Mispricing, momentum, and market timing: Essays on stock market puzzles and capital structure decisions

Publikation: Qualifikations-/Studienabschlussarbeit › Dissertation

Autoren

  • Jan Krupski

Organisationseinheiten

Forschungs-netzwerk anzeigen

Details

OriginalspracheEnglisch
QualifikationDoctor rerum politicarum
Gradverleihende Hochschule
Betreut von
  • Maik Dierkes, Betreuer*in
Datum der Verleihung des Grades22 März 2023
ErscheinungsortHannover
PublikationsstatusVeröffentlicht - 2023

Abstract

Diese Dissertation umfasst einen Aufsatz zum Risikomanagement von Momentum-Strategien und drei Aufsätze über die Auswirkungen von Schiefepräferenzen auf Finanzmärkte. Kapitel 1 enthält eine ausführliche Zusammenfassung und ordnet die Forschungsprojekte in den Rahmen der verhaltensorientierten Finanztheorie ein. In Kapitel 2 (gemeinsam mit Maik Dierkes verfasst) untersuchen wir das Momentum von Aktienrenditen und entwickeln einen neuartigen Ansatz zur Risikosteuerung von Momentum-Strategien. Die Momentum- Anomalie ist eine der bekanntesten Finanzmarkt-Anomalien und erzielt hohe risikobereinigte Renditen. Diese sind jedoch mit einem erheblichen Verlustrisiko verbunden, da sich wiederholt mehrmonatige Phasen stark negativer Renditen ereignen. Momentum-Crashes treten insbesondere in sich erholenden Bärenmärkten auf, wenn das Momentum-Portfolio zeitgleich ein negatives Beta und eine hohe Momentum-Volatilität aufweist. Auf Grundlage von ex-ante Schätzungen dieser Risikomaße konstruieren wir einen Crash-Indikator, welcher Momentum-Crashes erfolgreich isoliert. Infolgedessen stellen wir eine implementierbare Handelsstrategie vor, die systematisches und momentumspezifisches Risiko kombiniert und die Sharpe-Ratio der ursprünglichen Momentum-Strategie mehr als verdoppelt. Darüber hinaus übertrifft sie bestehende Risikomanagement- Strategien im Zeitraum von 1928-2020 sowie in Subperioden und im internationalen Kontext. In Kapitel 3 (gemeinsam mit Maik Dierkes und Sebastian Schrön verfasst) untersuchen wir die Auswirkungen von zeitlich variierenden Schiefepräferenzen, im Folgenden als Lotterienachfrage bezeichnet, auf kurz- und langfristige Renditen nach Börsengängen (IPOs). Aufbauend auf der Identifikationsstrategie von Dierkes (2013) messen wir die Lotterienachfrage anhand optionsimplizierter Wahrscheinlichkeitsgewichtungsfunktionen und stellen einen signifikant positiven Einfluss auf die Renditen am ersten Handelstag fest. Dieses Resultat ist gleichbedeutend mit einer stärkeren Unterbewertung der Emittenten (bezüglich des Eröffnungspreises) sowie höheren Opportunitätskosten. Darüber hinaus werden IPO-Renditen insbesondere durch die Interaktion von marktweiter Lotterienachfrage und firmenspezifischer Lotteriecharakteristika getrieben. Abschließend stellen wir fest, dass Unternehmen, deren Börsengang in Zeiten starker Lotterienachfrage erfolgt, über einen Zeitraum von bis zu fünf Jahren nach dem Börsengang schlechtere Renditen aufweisen. In Kapitel 4 (gemeinsam mit Maik Dierkes, Sebastian Schrön und Philipp Sibbertsen verfasst) nutzen wir stattdessen einen simulationsbasierten Ansatz, um volatilitätsabhängige Wahrscheinlichkeitsgewichtungsfunktionen zu schätzen und deren Auswirkungen auf das Pricing Kernel Puzzle zu untersuchen. Zunächst elizitieren wir risikoneutrale und physische Dichtefunktionen auf Basis des stochastischen Volatilitätsund Sprungmodells von Pan (2002) und schätzen damit Wahrscheinlichkeitsgewichtungsfunktionen gemäß der in Kapitel 3 vorgestellten Identifikationsstrategie. Über alle Volatilitätsniveaus hinweg weisen diese eine ausgeprägte inverse S-Form auf, gleichbedeutend mit der Übegewichtung (Untergewichtung) kleiner (großer)Wahrscheinlichkeiten. Bemerkenswerterweise nimmt die Wahrscheinlichkeitsgewichtung mit der Volatilität beinahe monoton zu, was auf ausgeprägtere Schiefepräferenzen in volatilen Märkten hinweist. Darüber hinaus schätzen wir die probabilistische Risikoeinstellung, also den Anteil der Risikoaversion, der durch Wahrscheinlichkeitsgewichtung hervorgerufen wird, und untersuchen damit das Pricing Kernel Puzzle. Während die mit Pan (2002) geschätzten Pricing Kernel, übereinstimmend mit der Literatur, U-förmig sind, weisen die um die probabilistische Risikoeinstellung bereinigten Kernel-Funktionen einen monoton fallenden Verlauf auf und stehen somit im Einklang mit der ökonomischen Theorie. Infolgedessen ist die Risikoaversion über alle Vermögensniveaus hinweg positiv. Abschließend verwenden wir in Kapitel 5 (gemeinsam mit Maik Dierkes verfasst) die idiosynkratische Schiefe als einen Proxy für unternehmensspezifische Fehlbewertungen und untersuchen anhand dessen die Auswirkungen von Market Timing auf Kapitalstrukturentscheidungen. Im Einklang mit der Market-Timing-Theorie hat die idiosynkratische Schiefe einen signifikant positiven Effekt auf die Emission von Aktien, während der Einfluss auf die Emission von Schuldtiteln negativ und von geringerer Bedeutung ist. Zudem stellen wir fest, dass Aktienemissionen in der Regel durch den Abbau von Schulden begleitet werden. Entgegen der Market-Timing-Theorie sind diese Effekte jedoch nicht von Dauer und verschwinden nach etwa drei Jahren. In Übereinstimmung mit Alti (2006) unterstützen unsere Ergebnisse daher eine modifizierte Version der Trade-Off-Theorie, welche Market Timing als kurzfristigen Faktor einbezieht.

