Download or read book Essays on Jump Diffusion Models in Asset Pricing and on the Prediction of Aggregate Stock Returns written by Roman Frey and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Diese Dissertation besteht aus drei individuellen Aufsätzen, die jeweils eine in sich geschlossene Forschungsarbeit darstellt. Im ersten Aufsatz, "Out-of-Sample Performance of Jump-Diffusion Models for Equity Indices: What the Financial Crisis was Good For", analysieren wir die out-of-sample Performance von zeitstetigen affinen und nicht affinen stochastischen Volatilitätsmodellen. Die out-of-sample Modellperformance ist eine Kennzahl mit zentraler Bedeutung für Investoren. Sie spielt unter anderem im Risikomanagement, der Asset Allocation wie auch in der Bewertung von derivativen Instrumenten, eine entscheidende Rolle. In dieser empirischen Studie, die auf täglichen Renditen des Aktienindex S&P 500 basiert, testen wir insgesamt 24 verschiedene Modellspezifikationen. Unser Testansatz evaluiert die durch die Modelle vorhergesagten Verteilungsdichten. Der entscheidende Vorteil dieser Methodik liegt darin, dass wir jeweils die gesamte modellinduzierte Dichte berücksichtigen. Unsere empirischen Resultate zeigen, dass sich die, in der Literatur häufig diskutierte, gute in-sample Modellperformance in out-of-sample Anwendungen generell nicht bestätigen lässt. Mittels eines rollierenden Zeitfensters beobachten wir, dass Modellparameter, die während einer genügend volatilen Marktphase geschätzt wurden, deutlich bessere out-of-sample Resultate liefern. Vielversprechend ist demzufolge die out-of-sample Performance, wenn die Modellparameter auf der sich kürzlich abgespielten Finanzkrise geschätzt und zur Vorhersage von Verteilungsdichten verwendet werden. Generell beobachten wir, dass zum einen affine Modelle bessere Resultate erreichen als nicht affine. Zum anderen deuten unsere Ergebnisse darauf hin, dass Modelle mit Sprüngen in den Renditen sowie Varianzen besser performen als pure Diffusionsmodelle. Der zweite Aufsatz mit dem Titel "Pricing CO2 Futures Options - Empirical In- and Out-of-Sample Performance Analysis" analys.

Download or read book Essays on the Specification Testing for Dynamic Asset Pricing Models written by Jaeho Yun and published by . This book was released on 2009 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation consists of three essays on the subjects of specification testing on dynamic asset pricing models. In the first essay (with Yongmiao Hong), "A Simulation Test for Continuous-Time Models," we propose a simulation method to implement Hong and Li's (2005) transition density-based test for continuous-time models. The idea is to simulate a sequence of dynamic probability integral transforms, which is the key ingredient of Hong and Li's (2005) test. The proposed procedure is generally applicable whether or not the transition density of a continuous-time model has a closed form and is simple and computationally inexpensive. A Monte Carlo study shows that the proposed simulation test has very similar sizes and powers to the original Hong and Li's (2005) test. Furthermore, the performance of the simulation test is robust to the choice of the number of simulation iterations and the number of discretization steps between adjacent observations. In the second essay (with Yongmiao Hong), "A Specification Test for Stock Return Models," we propose a simulation-based specification testing method applicable to stochastic volatility models, based on Hong and Li (2005) and Johannes et al. (2008). We approximate a dynamic probability integral transform in Hong and Li' s (2005) density forecasting test, via the particle filters proposed by Johannes et al. (2008). With the proposed testing method, we conduct a comprehensive empirical study on some popular stock return models, such as the GARCH and stochastic volatility models, using the S&P 500 index returns. Our empirical analysis shows that all models are misspecified in terms of density forecast. Among models considered, however, the stochastic volatility models perform relatively well in both in- and out-of-sample. We also find that modeling the leverage effect provides a substantial improvement in the log stochastic volatility models. Our value-at-risk performance analysis results also support stochastic volatility models rather than GARCH models. In the third essay (with Yongmiao Hong), "Option Pricing and Density Forecast Performances of the Affine Jump Diffusion Models: the Role of Time-Varying Jump Risk Premia," we investigate out-of-sample option pricing and density forecast performances for the affine jump diffusion (AJD) models, using the S&P 500 stock index and the associated option contracts. In particular, we examine the role of time-varying jump risk premia in the AJD specifications. For comparison purposes, nonlinear asymmetric GARCH models are also considered. To evaluate density forecasting performances, we extend Hong and Li's (2005) specification testing method to be applicable to the famous AJD class of models, whether or not model-implied spot volatilities are available. For either case, we develop (i) the Fourier inversion of the closed-form conditional characteristic function and (ii) the Monte Carlo integration based on the particle filters proposed by Johannes et al. (2008). Our empirical analysis shows strong evidence in favor of time-varying jump risk premia in pricing cross-sectional options over time. However, for density forecasting performances, we could not find an AJD specification that successfully reconcile the dynamics implied by both time-series and options data.

