We find that the asymmetric volatility phenomenon is reversed in the Shanghai Stock Exchange during bull markets. That is, volatility increases more with good news than with bad news. This evidence is inconsistent with the US markets (Wu 2001, and Bae, Kim and Nelson 2007). Further examination of this phenomenon reveals that the positive impact of good news on volatility is driven by return chasing behaviour of investors in large stocks during bull markets. We also find that volatility increases after stock price declines in bear markets especially for small stocks. This increase in volatility of small stocks after bad news in bear markets is partly driven by liquidity. After controlling for liquidity shifts, there are no significant patterns in the volatility of small stocks during bear markets. We posit that institutional and behavioural factors are the major driving forces of observed volatility patterns in Chinese stock market.

We compare the effects of futures market margin policy on trading activity and volatility between the China margin system and the U.S. margin system. In China margin levels are set as a fixed percentage of the underlying futures contract value and change daily as futures prices change over time. In contrast, margin is set at a fixed dollar amount for most contracts in the United States and is infrequently adjusted at the discretion of the exchange’s clearinghouse. We provide a theoretic model on how the changing margin cost between market-up days and market-down days would affect the demand and supply of short term speculators and long term hedgers in the Chinese futures market and their different effects on market volatility. The model shows that the futures price shocks should have an asymmetric effect on trading volume and volatility in the Chinese market but symmetric effect in the U.S. market and futures price should have a return dynamics that is more stable in the Chinese market than in the U.S. market. Using Soybean futures data from the Chinese and U.S. markets, we compare price and volatility dynamics between the two markets and find empirical support for our theoretic model and hypothesis.

We hypothesize and test an inverse relationship between liquidity and price volatility derived from microstructure theory. Two important facets of liquidity trading are examined: thickness and noisiness. As represented by expected volume (thickness) and realized average commission cost per share (noisiness) of NYSE equity trading, both facets are found negatively associated with ex post and ex ante price volatilities of the NYSE stock portfolios and the NYSE composite index futures. Furthermore, the inverse association between volatility and noisiness is amplified in times of market crisis. The overall results demonstrate that volatility increases as noise trading declines. All findings retain statistical significance and materiality after controlling for a number of specifications. This inverse liquidity-volatility relationship reflects a microstructure interpretation of the liquidity risk premium documented in the asset pricing literature.

This paper analyzes the impact of changes in the securities transaction tax (STT) rate on the local A-shares market in China. We find that, on average, a 22-base-point- increase in the STT rate is associated with about a 28% drop in trading volume, while a 17-base-point- reduction in the STT rate is associated with about a 89% increase in trading volume in the Chinese A-shares market. Both the increases and reductions in the STT rate result in a significant increase in the market return volatility. Besides, the increases in the STT rate have mixed effects on market efficiency, either improving or curbing it. The reductions usually either make the market less efficient or have not effect on it. The empirical results together show that levying the STT on trading is not an effective tool to regulate stock market, at least in this emerging market.

This paper studies idiosyncratic risk of new ventures. An option-based model of a new venture with multistage investments and jumps is developed. Our model ex- plains (1) why new ventures?idiosyncratic volatility eventually decreases as they clear R&D investment stages and become mature ?rms ?the stage-clearing e¤ect; (2) the negative relation between jumps in value and subsequent idiosyncratic volatility ?the jump e¤ect; (3) the dynamics of idiosyncratic volatility under di¤erent schedules of staged venture capital investments; and (4) the e¤ect of di¤erent schedules of staged investments on ?rm valuation with the presence of jumps. Empirically, we develop a generalized Markov-Switching EARCH model to simultaneously capture structural changes in ?rms?idiosyncratic volatility and the relation between jumps and idiosyn- cratic volatility. Using a hand-collected dataset of early-stage biotech ?rms, we ?nd empirical evidence supporting the jump e¤ect and the stage-clearing e¤ect described by our model.

