No‐arbitrage implies power‐law market impact and rough volatility

Market impact is the link between the volume of a (large) order and the price move during and after the execution of this order. We show that in a quite general framework, under no‐arbitrage assumption, the market impact function can only be of power‐law type. Furthermore, we prove this implies that the macroscopic price is diffusive with rough volatility, with a one‐to‐one correspondence between the exponent of the impact function and the Hurst parameter of the volatility. Hence, we simply explain the universal rough behavior of the volatility as a consequence of the no‐arbitrage property. From a mathematical viewpoint, our study relies, in particular, on new results about hyper‐rough stochastic Volterra equations.     

Asymmetric volatility spillovers between economic policy uncertainty and stock markets: Evidence from China

This study explores the spillovers between economic policy uncertainty (EPU) and stock market realized volatility (RV). The monthly index of Chinese and US EPU and RV are used to analyze the pairwise directional spillovers. We find that RV is a net receiver that is more vulnerable to shocks from U.S. EPU than to shocks from Chinese EPU. We further decompose the RV into good and bad volatility to test the asymmetric spillover effect between the stock market and EPU. The results suggest that EPU has a bigger effect on bad volatility in the stock market throughout most of the sample period. However, we find that good volatility spillovers become larger during periods of stimulated reform, whereas bad volatility spillovers become larger during periods of international disputes. We show that Chinese stock market volatility is sensitive to both U.S. and Chinese EPU and that the spillover is asymmetric in different periods.     

Does reputation of sponsors matter in IPO? Evidence from Hong Kong

Contrary to other markets where underwriters perform a combined role of underwriting and sponsoring in an Initial Public Offering (IPO), IPO issuers in Hong Kong must appoint at least one sponsor in addition to the underwriters. The splitting of the single role of underwriters into two separate ones offers an ideal setting to disentangle the effects of the two roles and to examine which of the two roles—sponsor or underwriter—is more important in explaining IPO underpricing and initial volatility in the Hong Kong equity market. Interestingly, our findings provide supportive evidence that the sponsor reputation does matter in an IPO and it is even more significant than the underwriter reputation in explaining the IPO underpricing phenomenon. Given the recent high-tech fervor, our research goes deeper to examine specifically the role of sponsors on high-tech firms, with results indicating that the reliance on sponsors is higher for traditional issuers than for technology firms. We further discover that sponsors and underwriters are playing substitution roles rather than complementary roles. In order to examine the regulatory policy impact, our research also compares the role of IPO sponsors before and after the launch of the new sponsor regulatory regime in 2013. The empirical findings lend support to our argument that after the launch of the new regulations, public awareness of sponsors is raised, respect towards more reputable sponsor increases, and thus, the role of sponsors becomes more important than before.     

Quantile spillovers and dependence between Bitcoin,equities and strategic commodities

This paper has two aims. We first examine the dynamic spillovers between Bitcoin and 12 developed equities, gold, and crude oil for different market conditions using a Bayesian Time-Varying Parameter Vector Autoregressive (TVP-VAR) model with daily spot prices. Our econometric approach enables us to capture the left and right tails as well as the shoulders of the return distribution corresponding to volatility spillovers under the bear, normal, and bull market states among these financial assets. We quantify and trace the dependence and directional predictability from Bitcoin to other assets using the sample cross-quantilogram. Our key findings offer convincing evidence of time variation in the level of volatility. Spillovers between Bitcoin and other financial assets intensify during extreme global market conditions. Secondly, results from the cross-quantilogram indicate strong dependence and positive directional predictability between Bitcoin and most equities and crude oil when market returns are bullish. However, during the bearish market period, there is negative dependence and predictability from Bitcoin to stocks in Finland, the Netherlands, the U.S.A, and the crude oil market only. This implies that Bitcoin can act as a hedge to stocks in Finland, the Netherlands, the U.S.A, and the crude oil market. However, insignificant dependence and directional predictability from Bitcoin to the remaining assets indicate that Bitcoin may act as a safe-haven to these assets during bearish markets. Our findings hold important implications for both international investors and portfolio managers who consider Bitcoin as part of their portfolio diversification and other investment strategies.     