Download or read book Essays in Empirical Asset Pricing written by Riccardo Sabbatucci and published by . This book was released on 2016 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: The focus of my dissertation is the study of stock market predictability. More precisely, I use econometric tools to understand, explain, and predict aggregate and cross-sectional patterns in stock prices. Predictability of aggregate stock market returns and dividend growth is a widely studied topic, of great interest to both academics and practitioners. It is related to theories of market efficiency and information diffusion, both rational and behavioral. It also allows us to determine which types of information generate the movements in stock prices that we observe. Understanding why stock prices move and what factors drive their variation is critical from theoretical and policy-making perspectives. Chapter 1 of my dissertation revisits one of the main findings of the predictability literature, namely that all variation in aggregate stock prices is explained by changes in aggregate risk through discount rates and none by news about firms' expected cash flows. I propose a more comprehensive measure of dividends that includes M&A cash flows and show that dividend growth is predictable and that cash flow news explains around 60% of the observed variation in prices, while the remaining 40% is accounted for by discount rate news. Chapter 2 shows that information about fundamentals of the aggregate economy derived from closely held firms help predict stock returns of public firms. A common feature of most stock market predictors is that they are constructed using financial data of public firms. I construct a new economy-wide dividend-price ratio that takes into account dividends and market capitalization of both listed (public) and non-listed (private) U.S. companies and show that it strongly predicts stock returns both in-sample and out-of-sample. I also find that changes in dividends of private firms lead those of public firms and that the economy-wide dividend-price ratio subsumes the standard dividend-price ratio in predictive regressions. Chapter 3, co-authored with Christopher A. Parsons and Sheridan Titman, explores geographic momentum: a positive lead-lag stock return relation between neighboring firms operating in different sectors. It shows that a portfolio of firms headquartered in the same area, but operating in different sectors, strongly forecasts individual stock returns up to one year ahead. The economic significance of a city-momentum trading strategy is of similar magnitude to that observed with industry momentum. However, while industry momentum is strongest among thinly traded, small firms, and/or those with scant analyst following, geographic momentum is unrelated to these proxies for information processing. We propose an explanation linking this to the structure of the investment analyst business, which is organized by sector, rather than by geographic region.

