This thesis comprises three chapters. It focuses on a unique dataset of the full trans- action records of traders in the Chinese futures market. Empirical techniques are used to analyse technical trading behaviour, margin trading, and market reactions to news in this market. Chapter 1, “Technical Trading Behaviour: Evidence from Chinese Futures Market", creates a new computational method to capture technical trading behaviour and finds technical trader's strategies can be classified in to 11 groups in Chinese rebar futures market. We use a simple model with macroeconomic news to filter pure technical traders from the unique data. Based on the estimation of 81000 technical trading rules, we find the potential technical strategies of each trader and we use K-means clustering algorithm to classify them. The coordinates of each cluster summarize the technical trading characteristics of members in each group. High percentage of traders in each group would apply the similar and corres- ponding strategies; Chapter 2, “Margin Trading: Hedonic Returns and Real Losses", focus on margin trading in the Chinese rebar futures market. We find market parti- cipants have a positive chance of a large gain and a large chance of a small limited loss under the mechanism. This kind of hedonic returns looks like that of people who play in a casino or buy lottery tickets. According to the unique dataset, we show that both expected and observed losses are substantial and that the optimal portfolio never contains rebar futures. Based on the analysis of traders' behaviour, we indicate that it is hard to rationalise their trading without a hedonic motive. Their trading behaviour can be easily understood as form of entertainment, such as gambling; Chapter 3, “The Influence of Scheduled Macroeconomic Announcements on the Futures Market: Evidence from Commodity Futures in China", is a com- prehensive empirical analysis of the overall Chinese futures market, which covers 23 commodities futures to observe the relationship between futures and scheduled macroeconomic news. We find the scheduled news affect commodity futures around 20 days before the announcements date and the following adjustment needs several days around the announcement date to be absorbed. Different kinds of commodities futures have different sensitivity levels to the scheduled news and this sensitivity does not depend on the trading activity. We also indicate the influence of scheduled news can happen in any stages of a business cycle. We finally use 36070 traders in the unique data to prove that market participants cannot make excess returns by following macroeconomics news in Chinese futures market.