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Inflation has recently become a phenomenon of both global concern and interest. Thus, it is of increasing importance to distinguish which assets perform well under the current inflationary circumstances. This study leverages event-study techniques to investigate how Bitcoin prices move with inflation in comparison to stock indices on a multi-market level. I find no strong confirmation of Bitcoin’s inflation hedging capabilities, although it performs relatively better than the stock index over the pe- riod of time considered. Additionally, volatility in Bitcoin market does not seem very responsive to either inflationary events or surprises

Since its peak in 1996, the number of publicly listed US ?rms has declined by approximately 50%. In addition, US publicly listed ?rms are now on average larger and older than they were two decades ago. We collect a set of empirical facts on the changes in the distributions as well as entry and exit rates for public and private firms. We develop a model to evaluate which of two mechanisms | an increase in the cost of being public or a shift in the supply of private firm financing | can explain the decline in US public listings and changes in the firm distribution. We calibrate the model to match the data prior to 1996 and then quantify the extent to which these two mechanisms can explain the changes observed in the data.

In the U.S. equity market, high-frequency trading firms with access to fast networks engage in latency arbitrage. In this dissertation, we study both theoretically and empirically whether the artificial latency (“speed bump”) implemented by Investors Exchange (IEX) and NYSE American protects slow traders from HFT predatory trading and improves market quality. In the first chapter, we look at daily TAQ data around the implementation of these two speed bumps, and find empirical evidence that the IEX speed bump improves the overall market quality, while the NYSE American speed bump makes little difference. We find that the IEX speed bump has a larger impact on more volatile stocks and stocks traded on exchanges closer to IEX, while the NYSE American speed bump mostly affects trading handled by its Designated Market Makers. We also study latency reductions on several NYSE exchanges and find that they do not improve market quality. In the second chapter, we build a model to study how a speed bump affects investors and the market. Fundamental investors, high-frequency arbitrageurs and market makers trade on two exchanges. When we introduce a speed bump to one of them, overall price discovery improves while the market has lower liquidity. Fundamental investors become more profitable at the expense of HF traders, while uninformed investors can be better or worse. We find that investors’ trading behavior depends on information production, communication between market makers, as well as venue choice of uninformed investors, which in turn determine the impact of introducing a speed bump.

In the first chapter, we investigate the asset pricing implications of disagreement about the unobservable process that drives monetary policy. We construct a monetary economy with two investors who have heterogeneous priors about the unobservable expected growth of money, namely, the underlying monetary stance. The key friction is that information about this unobservable variable is symmetric but incomplete. Investors estimate it from observed realizations of money supply in a Bayesian framework. Investors value real money holdings intrinsically, which gives rise to a demand for money. In equilibrium, the demand for money and investors’ estimates endogenously determine the nominal short rates and expected inflation through a portfolio rebalancing channel. Disagreement about money growth is one driver of the conditional variation in all nominal interest rates, expected inflation, and inflation risk-premium. Through a parameterized example, we show that the volatility of nominal interest rates tend to rise with increases in disagreement. We show that the relation between disagreement about money growth and asset prices crucially depends on the persistence of the unobservable growth rate of money. We further use the model to investigate the consequences of allowing for heterogeneous interpretations of public information (e.g. central bank statements) on interest rates. We introduce a public signal on which investors may have different views. One steadfast investor believes the signal conveys relevant information about the unobservable process, while a doubtful one believes it contains only noise. Depending on the persistence of the unobservable process, interest rates may be more or less volatile in an economy populated by one steadfast investor and one doubtful investor that in an economy with two doubtful investors. In the second chapter, we propose a method to measure the importance of private information about fundamentals as a determinant of market power in the primary market for sovereign debt. The method is based on the estimation of a divisible good uniform price auction model presented in Vives (2010, 2011). We establish conditions under which the model is identified from bidding data. Through an application to the Colombian debt market, we show that private information decreases and inventory costs rise after the rebalancing of two emerging markets debt indices. These two findings have opposite effects on bid shading. The estimation results indicate that the change in revenue for the treasury is lower than two basis points of the par value of the bond offering. However, this result masks the economically meaningful impact that private informationand inventory costs separately have on market power. We use the model estimates to quantify the effect of these changes on bidders’ market po to reduce borrowing costs. Finally, in the third chapter, we provide model-free evidence that supports the estimated reduction in the importance of private information and the increase in inventory costs from our structural estimates. If bidders are privately informed in this market, then an auction’s cutoff price would reflect bidders’ private information about fundamentals that were not already captured by observable market prices. We show that auctions with high cutoff prices relative to a pre-auction benchmark predict high future secondary market prices. After the rebalancing, this effect either shrinks or vanishes altogether, consistent with a decline in the importance of private information. Furthermore, we find higher mean-reversion in inventories after the rebalancing. On average, it takes bidders 11.7 days to offload half of their inventories before the rebalancing, but only 7.5 days afterwards. Finally, we provide reduced-form evidence that is consistent with the assumptions regarding primary market participation from the theoretical model and our empirical identification and estimation strategies.

