Three Essays in Empirical Asset Pricing

The financial crisis of 2007-2008 led to extraordinary government intervention in firms and markets. The scope and depth of government action rivaled that of the Great Depression. Many traded markets experienced dramatic declines in liquidity leading to the existence of conditions normally assumed to be promptly removed via the actions of profit seeking arbitrageurs. These extreme events motivate the three essays in this work. The first essay seeks and fails to find evidence of investor behavior consistent with the broad 'Too Big To Fail' policies enacted during the crisis by government agents. Only in limited circumstances, where government guarantees such as deposit insurance or U.S. Treasury lending lines already existed, did investors impart a premium to the debt security prices of firms under stress. The second essay introduces the Inflation Indexed Swap Basis (IIS Basis) in examining the large differences between cash and derivative markets based upon future U.S. inflation as measured by the Consumer Price Index (CPI). It reports the consistent positive value of this measure as well as the very large positive values it reached in the fourth quarter of 2008 after Lehman Brothers went bankrupt. It concludes that the IIS Basis continues to exist due to limitations in market liquidity and hedging alternatives. The third essay explores the methodology of performing debt based event studies utilizing credit default swaps (CDS). It provides practical implementation advice to researchers to address limited source data and/or small target firm sample size.

Essays in asset price bubbles

This thesis studies the field of asset price bubbles. It is comprised of three independent chapters. Each of these chapters either directly or indirectly analyse the existence or implications of asset price bubbles. The type of bubbles assumed in each of these chapters is consistent with rational expectations. Thus, the kind of price bubbles investigated here are known as rational bubbles in the literature. The following describes the three chapters. Chapter 1: This chapter attempts to explain the recent US housing price bubble by developing a heterogeneous agent endowment economy asset pricing model with risky housing, endogenous collateral and defaults. Investment in housing is subject to an idiosyncratic risk and some mortgages are defaulted in equilibrium. We analytically derive the leverage or the endogenous loan to value ratio. This variable comes from a limited participation constraint in a one period mortgage contract with monitoring costs. Our results show that low values of housing investment risk produces a credit easing effect encouraging excess leverage and generates credit driven rational price bubbles in the housing good. Conversely, high values of housing investment risk produces a credit crunch characterized by tight borrowing constraints, low leverage and low house prices. Furthermore, the leverage ratio was found to be procyclical and the rate of defaults countercyclical consistent with empirical evidence. Chapter 2: It is widely believed that financial assets have considerable persistence and are susceptible to bubbles. However, identification of this persistence and potential bubbles is not straightforward. This chapter tests for price bubbles in the United States housing market accounting for long memory and structural breaks. The intuition is that the presence of long memory negates price bubbles while the presence of breaks could artificially induce bubble behaviour. Hence, we use procedures namely semi-parametric Whittle and parametric ARFIMA procedures that are consistent for a variety of residual biases to estimate the value of the long memory parameter, d, of the log rent-price ratio. We find that the semi-parametric estimation procedures robust to non-normality and heteroskedasticity errors found far more bubble regions than parametric ones. A structural break was identified in the mean and trend of all the series which when accounted for removed bubble behaviour in a number of regions. Importantly, the United States housing market showed evidence for rational bubbles at both the aggregate and regional levels. In the third and final chapter, we attempt to answer the following question: To what extend should individuals participate in the stock market and hold risky assets over their lifecycle? We answer this question by employing a lifecycle consumption-portfolio choice model with housing, labour income and time varying predictable returns where the agents are constrained in the level of their borrowing. We first analytically characterize and then numerically solve for the optimal asset allocation on the risky asset comparing the return predictability case with that of IID returns. We successfully resolve the puzzles and find equity holding and participation rates close to the data. We also find that return predictability substantially alter both the level of risky portfolio allocation and the rate of stock market participation. High factor (dividend-price ratio) realization and high persistence of factor process indicative of stock market bubbles raise the amount of wealth invested in risky assets and the level of stock market participation, respectively. Conversely, rare disasters were found to bring down these rates, the change being severe for investors in the later years of the life-cycle. Furthermore, investors following time varying returns (return predictability) hedged background risks significantly better than the IID ones.