Download or read book Three Essays on Empirical Asset Pricing written by Gang Li and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation contains three essays on empirical asset pricing. In the first essay, I study the relationship between idiosyncratic volatility and expected returns of risky assets. I find that when the true asset pricing model cannot be identified, the idiosyncratic volatility obtained from a misspecified model contains information regarding the hedge portfolio in Merton's (1973) ICAPM. Empirically, I find that from 1815 to 2018, a combination of equal-weighted idiosyncratic volatility (EWIV) and value-weighted idiosyncratic volatility (VWIV) can strongly forecast stock market returns over short- and long-term horizons. Furthermore, EWIV and VWIV jointly can explain the cross-section of average stock returns. I show that the combination of EWIV and VWIV is a proxy for the conditional covariance risk in the ICAPM. The deduction also provides new insights concerning the tail risk measure proposed by Kelly and Jiang (2014). The second essay is a joint work with Bing Han. We propose a new and robust predictor of stock market returns and real economic activities based on information from equity options. We aggregate the difference in implied volatilities of at-the-money call and put options across stocks and find that the aggregate implied volatility spread (IVS) is significantly and positively related to future stock market returns. We attribute the predictive power to common informed trading in equity options instead of time-varying risk premium. The third essay, coauthored with Yoontae Jeon and Raymond Kan, studies the expected option return under an extended Black-Scholes model that incorporates the presence of stock return autocorrelation. We show that expected returns of both call and put options are increasing functions of return autocorrelation coefficient of the underlying stock. We find strong empirical evidence from the cross-section of average returns of equity options to support this prediction. Average returns of calls and puts as well as straddle returns all show monotonically increasing relationship with the degree of underlying stock's return autocorrelation coefficient. We also examine how the information on stock return autocorrelation helps investors to improve the out-of-sample performance of their portfolios.

Download or read book Essays on Multi asset Jump Diffusion Models written by Cheng-Yu Yang and published by . This book was released on 2016 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Essays on Asset Pricing Models written by Yan Li and published by . This book was released on 2009 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: My dissertation contains three chapters. Chapter one proposes a nonparametric method to evaluate the performance of a conditional factor model in explaining the cross section of stock returns. There are two tests: one is based on the individual pricing error of a conditional model and the other is based on the average pricing error. Empirical results show that for valueweighted portfolios, the conditional CAPM explains none of the asset-pricing anomalies, while the conditional Fama-French three-factor model is able to account for the size effect, and it also helps to explain the value effect and the momentum effect. From a statistical point of view, a conditional model always beats a conditional one because it is closer to the true data-generating process. Chapter two proposes a general equilibrium model to study the implications of prospect theory for individual trading, security prices and trading volume. Its main finding is that different components of prospect theory make different predictions. The concavity/convexity of the value function drives a disposition effect, which in turn leads to momentum in the cross-section of stock returns and a positive correlation between returns and volumes. On the other hand, loss aversion predicts exactly the opposite, namely a reversed disposition effect and reversal in the cross-section of stock returns, as well as a negative correlation between returns and volumes. In a calibrated economy, when prospect theory preference parameters are set at the values estimated by the previous studies, our model can generate price momentum of up to 7% on an annual basis. Chapter three studies the role of aggregate dividend volatility in asset prices. In the model, narrow-framing investors are loss averse over fluctuations in the value of their financial wealth. Persistent dividend volatility indicates persistent fluctuation in their financial wealth and makes stocks undesirable. It helps to explain the salient feature of the stock market including the high mean, excess volatility, and predictability of stock returns while maintaining a low and stable risk-free rate. Consistent with the data, stock returns have a low correlation with consumption growth, and Sharpe ratios are time-varying.

Download or read book Essays in Asset Pricing written by Michael Shane O'Doherty and published by . This book was released on 2011 with total page 159 pages. Available in PDF, EPUB and Kindle. Book excerpt: Using a variety of test portfolios, the optimal pool of models consistently outperforms the best individual model on both statistical and economic grounds.

