Adlai Fisher

This dissertation is a collection of three essays that explore new directions in empirical asset pricing. The first essay studies the role of textual information in analyst reports. I show that analysts use the report text to convey soft information that has not yet been incorporated into their numerical forecasts. A simple tone measure predicts forecast revisions and forecast errors several periods ahead. Market prices quickly and adequately absorb the soft earnings information in analyst tone after the report publication. I demonstrate that analyst tone can be used to measure the saliency of upside or downside risks. The second essay proposes a novel deep learning approach to identify predictors of announcement returns from text. The method reveals that stock returns on earnings announcement days are predictable using analyst reports published weeks before the announcements. The identified predictors perform well for several years out-of-sample but eventually vanish. The predictability arises from a persistent underreaction to firm-specific news. A portfolio strategy based on out-of-sample announcement predictions earns large significant alpha. The findings are consistent with biased expectations and not in line with common risk-based explanations. The third essay studies the pricing of technological innovators in the stock market. It shows that technological innovators are priced differently, earning high stock returns controlling for standard factors, with less punishment for high capital investment and weak profitability. We create the persistent new firm variable patent intensity (PI), patents received divided by market capitalization, available from 1926. Aged PI portfolios and standard factors show high alpha and low profitability lasting more than a decade past formation for firms with high patenting intensity. Adding an expected growth factor, alphas become insignificant at most horizons, and loadings show large but declining growth, aggressive and increasing investment, and weak but improving profitability. The essay discusses partly unifying interpretations of some important factor models and the essential role of expected growth.

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In this thesis, I study the asset pricing aspect of institutional investors and their ability to provide financial services to households. The thesis consists of three essays. In the first essay, I theoretically investigate how institutional investors with different holding horizons allocate capital and the related asset pricing implications. I propose a model in which some institutions have shorter holding horizons, defined as short-term institutions, than other institutions, i.e. long-term institutions. The optimal portfolio of short-term institutions tilts towards speculative stocks that experience more volatile future demand shocks, which create transient trading opportunities. The current demand from short-term institutions increases the prices of these speculative stocks and reduces their buy-and-hold returns, making them less desirable for long-term investors. The model provides predictions relating a stock's short-term institutional ownership, trading opportunity, and expected return.In the second essay, I test the predictions of the first essay. Empirically, short-term institutions, identified as high-turnover institutions, invest more in stocks with higher CAPM beta, higher idiosyncratic volatility, and lower buy-and-hold abnormal returns. The difference in the buy-and-hold abnormal return between stocks with least and most short-term institutional investors is more than 3% per year. Stocks with more short-term institutional investors also provide more trading opportunities, allowing short-term institutions to make more trading profits. Their trading profits increase with market sentiment. This essay demonstrates that the desirability of investing in speculative stocks depends on an institution's holding horizon.The third essay examines the well-established negative relation between expense ratios and future net-of-fees performance of actively managed equity mutual funds. I show that this relation is an artifact of the failure to adjust a fund's performance for its exposures to the profitability and investment factors. High-fee funds exhibit a strong preference for stocks with low operating profitability and high investment rates, characteristics associated with low expected returns. After controlling for exposures to profitability and investment factors, I find that high-fee funds significantly outperform low-fee funds before fees and perform equally well net of fees. These results support the theoretical prediction that skilled managers extract rents by charging high fees.

