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This paper investigates the profitability of several types of zero-cost price momentum and contrarian strategies in the Chinese stock market for the 1994-2013 period. Several distinct features of Chinese market are documented. We find that contrarian strategies that use Jegadeesh and Titman's (1993) method with weekly frequency are profitable. However, investment strategies based on the 'nearness' to of 52-week high or the recency of the 52-week high are not profitable. Our analysis also shows that contrarian profits are higher during the crisis period of 2008-2012. In addition, the return reversal of the winner and loser portfolios suggests that contrarian profits can be attributed to overreaction. Finally, we also find evidence of herding behaviour in the Chinese market; and the degree of herding behaviour is positively correlated with the profits of contrarian trading strategies.

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Using the most comprehensive weekly dataset of 'A' shares listed on the Chinese stock market, this paper examines short-term contrarian strategies under different market states from 1995-2010. We find statistically significant profits from contrarian strategies, especially during the period after 2007, when China (along with other countries) experienced an economic downturn following the worldwide financial crisis. Our empirical evidence suggests that: (1) no significant profit is generated from either momentum or contrarian strategies in the intermediate horizon;(2) after microstructure effects are adjusted for, contrarian strategies with only four to eight weeks holding periods based on the stocks' previous four to eight week's performance generate statistically significant profits of around 0.2% per week; (3) the contrarian strategy following a 'down' market generates higher profit than those following an 'up' market, suggesting that a contrarian strategy could be used as a shelter when the market is in decline. The profits following a 'down' market are robust after risk adjustment.

Given a dominant exchange, how should other exchanges set their trading hours? We examine the introduction of a night session by the Shanghai Futures Exchange, allowing trading concurrently with daytime trading at the Commodity Exchange in the United States. After developing hypotheses, results for gold and silver show: trading activity has increased; liquidity in Shanghai has risen and prices are less volatile at market opening; the price discovery share of Chinese gold futures has fallen but this is not a sign of weakening market quality; and volatility spillovers increase bidirectionally. Longer trading hours have decreased market segmentation and increased information flow.

In this paper, we are interested in exploring the role of price impact, derived from the order book, in modeling and predicting stock volatility. This is motivated by the market microstructure literature that examines the mechanics of price formation and its relevance to market quality. Using a comprehensive dataset of intraday bids, asks, and three levels of market depths for 148 stocks in the Shanghai Stock Exchange from 2005 to 2016, we find substantial intraday impact from incoming bid and ask limit and market orders on stock prices. More importantly, the permanent price impact at the daily level is a significant determinant of stock volatility dynamics as suggested by the panel VAR estimation. Furthermore, when we augment traditional volatility models with the time series of daily price impact, the augmented models produce significantly more accurate volatility predictions at the one-day ahead forecasting horizon. These volatility predictions also offer economic gains to a mean-variance utility investor in a portfolio setting.

We consider the effects of interventions by the Bank of Japan's (BoJ) on the intraday volatility of the US dollar/Japanese yen (USD/JPY) exchange rates and their spillovers to volatility of the euro/JPY exchange rates. We use 15-minute data during the period 2000-2004 and employ multivariate generalized autoregressive conditional heteroskedasticity (GARCH) modeling and quartile plots of intraday volatility to analyze the intraday effects of the BoJ interventions on exchange rate volatility. The results indicate that the BoJ interventions decrease daily volatility of the USD/JPY exchange rate but increase the volatility of the euro/JPY series. On intervention days, the intraday volatility has different patterns to those on nonintervention days.

Given the unique institutional regulations in the Chinese commodity futures market as well as the characteristics of the data it generates, we utilize contracts with three months to delivery, the most liquid contract series, to systematically explore volatility forecasting for aluminum, copper, fuel oil, and sugar at the daily and three intraday sampling frequencies. We adopt popular volatility models in the literature and assess the forecasts obtained via these models against alternative proxies for the true volatility. Our results suggest that the long memory property is an essential feature in the commodity futures volatility dynamics and that the ARFIMA model consistently produces the best forecasts or forecasts not inferior to the best in statistical terms.