Download or read book Essays on Volatility Risk Asset Returns and Consumption based Asset Pricing written by Young Il Kim and published by . This book was released on 2008 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: My dissertation addresses two main issues regarding asset returns: econometric modeling of asset returns in chapters 2 and 3 and puzzling features of the standard consumption-based asset pricing model (C-CAPM) in chapters 4 and 5. Chapter 2 develops a new theoretical derivation for the GARCH-skew-t model as a mixture distribution of normal and inverted-chi-square in order to represent the three important stylized facts of financial data: volatility clustering, skewness and thick-tails. The GARCH-skew-t is same as the GARCH-t model if the skewness parameter is shut-off. The GARCH-skew-t is applied to U.S. excess stock market returns, and the equity premium is computed based on the estimated model. It is shown that skewness and kurtosis can have significant effect on the equity premium and that with sufficiently negatively skewed distribution of the excess returns, a finite equity premium can be assured, contrary to the case of the Student t in which an infinite equity premium arises. Chapter 3 provides a new empirical guidance for modeling a skewed and thick-tailed error distribution along with GARCH effects based on the theoretical derivation for the GARCH-skew-t model and empirical findings on the Realized Volatility (RV) measure, constructed from the summation of higher frequency squared (demeaned) returns. Based on an 80-year sample of U.S. daily stock market returns, it is found that the distribution of monthly RV conditional on past returns is approximately the inverted-chi-square while monthly market returns, conditional on RV and past returns are normally distributed with RV in both mean and variance. These empirical findings serve as the building blocks underlying the GARCH-skew-t model. Thus, the findings provide a new empirical justification for the GARCH-skew-t modeling of equity returns. Moreover, the implied GARCH-skew-t model accurately represents the three important stylized facts for equity returns. Chapter 4 provides a possible solution to asset return puzzles such as high equity premium and low riskfree rate based on parameter uncertainty. It is shown that parameter uncertainty underlying the data generating process can lead to a negatively skewed and thick-tailed distribution that can explain most of the high equity premium and low riskfree rate even with the degree of risk aversion below 10 in the CRRA utility function. Chapter 5 investigates a possible link between stock market volatility and macroeconomic risk. This chapter studies why U.S. stock market volatility has not changed much during the "great moderation" era of the 1980s in contrast to the prediction made by the standard C-CAPM. A new model is developed such that aggregate consumption is decomposed into stock and non-stock source of income so that stock dividends are a small part of consumption. This new model predicts that the great moderation of macroeconomic risk must have originated from declining volatility of shocks to the relatively large non-stock factor of production while shocks to the relatively small stock assets have been persistently volatile during the moderation era. Furthermore, the model shows that the systematic risk of holding equity is positively associated with the stock share of total wealth.

Download or read book Transform Analysis and Asset Pricing for Affine Jump diffusions written by Darrell Duffie and published by . This book was released on 1999 with total page 56 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the setting of affine' jump-diffusion state processes, this paper provides an analytical treatment of a class of transforms, including various Laplace and Fourier transforms as special cases, that allow an analytical treatment of a range of valuation and econometric problems. Example applications include fixed-income pricing models, with a role for intensityy-based models of default, as well as a wide range of option-pricing applications. An illustrative example examines the implications of stochastic volatility and jumps for option valuation. This example highlights the impact on option 'smirks' of the joint distribution of jumps in volatility and jumps in the underlying asset price, through both amplitude as well as jump timing.

Download or read book Three Essays on Statistical Inference for Stock Return Predictions and Capital Asset Pricing Models written by Sungju Chun and published by . This book was released on 2012 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: In this dissertation, I focus on econometric issues arising in the fields of Financial Economics. In the first chapter, I study return predictability in international equity markets focusing on the effects of the bias and spurious regression problems for statistical inference. The slope coefficient estimator in predictive regressions for stock returns is biased in the presence of a lagged stochastic regressor. Spurious regression may also occur if the underlying expected return is highly persistent. I consider the effect of these biases in the presence of data mining for the predictive variables. I find that the two biases can reinforce or offset each other, depending on the parameters of the model. I present a new bias expression valid with an unobserved true expected returns and re-evaluate return predictability in international equity markets adjusting for data mining associated with both effects. The second chapter studies tests for structural changes in the trend function of a univariate time series that are robust to whether the noise component is stationary (I (0)) or contains an autoregressive unit root (I (1)). The tests of interest are the robust procedures recently proposed by Perron and Yabu (2009) and Harvey, Leybourne and Taylor (2009), both of which attain the same limit distribution under I (0) and I (1) errors. We compare their finite sample size and power under different data-generating processes for the noise components. We apply the tests to a large historical panel of real exchange rates with respect to the U.S. dollar for 19 countries and document simultaneous shifts in level and trend for many series. The third chapter studies the sampling interval effect in estimating capital asset pricing models. In past empirical studies, the beta coefficient estimates are documented to be sensitive to the sampling interval used for returns. We provide a theoretical framework to explain this sampling interval effect. We show that it can be attributable to the existence of transitory components in stock prices, and provide empirical evidence supporting its presence.