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Technological innovations are important for economic growth but they are also a source of various risks. This thesis is a collection of three self-contained essays in which I study how technology shocks create risk for firms and households, and affect stock prices. Overall, the thesis helps us better understand the role of labor in the transmission of these shocks to stock prices. The first essay examines the asset pricing implications of technological innovations that allow capital to displace labor: automation. I develop a theory in which firms with high share of displaceable labor are negatively exposed to such technology shocks due to competition that makes technology adoption appear profitable but in equilibrium erodes the expected profits. Empirically, I develop a firm-level measure of displaceable labor share, based on detailed job classifications from the O*NET database, and find that firms with high displaceable labor share have negative exposure to technology shocks. A long-short portfolio based on this new measure is highly correlated with macroeconomic measures of technology shocks. I further show that firms with negative exposure to these technology shocks earn a 4% per year return premium. At the firm level, I provide support for the hypothesis of costly automation following technology shocks. In the second essay, I study how investment shocks affect different types of labor. I construct panel data sets of geographical areas, manufacturing industries and individual workers to examine the effects of investment shocks at three different levels of observations. I utilize the cross-sectional variation in routine intensity of occupations across these three panel data sets. I show that investment shocks are an important source of job displacement and labor income risk. The third essay examines how a firm's capital intensity can affect the measurement of firm's exposure to investment shocks by a popular measure, the IMC portfolio. I show that this measure suggests a considerable premium for an exposure to investment shocks when applied in a sample of capital-intensive firms but almost no premium for the same exposure when applied in labor-intensive sample. I extend a model from previous literature by capital intensity to provide a possible explanation.

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The relationship between information and stock returns is one of the most fundamental questions in finance and economics. This thesis aims to enhance our understanding of this relationship by using novel datasets and methods. In particular, I present a collection of three essays on the impacts of information on stock returns. I study both traditional sources of information, such as earnings announcements, macroeconomic news, and media coverage, as well as non-traditional sources of information, such as online employee reviews. The first essay “Asset Pricing in the Information Age: Employee Expectations and Stock Returns” studies the investment value of employees' information in financial markets, using a novel dataset of nearly one million employee reviews. This essay shows that employee expectations of their employers' business prospects predict future returns. I find that employee reviews are related to firms' fundamentals because they predict cash flow news. This essay highlights the importance of online information about firms' fundamentals, which is beyond traditional information sources such as analyst forecasts. Investors often face multiple types of news at the same time. Thus, the interaction between different types of news is crucial for understanding how information is incorporated into stock prices. My second essay “Macro News, Micro News, and Stock Prices” investigates interactions between macro-announcements and the processing of earnings news. Existing theories suggest that macro-news should crowd out attention to firm-level news, implying less efficient pricing. However, I find the opposite: on macro-news days price efficiency of earnings announcements is better when macroeconomic announcements are released on the same day. The news text is a new source of data which allows us to measure intangible but important variable, such as investor attention. In my third essay, “Media Attention, Macroeconomic Fundamentals, and the Stock Markets” (co-authored with Adlai Fisher and Charles Martineau), we construct indices of media attention to macroeconomic risks including employment, growth, and monetary policy. We study the properties of these attention indices and link them to stock markets. We conclude that media attention to macroeconomic fundamentals provides market-relevant information beyond the contents and dates of macroeconomic announcements.

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I present three essays on Information Economics. The first essay consists of analyzing high-frequency price dynamics around earnings announcements for the largest 1,500 U.S. stocks between 2011 and 2015. Price discovery following earnings surprises mostly occurs in the after-hours market, following the earnings announcement, and is generally complete by 10 a.m. Eighty percent of the price response to earnings surprises in the after-hours market occurs upon arrival of the first trades. Price reactions are largely explained by earnings surprises and not by order flow, consistent with the theoretical view that news can incorporate prices instantly. In the second essay, co-authored with Oliver Boguth and Vincent Grégoire, we show that in an effort to increase transparency, the Chair of the Federal Reserve now holds a press conference following some, but not all, Federal Open Market Committee announcements. Press conferences are scheduled independently of economic conditions and communicate little information. Evidence from financial markets demonstrates that investors lower their expectations of important decisions on days without press conferences, and we show that they shift attention away from these announcements. Both channels prevent effective monetary policy, as the committee is averse to surprising markets and aims to coordinate market expectations. Correspondingly, we show that announcements without press conferences convey less price-relevant information. In the third essay, co-authored with Adlai J. Fisher and Jinfei Sheng, we construct indices of media attention to macroeconomic risks including employment, growth, inflation and monetary policy. Attention rises around macroeconomic announcements and following changes in fundamentals over quarterly, annual, and business cycle horizons. The effect is asymmetric, with bad news raising attention more than good news. Increases in aggregate trade volume and volatility coincide with rising attention, controlling for announcements. Finally, changes in attention prior to the unemployment announcement predict both the announcement surprise and stock returns on the announcement day. We conclude that media attention to macroeconomic fundamentals provides useful information beyond the dates and contents of macroeconomic announcements.

