparametric test, we find that, while there is no evidence of predictability of squared stock returns barring one case, at times, there are nearly 50 percent of the countries where the aggregate risks and its components tend to predict stock returns and realized volatility.     

Gram–Charlier densities: a multivariate approach

This paper introduces a new family of multivariate distributions based on Gram–Charlier and Edgeworth expansions. This family encompasses many of the univariate semi-non-parametric densities proposed in financial econometrics as marginal of its different formulations. Within this family, we focus on the analysis of the specifications that guarantee positivity to obtain well-defined multivariate semi-non-parametric densities. We compare two different multivariate distributions of the family with the multivariate Edgeworth–Sargan, Normal, Student's t and skewed Student's t in an in- and out-of-sample framework for financial returns data. Our results show that the proposed specifications provide a reasonably good performance, and would therefore be of interest for applications involving the modelling and forecasting of heavy-tailed distributions.     

Metropolitan vision making – using backcasting as a strategic learning process to shape metropolitan futures

The need for new forward-looking tools in urban planning is immense: new functional relations and structures are now stretching beyond our capacity to ‘rationally’ capture modern metropolitan spaces (Neumann & Hull, 2009). At the same time, cities struggle to find tools to help manage their long-term transition towards a low-carbon, resource-smart economy.In 2006–2007, the municipalities in the Helsinki metropolitan region organised an international competition for ideas titled “Greater Helsinki Vision 2050.” It drew a good number of entries in the competition stage and later helped bring together the awarded participants with local planning professionals and citizens.This paper explores the process behind the vision-making exercise and evaluates its success in providing new tools for the long-term transition to a low-carbon, resource-smart Helsinki metropolitan region. The theoretical framework used in this paper is ‘incrementalism with perspective’ (Ganser, Siebel & Sieverts, 1993) and its ideas on using long-term visions in the integration and coordination of incremental activities in various institutions. We perceive the backcasting scenario method (Dreborg, 1996) as a tool for implementing this approach and hence interpret the case example’s results through the framework of this method.The Greater Helsinki Vision 2050 competition was an example of a vision-oriented planning process that provided new tools for bringing the ‘unmanageable’ metropolitan region within the scope of the manageable. The backcasting approach was deployed as a tool for emancipating stakeholders to imagine alternative futures for metropolitan spaces.The backcasting scenario method should be considered a viable tool when managing vision-oriented planning processes: longer than usual time horizons help initiate strategic learning among stakeholders. However, in addition to civil servants, citizens and other stakeholders should be widely engaged in order to secure sustainable results.     

Valuation of asset and volatility derivatives using decoupled time-changed Lévy processes

In this paper we propose a general derivative pricing framework that employs decoupled time-changed (DTC) Lévy processes to model the underlying assets of contingent claims. A DTC Lévy process is a generalized time-changed Lévy process whose continuous and pure jump parts are allowed to follow separate random time scalings; we devise the martingale structure for a DTC Lévy-driven asset and revisit many popular models which fall under this framework. Postulating different time changes for the underlying Lévy decomposition allows the introduction of asset price models consistent with the assumption of a correlated pair of continuous and jump market activity rates; we study one illustrative DTC model of this kind based on the so-called Wishart process. The theory we develop is applied to the problem of pricing not only claims that depend on the price or the volatility of an underlying asset, but also more sophisticated derivatives whose payoffs rely on the joint performance of these two financial variables, such as the target volatility option. We solve the pricing problem through a Fourier-inversion method. Numerical analyses validating our techniques are provided. In particular, we present some evidence that correlating the activity rates could be beneficial for modeling the volatility skew dynamics.     

Modeling of group-specific mortality in China using a modified Lee–Carter model

The paper assesses sex-age-specific mortality rates of the four groups of people in China, the country, cities, towns, and counties, based on the mortality data from the China Population Statistics Yearbooks (1988–2009) using a newly proposed modified Lee–Carter model. The results show that in general, the expected age-specific mortality rates decrease over the years, and the decreasing speed increased in the past decade. During 2000–2008, the expected mortality rates decreased over the years for females of all ages and groups and males in cities, remained with no changes for males ages 13–36 in the country and towns, but increased for males ages 13–43 in counties. Predictions for 2009 are made based on the 2000–2008 data, and comparisons to the observed rates from an annual survey show that they match each other well except for males ages 13–43 in counties, whose mortality rates reached record highs around 2005, and bounced back to the level of 2000 in 2008 and was reduced a little further in 2009, benefiting from the promulgations and enforcements of some safety regulations by the government on construction and mining sites where most labors are from counties. The predicted age-specific mortality rates from the model are compared to the assumed rates in the China Life Insurance Mortality Table (2000–2003) promulgated by the China Insurance Regulatory Commission, and they show a great deal of similarity in terms of changing trends over the ages.     

Non-implementability of Arrow–Debreu equilibria by continuous trading under volatility uncertainty

In diffusion models, a few suitably chosen financial securities allow to complete the market. As a consequence, the efficient allocations of static Arrow–Debreu equilibria can be attained in Radner equilibria by dynamic trading. We show that this celebrated result generically fails if there is Knightian uncertainty about volatility. A Radner equilibrium with the same efficient allocation as in an Arrow–Debreu equilibrium exists if and only if the discounted net trades of the equilibrium allocation display no ambiguity in the mean. This property is violated generically in endowments, and thus Arrow–Debreu equilibrium allocations are generically unattainable by dynamically trading a few long-lived assets.     

Stock market closure and intraday stock index futures market volatility: “contagion”, bid–ask bias or both?

Chang et al. [Journal of Business 68 (1) (1995) 61] examine the impact of the closure of the New York Stock Exchange (NYSE) on S&P500 stock index futures traded on the Chicago Mercantile Exchange. They document a decline in futures market volatility immediately after the close of the NYSE, and an increase 15 minutes later when the futures market closes. They attribute this to contagion–i.e. a decline in information transfer from equities to futures markets following the closure of the underlying market. This paper examines the impact of the extension of trading hours in Hang Seng Index futures traded on the Hong Kong Futures Exchange on the 20 November, 1998 to 15 minutes after the close of the underlying market (the Stock Exchange of Hong Kong). Using the unique natural experiment provided by this change, a pattern similar to US markets is documented for the Hang Seng Index Futures following the change in trading hours. This provides strong evidence that the intraday pattern in volatility is caused by market closure. Unlike US futures exchanges, price reporters on the floor of the Hong Kong Futures Exchange collect quote data in addition to trade data. This data facilitates a test of another plausible microstructure explanation for the observed behaviour–bid–ask bounce associated with trading activity. This paper provides evidence that bid–ask bounce also explains part of the observed intraday behaviour in price volatility.     

Causality-in-mean and causality-in-variance among electricity prices,crude oil prices,and yen–US dollar exchange rates in Japan

In this study, we test the Granger-causality-in-mean and Granger-causality-in-variance among electricity prices, crude oil prices, and yen-to-US-dollar exchange rates in Japan using a cross-correlation function approach. We find Granger-causality-in-mean from neither the exchange market nor the oil market to the power market; the same was true of Granger-causality-in-variance, although both the exchange rates and oil prices greatly influence power generation costs in Japan. We suspect the efficiency of this market is at play.