Lottery mindset,mispricing and idiosyncratic volatility puzzle: Evidence from the Chinese stock market

This study investigates the MAX effect regarding lottery mindset in the Chinese stock market. The MAX effect significantly affects stock returns through quintile portfolio and cross-sectional regression analyses. The most-overpriced stock groups, as categorized by mispricing index, show more support for the MAX effect. However, the idiosyncratic volatility (IVOL) effect continues regardless of consideration for the MAX effect, indicating that the MAX effect is not a source of the IVOL effect. Our results suggest that the MAX effect, which is highly relevant for overpriced stocks, might have information for determining stock price, and appears to be independent from information of the IVOL effect in the Chinese stock market.     

Connectedness and systemic risk spillovers analysis of Chinese sectors based on tail risk network

This paper investigates the systemic risk spillovers and connectedness in the sectoral tail risk network of Chinese stock market, and explores the transmission mechanism of systemic risk spillovers by block models. Based on conditional value at risk (CoVaR) and single index model (SIM) quantile regression technique, we analyse the tail risk connectedness and find that during market crashes, stock market exposes to more systemic risk and more connectedness. Further, the orthogonal pulse function shows that Herfindahl-Hirschman Index (HHI) of edges has a significant positive effect on systemic risk, but the impact shows a certain lagging feature. Besides, the directional connectedness of sectors shows that systemic risk receivers and transmitters vary across time, and we adopt PageRank index to identify systemically important sector released by utilities and financial sectors. Finally, by block model we find that the tail risk network of Chinese sectors can be divided into four different spillover function blocks. The role of blocks and the spatial spillover transmission path between risk blocks are time-varying. Our results provide useful and positive implications for market participants and policy makers dealing with investment diversification and tracing the paths of risk shock transmission.     

Valuation of VIX and target volatility options with affine GARCH models

In this paper we propose semiclosed-form solutions, subject to an inversion of the Fourier transform, for the price of VIX options and target volatility options under affine GARCH models based on Gaussian and Inverse Gaussian distributions. We illustrate the advantage of the proposed analytic expressions by comparing them with those obtained from benchmark Monte–Carlo simulations. The empirical performance of the two affine GARCH models is tested using different calibration exercises based on historical returns and market quotes on VIX and SPX options.     

Oil price dynamics and airline earnings predictability

This study examines the effect of oil price dynamics on quarterly earnings and their predictability with a sample of 30 airlines for 1994–2017. First, we document a significantly positive impact of demand-driven oil shocks on airline earnings, suggesting that the revenue effect from shifting air travel demands dominates the cost effect of aviation fuels. Regarding earnings predictability, we find evidence of deterioration in oil-volatile quarters as indicated by both the earnings variability based on common benchmarks and the quality of analyst forecasts issued early in the quarter. We further show that supply-driven oil shocks have a more detrimental impact on earning predictability than demand-driven oil shocks. Finally, we do not find supporting evidence for the possible moderating effect of hedging.     

跨国公司研发投资技术外溢效应探究:浙江案例

近年来,浙江吸收的跨国投资在促进产业结构升级、推动经济增长方式转型方面具有独特的优势。本文综合运用相关理论,通过实证研究,对跨国公司研发投资的技术外溢效应进行了实证分析。本文创新点在于,外溢效应的大小,更多地取决于本土企业竞争力的强弱,只有不断增强本地企业的技术创新能力,才能吸收跨国企业的技术外溢效应。     

Accounting quality,information risk and the term structure of implied volatility around earnings announcements

We examine the association between accounting quality, which is used as a proxy for firm information risk, and the behavior of the term structure of implied option volatility around earnings announcements. By employing a large sample of US firms having options traded on their equity during 1996–2010, we find that lower (higher) accounting quality is significantly associated with stronger (weaker) changes in the steepness of the term structure of implied volatility curve around quarterly earnings announcements. This finding (which is robust to controls for business-stemming uncertainty regarding future firm performance) is consistent with a stronger differential of short vs. long-term uncertainty for higher information risk firms, indicating greater uncertainty on the future economic performance of poorer vs. stronger accounting quality firms. We also establish the trading implications of these findings by demonstrating a (profitable in-sample) self-financed option trading strategy that is based on the quality of the accounting information released on earnings announcement days.