This thesis consists of three essays on the liquidity characteristics and traders behavior in the main market for agricultural commodity futures in India, the National Commodity and Derivatives Exchange. This electronic trading platform was launched at the end of 2003 and subsequently became the third largest agricultural futures market globally. The first essay estimates the impact of speculators capital constraints on their willingness to provide liquidity as measured by trade participation, and on overall market liquidity as measured by bid-ask spread. To overcome the standard identification problem, the study exploits exogenous variation in trading performance in the form of losses in one asset unrelated to the fundamentals of another asset. The study finds that a small number of traders accounts for an overwhelming share of trading activity and participate in the market for a large number of commodities. Consistent with theoretical predictions, a negative shock to these active traders aggregate capital causes an increase in future bid-ask spread, but the economic magnitude of the estimated effect is small. Changes in competition to provide liquidity explain a considerable fraction of the variation in subsequent market liquidity. The effect is non-linear: the bid-ask spread is smallest around a natural level of competition, but increases as competition intensity deviates away from this point. Using the same dataset, the second essay investigates sources of traders superior returns in local commodities. Investors bias their portfolios towards local commodities, crops that are differentially grown within 100km of their location, and earn returns in these commodities that are 3.2% higher than in their non-local commodities, even amongst traders who turnover positions frequently. This differential is greatest in crops that are weather sensitive and for which India has a high percentage of world production. The results are consistent with traders possessing superior domestic supply information on local commodities because their proximity to crop production causes information acquisition costs to be lower. The third essay analyzes the trading decisions and performance of all three trader categories – individuals, brokers, and commercial institutions – participating in agricultural commodity markets in India. In contrast to U.S. commodity markets, individuals represent about 80% of participants by number, and contribute between 40-50% of trading activity and open interest in the market. Client commercial institutions account for less than 5% of overall trading activity, but for up to 35% of open interest； although fewest by number, broker proprietary trading desks account for a large portion of trading activity. Brokers are the most active group in spread strategies, while both brokers and individuals engage frequently in day-trading activities. Broker proprietary accounts are highly diversified across commodities trading 14 commodities on average, compared to about 4 traded by the other types. In aggregate, brokers make the largest amount of profits, and they do so consistently over time. The mean broker accounts profits from both intra-day and overnight profits is almost 40 to 60 times larger than the corresponding profits obtained by the mean client institution or individual. In contrast, individuals lose significant amounts of money. Trading activity, open interest and profitability are concentrated within each market participant group. This study also analyzes the impact of market-wide characteristics, and beyond that, the impact of peer actions and outcomes on individuals decisions to enter into commodities futures market. Aggregate entry rates of both individuals and companies in the commodity futures market are positively serially correlated, and increasing with trading volume and commodity market returns. The actions and market outcomes of local peers affect entry decisions. The number of new individual traders in a zip-code is highly positively serially correlated, and zip-codes with more active participants experience higher entry rates in the future. Moreover, the recent returns of individual traders in a zip-code are positively correlated with the future number of individual entries in that zip-code； the influence of peer returns is restricted to situations when neighbors experience negative returns. Our findings suggest that information about negative peer performance is more likely to spread among individuals than information about positive peer performance, or that the individuals in our sample react only to learning about negative peer returns.