Intraday bidirectional volatility spillover across international stock markets: does the global financial crisis matter?

This article studies volatility spillover between the US and the three largest European stock markets (Frankfurt, London and Paris) around the time of the recent Subprime crisis. In order to investigate the impact of the latter, we break our sample down into two sub-periods: a pre-crisis period and a post-crisis period, using a structural break test that has the advantage of endogenously testing for further breaks in the data. Unlike previous studies that have frequently investigated this issue using low frequency data, our article makes use of intraday data. Accordingly, using Threshold generalized autoregressive conditional heteroscedasticity (GARCH) model estimations, we find weak evidence of volatility transmission between the two regions before the Subprime crisis. However, during the post-crisis period, we record returns and volatility spillover from US to European markets and vice versa at different times of the trading day, indicating that the two regions became more dependent during the recent Subprime crisis, a finding that supports the contagion hypothesis between the US and European stock markets.     

Oil price shocks and American depositary receipt stock returns

In this paper we examine the impact of oil price shocks on twelve countries American Depositary Receipt (ADR) returns using monthly data from 1999.01 to 2014.12. The results show that oil price shocks have a positive and statistically significant impact on ADR return in all twelve countries. These results are robust to the inclusion of other explanatory variables such as oil price volatility and the spillover of the United States stock market. Further analysis shows that this effect is stronger in the post financial crisis time period compared to the pre-financial crisis time period.     

The stock market effects of a securities transaction tax: Quasi-experimental evidence from Italy

In the aftermath of the financial crisis, in several countries new levies on the financial sector have been proposed and in some cases implemented. We focus in particular on the recent introduction of a securities transaction tax (STT) in Italy. A peculiarity of the Italian STT is that it only concerns stocks of corporations with a market capitalization above € 500 million. We exploit this feature via a differences-in-differences approach – comparing taxed and non-taxed stocks before and after the introduction of the tax – and via a regression discontinuity design – comparing the performance of stocks just above the threshold with those just below. Focusing on the regulated market, we find that the new tax reduced liquidity, but it left transaction volumes and returns substantially unaffected. There is also evidence – although not conclusive – that the tax increased volatility.     

PRICING DERIVATIVES ON MULTISCALE DIFFUSIONS: AN EIGENFUNCTION EXPANSION APPROACH

Using tools from spectral analysis, singular and regular perturbation theory, we develop a systematic method for analytically computing the approximate price of a large class of derivative‐assets. The payoff of the derivative‐assets may be path‐dependent. In addition, the process underlying the derivatives may exhibit killing (i.e., jump to default) as well as combined local/nonlocal stochastic volatility. The nonlocal component of volatility may be multiscale, in the sense that it may be driven by one fast‐varying and one slow‐varying factor. The flexibility of our modeling framework is contrasted by the simplicity of our method. We reduce the derivative pricing problem to that of solving a single eigenvalue equation. Once the eigenvalue equation is solved, the approximate price of a derivative can be calculated formulaically. To illustrate our method, we calculate the approximate price of three derivative‐assets: a vanilla option on a defaultable stock, a path‐dependent option on a nondefaultable stock, and a bond in a short‐rate model.     

Price and Volatility Transmission and Market Power in the German Fresh Pork Supply Chain

We investigate the relationship between the transmission of price volatility and market power in the German fresh pork supply chain. We use a theoretical model underpinning this relationship followed by an empirical application that uses monthly farm, slaughterhouse and retail pork price data for the period 2000–2011. We examine both the relationships of market power with price level transmission and price volatility transmission in the chain. We use a vector error correction model and least squares regressions to analyse price transmission and price volatility transmissions, respectively. Results show that retail market power limited both types of transmissions. Competition inducing policy measures coupled with measures that support price risk management initiatives of chain actors are suggested.     

Information transmission between large shareholders and stock volatility

Does information transmission between large shareholders exacerbate stock volatility or reduce stock volatility? In this study, based on the common shareholding data in the Chinese stock market from 2007 to 2017, we establish the shareholder’s coshareholding network, and use the weighted network clustering coefficient to measure the information transmission speed. Moreover, we investigate the impact of information transmission speed on stock volatility. The empirical results show that a nonlinear U-shaped relationship exists between information transmission speed and stock volatility. The findings are robust to the inclusion of other determinants of stock volatility identified in the literature. Finally, we verify the existence of private information interaction in the coshareholding network.     

Conditional higher order moments in metal asset returns

This study examines the role of higher order moments in the returns of four important metals, aluminium, copper, gold and silver, using the asymmetric GARCH (AGARCH) model with a conditional skewed generalized-t (SGT) distribution. Implications of higher order moments in metal returns are evaluated by comparing the performances of conditional value-at-risk measures obtained from the AGARCH models with SGT distributions to those obtained from the AGARCH models with normal and student-t distributions. With the exception of gold, the AGARCH model with the SGT distribution appears to have the best fit for all metals examined.     

融资融券对我国股市波动性的影响

本文采集股价指数月收益率和融资融券交易额每月日平均变化率的数据,针对融资融券对我国股市波动性的影响,进行实证检验,并对结果做进一步的解释。     

Asset price volatility and banks

This paper examines the operation of Diamond–Dybvig banks when depositors have access to the asset market. Previous studies have shown that banks are redundant in this environment since it is impossible to prevent the strategic withdrawals. This paper shows that the strategic withdrawals can be prevented if the market risk, due to asset price volatility, is considered. Banks provide deterministic returns to the depositors since the aggregate withdrawals are predictable, and therefore, banks can choose the portfolio such that no asset liquidation is involved. However, an individual consumer with stochastic liquidity need is vulnerable to the price volatility if he holds the asset directly. Therefore, banks improve the consumers’ welfare by providing the insurance against not only the liquidity shock but also the market risk. Banks are not redundant.     

Revisiting the risk-return relation in the Chinese stock market: Decomposition of risk premium and volatility feedback effect

The empirical results of the risk-return relationship are mixed for both mature and merging markets. In this paper, we develop a new volatility model to revisit the risk-return relation of the aggregate stock market index by extending the Realized GARCH model of Hansen et al. (2012) with the Wang and Yang (2013) framework, in which the overall risk-return relation is decomposed into a risk premium and a volatility feedback effect. An empirical analysis of three major Chinese stock indices reveals positive risk premium and negative volatility feedback effect, and those findings are stable across different markets and sub-samples. However, their relative magnitudes differ between markets and varies through time.