STATISTICAL METHODS FOR ADVANCED ECONOMETRIC MODELS WITH APPLICATIONS TO VEHICLE HOLDING AND SPEED QUANTILES DISTRIBUTION

This dissertation proposes statistical methods to formulate, estimate and apply complex transportation models. Two main problems are part of the analyses conducted and presented in this dissertation. The first method solves an econometric problem and is concerned with the joint estimation of models that contain both discrete and continuous decision variables. The use of ordered models along with a regression is proposed and their effectiveness is evaluated with respect to unordered models. Procedure to calculate and optimize the log-likelihood functions of both discrete-continuous approaches are derived, and difficulties associated with the estimation of unordered models explained. Numerical approximation methods based on the Genz algortithm are implemented in order to solve the multidimensional integral associated with the unordered modeling structure. The problems deriving from the lack of smoothness of the probit model around the maximum of the log-likelihood function, which makes the optimization and the calculation of standard deviations very difficult, are carefully analyzed. A methodology to perform out-of-sample validation in the context of a joint model is proposed. Comprehensive numerical experiments have been conducted on both simulated and real data. In particular, the discrete-continuous models are estimated and applied to vehicle ownership and use models on data extracted from the 2009 National Household Travel Survey. The second part of this work offers a comprehensive statistical analysis of free-flow speed distribution; the method is applied to data collected on a sample of roads in Italy. A linear mixed model that includes speed quantiles in its predictors is estimated. Results show that there is no road effect in the analysis of free-flow speeds, which is particularly important for model transferability. A very general framework to predict random effects with few observations and incomplete access to model covariates is formulated and applied to predict the distribution of free-flow speed quantiles. The speed distribution of most road sections is successfully predicted; jack-knife estimates are calculated and used to explain why some sections are poorly predicted. Eventually, this work contributes to the literature in transportation modeling by proposing econometric model formulations for discrete-continuous variables, more efficient methods for the calculation of multivariate normal probabilities, and random effects models for free-flow speed estimation that takes into account the survey design. All methods are rigorously validated on both real and simulated data.

Pricing derivatives with stochastic volatility

This Ph.D. thesis contains 4 essays in mathematical finance with a focus on pricing Asian option (Chapter 4), pricing futures and futures option (Chapter 5 and Chapter 6) and time dependent volatility in futures option (Chapter 7). In Chapter 4, the applicability of the Albrecher et al.(2005)'s comonotonicity approach was investigated in the context of various benchmark models for equities and com- modities. Instead of classical Levy models as in Albrecher et al.(2005), the focus is the Heston stochastic volatility model, the constant elasticity of variance (CEV) model and the Schwartz (1997) two-factor model. It is shown that the method delivers rather tight upper bounds for the prices of Asian Options in these models and as a by-product delivers super-hedging strategies which can be easily implemented. In Chapter 5, two types of three-factor models were studied to give the value of com- modities futures contracts, which allow volatility to be stochastic. Both these two models have closed-form solutions for futures contracts price. However, it is shown that Model 2 is better than Model 1 theoretically and also performs very well empiri- cally. Moreover, Model 2 can easily be implemented in practice. In comparison to the Schwartz (1997) two-factor model, it is shown that Model 2 has its unique advantages; hence, it is also a good choice to price the value of commodity futures contracts. Fur- thermore, if these two models are used at the same time, a more accurate price for commodity futures contracts can be obtained in most situations. In Chapter 6, the applicability of the asymptotic approach developed in Fouque et al.(2000b) was investigated for pricing commodity futures options in a Schwartz (1997) multi-factor model, featuring both stochastic convenience yield and stochastic volatility. It is shown that the zero-order term in the expansion coincides with the Schwartz (1997) two-factor term, with averaged volatility, and an explicit expression for the first-order correction term is provided. With empirical data from the natural gas futures market, it is also demonstrated that a significantly better calibration can be achieved by using the correction term as compared to the standard Schwartz (1997) two-factor expression, at virtually no extra effort. In Chapter 7, a new pricing formula is derived for futures options in the Schwartz (1997) two-factor model with time dependent spot volatility. The pricing formula can also be used to find the result of the time dependent spot volatility with futures options prices in the market. Furthermore, the limitations of the method that is used to find the time dependent spot volatility will be explained, and it is also shown how to make sure of its accuracy.