Liquidity is a central feature in the research of financial markets. Broadly speaking, liquidity describes the ease with which an asset can be traded both quickly and withoutdeviating much from the current market price. In this collection of essays, I investigate three aspects of liquidity ��� one affecting stocks in the context of a limit order bookmarket, and two in the context of the over-the-counter market governing U.S. corporate bonds. In the first essay, measuring liquidity as the depth of the limit order book atprice levels extending from the mid-quote price, I explore the implications of private information which can be drawn from the dynamic levels of liquidity in the order book. In the second essay, measuring illiquidity as the effective bid-ask spread, I create an estimate for the aggregate illiquidity of the broader over-the-counter market for U.S. corporate bonds from the observed illiquidity of bonds that are traded. In the third essay, measuring liquidity as the market���s ability to absorb the large demand to sell bonds resulting from a fire sale, I observe the unintended impacts that Dodd-Frankregulations have on bond market liquidity and the indirect effects they have on the cost of capital faced by corporations when raising debt in the bond market.

A significant portion of household wealth is managed by financial professionals and investment companies. How these entities create value for their investors and whether their contributions are sufficient to justify the compensation are of great interest to both researchers and the general public. In this dissertation, we seek to further our understanding of the asset management industry. Chapter 1 explores the relationship between the fee of an investment product and how it is described by the money manager. To control for variations in dynamic strategies of differentfunds, we focus on Unit Investment Trust (UIT), a class of investment product with buy-and-hold portfolios and fixed life spans. In order to compare different portfolios, we adopt the method of collaborative filtering to transform the portfolio to a latent representation. A significant portion of dispersion in fees of UITs is correlated with how the investment objectives are stated, even after controlling for the variation in the portfolios. UITs whose investment statements include morepersuasive marketing languages and more discussions on stock selection procedures, diversification, and stock weightings charge higher sales fees. In Chapter 2, we consider a model of money management that reconciles the investment expertise of institutional investors and the lack of outperformance on their in-house managed capital.Due to the synergy between institutions' knowledge and external asset managers' skill, institutions never trade on their information directly. Instead, informed institutions delegate investment decisions to external asset managers while passing on their investment knowledge. Only uninformed institutions invest in-house due to the search cost of finding a skilled asset manager. We discuss how management fees and the size of the money management industry are related to the number of institutions with expertise and the value of institution expertise. Price is more informative when knowledge of institutions is more diffused.Chapter 3 is based on a joint paper with Bryan Routledge and Matthew Denes. We model the dynamic decisions of a Venture Capital (VC) fund during fundraising and capital deployment. VCs with better access and network receive greater deal flows, raise larger funds, and deploy capitalmore frequently. On the contrary, VCs with better screening abilities deploy capital at a slower rate due to the higher expected payoffs of future prospective projects. We estimate the model using VC deal data at each fund level. Funds differ mainly in access and are homogeneous in terms ofscreening ability. Differences in deal flows alone account for almost all the dispersion in fund values. By optimally matching estimated deal flow and screening, we can improve the average fund value by 2.5 percent. This corresponds to the unrealized gain from complementarity.

I analyze the relationship between bank failures that occur in the financial sector and the banking performance and condition ratios. The performance ratio that I chose to use in my analysis is the return on equity and the condition ratios are the capital adequacy ratio, the leverage ratio and the loan-deposit ratio. To achieve this goal, I use Estrella's model (2000) as my main framework and observe the banking sector over the recent credit crisis. I apply logit regression analysis to see if making predictions about future bank failures is possible with the available past data. In the regression analysis, I use both three-factor models and single factor models to assess the efficiency of more previously collected data. In order to see the motivators behind the banking firms' decisions, I also apply correlation tests between each performance and condition ratio.