Download or read book Jump diffusion Models in Empirical Asset Pricing written by Adam Alexander Purzitsky and published by . This book was released on 2007 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt: Continuous-time Markov processes are widely used to model a variety of variables in financial economics. When estimating the parameters of a continuous-time Markov model the method of choice, from a classical perspective, is maximum likelihood. However, in most cases the transition density of the process is not known in closed form and so the likelihood is uncomputable in closed form. In the first chapter of this dissertation I construct a closed form series expansion for the unknown likelihood for jump-diffusion models. In particular I can treat jump-diffusions with very little restriction on the state dependency of the jump distribution and this potentially allows for the construction of flexible models for state variables such as nominal interest rates or volatilities that have a natural finite boundary. It is well known that GARCH models, when viewed as filters and not as the data generating process, can consistently filter the unobservable volatility state of a diffusion process with stochastic volatility. However although the use of GARCH models remains widespread, if one accepts that in most applications the underlying process is likely to exhibit jumps then it is not clear what, if anything, the GARCH model is estimating. The second chapter of this dissertation shows that GARCH models retain their consistency for the diffusive volatility when the data generating process has jumps, provided that the diffusive volatility follows a diffusion. In a situation where ultra high frequency data is unavailable a GARCH type model is likely to be appropriate for volatility estimation. The result of this paper implies that in the presence of jumps the GARCH type model is still applicable provided the jumps are included in the quasi-likelihood of the time series model. Finally in the third chapter I construct a measure of "jumpiness" that does not require intra-day data and is robust to a realistic amount of error in the filtering of the diffusive volatility. This allows me to design a test for the presence of jumps that is applicable in the absence of ultra-high frequency data. An application to USD swap rate data indicates that jumps are prevalent in the yield curve and that jumps account for roughly a quarter of the variation in 10 year USD swap rates.

Download or read book Asset Pricing Under Uncertainty about Shock Propagation written by and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: We analyze the equilibrium in a two-tree (sector) economy with two regimes. The output of each tree is driven by a jump-diffusion process, and a downward jump in one sector of the economy can (but need not) trigger a shift to a regime where the likelihood of future jumps is generally higher. Furthermore, the true regime is unobservable, so that the representative Epstein-Zin investor has to extract the probability of being in a certain regime from the data. These two channels help us to match the stylized facts of countercyclical and excessive return volatilities and correlations between sectors. Moreover, the model reproduces the predictability of stock returns in the data without generating consumption growth predictability. The uncertainty about the state also reduces the slope of the term structure of equity. We document that heterogeneity between the two sectors with respect to shock propagation risk can lead to highly persistent aggregate price-dividend ratios. Finally, the possibility of jumps in one sector triggering higher overall jump probabilities boosts jump risk premia while uncertainty about the regime is the reason for sizeable diffusive risk premia.