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Governments play an important role in financial markets around the world. This thesis studies theoretical mechanisms and empirical consequences of government actions in financial markets in order to better understand the organization of the financial sector and the inner working of governments. The first essay “Shadow Banks, Deposit Competition, and Monetary Policy” studies the transmission mechanism of monetary policy through the shadow banking system, a group of non-bank financial intermediaries conducting banking business in the economy. This essay shows empirically and theoretically that the shadow banking system partially offsets the impact of monetary policy on the traditional commercial banking system and may lead to unintended consequences in terms of the stability of the financial system. The second essay “Regulation and Market Liquidity” (co-authored with Professor Francesco Trebbi), explores whether the post-crisis financial regulations, including the Dodd-Frank Act and Basel III, have caused liquidity deterioration in the U.S. fixed income market. Against the popular claim that post-crisis regulations hurt liquidity, this essay finds no evidence of liquidity deterioration during periods of regulatory intervention. Instead, liquidity seems to have improved in this period. The third essay, “Factions in Nondemocracies: Theory and Evidence from the Chinese Communist Party” (co-authored with Professor Patrick Francois and Professor Francesco Trebbi), investigates theoretically and empirically the factional arrangements and dynamics within the Chinese Communist Party (CCP), the governing political party of the People's Republic of China. This essay documents a set of new empirical findings showing how factional politics affects the promotion of individual politicians within the CCP hierarchy. This essay proposes a theoretical model to rationalize these findings and conduct a set of counterfactual analyses of possible institutional changes within the CCP.

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The present thesis is a collection of three essays in Macro Finance. The first essay examines the effects of industry competition on the cross-section of credit spreads and levered equity returns. I build a quantitative model where firms make investment, financing, and default decisions subject to aggregate and firm-specific risk. Firms operate in heterogeneous industries that differ by the intensity of product market competition. Higher competition reduces profit margins and increases default risk for debtholders. Equityholders are protected against default risk due to the option value arising from limited liability. In equilibrium, competitive industries are characterized by higher credit spreads, but lower expected equity returns. I find strong empirical support for these predictions across concentration quintiles. Moreover, the calibrated model generates cross-sectional variation in leverage and valuation ratios in line with the data.The second essay provides new evidence that imperfect competition is an important channel for time varying risk premia in asset markets. To this end, we build a general equilibrium model with monopolistic competition and endogenous firm entry and exit. Endogenous variation in industry concentration generates countercyclical markups, which amplifies macroeconomic risk. The nonlinear relation between the measure of firms and markups endogenously generates countercyclical macroeconomic volatility. With recursive preferences, the volatility dynamics lead to countercyclical risk premia forecastable with measures of competition. Also, the model produces a U-shaped term structure of equity returns.The final essay explores the interactions between yield curve dynamics and nominal government debt maturity operations in a New Keynesian model with endogenous bond risk premia. Violations of debt maturity neutrality occur when the yield curve slope is nonzero in a fiscally-led policy regime. When the risk profiles of government liabilities differ, rebalancing the maturity structure changes the government cost of capital. In the fiscal theory, changes in discount rates affect inflation through the intertemporal government budget equation. When the yield curve is upward-sloping (downward-sloping), the fiscal discount rate channel implies that shortening the maturity structure has contractionary (expansionary) effects.

