Дисертації з теми "Pricing Risk"

The thesis covers a wide range of topics from the credit risk modeling with the emphasis put on pricing of the claims subject to the default risk. Starting with a separate general contingent claim pricing framework the key topics are classified into three fundamental parts: firm-value models, reduced-form models, portfolio problems, with a possible finer sub-classification. Every part provides a theoretical discussion, proposal of self-developed methodologies and related applications that are designed so as to be close to the real-world problems. The text also reveals several new findings from various fields of credit risk modeling. In particular, it is shown (i) that the stock option market is a good source of credit information, (ii) how the reduced-form modeling framework can be extended to capture more complicated problems, (iii) that the double t copula together with a self-developed portfolio modeling framework outperforms the classical Gaussian copula approaches. Many other, partial findings are presented in the relevant chapters and some other results are also discussed in the Appendix.

This thesis focuses on the impact of counterparty-risk in CDS (Credit Default Swap) pricing. The exponential growth of the Credit Derivatives Market in the last decade demands an upsurge in the fair valuation of various credit derivatives such as the Credit Default Swap (CDS), the Collateralized Debt Obligation (CDO). Financial institutions suffered great losses from Credit Derivatives in the sub-prime mortgage market during the credit crunch period. Counterparty risk in CDS contracts has been intensively studied with a focus on losses for protection buyers due to joint defaults of counterparty and reference entity. Using a contagion framework introduced by Jarrow and Yu (2001)[48], we calculate the swap premium rate based on the change of measure technique, and further extend both the two-firm and three-firm model (with defaultable protection buyer) with continuous premium payment. The results show more explanatory power than the discrete case. We improve the continuous contagion model by relaxing the constant intensity rate assumption and found close results without loss of generality. Empirically this thesis studies the behaviour of the historical credit spread of 55 sample corporates/ financial institutions, a Cox–Ingersoll–Ross model is applied to calibrate spread parameters. A proxy for counterparty spread is introduced as the difference between the spread over benchmark rate and spread over swap rate for 5 year maturity CDS. We then investigate counterparty risk during the crisis and study the shape of term structure for the counterparty spread, where Rebonato’s framework is deployed to model the dynamics of the term structure using a regime-switching framework.

The aim of the analysis is to investigate if bond risk is priced. The idea to examine this topic rises by the interest to analyze in depth the movements of the bond financial market. The general framework reveals an increase of the use of fixed income securities and, consequently, an increase of the use of bonds among investors during last years. Credit institutions started to issue a large multiplicity of financial instruments; an example are perpetual bonds that were not frequently used in the past. Moreover, the increase of government bonds issued was drastic: during the period of the crisis, the European countries frequently asked money to the financial market in order to be able to guarantee their solvability. Consequently, the bond market became more interesting to investors than before and became more attractive and dynamic with respect to the past. The question that I asked to myself was if bonds returns changes affect the decisions of investors and their asset allocation. More in details, it arises the question “Is government bonds risk priced?”. In order to answer this question, the research unfolds in three main paragraphs. In the first part the characteristics of bonds are analyzed and the variables to take into account in order to understand the value of a bond are highlighted. The following features are presented: the relation between the bond and the interest rate, the difference between a long-term and a short-term bond, and some indicators, such as the duration and the Yield curve, that helps to interpret the real movements of a bond. The second part is built in order to investigate the consequences of the 2007 financial crisis and of the crisis of Sovereign Debt. In particular, the information that the Yield curve provides to investors are explained; for example, the analysis of the inversion of the yield curve is one of the main signals of an imminent crisis. Then, the causes and the consequences of the Crisis of Sovereign Debt are studied with the aim to highlight the different economic positions of different countries in the Eurozone. Finally, there is an insight about some strategies of asset allocations commonly used during crisis period that directly affected the bond market. In the Third paragraph, the empirical analysis is deployed. In order to understand if bond risk is priced, a cross sectional asset pricing test is implemented. The process to obtain the final result is composed by a two-step regression. The first regression consists of a time-series regression of the returns of some bond risk factors previously built on the return of some selected portfolios. The second regression is a cross-section regression between the ß obtained in the first regression and the mean of returns of the portfolio selected. The final results are the coefficient "gamma" that are analyzed in order to understand if bond risk is priced. The regressions are done over the period between 01/01/2002 and 01/06/2019. In addition, the same analysis is run also with a specific focus on the crisis period, from 01/01/2011 to 01/01/2016. In this part some statistical insights are presented in order to explain all the passages done to obtain the final results. To complete the analysis, the third part ends with a paragraph in which the weaknesses of the model selected and of the variables used are exposed. Finally, the analysis of results reveals that the bond risk seems to be priced in some circumstances; however, in order to better investigate the topic and to obtain more reliable results, it is probably necessary to develop a different method to run the cross section asset pricing test or, at least, to improve the quality of the method used enhancing the quality of the variables selected.