Download or read book Essays on Empirical Asset Pricing written by Chishen Wei and published by . This book was released on 2011 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation contains two essays that use empirical techniques to shed light on open questions in the asset pricing literature. In the first essay, I investigate whether foreign institutional investors affect stock liquidity in domestic equity markets. The evidence indicates that stocks with higher foreign institutional ownership subsequently experience higher liquidity. However, it is difficult to interpret the causal relation of this finding because institutional investors self-select into more liquid stocks. To solve this problem, I exploit a provision in the 2003 US dividend tax cut which extends tax-relief to dividends from US tax-treaty countries but not to dividends from non-treaty countries. This natural experiment suggests a causal link between foreign institutional investors and liquidity. Consistent with the predictions of theoretical models, I find that liquidity improves due to foreign institutional investors increasing information competition. In the second essay, I introduce a new measure of difference of opinion using mutual fund portfolio weights to test prominent competing theories of the effect of heterogeneous beliefs on asset prices. The over-valuation theory (Miller (1977)) proposes that in the presence of short-sale constraints stock prices reflects only the view of optimistic investors which implies lower subsequent returns. Alternatively, neo-classical asset pricing models (Williams (1977), Merton (1987)) suggest that differences of opinions indicate high levels of information uncertainty or risk which implies higher expected returns. My initial result finds no support for the over-valuation theory. Instead, the measure used in this study finds that high differences of opinion stocks weakly outperform low differences of opinion stocks by 2.42% annually which is more consistent with the information uncertainty explanation.

Download or read book Two Essays on Asset Pricing Anomalies written by Che Kuan Chen and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation investigates the impact of mutual funds in the cross-sectional stock returns and examines a conflict in the existing literature that characterizes momentum. In the first essay, I examine the explanatory power of aggregate mutual fund flows for the profitability of price-based (i.e., momentum and 52-week high) and non-price-based (i.e., earnings surprises, profitability, share issuance, accrual and asset growth) anomalies in the cross-section of returns. I find that the flow-based trading of mutual funds contributes to mispricing as measured by the profits to price-based anomalies, especially at times when market-wide funding costs are high. The effect also exists for non-price-based anomalies, but only through the dependence of their profits on momentum. My findings support the view of Lou (2012) and Vayanos and Woolley (2013) that mutual funds’ trading on flows creates feedback that strengthens price-based anomalies, as high-performing funds buy additional shares of high-performing stocks and poorly performing funds sell shares of poorly performing stocks. However, the explanatory power of aggregate mutual fund flows for price-based anomaly returns is only partly attenuated by fund-level variables designed to capture the feedback effect. The flow-induced trading by mutual funds appears to contribute to mispricing for reasons beyond the feedback effect. The second essay examines the extent to which momentum profits depend on the state of credit markets. The state of credit markets does affect momentum, but the results are not consistent with a credit channel effect on momentum. For non-financial firms, the momentum profits are stronger among portfolios formed under favorable credit conditions. For financial firms, credit conditions do not matter to the momentum profits. Price continuations in financial firms are related to whether the firms are performing poorly, but not whether that performance is attributable to credit conditions that are favorable or poor.

Download or read book Empirical Performance and Asset Pricing in Markov Jump Diffusion Models written by and published by . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 為了改進Black-Scholes模式的實證現象, 許多其他的模型被建議有leptokurtic特性以及波動度聚集的現象. 然而對於其他的模型分析的處理依然是一個問題. 在本論文中, 我們建議使用馬可夫跳躍擴散過程, 不僅能整合leptokurtic與波動度微笑特性, 而且能產生波動度聚集的與長記憶的現象. 然後, 我們應用Lucas的一般均衡架構計算選擇權價格, 提供均衡下當跳躍的大小服從一些特別的分配時則選擇權價格的解析解. 特別地, 考慮當跳躍的大小服從兩個情況, 破產與lognormal分配. 當馬可夫跳躍擴散模型的馬可夫鏈有兩個狀態時, 稱為轉換跳躍擴散模型, 當跳躍的大小服從lognormal分配我們得到選擇權公式. 使用轉換跳躍擴散模型選擇權公式, 我們給定一些參數下研究公式的數值極限分析以及敏感度分析.

Download or read book Asset Pricing Under Jump Diffusion written by Jin E. Zhang and published by . This book was released on 2006 with total page 33 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Three Essays on Empirical Asset Pricing written by Wenqing Wang and published by . This book was released on 2004 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: