This paper studies dynamical and cross-sectional structures of bonds, typically used as risk-free assets in mathematical finance. After reviewing a mathematical theory on common factors, also known as principal components, we compute empirical common factors for 10 US government bonds (3month, 6month, 1year, 2year, 3year, 5year, 7year, 10year, 20year, and 30year) from the daily data for the period 1993-2006 (data for earlier period is not complete) obtained from the official web site www treas.gov. We find that the principal common factor contains 91% of total variance and the first two common-factors contain 99.4% of total variance. Regarding the first three common factors as stochastic processes, we find that the simple AR(1) models produce sample paths that look almost indistinguishable (in characteristic) from the empirical ones, although the AR(1) models do not seem to pass the normality based Portmanteau statistical test. Slightly more complicated ARMA(1,1) models pass the test. To see the independence of the first two common factors, we calculate the empirical copula (the joint distribution of transformed random variables by their marginal distribution functions) of the first two common-factors. Among many commonly used copulas (Gaussian, Frank, Clayton, FGM, Gumbel), the copula that corresponds to independent random variables is found to fit the best to our empirical copula. Loading coefficients (that of the linear combinations of common factors for various individual bonds) are briefly discussed. We conclude from our empirical analysis that yield-to-maturity curves of US government bonds from 1993 to 2006 can be simply modelled by two independent common factors which, in turn, can be modelled by ARMA(1,1) processes.

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.

Gaussian normal error assumption and OLS-based regression estimations form the basis of co-integration testing techniques. However, many studies have found evidence that financial and some important economic time series data such as exchange rate returns and inflation rates are subject to high variability. In particular, their innovations exhibit the features of skewness, excessive peakness around the mean and heavier tails than those of the Gaussian normal distribution. Stable distributions which are used to model high variability in data and infinite-variance processes) provide more realistic distributional assumptions than the Gaussian distribution for heavy-tailed financial and economic time series. Least Absolute Deviation LAD) based estimators often yield robust results for heavy-tailed data compared to least squares based estimators. In this dissertation, as a natural extension of the extant studies, we consider a new robust residual-based co-integration test under the assumption of infinite-variance errors which are in the domain of attraction of a stable law. We implement the least absolute deviation LAD) procedure in our regression estimations. In part I, the new co-integration tests are proposed. The test is parametric: the critical values of the test statistic depend on the stability index of the stable distribution from which the errors are driven. The unit root test statistic we consider under the null of no co-integration is taken from Samarakoon and Knight 2009, Econometric Reviews, 28, 314–334). We find the critical values of these new co-integration tests through Monte Carlo simulations and observe that the null convergence of the test statistic is faster for lighter tails. Size and power comparisons are included to evaluate the performance of the new residual-based tests relative to conventional OLS-based ones which are due to Caner 1998, J. of Econometrics, 86, 155–175). We observe that the LAD-based tests have power advantages over the OLS-based tests as the sample size gets larger and the tails get heavier with infinite-variance error assumption, yet there are more size distortions associated with LAD-based tests especially for small sample sizes compared to OLS-based ones. The new tests are employed to test for forward rate unbiasedness hypothesis FRUH) with daily frequency data for a sample of eight currencies Australian dollar, Canadian dollar, French franc, German mark, Italian lira, Japanese yen, Swiss franc and U.K. pound) against the U.S. dollar for 1-month, 3-month, 6-month and 1-year forward contracts. We also run fully-modified ordinary least squares FM-OLS) and fully-modified least absolute deviation FM-LAD) estimators on the co-integrating regressions to test the coefficient restrictions which are implied by the FRUH. We observe that tests involving longer maturity forward contracts 6-month and 1-year) and LAD-based co-integration tests mostly provide the evidence that is inconsistent with FRUH. In part II, weak and strong-form purchasing power parity PPP) relations are re-examined by using LAD-based procedures under infinite-variance error assumption. LAD-based co-integration tests that are proposed in part I are used to test for weak-form PPP. FM-OLS and FM-LAD procedures are used to test for the strong-form PPP hypothesis. The results from LAD-based estimations are compared to their OLS-based counterparts. Monthly exchange rate per U.S. dollar) and PPI data for a sample of eight countries Austria, Canada, Denmark, Germany, Japan, Netherlands, Sweden and the U.K.) from 1973:1 to 2009:12 are used for estimation purposes. Neither weak-form nor strong-form PPP relations can be justified empirically regardless of the estimation procedure. Results from the new residual-based co-integration tests give slightly more support of the weak-form PPP.