Zitieren

Mispricing, momentum, and market timing: Essays on stock market puzzles and capital structure decisions. / Krupski, Jan.
Hannover, 2023. 218 S.

Publikation: Qualifikations-/Studienabschlussarbeit › Dissertation

Krupski, J 2023, 'Mispricing, momentum, and market timing: Essays on stock market puzzles and capital structure decisions', Doctor rerum politicarum, Gottfried Wilhelm Leibniz Universität Hannover, Hannover. https://doi.org/10.15488/13374
Krupski, J. (2023). Mispricing, momentum, and market timing: Essays on stock market puzzles and capital structure decisions. [Dissertation, Gottfried Wilhelm Leibniz Universität Hannover]. https://doi.org/10.15488/13374
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title = "Mispricing, momentum, and market timing: Essays on stock market puzzles and capital structure decisions",
abstract = "This doctoral thesis comprises one essay on the risk management of momentum strategies and three essays on the implications of skewness preferences on financial markets. Chapter 1 provides an extensive summary and links all projects within the framework of behavioral finance. In Chapter 2 (co-authored with Maik Dierkes), we investigate momentum in stock returns and propose a novel approach to manage the downside risk of momentum strategies. Across markets, momentum is one of the most prominent anomalies and leads to high risk-adjusted returns. However, these returns come at the cost of substantial tail risk as there are short but persistent periods of highly negative returns. Momentum crashes occur in rebounding bear markets, when the momentum portfolio exhibits a negative beta and momentum volatility is high. Based on ex-ante estimates of these risk measures, we construct a crash indicator that effectively isolates momentum crashes. Subsequently, we propose an implementable trading strategy that combines both systematic and momentum-specific risk and more than doubles the Sharpe ratio of the original momentum strategy. Moreover, it outperforms existing risk management approaches over the 1928-2020 period, in sub-samples, and internationally. In Chapter 3 (co-authored with Maik Dierkes and Sebastian Schroen), we address the effects of time-varying skewness preference, referred to as lottery demand, on first-day returns and the long-term performance of initial public offerings (IPOs). Following the identification approach of Dierkes (2013), we measure lottery demand in terms of option-implied probability weighting functions and find a significantly positive impact on first-day returns, tantamount to higher IPO underpricing and more money left on the table. Furthermore, disentangling the effects of lottery demand and cross-sectional expected skewness reveals that IPO returns are particularly driven by the interaction of market-wide lottery demand and asset-specific lottery characteristics. In the long run, firms that went public during periods of high lottery demand perform poorly for up to five years after the IPO. In Chapter 4 (co-authored with Maik Dierkes, Sebastian Schroen, and Philipp Sibbertsen), we perform a simulation-based approach to estimate volatility-dependent probability weighting functions and investigate the impact of probability weighting on the pricing kernel puzzle. We first obtain risk neutral and physical densities from the Pan (2002) stochastic volatility and jumps model and then estimate probability weighting functions according to the identification strategy presented in Chapter 3. Across volatilities, we find pronounced inverse S-shapes. Hence, small (large) probabilities are overweighted (underweighted), and probability weighting almost monotonically increases in volatility, suggesting higher skewness preferences in volatile markets. Moreover, by estimating probabilistic risk attitudes, equivalent to the share of risk aversion related to probability weighting, we shed further light on the pricing kernel puzzle. While pricing kernels estimated from the Pan (2002) model display the typical U-shape documented in the literature, adjusted pricing kernels are monotonically decreasing and thus in line with economic theory. As a result, risk aversion functions are positive throughout wealth levels. Finally, in Chapter 5 (co-authored with Maik Dierkes), we employ idiosyncratic skewness as a proxy for firm-specific mispricing and investigate the impact of market timing on capital structure decisions. Consistent with the market timing theory, idiosyncratic skewness is significantly positively related to equity issues, while the impact on debt issues is negative and less important. Moreover, we find equity issues to be accompanied by debt retirement programs. Challenging the market timing theory, effects are not persistent and vanish after about three years. In line with Alti (2006), our results are therefore consistent with a modified version of the trade-off theory, including market timing as a short-term factor.",
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Download