Standard asset pricing theories suggest that only systematic risk is priced. Empirical studies report a relationship between idiosyncratic volatility or risk (IVOL) and asset price. The most common explanation for this anomaly is that households under-diversify creating a Bad Model problem. This paper uses an Intermediary Asset Pricing Model (IAPM) as a way to control for under-diversification in evaluating the relationship between IVOL and asset price. We find that IVOL premia is lower in an IAPM. Our findings indicate that under-diversification can explain the anomaly partially.

This thesis attempts to address a number of issues that have been identified in the asset pricing literature as essential for shaping stock returns. These issues include the need to uncover the link between the macroeconomic variables and stock returns. In addition to this, is the need to decide, in light of the findings of the literature, whether to advise investors to include idiosyncratic risk and downside risk as risk factors in their asset pricing models. The results presented here suggest, consistent with other previous studies, that stock returns are a function of a number of previously identified risk factors along with the wider set of macroeconomic variables. These macroeconomic variables could be represented by a number of estimated macro factors. However, only one of these estimated factors emerged as significant in explaining the cross-section of stock returns. Nevertheless, it is important to note that the size (SMB) and value (HML) factors remain important factors in explaining the cross sectional returns on UK stocks, even with the existence of the other risk factors. This finding of inability of the examined macroeconomic variables to capture the pricing power of the SMB and the HML may cast doubt on the possibility of finding more macroeconomic factors that are able to account for these two factors in the cross section of returns in the UK. Interestingly, this conclusion seems to contradict previous authors' findings of potential links in the UK market. The results also support past studies that find that downside risk is an important risk factor and by allowing the downside risk premium to vary with business cycle conditions, downside risk might be a better measure of risk than market risk. Nevertheless, this thesis shows that although this finding is applicable in times of economic expansion, during recession, there is no conclusive relationship between . downside risk and stock returns. Furthermore, this thesis supports the studies which find that idiosyncratic risk is not significant in pricing stocks. However in contrast to other studies, it reveals this by showing that time-varying risk could be the reason behind the potentially illusive findings of idiosyncratic risk effect. This thesis confirms that, for London Stock Exchange investors, macroeconomic variables should never be overlooked when estimating stock returns and downside risk could be an influential risk factor.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, 2012.
Cataloged from PDF version of thesis.
Includes bibliographical references.
This thesis consists of three chapters in asset pricing. Chapter 1 considers an international asset pricing setting with traded and non-traded out puts. It shows that output fluctuations in nontraded industries are a central risk factor driving asset prices in all countries. This is because nontraded industries entail a growth risk that is mostly non-diversifiable, and constitute the largest component of gross domestic product (GDP) of a country. Supportive empirical evidences include; (i) the effect of an industry's growth volatility on the interest rate increases significantly with its non-tradability and (ii) carry trade strategies employing currency portfolios sorted on nontraded output growth volatility earns a sizable mean return and Sharpe ratio for US investors. Chapter 2 considers heterogeneous-agent setting in which agents differ in risk preference, time preference and/or expectations. It shows that, because of equilibrium risk sharing, the precautionary savings motive in the aggregate can vastly exceed that of even the most prudent actual agent in the economy. Consequently, a low real interest rate, resulting from large aggregate savings, can prevail with reasonable risk aversions for all agents. However, as savings rates become extremely sensitive to output fluctuation when savings motive is large, tie same mechanism that produces realistically low interest rates tends to make them unrealistically volatile. A powerful isomorphism allows differences in time preference and expectations to be swept away in the analysis, yielding an equivalent economy whose agents differ merely in risk aversion. Chapter 3 considers a novel tractable and structural pricing framework. It shows that any risk-neutral statistical distribution of state variables can be consistently tied to the economic contents of the underlying pricing model. It establishes this structural linkage by requiring that the economy's stochastic discount factor (SDF) be a proper but unspecified function of the state variables. Consequently, the structural content of the economy as characterized by the SDF can he determined from state variables dynamics through a simple linear differential equation. As a result, state variables' distribution in physical measure can also be recovered,
by Ngoc-Khanh Tran.
Ph.D.

Every day market operators exchange tens of thousand of stocks, creating an extremely rich information set to study price dynamics. Indeed, the pattern followed by asset returns have been a fundamental topic in finance literature for decades. Several studies provide evidence, Ball and Torous (1983), Jarrow and Rosenfeld (1984), and Jorion (1988) among others, that stock prices show sudden but infrequent movements of large magnitude, that are commonly known as jumps. Thus, it is a standard to design the dynamic of stock prices as a combination of a continuous diffusion component, plus discontinuous jumps. Because of their relevance in economics, finance, and decision sciences, the present thesis focuses on jumps in stock returns. Note, Chapters 1 and 2 represent two different papers, respectively entitled “Jump risk and pricing implications” and “The cross-sectional diffusion of jumps and the identifcation of collective sectorial movements”, each of them develops the main theme in a different direction. Chapter 1: construction of a jump risk factor. A central model in the description of market returns and risks is the Sharpe (1964), Lintner (1965), Mossin (1966) and Black (1972) CAPM. Subsequently, Fama and French (1993) and Carhart (1997) among others, proposed alternative asset-pricing models that add to the CAPM additional risk sources. Chapter 1 contributes to the existing literature by proposing a factor which captures investors fear of future jumps. Moreover, we add it to the Carhart (1997) model, thus putting forward a 5-factor model, and show that not only our factor is able to capture common variation in stock returns, but also that its use improves the model performance. We additionally compute the risk premiums for the five risk sources of the model and find that they are always positive and not signifcantly different from their factor means. In doing this we employ all CRSP stocks over the 1925-2014 sample period, which leads to 89 years of assets prices and more than 24,000 stocks. Chapter 2: cross-sectional jump diffusion. Even if there is evidence of price jumps in various markets, there is still little understanding about their cross-sectional diffusion. Chapter 2 investigates the presence of contemporaneous jumps among a large number of stocks, the multivariate jumps (or MJs), using a high-frequency dataset of considerable dimension. The database includes 1-minute prices for all 3,509 stocks belonging to the Russell 3000 index between January 2, 1998 and June 5, 2015 (4,344 days), data that we treat both as a whole as well by focusing on its 11 industries. Using the information about MJs, we then propose two indexes which summarize data on cross-sectional jump diffusion: the daily diffusion index (or DID), and the intraday diffusion index (or DII). Results confirm the usefulness of both DID and DII, which trends and residuals show more and higher spikes in correspondence of important economic moments, as in 2008 and 2010. Moreover, we observe a positive and signifcant association of diffusion indexes with the market, and highlight that limiting the analysis to systemic events could be misleading and incomplete, while we suggest a combined use of systemic and non-systemic MJs. We additionally establish a relationship between detected MJs and market-level news. Our results have important implication not only for asset allocation and hedging, but also in asset pricing. Regarding this last point, by including our diffusion indexes to the CAPM model, we prove that DID and DII capture common variation in stock returns that is missed by the market factor. This advocates to employ mulivariate jump information to build a factor capturing the cross-sectional jump risk, which could then be added, e.g., to the 5-factor model we propose in Chapter 1.
Ogni giorno gli operatori di mercato si scambiano decine di migliaia di titoli, creando in questo modo un ricco bacino d'informazione che può essere utilizzato per studiare la dinamica dei prezzi. Infatti, il processo seguito dai rendimenti dei titoli rappresenta un argomento fondamentale nella letteratura finanziaria da decenni. Diversi studi forniscono prove, tra gli altri Ball e Torous (1983), Jarrow e Rosenfeld (1984), e Jorion (1988), circa la presenza di improvvisi ed infrequenti movimenti di grande ampiezza nei prezzi delle azioni, conosciuti con il nome di jump (salti). Pertanto, è uno standard disegnare la dinamica dei prezzi delle azioni combinando una componente diffusiva continua e una componente discontinua rappresentata dai jump. A causa della loro rilevanza in economia, finanza e scienze delle decisioni, la presente tesi si concentra sui jump nei rendimenti azionari. Si noti che