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Liquidity and traders' behaviors in financial markets

Dissertation
Author: Laura Elena Serban
Abstract:
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 account's 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.

Table of Cont ent s Abstract iii Acknowledgments viii i. Active Traders, Capital and Liquidity 1 1.1 Introduction 1 1.2 Institutional Context and Data 10 1.3 Identification and Characteristics of Liquidity Providers in an Order Driven Market 13 1.4 Measuring Liquidity and Capital Availability 24 1.4.1 Liquidity Measures 24 1.4.2 Exogenous Capital Shocks as Trading Revenue in Fundamen tally Unrelated Commodities 28 1.4.3 Intra-day Round Trip versus Overnight Inventory Related Rev enues 30 1.5 Active Traders' Aggregate Revenues and Individual Security Liquidity 33 1.6 Active Traders' Competition and Individual Security Liquidity 50 1.7 Robustness JJ 1.8 Active Traders' Revenues and Participation Decisions j] 1.9 Conclusion 68 2. What are Local Traders Informed About and When? Evidence from Agricultural Com modity Futures 70 2.1 Introduction 70 2.2 Data and Descriptive Statistics yy 2.3 Local Bias 85 2.3.1 Measures of Locality 85 2.3.2 Local Bias 87 2.4 Local Performance 92 2.4.1 Measurement of Returns and Capital 93 2.4.2 Performance for Local Traders 94 2.4.3 Performance and Information on Domestic Supply Shocks .... 99 VI

2.5 Discussion 108 2.6 Conclusion 110 3. The Trading Decisions and Performance of Various Investor Types: an Anatomy of a Large Commodity Futures Market 112 3.1 Introduction 112 3.2 Literature Review 119 3.3 Data and Market Rules 128 3.3.1 NCDEX Market Rules . 130 3.3.2 India's Commodity Markets: World Placement and Brief History 132 3.4 Market Participants' Types and Characteristics 136 3.5 Trading Activity over Time 145 3.6 Share of Trading Activity of Aggregate Trader Type 150 3.7 Performance of Aggregate Trader Types 157 3.8 The Trading Strategies of Aggregate Trader Types 163 3.8.1 Attrition Levels 164 3.8.2 Common Futures Trading Strategies 168 3.9 Trading Activity Concentration by Trader Type 173 3.10 Heterogeneity of Trading Activity and Performance by Trader Type . . 181 3.11 Market-Wide and Neighborhood Determinants of Entry Decisions . . . 190 3.12 Conclusion 207 Appendix 211 A. Appendix to Chapter 1 2x2 A.i NCDEX Trading Platform 212 A.2 Trading Revenue Decomposition: Intra-Day Round-Trip Trades vs Overnight Inventory 215 B. Appendix to Chapter 3 219 Vl l

ACKNOWLEDGMENTS This thesis owes its existence to the help, support, and advice of many people. My deepest gratitude goes to the chair of my thesis committee, Prof. John Y. Campbell, for his patient guidance, encouragement and excellent advice throughout this study. His thoroughness, rigor, efficiency, wealth and generosity of thought will always be an inspiration for me. I am forever indebted to my long-standing advisor, Prof. Shawn Cole, for his constant support and for his unflinching confidence in my ability to succeed! I have learned a great deal from our frequent research discussions where he pushed me to be refine my ideas, improve my analysis, clarify my interpretations, and always work harder. The generosity of his time, as well as the constructive comments in the final stages of this thesis will never be forgotten; his down-to-earth attitude and positive energy are a lesson for life. I was also lucky to benefit from Prof. Erik Stafford's advice. His imagination, high research standards, insightful comments, and writing advice have helped me to become a more creative and sophisticated researcher. I have also benefited greatly from discussion and advice from Prof. Jeremy Stein, Prof. Josh Coval, and Prof. Robin Greenwood. I am grateful for their insightful suggestions on the various topics covered in this thesis, as well as for pushing me to think of relevant, hard and out-of-the-box research questions. My academic life was also shaped by wonderful teachers and mentors. I was fortunate to have the opportunity to talk extensively with my general examiners Prof. Alvin Roth and Prof. David Parkes, as well as with Susan Athey. They all taught me about the relevance of models and mathematics in the real world, and have kindled a passion for market design, a field to which I hope to contribute some day. I would also viii

like to acknowledge Gary Chamberlain and Jim Stock from whom I learned statistics and econometrics. I would have never started a Ph.D. in Economics without the inspirational advice of Prof. David Laibson, who guided my first steps in economics research. This thesis would have taken a very different shape without my colleague and co authors, Stefan Hunt, who generously introduced me to the dataset on commodity futures on which the results in this thesis rely, and to the management team at the National Commodity and Derivatives Exchange in India, which whom he had devel oped a prior relationship. I am thankful for our numerous and long discussions that sharpened my thinking and iorced me to become more organized, as well as for his help with my presentation skills! Despite some rough times in our working relation ship, our co-authorship has been an invaluable experience for me! My colleagues Erik Budish, Daniel Carvalho, Paul Niehaus, Thomas Mertens, Soojin Yim, Tarek Hassan, Justin Ho, Itay Fainmesser, Elias Albagli, Fuhito Kojima, and Mihai Manea have also provided inspiration and a pleasant work environment. I am also indebted to the National Commodity and Derivatives Exchange for their support and assistance in obtaining the data set used in this thesis, and for sharing their extensive experience and insights with me. Special thanks are due to the Ramalinga Ramasehsan, Jagdish Choudhry, Anand Iyer, Somesh Vaidya, Ankur Garg, Raj Benahalkar, Nirmalendu Jajodia, Uma Mohan, Ravinder Sachdev, and Sid- dharth Surana. I would also like to acknowledge financial support from the South Asia Initiative Fellowship and the Warburg Research Funds, as well as from the Har vard Business School Doctoral Programs Office. Special thanks are due to Janice McCormick, John Korn, Debra Hoss, LuAnn Langan and Jennifer Mucciarone for their care, promptness, and efficiency in running the program. IX

I could not imagine my life in Cambridge and Boston without my Romanian friends. A few words cannot summarize the impact they have had on my life. I would like to thank Tatiana Truhanov for her optimism and resourcefulness; Cristina Bucur for her kind care; Florin Morosan for his tireless advice, insightful discussions, and wonderful cooking; Alex Salcianu and Emanuel Stoica for always sharing the depth and wealth of their knowledge, and for perfectly organized MIT events, especially the Romanian parties; Andreea Balan-Cohen and Charles Cohen for their original entertainment recommendations; Florin Albeanu for many wonderful coffee breaks; and Mihaela Enachescu for her long and always supportive friendship. I am most grateful to Emma Voinescu and Crisii Jitianu for their unquestioning and consistent support when I needed it most, and for all the great times we spent together! I am also grateful to my boyfriend, Dan Iancu, for being next to me throughout my Ph.D. journey. His perseverance, passion for detail, and kindness have certainly made me a better person! I will always carry with me his inspired and perfectly timed gifts, including my favorite Starbucks bears, and cherish the memories we built together over the last five years. I would have never been able to complete this Ph.D. without my family. Their tireless love, unconditional support, and constant encouragement have kept me afloat through the toughest times of my life. I owe my direction in life to my father, who has taught me to ask questions, to insist on finding a solution to any problem, to persevere in spite of any difficulties, and to always believe in myself! I have always tried to emulate his unbounded optimism, as well as his passion for work and research. I am grateful to my mother for her immense love and care, and for never tiring in trying to make me a better person. Her kind advice has prevented me from making many mistakes! My sister has always been there for me for the good as well as the x

bad, and I could not imagine a better sibling! Her thoughtfulness, reserved manner, and refined taste have always been great resources for me. I am also grateful to my brother-in-law for his optimism and humor, and to my cutest baby nephew, who has truly enlightened our lives ever since he came into this world! This thesis is dedicated to my beautiful family! XI

i. Active Traders, Capi t al and Liquidity 1.1 Introduction Many asset classes exhibit significant cross-sectional and time-series variation in liquidity. Understanding the causes of variation in liquidity is important for a num ber of reasons. First, according to recent extensions of the capital asset pricing model, liquidity risk is a systematic determinant of asset prices. Second, liquidity is impor tant for our understanding of how traders affect asset prices. Third, efficient trading requires liquid markets; thus, understanding what determines liquidity is crucial to the design of financial markets. While there is significant literature on the cross-sectional determinants of liquid ity (Stoll, 2000, 2003), the time-series variation in liquidity received less attention. Yet, there is considerable daily variation in the liquidity of a security when measured by bid-ask spread, market depth, price impact, or price reversals. Moreover, recent studies have suggested that there are common liquidity components within an asset class (e.g., stocks) as well as across asset classes (e.g., stocks and bonds). What are the sources of high-frequency variation in liquidity? To what extent are these due to changes in adverse selection costs faced by liquidity providers, shocks to their ag gregate capital, or related variation in the intensity of their competition? Are there liquidity spillovers due to market-making arbitrageurs trading across multiple secu rities? 1

In this paper, I attempt to provide answers to these questions using a unique dataset and an innovative empirical strategy. The data consist of the entire history of trader-identified order and transaction activity records along with institutional types of all participants on the National Commodity and Derivatives Exchange (NCDEX) of India, globally the third largest exchange for agricultural commodity futures from inception on the 15th of December 2003 to the end of the first quarter in 2008. This data-set is particularly suited for my research questions for several reasons. First, the NCDEX trading platform is a fully electronic limit order book allowing for the computation of comprehensive liquidity measures. Second, over the sample period, close to 85% of trading activity in commodity futures in India occurred on NCDEX providing a centralized, rather than a fragmented picture of liquidity. Third, there are no designated market makers on NCDEX, a feature common across the majority of financial exchanges nowadays, allowing me to investigate the questions of interest in a general setting. Fourth, India is an environment where trading capital resources are likely scarce on a regular basis: NCDEX is a young trading platform in a developing country where banks, and institutional and foreign traders are restricted from trad ing. Most importantly, the combination of the large variety of commodities traded on NCDEX with the existence of multi-commodity high-frequency traders allows for an innovative empirical design that isolates relatively exogenous shocks to trading capital. Traditional models useful for the characterization of liquidity point to two main sources. The first relates to asymmetric information and suggests that liquidity providers should rationally shade quoted prices to account for the probability of trading with a better informed trader (Kyle, 1985; Glosten and Milgrom, 1985). The second relates to either inventory holding costs and risks in dealer markets (Ho and 2

Stoll, 1983) or to waiting costs and risks in the execution of limit orders (Rosu, 2005) in order-driven markets. These models assume that market makers' trading budgets are infinite. Recent work by Brunnermeier and Pedersen (2007) focuses on specula tors' capital availability and shows that when capital constraints are tight - because of higher margins or trading losses - speculators reduce positions and market liquidity declines. Orthogonally, a number of models emphasize that the level of competi tion among liquidity providers is causally related to market liquidity. Grossman and Miller (1988) show that because market makers face fixed costs of monitoring and maintaining a presence in the market and aggregate profits from liquidity provision are bounded, there is an optimal number of such traders. Their model implies that deviations away this point may cause a decrease in liquidity. Chacko, Jurek, and Stafford (2008) find that a simple imperfect-competition (and full-information) model of market-making is able to fit a wide range of features of real-word transaction costs. Transaction costs are modeled as the rents that a quasi-monopolistic market maker extracts from impatient investors who trade via limit orders. Importantly, the magni tude of these rents depends on the competition from opposing order flow. In this paper, I use a novel empirical strategy to investigate the extent to which speculators' capital constraints and the intensity of their competition cause time-series variation in liquidity. First, although, in limit order markets, no trader has an affirma tive commitment to provide an option to trade at all times, the natural market-maker candidates are participants who trade frequently and persistently - I refer to these traders as active. If market-making arbitrageurs arise naturally, they almost surely fall within this group. I find that a small fraction - close to 4% (about 7,400 traders) - of all traders on NCDEX account for slightly more than 60% of the average daily traded volume. I 3

characterize the portfolios, institutional features, trading behavior and performance of active traders. Broadly, I find that the median active trader participates in the mar ket for about 15 commodities and at least two different commodity types. The mean active trader is classified as such in at least 2 commodities with some being active in as many as 33 distinct commodities. About 54% of broker proprietary accounts and 11% of institutional clients are active traders, while only 4% of individual traders are so. Active traders perform particularly well in commodities in which they are classi fied as such, while losing especially on open positions in other commodities held in their portfolio. I proxy for changes in speculators' wealth by trading revenues on the NCDEX trading platform; specifically, I am able to precisely reconstruct the history of profit and losses of each trader in all commodities in which he participates. However, using changes in capital from trading in a certain commodity to identify the link between capital and the liquidity of that commodity is problematic. For example, suppose I observe that a wheat trader who suffered a major loss in wheat futures becomes sub stantially less willing to provide liquidity in wheat. Is this because he suffered a neg ative capital shock, because he updated his view on whether others possessed better information than he did, or because his long-term view on the expected price evolu tion of wheat has changed? Even with precise trading data, it is nearly impossible to discern between these motives. The ideal way to address such issues is to identify exogenous shocks to speculators' capital and competition intensity and to examine market liquidity around such events. My novel empirical strategy draws on this in sight and uses three features of the data. I use the fact that active traders participate in the market for multiple, diverse commodities. For a commodity, such as wheat, I can separate the remaining contracts traded into fundamentally related futures, e.g., 4

other cereals, and fundamentally unrelated futures such as metals or spices. I then proxy for an exogenous shock to a liquidity provider's capital with a gain or loss in one market unrelated to the fundamentals of another market. Commodities are the appropriate asset class for my methodology. In contrast to equities and bonds, which co-move with the market portfolio in commodity space, I can track pairs of securities that are fundamentally unrelated by measuring their price correlation and selecting low correlation pairs. Finally, I decompose a trader's daily revenue into a component due to intra-day round-trip trades within a contract and a component due to holding a position overnight for at least one day. As trading revenue from intra-day, round- trip trades may be mechanically correlated with future liquidity measures 1, I argue that an active trader's second type of revenue, derived from fundamentally unre lated commodities, serves as a source of plausibly exogenous variation in his capital, which allows me to directly identify the relationship between capital and willingness to trade and provide liquidity. The identification restriction is that changes in prices of unrelated commodities have no effect on a trader's desire to trade in a commodity, except through affecting that trader's capital. I quantify the effect of plausibly exogenous variation in active traders' aggregate capital on overall individual security liquidity as measured by average daily bid- ask spread. While my estimates are consistent with theory - an exogenous negative shock to active traders' aggregate capital causes an increase in next-day liquidity - the economic magnitudes are small. To my knowledge, this paper is the first to provide credible causal estimates of the capital channel for liquidity in a competitive market 1 For example, if liquidity providers trade with limit orders, their intra-day trading revenue should be larger on days when the bid-ask spread is large. If liquidity measures are persistent over time, then intra-day revenues may be mechanically positively associated with short-run liquidity. The concern extends to intra-day, round-trip revenue from uncorrelated commodities, if for any reason, liquidity across price uncorrelated commodities has common components due to causes other than constraints or competition among multi-commodity trading arbitrageurs. 5

environment. In order to further investigate the impact of capital shocks on liquidity provision, I turn to active traders' participation decisions. Although I do find that a decrease in capital due to trading in an unrelated security, lowers participation as measured by a participation indicator, number of trades or traded value and that this effect is non-linear, the magnitude of the estimated coefficients is again economically small. Interestingly, I also find that the effects of intra-day round-trip trading losses on liquidity as well as on participation levels in a particular commodity are considerably larger than those due to revenues from overnight positions even when the loss comes from trading in unrelated commodities. However, as pointed out earlier, the former effect could potentially be due to a mechanical correlation. I next ask whether changes in competition for liquidity provision cause variation in subsequent market liquidity. Intuitively, profitable active traders are natural com petitors for liquidity provision. As such, for each commodity, I measure competition intensity as the ratio of profitable active traders to the total number of active traders. Following a similar empirical design as above, I find that plausibly exogenous shocks in competition for liquidity provision due changes to in the number of winning ac tive traders in uncorrelated commodities explain a large fraction of the variation - between 20-30% - in subsequent bid-ask spreads. The effect is non-linear: the bid- ask spread is smallest around a naturally optimal level of competition, but increases as competition intensity deviates away from this threshold. An increase in the ratio of winning active traders in uncorrelated commodities to the total number of active traders from o to 0.4 corresponds a decrease in next day bid spread of 20 basis points (50% of a standard deviation). However, an identically sized increase in this ratio beyond the 0.5 cutoff corresponds to an increase in next day bid-ask spread of 18 to 6