Estimating dynamic models with aggregate shocks and an application to mortgage default in Colombia

We estimate a dynamic model of mortgage default for a cohort of Colombian debtors between 1997 and 2004. We use the estimated model to study the effects on default of a class of policies that affected the evolution of mortgage balances in Colombia during the 1990's. We propose a framework for estimating dynamic behavioral models accounting for the presence of unobserved state variables that are correlated across individuals and across time periods. We extend the standard literature on the structural estimation of dynamic models by incorporating an unobserved common correlated shock that affects all individuals' static payoffs and the dynamic continuation payoffs associated with different decisions. Given a standard parametric specification the dynamic problem, we show that the aggregate shocks are identified from the variation in the observed aggregate behavior. The shocks and their transition are separately identified, provided there is enough cross-sectionavl ariation of the observeds tates.

Liquidity, Governance and Adverse Selection in Asset Pricing

A plethora of recent literature on asset pricing provides plenty of empirical evidence on the importance of liquidity, governance and adverse selection of equity on pricing of assets together with more traditional factors such as market beta and the Fama-French factors. However, literature has usually stressed that these factors are priced individually. In this dissertation we argue that these factors may be related to each other, hence not only individual but also joint tests of their significance is called for. In the three related essays, we examine the liquidity premium in the context of the finer three-digit SIC industry classification, joint importance of liquidity and governance factors as well as governance and adverse selection. Recent studies by Core, Guay and Rusticus (2006) and Ben-Rephael, Kadan and Wohl (2010) find that governance and liquidity premiums are dwindling in the last few years. One reason could be that liquidity is very unevenly distributed across industries. This could affect the interpretation of prior liquidity studies. Thus, in the first chapter we analyze the relation of industry clustering and liquidity risk following a finer industry classification suggested by Johnson, Moorman and Sorescu (2009). In the second chapter, we examine the dwindling influence of the governance factor if taken simultaneously with liquidity. We argue that this happens since governance characteristics are potentially a proxy for information asymmetry that may be better captured by market liquidity of a company’s shares. Hence, we jointly examine both the factors, namely, governance and liquidity – in a series of standard asset pricing tests. Our results reconfirm the importance of governance and liquidity in explaining stock returns thus independently corroborating the findings of Amihud (2002) and Gompers, Ishii and Metrick (2003). Moreover, governance is not subsumed by liquidity. Lastly, we analyze the relation of governance and adverse selection, and again corroborate previous findings of a priced governance factor. Furthermore, we ascertain the importance of microstructure measures in asset pricing by employing Huang and Stoll’s (1997) method to extract an adverse selection variable and finding evidence for its explanatory power in four-factor regressions.

Newtonian perturbations on models with matter creation

Creation of cold dark matter (CCDM) can macroscopically be described by a negative pressure, and, therefore, the mechanism is capable to accelerate the Universe, without the need of an additional dark energy component. In this framework, we discuss the evolution of perturbations by considering a Neo-Newtonian approach where, unlike in the standard Newtonian cosmology, the fluid pressure is taken into account even in the homogeneous and isotropic background equations (Lima, Zanchin, and Brandenberger, MNRAS 291, L1, 1997). The evolution of the density contrast is calculated in the linear approximation and compared to the one predicted by the Lambda CDM model. The difference between the CCDM and Lambda CDM predictions at the perturbative level is quantified by using three different statistical methods, namely: a simple chi(2)-analysis in the relevant space parameter, a Bayesian statistical inference, and, finally, a Kolmogorov-Smirnov test. We find that under certain circumstances, the CCDM scenario analyzed here predicts an overall dynamics (including Hubble flow and matter fluctuation field) which fully recovers that of the traditional cosmic concordance model. Our basic conclusion is that such a reduction of the dark sector provides a viable alternative description to the accelerating Lambda CDM cosmology.

