Browsing by Author "Back, Kerry"

Now showing 1 - 5 of 5
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    Asset Prices with Labor and Jump Risk
    (2016-04-21) Zekhnini, Morad; Back, Kerry
    This dissertation investigates the asset pricing implications of labor-induced leverage and the incidence of jumps. Due to wage stickiness and firm-specific human capital, labor induces operating leverage that contributes to the risk exposure of the firm. This leverage produces momentum in returns as well as a positive relationship between profits and subsequent returns. Empirically, momentum and profitability returns are more pronounced in the presence of labor-induced operating leverage. A novel implication of the model is that recession-resistant stocks earn higher returns during subsequent expansions. This prediction holds empirically and is distinct from other anomalies. The entire annual return of a typical stock accrues on the four trading days when its price "jumps". Consistent with an idiosyncratic jump risk premium, prices decline by over 2% in the 30 days prior to both positive and negative jumps. This negative drift is proportional to changes in option implied jump probabilities over the period. Both the jump premium and the negative drift are present during periods of low jump clustering and are related to proxies for investor diversification and limits to arbitrage.
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    Essays in Financial Economics
    (2019-07-19) Barton, Paul; Back, Kerry
    Financial markets often feature interactions between agents who do not have the same amount of information about a financial asset. The presence of asymmetric information in financial market interactions has significant implications for equilibrium outcomes, and can account for the behavior observed in certain empirical puzzles. In the first chapter, I study the formation of a firm’s capital structure. I show that asymmetric information between firms and investors causes firms to signal their quality to the market via their debt issuance decisions. In contrast to the previous literature, I show that this setting can result in high quality firms borrowing less than low quality firms. An effect similar to that of credit rationing drives this result. This finding can explain the zero leverage puzzle, i.e. some high quality firms use almost no leverage; as well as the negative correlation between profitability and leverage and findings of no (or negative) announcement effects for debt issuance. In the second chapter, I construct a model of informed trading through a public exchange and a dark pool, where the informed trader has price impact. In this model, the dark pool makes the price less accurate by reducing the quantity of public exchange trading from the informed agent. This reduction in trade is due to the fact that the informed agent can profit from the dark pool, but only if he does not make the price on the public exchange too accurate. In the third chapter, which is co-authored with Kerry Back, we examine the case of traders with differing private values for an asset such that there are gains to trade. We show that if traders are unwilling to display liquidity due to the information revealed by orders, then an opportunity to trade in the dark can be welfare enhancing. We introduce a dark mechanism into a model of two-sided bargaining with incomplete information and strategic delay. Traders delay displaying liquidity even further when it is possible to trade in the dark, but the net effect of trading in the dark is to accelerate trade and increase welfare.
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    Essays in Financial Economics and Asset Pricing
    (2024-08-06) Zhao, Binyu; Back, Kerry; Tang, Xun
    The dissertation consists of three essays that investigate the information contents and the implications of the formulation process of financial asset prices. Chapter 1, The Information Content of Municipal Bond Auctions, explores the information contents of municipal bond auctions. Based on the auction data of municipalities in the U.S. from the year 2018 to 2019, this paper tests whether the dispersion of bidders’ values leads to overpricing of municipal bonds, and whether the price informativeness of municipal bonds decreases with the dispersion. An affiliated private value auction model is applied to estimate the variances of bidders’ values, and then regression analysis is performed. The main finding is that bonds issued by municipalities with larger dispersion tend to be overpriced. One standard deviation increase in the dispersion causes around a 0.0531 standard deviation decrease in spreads. Another finding is that the correlation between bond prices and local economy is significant only for counties with value variances in the second quartile, which suggests that the dispersion decreases the price informativeness of municipal bonds. Chapter 2, Information Precision, Liquidity, and Risk Premiums: Evidence from Stock Call Auctions in the U.S., investigates the effects of information precision on financial market outcomes. Using the data from NYSE Arca call auctions, this paper tests the empirical implications of the demand schedule submission model in Kyle (1989). After showing the solid predictive power of order books and estimating the predictive precision, this paper demonstrates that higher precision increases market liquidity and that the precision levels of different types of traders do not interact with each other to affect liquidity measures such as daily turnover. Another finding is that precision is priced in excess returns, but the relation between precision and risk premiums is not linear. The main channel for precision to take effects is marginal utility. The sensitivity of a trader's marginal utility to her trading quantity is determined by her risk aversion and her own information precision. Therefore, precision affects the elasticity of demand curves and thus affects the final market outcomes. Chapter 3, A Discussion on Call Auction Data: Explore the Predictive Power of Order Books, explores the predictive power of order book data during NYSE Arca closing call auctions by applying various machine learning algorithms, including Gradient Boosting, Random Forests, Lasso, and Ridge. For each algorithm, predictions are evaluated over different tuning parameter choices. Then grid search is applied to determine the optimal parameters for each algorithms, and the performances of different algorithms are compared. The findings include that the overall prediction performances could not increase monotonically with the model complexity, because the increase in the model complexity also leads to over-fitting and finally impairs prediction accuracy. For the order book data analyzed, Random Forests achieves the best prediction performance. In general, tree-based models perform better than linear models. It suggests that the relation between order book statistics and future equity returns could have a complex non-linear form.
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    Essays on Financial Market Structure and Shareholder Voting
    (2024-12-06) Blonien, Patrick; Back, Kerry
    Chapter 1: Size Discovery in Slow Markets Adding a size-discovery trading protocol, where a break in the limit order book occurs to match orders at a fixed price, can increase allocative efficiency in markets with slow trading frequency. A high trading frequency spreads liquidity, resulting in a strong incentive to wait for a size-discovery session. This incentive to delay trade is smaller in slower markets, and its negative effect on efficiency can be offset in slower markets by the positive effect of size discovery. This result rationalizes the empirical fact that size-discovery protocols only exist in slower markets. Potential conflicts of interest between traders and platform operators are identified but seem unlikely to drive the existence of size-discovery trading protocols. Chapter 2: Is 24/7 Trading Better? with Alexander Ober Are daily market closures still needed? In a model of large traders who manage inventory risk, we show that even short market closures can significantly improve liquidity. Anticipating these closures, traders engage in aggressive trading, which concentrates and coordinates liquidity. A market structure with a daily closure improves allocative efficiency relative to a continuously open market, even though traders cannot trade during the closure itself. If traders have heterogeneous information about the asset value, trade is less aggressive on the whole, but closure still retains its substantial welfare benefits. Our findings suggest moving to a longer trading day could be beneficial, but moving to 24/7 trading would harm welfare. Chapter 3: Proxy Advice and Errors in Shareholder Voting with Alan Crane, Kevin Crotty, and David De Angelis How does proxy advice relate to voting mistakes? Structural estimates of latent proposal quality imply advisor ISS’s recommendations are wrong half the time for shareholder proposals. Vote outcomes, however, are correct the vast majority of the time because positive recommendations, which are particularly uninformative, are less influential. Our results support recent theory that proxy advice crowds out information collection by institutional investors and aims to create controversy. Recommendations are less informative than most mutual funds' votes. Vanguard’s votes are a considerably better benchmark for proposal quality than ISS recommendations. Overall, our analysis implies limiting ISS’s influence would improve voting outcomes.
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    Essays on Information Asymmetry, Strategic Trading, Liquidity, and Heterogeneity
    (2017-05-10) Mokak Teguia, Alberto; Back, Kerry
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