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This thesis contains two essays related to passive investing and passive investment vehicles.In the first essay, I introduce a general equilibrium model with active investors and indexers. The presence of indexers causes market segmentation, and the degree of segmentation is linked to the relative wealth of indexers in the economy. Any shock to this relative wealth generates excess comovement by inducing correlated shocks to discount rates of index stocks. The wealthier the indexers are, the greater the resulting excess comovement is. In the data, I find that S&P 500 stocks tend to comove more with other index stocks and less with non-index stocks, but this was not the case until the 1970s when indexing gained in popularity. I use passive holdings of S&P 500 stocks as a proxy for the wealth of indexers and find that changes in passive holdings are positively related to changes of excess comovement in S&P 500 stocks. In the second essay, I use liquid exchange traded funds to study the issue of international mutual fund predictability. Mutual fund returns are predictable when the Net Asset Value is computed from prices that do not reflect all available information. This problem was brought to the public eye with the late trading and market timing scandal of 2003, which led to SEC intervention in 2004. Since these events, mutual fund managers have been more active in adjusting NAV, reducing predictability by about half. The simple trading strategy I present yields annual returns of 33% from 2001 to 2004 and 16% from 2005 to 2010. Even after accounting for trading restrictions in mutual funds, an arbitrager could earn annual returns of 2.73% from 2005 to 2010, suggesting the problem is not fully resolved. The main methodological contribution of this essay is to develop a filtering approach based on a state-space model that embeds the fund manager problem, thus accounting for unobserved actions of fund managers. I also show that predictability increases significantly when information sources suggested by prior literature, such as index and futures returns, are supplemented by premiums on related exchange traded funds.

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In the first chapter of this thesis, I propose a nonlinear filtering method to estimate latent processes based on the Taylor series approximations. The filter extends conventional methods such as the extended Kalman filter or the unscented Kalman filter and provides a tractable way to estimate filters of any order. I apply the filter to different models and demonstrate that this method is a good approach for the estimation of unobservable states as well as for parameter inference. I also find that filters with Taylor approximations can be as accurate as conventional Monte Carlo filters and computationally more efficient. Through this chapter I show that filters with Taylor approximations are a good approach for a number of problems in finance and economics that involve nonlinear dynamic modeling. In the second chapter, I investigate the recently documented, large time-series variation in the empirical market Sharpe ratio. I revisit the empirical evidence and ask whether estimates of Sharpe ratio volatility may be biased due to the limitations of the standard ordinary least squares (OLS) methods used in estimation. Based on simulated data from a standard calibration of the long-run risks model, I find that OLS methods used in prior literature produce Sharpe ratio volatility five times larger than its true variability. The difference arises due to measurement error. To address this issue, I propose the use of filtering techniques that account for the Sharpe ratio's time variation. I find that these techniques produce Sharpe ratio volatility estimates of less than 15% on a quarterly basis, which match more closely the predictions of standard asset pricing models.

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In this thesis, I explore the implications of investor information for asset returns in general equilibrium economies with production.In the first chapter, I study what determines the relationship between information quality and long-run risk in a Cox-Ingersoll-Ross type model with recursive preferences. Building on the recent work by Ai (2010), I separate the risk premium into the short-run and long-run components to highlight aspects of preferences that are important for this relationship. It is shown that the attitude towards temporal resolution of uncertainty determines the direction in which changes in information quality alter the compensation for long-run risk, while the elasticity of intertemporal substitution is important for the amplitude of this effect.In the second chapter, I investigate how incomplete information affects asset returns in a real business cycle model with Epstein-Zin preferences. In the model economy, productivity is altered by both transitory and permanent shocks. The representative agent observes movements in productivity but cannot perfectly distinguish their sources. As a result he must solve a signal extraction problem. This incomplete information model is found to be quantitatively consistent with some common observations about asset prices and aggregate quantities, including, for example, the equity premium, the risk-free rate, the price-dividend ratio and the dynamics of consumption and output. Furthermore, the model generates a downward sloping term structure of equity risk as empirically observed-namely, assets with short-duration of cash flows have larger risk premium and return volatility than assets with long-duration of cash flows.