Log-modified Weibull regression models with censored data: Sensitivity and residual analysis

This paper proposes a regression model considering the modified Weibull distribution. This distribution can be used to model bathtub-shaped failure rate functions. Assuming censored data, we consider maximum likelihood and Jackknife estimators for the parameters of the model. We derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and we also present some ways to perform global influence. Besides, for different parameter settings, sample sizes and censoring percentages, various simulations are performed and the empirical distribution of the modified deviance residual is displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended for a martingale-type residual in log-modified Weibull regression models with censored data. Finally, we analyze a real data set under log-modified Weibull regression models. A diagnostic analysis and a model checking based on the modified deviance residual are performed to select appropriate models. (c) 2008 Elsevier B.V. All rights reserved.

The Modified Card Sorting Test: Test-retest stability and relationships with demographic variables in a healthy older adult sample

Objectives. To investigate the test-retest stability of a standardized version of Nelson's (1976) Modified Card Sorting Test (MCST) and its relationships with demographic variables in a sample of healthy older adults. Design. A standard card order and administration were devised for the MCST and administered to participants at an initial assessment, and again at a second session conducted a minimum of six months later in order to examine its test-retest stability. Participants were also administered the WAIS-R at initial assessment in order to provide a measure of psychometric intelligence. Methods. Thirty-six (24 female, 12 male) healthy older adults aged 52 to 77 years with mean education 12.42 years (SD = 3.53) completed the MCST on two occasions approximately 7.5 months (SD = 1.61) apart. Stability coefficients and test-retest differences were calculated for the range of scores. The effect of gender on MCST performance was examined. Correlations between MCST scores and age, education and WAIS-R IQs were also determined. Results. Stability coefficients ranged from .26 for the percent perseverative errors measure to .49 for the failure to maintain set measure. Several measures were significantly correlated with age, education and WAIS-R IQs, although no effect of gender on MCST performance was found. Conclusions. None of the stability coefficients reached the level required for clinical decision making. The results indicate that participants' age, education, and intelligence need to be considered when interpreting MCST performance. Normative studies of MCST performance as well as further studies with patients with executive dysfunction are needed.

General properties of cosmological models with an isotropic singularity

Much of the published work regarding the Isotropic Singularity is performed under the assumption that the matter source for the cosmological model is a barotropic perfect fluid, or even a perfect fluid with a gamma-law equation of state. There are, however, some general properties of cosmological models which admit an Isotropic Singularity, irrespective of the matter source. In particular, we show that the Isotropic Singularity is a point-like singularity and that vacuum space-times cannot admit an Isotropic Singularity. The relationships between the Isotropic Singularity, and the energy conditions, and the Hubble parameter is explored. A review of work by the authors, regarding the Isotropic Singularity, is presented.

Algebraic Bethe ansatz for integrable one-dimensional extended Hubbard models with open boundary conditions

Nine classes of integrable open boundary conditions, further extending the one-dimensional U-q (gl (212)) extended Hubbard model, have been constructed previously by means of the boundary Z(2)-graded quantum inverse scattering method. The boundary systems are now solved by using the algebraic Bethe ansatz method, and the Bethe ansatz equations are obtained for all nine cases.

Applying linear time-varying constraints to econometric models: With an application to demand systems

When linear equality constraints are invariant through time they can be incorporated into estimation by restricted least squares. If, however, the constraints are time-varying, this standard methodology cannot be applied. In this paper we show how to incorporate linear time-varying constraints into the estimation of econometric models. The method involves the augmentation of the observation equation of a state-space model prior to estimation by the Kalman filter. Numerical optimisation routines are used for the estimation. A simple example drawn from demand analysis is used to illustrate the method and its application.

Higgs pair production at the LHC in models with universal extra dimensions

In this Letter we study the process of gluon fusion into a pair of Higgs bosons in a model with one universal extra dimension. We find that the contributions from the extra top quark Kaluza-Klem excitations lead to a Higgs pair production cross section at the LHC that can be significantly altered compared to the Standard Model value for small values of the compactification scale. (C) 2007 Elsevier B.V. All rights reserved.