This dissertation uses flexible finite mixture distributions to simultaneously make inferences about the group membership of heterogenous firms and households and their behavior. It first exhibits the relationship existing among several alternative mixture models and shows how their comparison can be used to learn about specific features of a given panel data set. These models are then used to learn about a firms financial states and about the interdependence between these states and a firms investment decision using a panel data set on US manufacturing firms obtained from the COMPUSTAT database. Their comparison reveals that time dependence is a more important issue than the interdependence between the firms financial status and its investment decision when it comes to the fit of the models to the data. Similar models are also used to reexamine the effect of the 1997 healthcare reform enacted in Germany using a panel data set on the number of doctor visits derived from the German Socio-Economic Panel by Winkelmann 2004) for the period going from 1995 to 1999. Again, we find evidence in favor of time dependence. However, controlling for the presence of random effects in the mixture components leads to models which fit much better to the data.

This dissertation uses flexible finite mixture distributions to simultaneously make inferences about the group membership of heterogenous firms and households and their behavior. It first exhibits the relationship existing among several alternative mixture models and shows how their comparison can be used to learn about specific features of a given panel data set. These models are then used to learn about a firms financial states and about the interdependence between these states and a firms investment decision using a panel data set on US manufacturing firms obtained from the COMPUSTAT database. Their comparison reveals that time dependence is a more important issue than the interdependence between the firms financial status and its investment decision when it comes to the fit of the models to the data. Similar models are also used to reexamine the effect of the 1997 healthcare reform enacted in Germany using a panel data set on the number of doctor visits derived from the German Socio-Economic Panel by Winkelmann 2004) for the period going from 1995 to 1999. Again, we find evidence in favor of time dependence. However, controlling for the presence of random effects in the mixture components leads to models which fit much better to the data.

I study the importance of financial factors and real exchange rate shocks in explaining business cycle fluctuations, which have been considered important in the literature as non-technological factors in explaining business cycle fulctuations. In the first chapter, I study the implications of fluctuations in corporate credit spreads for business cycle fluctuations. Motivated by the fact that corporate credit spreads are countercyclical, I build a simple model in which difference in default probabilities on corporate debts leads to the spread in interest rates paid by firms. In the model, firms differ in the variance of the firm-level productivity, which is in turn linked to the difference in the default probability. The key mechanism is that an increase in the variance of productivity for risky firms relative to safe firms leads to reallocation of capital away from risky firms toward safe firms and decrease in aggregate output and productivity. I embed the above mechanism into an otherwise standard growth model, calibrate it and numerically solve for the equilibrium. In my benchmark case, I find that shocks to variance of productivity for risky and safe firms account for about 66% of fluctuations in output and TFP in the U.S. economy. In the second chapter, I study the importance of shocks to the price of imports relative to the price of final goods, led by the real exchange rate shocks, in accounting for fluctuations in output and TFP in the Korean economy during the Asian crisis of 1997-98. Using the Korean data, I calibrate a standard small open economy model with taxes and tariffs on imported goods, and simulate it. I find that shocks to the price of imports are an important source of fluctuations in Korea’s output and TFP in the Korean crisis episode. In particular, in my benchmark case, shocks to the price of imports account for about 55% of the output deviation (from trend), one third of the TFP deviation and three quarters of the labor deviation in 1998.

Accounting standard setters and financial information providers are interested in individual investors’ use of accounting information, but find it difficult to assess with conventional data sources. Financial message boards provide a unique medium to analyze individuals’ attention to accounting information on a large scale and in great detail. I examine accounting-related content in 1.94 million messages for 1,852 firms and find that individual investors pay considerable attention to accounting information. In accordance with the expectation that investors react to relevant information events, I find that accounting-related discussion is significantly elevated around earnings releases, 8-K reports, quarterly reports, and annual reports of the smallest firms. I also examine whether investors expand their accounting information acquisition and processing efforts in poor information climates. I show that accounting-related discussion increases in an environment of greater uncertainty, measured by information availability (lower analyst coverage), information precision (higher analyst forecast dispersion), and information ambiguity (higher trading volume). Lastly, I propose that greater attention to accounting information may be associated with evidence of a better-informed investor. I find evidence that higher accounting discussion around earnings announcements is associated with a reduction in information asymmetry but no evidence of a reduction in the post earnings announcement drift.