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N2 - This doctoral thesis comprises one essay on the risk management of momentum strategies and three essays on the implications of skewness preferences on financial markets. Chapter 1 provides an extensive summary and links all projects within the framework of behavioral finance. In Chapter 2 (co-authored with Maik Dierkes), we investigate momentum in stock returns and propose a novel approach to manage the downside risk of momentum strategies. Across markets, momentum is one of the most prominent anomalies and leads to high risk-adjusted returns. However, these returns come at the cost of substantial tail risk as there are short but persistent periods of highly negative returns. Momentum crashes occur in rebounding bear markets, when the momentum portfolio exhibits a negative beta and momentum volatility is high. Based on ex-ante estimates of these risk measures, we construct a crash indicator that effectively isolates momentum crashes. Subsequently, we propose an implementable trading strategy that combines both systematic and momentum-specific risk and more than doubles the Sharpe ratio of the original momentum strategy. Moreover, it outperforms existing risk management approaches over the 1928-2020 period, in sub-samples, and internationally. In Chapter 3 (co-authored with Maik Dierkes and Sebastian Schroen), we address the effects of time-varying skewness preference, referred to as lottery demand, on first-day returns and the long-term performance of initial public offerings (IPOs). Following the identification approach of Dierkes (2013), we measure lottery demand in terms of option-implied probability weighting functions and find a significantly positive impact on first-day returns, tantamount to higher IPO underpricing and more money left on the table. Furthermore, disentangling the effects of lottery demand and cross-sectional expected skewness reveals that IPO returns are particularly driven by the interaction of market-wide lottery demand and asset-specific lottery characteristics. In the long run, firms that went public during periods of high lottery demand perform poorly for up to five years after the IPO. In Chapter 4 (co-authored with Maik Dierkes, Sebastian Schroen, and Philipp Sibbertsen), we perform a simulation-based approach to estimate volatility-dependent probability weighting functions and investigate the impact of probability weighting on the pricing kernel puzzle. We first obtain risk neutral and physical densities from the Pan (2002) stochastic volatility and jumps model and then estimate probability weighting functions according to the identification strategy presented in Chapter 3. Across volatilities, we find pronounced inverse S-shapes. Hence, small (large) probabilities are overweighted (underweighted), and probability weighting almost monotonically increases in volatility, suggesting higher skewness preferences in volatile markets. Moreover, by estimating probabilistic risk attitudes, equivalent to the share of risk aversion related to probability weighting, we shed further light on the pricing kernel puzzle. While pricing kernels estimated from the Pan (2002) model display the typical U-shape documented in the literature, adjusted pricing kernels are monotonically decreasing and thus in line with economic theory. As a result, risk aversion functions are positive throughout wealth levels. Finally, in Chapter 5 (co-authored with Maik Dierkes), we employ idiosyncratic skewness as a proxy for firm-specific mispricing and investigate the impact of market timing on capital structure decisions. Consistent with the market timing theory, idiosyncratic skewness is significantly positively related to equity issues, while the impact on debt issues is negative and less important. Moreover, we find equity issues to be accompanied by debt retirement programs. Challenging the market timing theory, effects are not persistent and vanish after about three years. In line with Alti (2006), our results are therefore consistent with a modified version of the trade-off theory, including market timing as a short-term factor.

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