20 basis points. In general, the magnitudes and statistical significance of the estimated effects of interest are larger when predicting liquidity in the non-nearby contracts than in the nearby contract 2. This is encouraging because the degree of non-synchronicity in natural customer order flow is higher in non-nearby contracts and hence shocks to liquidity supply from market making intermediaries are expected to have a more pronounced impact on the aggregate liquidity of these contracts. My results suggest that although on the NCDEX market, intermediary-speculators' capital constraints do generate spill-overs in participation and liquidity from one se curity to another, such spill-overs are economically small. In contrast, competition spill-overs defined as competition among active traders who made profits in other, unrelated commodities appears to be an economically important channel. My paper is most closely related to a study by Camerton-Forde, Hendershott, Jones, Moulton, and Seasholes (2008) who show that aggregate market and specialist- firm level effective bid-ask spreads widen following periods when the NYSE special ists have large positions or lose money, suggesting that market makers' financing constraints are associated with lower future liquidity. Several earlier studies have also suggested that this channel is important for the time-series variation of liquidity. Hatch and Shane (2002) show that specialist firm acquisitions are followed by a lower bid-ask spread in stocks assigned to the acquired firm potentially due to an easing of financing constraints. Coughenour and Saad (1998) compare the liquidity charac teristics of assigned stocks across specialist firms with different organizational forms showing that the stocks assigned to partnerships whose access to capital is tighter relative to firms capitalized by larger parent companies exhibit worse liquidity fea- 2 The nearby contract is the contract with the closest expiration date, but does not expire in the current month. On a given day, the contract records the highest traded volume. 7

tures. There are at least three drawbacks to these studies. First, they all focus on NYSE specialist firms and hence are relevant only to this specific market structure. Second, the sample period examined ends before 2007 when the NYSE adopted its electronic hybrid market structure, significantly decreasing the importance of spe cialists for liquidity provision. Most importantly, none of these estimates can be interpreted causally. My main contribution to this literature is to provide plausible causal estimates of the capital-channel for liquidity variation. In addition, my setting is that of an electronic, limit order market with no designated market makers, the market structure most common nowadays. My study also relates to an extensive theoretical (Amihud and Mendelson, 1980; Ho and Stoll, 1981, 1983) and empirical literature (Hasbrouck, 1998a; Hasbrouck and Sofianos, 1993; Hasbrouck, 1998b; Naik and Yadav, 2003; Wahal, 1998) that character izes the trading behavior and market quality impact of designated dealers focusing on specialists on the NYSE and dealers on NASDAQ. For example, the empirical study of Hasbrouck and Sofianos (1993) investigates the trading activity of specialist on the NYSE, finding that they make profits largely from short-term market making activity rather than from long-term value positions. Wahal (1998) finds that the entry and exit of dealers on NASDAQ has a significant effect on spreads in addition to other known determinants. However, he does not have access to dealers' positions and performance and hence cannot directly estimate the link between capital and liquidity. My work indirectly contributes to the recent literature that exhibits common fac tors in the liquidity of stocks (Chordia and Subrahmanyam, 2005a; Huberman and Halka, 2001; Hasbrouck and Seppi, 2001) and across different asset classes such as stocks and bonds (Chordia and Subrahmanyam, 2005b). While studies such as that 8

of Chordia and Subrahmanyam (2005b) and Hameed, Kang, and Viswanathan (2008) point to macro-economic factors as driving such commonality, others suggest that it could be due informational spill-overs or capital constraints of speculators trading across different asset classes. For example, Coughenour and Saad (1998) find that stocks traded by the same specialist firm share a common liquidity component and suggest that this might be due the specialist firm's capital constraints. I contribute to this debate through my empirical design, which strives to distinguish between the informational and capital constraints channel. Through the use of data from commodity futures markets, my study also relates to an older article that examines the activities of floor traders in CBOT's futures pits (Manaster and Mann, 1996). The authors focus on cross-sectional relationships be tween market makers' inventory positions and document that they control inventory throughout the trading day. However, they also show that floor traders' behavior con tradicts typical inventory control models as their inventories and reservation prices are positively correlated consistent with active position taking. My work examines naturally arising rather than designated market makers and focuses on the effect of capital constraints and competition intensity on liquidity. The paper proceeds as follows. Section 1.2 briefly describes the institutional con text of commodity futures markets and the National Commodity and Derivatives Exchange in India, the data and my sample selection criteria. Section 1.3 describes my procedure for the selection of active traders as well as these traders' portfolios, trading and performance characteristics. Section 1.4 describes the main features of my methodology, which isolates exogenous shocks to active traders' capital. Sections 1.5 and 1.6 focus on the impact of active trades' capital and competition intensity on the liquidity of the securities in which they trade. Section 1.8 evaluates the effect of 9

Full document contains 248 pages
Abstract: 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 account's 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.