This study investigates the impact of portfolio disclosure on hedge fund performance. Using a regression discontinuity design, I investigate the effect of the disclosure requirements that take effect when an investment company’s assets exceed $100 million； when that occurs, a fund is required by the SEC to submit form 13F disclosing its portfolio holdings. Consistent with the argument that portfolio disclosure reveals “trade secrets” and also raises front running costs thus harms the funds that disclose, I find that there is a drop in fund performance (about 4% annually) after a fund begins filing form 13F, as well as an increase in return correlations with other hedge funds in the same investment style. The drop in performance cannot be explained by a change in the assets under management or a mean reversion in returns. Consistent with the idea that funds with illiquid holdings tend to employ sequential trading strategies, which increase the likelihood of being taken advantage of by free riders and front runners, the drop in performance is more dramatic for funds that have more illiquid holdings. In addition, I find that the incentive fees paid to fund managers are 1% higher when portfolio disclosure is required, which supports the hypothesis that investors’ monitoring of portfolio holdings disciplines adverse risk-taking by fund managers and allows for higher convexity in the optimal compensation structure. Finally, there is a drop in flows into funds that file 13F, which suggests that hedge fund investors negatively value 13F disclosure. Overall, this study suggests that the cost of portfolio disclosure is economically large. It contributes to the policy debate over what constitutes optimal disclosure.

Informed traders might prefer the option markets over stock markets due to advantages offered by option trading such as reduced transaction costs, enhanced opportunities for taking short positions and higher leverage. The first chapter of this dissertation provides a brief review of the empirical and theoretical literatures related to this question. The second chapter investigates the intertemporal relation between volatility spreads and expected market returns. If informed traders who prefer to trade in the option markets demand more put call) options before negative positive) price movements due to their private information, then one would expect to see a significantly negative intertemporal relation between put minus call implied volatility spreads and aggregate returns. The results indicate that volatility spreads are significantly and negatively related to expected market returns after controlling for conditional variance and macroeconomic variables that proxy for the changes in future investment opportunities. Since the volatility spreads may also proxy for skewness, direct physical and risk-neutral skewness measures are constructed and the results indicate that there is no significant relation between various measures of skewness and expected market returns. The predictive ability of volatility spreads is stronger when consumer sentiment index is unusually high or low. The third chapter brings a more thorough look into the predictive ability of deviations from put-call parity on stock returns. If the trading activity of informed investors is an important driver of deviations from put-call parity, then the predictability of stock returns should be more pronounced during major information events such as earnings announcements. These deviations are measured by the implied volatility spreads between pairs of matched put and call options. During a two-day earnings announcement window, the abnormal returns to a portfolio that buys stocks with relatively expensive call options is about 2 percent greater than the abnormal returns to a portfolio that buys stocks with relatively expensive put options. The informational role of option markets is further supported by the findings that the degree of announcement return predictability is stronger when deviations from put-call parity are measured using more liquid options, information environment is more asymmetric and stock liquidity is low.

This dissertation takes advantage of recent developments in market microstructure literature that offer estimation of informed trading which is used to examine information content of earnings, dividends, tender offers and Dutch auctions announcements. Studying the information content is important in order to understand the relevance of the announcement itself, and the trading strategies of the market participants, to decide on the managerial choice of appropriate announcement to convey value relevant information. The major innovation of this research design is a combination of assessing information contents of dividends and earnings announcements based on their surprises and estimating informed trading to understand market reaction. The premise of this study is that if announcements contain information it should reflect on traders trading patterns. Based on this premise, I find evidence of significant change in informed trading for dividend announcements but not for earnings announcements when the announcements are made concurrently, an issue which the existing literature does not address. I also find significant differences in informed trading when dividend announcements contain surprises but not when dividends announcements contain no surprises. Existing literature provides no empirical evidence on this issue. Finally, for tender offers and Dutch auction, I do not find any significant change in informed trading. These results collectively imply that not all corporate announcements reduce asymmetry of information. More importantly, contrary to recent findings that suggest a decline in information content of dividends, this study confirms significant information content of dividends and also highlights importance of disaggregating dividends announcements based on its surprises which previous study fails to incorporate in its research design. Finally, the recent trend in increase share repurchase not necessarily implies that the firms are conveying value relevant information.