Over the past few decades, information communication technology (ICT) and Internet interaction has developed drastically, causing more companies to join the phenomenon of Bricks and Mortar business model. Furthermore, as the trend persists, new business models have appeared: social networking sites, those who support online interaction and communication among the peers (such as Facebook and Twitter), email services and behavioral advertisement, electronic commerce for more convenient shopping experience, and information mediation online corporations, those who reduce individual search cost (such as online travel agency, OTA). Here, many times these corporations are not transparent in information and terms of use. If users do not agree to sometimes unfair statements, users are not permitted to use the service, which does not leave many choices for the users. This is much like the act of monopoly only except that it is overruling information instead of price. In order to combat this, we recall our traditional business model: competition brings about equilibrium in the market. In this research, we are going to investigate the fair terms of use and information transparency of online websites.

Are cryptocurrencies indeed currencies? Anecdotal evidence on the volatility of cryptocurrency prices suggest that these “currencies” are not a good store of value, and similarly the time delays in validating and publishing crypto-based transactions suggest that they are not a good medium of exchange either. Due to the context it is defined in, it seems to not follow social conventions of fiat currencies. In this thesis, we undertake a systematic evaluation of how much do cryptocurrency prices behave like fiat currency prices, focusing on the predominant cryptocurrency — Bitcoin. We test the usefulness of various time series and structural models to predict future changes in Bitcoin prices and conclude that when predicting out of sample, its price is as unpredictable as fiat currency prices. Since cryptocurrencies generally have no central authority and hence receive no regulation, we explore its country-dependent characteristics, and find that the overall conclusions apply. We also examine if nominal interest rate differentials denominated in fiat currencies versus Bitcoin predict exchange rate movements, and find that in addition to the persistent violation in short-run, interest parity suggest that Bitcoin price has not been rising fast enough. We conclude that we have to refine the definition of monetary parameters on cryptocurrencies to better capture its properties, but as far as our examination indicates, the price of the predominant cryptocurrencies behaves similarly to most fiat currencies. In our point of view, Bitcoin is a currency.

In this paper, I seek to answer the following question: How can microfinance institutions attract more people to take advantage of the lending services provided by microfinance institutions in rural India? Much research has been conducted on the effects of interest rates on attainment of clients of microfinance institutions but little attention has been paid to other terms and conditions of lending policies such as the payment plans and also other services provided by microfinance institutions. To address my research question, I have collected a rich dataset consisting of information on 6,798 households living in slums in Hyderabad, Andhra Pradesh (India’s fifth largest city). My data comes from several datasets made available by the Centre for Microfinance. The specific data that I will be using was collected by Spandana Spoorthy Financial Limited, one of the world’s largest microfinance institutions. I expect changing payment plans and providing other services to have a larger effect on customer attainment than changing interest rates. I will be analyzing existing policies on microfinance loans using this dataset and other studies. Then, I will be using behavioral economics, specifically economic behavior anomalies, to propose new policies on microfinance loans in the hope of attracting more clients to microfinance institutions.

This paper seeks to provide a general methodology for the valuation of alternative energy proposals in stochastic markets. Assuming that the markets for energy, fuel, and related financial derivatives are efficient and that prices between various fuels and energies are well understood, I will explain the existing theory of how these prices can be modeled as stochastic processes in relation to one another. I then postulate how these stochastic models can be incorporated into a mathematical framework to determine the value of an alternative energy proposal from the standpoint of consumers, investors, and society as a whole. While the mathematics supporting this argument have well been established, their application to proposal valuations as well as policy analysis has not been widely developed leaving most decision makers to rely on oversimplified discrete time models.

Catastrophe bonds, whose payoffs to investors are tied to the occurrence of natural disasters, provide primary insurers and reinsurers a mechanism by which they can securitize and transfer some of their residual risk to capital markets. We note that catastrophe bonds can be very attractive to investors as they provide the unique opportunity to improve a portfolio managers allocation by offering them an instrument that has both an attractive return and low covariability with financial markets. While catastrophe bonds are theoretically attractive, they have remained marginal relative to tranditional reinsurance. This paper proposes that a possible explanation for this marginality can be attributed to the lack of discussion about the pricing and valuation of these instruments in a public forum. We hope that this paper, which draws parallels between the modeling of defaultable bonds in a reduced-form setting and the pricing of catastrophe bonds, can serve as a springboard for future research in the insurance linked securities space.