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In this thesis, I study the relationship between excess cash holdings of corporations and mutual funds and future performance of these entities. In the first chapter, I document a positive relationship between corporate excess cash holdings and future stock returns. The difference in returns of portfolios of high and low excess cash firms amounts to 5% annually or 6% after standard three-factor risk adjustment. Firms with more excess cash have higher market betas and earn lower returns during market downturns. High excess cash companies invest considerably more in the future than do their low cash peers, but do not experience stronger future profitability. On the whole, this evidence is consistent with the notion that excess cash holdings proxy for risky growth options. In the second chapter, I document a positive relationship between excess cash holdings of actively managed equity mutual funds and future fund performance. The difference in returns of portfolios of high and of low excess cash funds amounts to over 2% annually, or approximately 3% after standard risk adjustment. I study whether this difference in performance can be explained by the differences in managerial stock selection skills, market-timing abilities, fund liquidity needs, and operating costs. I show that managers of high excess cash funds make more profitable stock purchasing decisions, while low excess cash fund managers make better sell decisions. Neither high nor low excess cash groups exhibit significant market-timing skills; however, funds with volatile excess cash holdings are successful market timers. The difference in returns between high and low excess cash groups is particularly pronounced during periods of low fund flows, suggesting that high excess cash funds are better able to anticipate fund outflows. Finally, I show that high excess cash funds incur significantly lower operating expenses than do their low excess cash peers. I additionally document new important determinants of mutual fund cash balances, showing that funds with riskier or less liquid shareholdings, as well as those with higher return gap measures hold more cash. The determinants I consider jointly explain three times more cross-sectional variation in cash positions than variables studied in prior literature.

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This thesis contains two essays. In the first essay, we investigate the impact of time varying volatility of consumption growth on the cross-section and time-series of equity returns. While many papers test consumption-based pricing models using the first moment of consumption growth, less is known about how the time-variation of consumption growth volatility affects asset prices. In a model with recursive preferences and unobservable conditional mean and volatility of consumption growth, the representative agent's estimates of conditional moments of consumption growth affect excess returns. Empirically, we find that estimated consumption volatility is a priced source of risk, and exposure to it predicts future returns in the cross-section. Consumption volatility is also a strong predictor of aggregate quarterly excess returns in the time-series. The estimated negative price of risk together with the evidence on equity premium predictability suggest that the elasticity of intertemporal substitution of the representative agent is greater than unity, a finding that contributes to a long standing debate in the literature.In the second essay, I present a simple model to show that if agents face binding portfolio constraints, stocks with high volatility in states of low market returns demand a premium beyond the one implied by systematic risks. Assets whose volatility positively covaries with market volatility also have high expected returns. Both effects of this idiosyncratic volatility risk premium are strongest for assets that face more binding trading restrictions. Unlike the prior empirical literature that obtains mixed results when focusing on the level of idiosyncratic volatility, I investigate the dynamic behavior of idiosyncratic volatility and find strong support for my predictions.Comovement of innovations of idiosyncratic volatility with market returns negatively predicts returns for trading restricted stocks relative to unrestricted stocks, and comovement of idiosyncratic volatility with market volatility positively predicts returns for restricted assets.

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This thesis comprises two essays that apply nonparametric methods to the estimation of portfolio allocations.In the first essay, I test the significance to investor welfare of (i) adding additional assets to the portfolio choice set and (ii) conditioning on predictor variables.I estimate unconditional and conditional optimal allocations of a constant relative risk aversion investor by maximizing a nonparametric approximation of the expected utility integral. Investors can improve their expected utility significantly over that of an equities and cash investor by adding portfolios based on the value or momentum premiums into their asset allocation decision. In contrast, neither a size premium portfolio nor a long-term bond portfolio improves expected utility.The significance of predictability is increased by simultaneously conditioning on the two strongest predictors (of eight) studied: the term spread and the gold industry trend.In the second essay, I formulate a nonparametric estimator that permits combining historical data with a qualitative prior. I investigate the impact of an investor belief, motivated by asset-pricing theory, that optimal allocations are positive. In the estimator construction, I use a Bayesian approach to perturb the probabilities associated with each data point in the empirical distribution to reflect qualitative prior beliefs.In a simulation study and in out-of-sample tests, I find that portfolio estimates conditioned on a belief in the positivity of portfolio weights are significantly more stable than those estimated by an uninformed investor, and that the model performs better in out-of-sample tests than a number of plug-in models. However, the out-of-sample performance lags that of the minimum-variance and 1/N policies.

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