In this paper, we derive the corresponding implied VIX formulas under the locally riskneutral valuation relationship proposed by Duan (1995) when various forms of GARCH model are proposed for S&P 500 index. The empirical study shows that the GARCH implied VIX is consistently and significantly lower than the CBOE VIX for all kinds of GARCH model investigated. Moreover, the magnitude of the difference suggests that the GARCH option pricing model is not capable of capturing the variance premium, which indicates the incompleteness of the GARCH option pricing under the locally risk-neutral valuation relationship. The source of this kind of incompleteness is then theoretically analyzed. It is shown that the framework of GARCH option pricing model fails to incorporate the price of volatility risk or variance premium.

This paper examines the impact of idiosyncratic risk on the cross-section of weekly stock returns from 1963 to 2006. I use an exponential GARCH model to forecast expected idiosyncratic volatility and employ a combination of the size e§ect, value premium, return momentum and short-term reversal to measure relative mispricing. I ?nd that stock returns monotonically increase in idiosyncratic risk for relatively undervalued stocks and monotonically decrease in idiosyncratic risk for relatively overvalued stocks. This phenomenon is robust to various subsamples and industries, and cannot be explained by risk factors or ?rm characteristics. Further, transaction costs, short-sale constraints and information uncertainty cannot account for the role of idiosyncratic risk. Overall, these ?ndings are consistent with the limits of arbitrage arguments and demonstrate the importance of idiosyncratic risk as an arbitrage cost.

Volatility long memory is a stylized fact that has been documented for a long time. Existing literature have two ways to model volatility long memory: component volatility models and fractionally integrated volatility models. This paper develops a new fractionally integrated GARCH model, and investigates its performance by using the Standard and Poor’s 500 index returns and cross-sectional European option data. The fractionally integrated GARCH model signi?cantly outperforms the simple GARCH(1, 1) model by generating 37% less option pricing errors. With stronger volatility persistence, it also dominates a component volatility model, who has enjoyed a reputation for its outstanding option pricing performance, by generating 15% less option pricing errors. We also con?rm the fractionally integrated GARCH model’s robustness with the latest option prices. This paper indicates that capturing volatility persistence represents a very promising direction for future study.

Until recently, Chinese companies publicly listed in domestic stock exchanges had two classes of stock: tradable and non-tradable shares. These two classes of stock had the same voting, cash flow, and all other legal rights except that non-tradable shares cannot be transferred at the open markets. From 2005 to mid-2007, Chinese government completed the ownership reform, so-called the Split Share Structure Reform (SSSR), to convert all non-tradable shares into tradable shares. Under this reform process, the holders of non-tradable shares had to negotiate with those of tradable shares to determine how much liquidity premium, or the compensation ratio, non-tradable shareholders have to pay to tradable shareholders in order to obtain the liquidity right. This paper starts with a theoretical model to identify the fundamental factors, including price discount before and after the SSSR reform, the percentage of non-tradable shares in total shares, the volatility of tradable share price, and the lockup period, that should determine the compensation ratio. We show that those factors except price discount before the reform are statistically significant in determining the compensation ratio proposed by non-tradable shareholders. We further show that the agency problems also reveal themselves in the compensation ratios. Specifically, when a firm is controlled by a governmental agency, the compensation is higher. However, the compensation is lower when more concentrated in the top ten holders, especially when shares are held by mutual funds. Thus, the evidence is consistent with the notion that the agency problem exists in China’s fund managers. Finally, we show that the existence of agency problems also reduce the importance of fundamental factors in determining the compensation ratios.

This paper examines the impact of idiosyncratic risk on the cross-section of weekly stock returns from 1963 to 2006. I use an exponential GARCH model to forecast expected idiosyncratic volatility and employ a combination of the size effect, value premium, return momentum and short-term reversal to measure relative mispricing. I ?find that stock returns monotonically increase in idiosyncratic risk for relatively undervalued stocks and monotonically decrease in idiosyncratic risk for relatively overvalued stocks. This phenomenon is robust to various subsamples and industries, and cannot be explained by risk factors or ?rm characteristics. Further, transaction costs, short-sale constraints and information uncertainty cannot account for the role of idiosyncratic risk. Overall, these ?findings are consistent with the limits of arbitrage arguments and demonstrate the importance of idiosyncratic risk as an arbitrage cost.