i capitoli 1 e 2 rappresentano due diversi paper, intitolati rispettivamente "Rischio legato ai jump e implicazioni sui prezzi" e "La diffusione nella cross-section dei jump e l'identificazione dei movimenti settoriali di tipo collettivo", ognuno dei quali sviluppa il tema principale in una diversa direzione. Capitolo 1: costruzione di un fattore di rischio legato ai jump. Un modello centrale nella descrizione dei rischi e rendimenti di mercato è quello proposto da Sharpe (1964), Lintner (1965), Mossin (1966) e Black (1972): il CAPM. Successivamente, Fama e French (1993) e Carhart (1997), tra gli altri, hanno proposto modelli di asset pricing alternativi, sviluppati espandono il CAPM con l’aggiunta di ulteriori fonti di rischio. Il primo capitolo contribuisce alla letteratura esistente proponendo un fattore in grado di catturare la paura degli investitori di futuri salti nei prezzi delle azioni, fattore che viene successivamente aggiunto al modello di Carhart (1997) creando, di conseguenza, un modello a cinque fattori. Tramite l’utilizzo di questo modello, dimostriamo che non solo il nostro fattore è in grado di catturare variazioni comuni nei rendimenti azionari, ma anche che il suo utilizzo migliora le prestazioni del modello. Infine calcoliamo i premi per il rischio associati alle cinque fonti di rischio del modello e mostriamo che essi sono sempre positivi e non significativamente diversi dai rendimenti medi dei fattori. Il database utilizzato per tutte le elaborazioni è costituito dalle informazioni reperibili tramite il CRSP per il periodo 1925-2014, scelta che ci permette di utilizzare una base di informazioni molto ampia: 89 anni di dati e più di 24.000 titoli. Capitolo 2: diffusione nella cross-section dei jump. Nonostante sia stata evidenziata la presenza di jump nei prezzi dei titoli per vari mercati, continua ad essere limitata la comprensione della loro diffusione nella cross-section. Il secondo capitolo indaga la presenza di jump che coinvolgono contemporaneamente un gran numero di azioni, i salti multivariati (o MJ), utilizzando un database di dati in alta frequenza di notevoli dimensioni. Il database include i prezzi a 1 minuto per tutti i 3.509 titoli appartenenti all'indice Russell 3000 tra il 2 Gennaio 1998 e il 5 Giugno 2015 (4.344 giorni), dati che trattiamo sia nel loro complesso sia concentrandoci sulle 11 industrie cui appartengono. Utilizzando le informazioni sui jump multivariati, proponiamo due indici informativi della diffusione in cross-section dei jump: un indice di diffusione giornaliero (o DID), e un indice di diffusione intraday (o DII). I risultati confermano l'utilità di entrambi gli indici, i cui trend e residui mostrano picchi più alti in corrispondenza di importanti fasi economiche, come ad esempio il 2008 e il 2010. Inoltre, osserviamo una correlazione positiva e significativa degli indici di diffusione con il mercato ed evidenziamo che un’analisi limitata agli eventi sistemici potrebbe essere fuorviante e incompleta. Diversamente si consiglia l’uso combinato di jump multivariati sistemici e non sistemici. Siamo inoltre in grado di stabilire una relazione tra jump multivariati e notizie a livello di mercato. I nostri risultati hanno importanti implicazioni non solo per le attività di asset allocation ed hedging, ma anche nel settore di asset pricing. Per quanto riguarda questo ultimo punto, includendo i nostri indici di diffusione in un modello CAPM, dimostriamo che, sia il DID che il DII, catturano variazioni comuni dei rendimenti azionari che sono invece tralasciate dal fattore di mercato. Questi risultati depongono a favore dell’utilizzo di informazioni sui jump multivariati per la costruzione di un fattore che catturi il rischio di jump nella cross-section, che potrebbe poi essere aggiunto, ad esempio, nel modello a 5 fattori che abbiamo proposto nel Capitolo 1.

Thesis (MSc)--Stellenbosch University, 2013.
ENGLISH ABSTRACT: In modern theory of finance, the so-called First and Second Fundamental Theorems of Asset Pricing play an important role in pricing options with no-arbitrage. These theorems gives a necessary and sufficient conditions for a market to have no-arbitrage and for a market to be complete. An early version of the First Fundamental Theorem of Asset Pricing was proven by Harrison and Kreps [30] in the case of a finite probability space. A more general version was proven by Harrison and Pliska [31] in the case of a finite probability space and discrete time. In the case of continuous time, Delbaen and Schachermayer [19] introduced a more general concept of no-arbitrage called "No-Free Lunch With Vanishing Risk" (NFLVR), and showed that for a locally-bounded semimartingale price process NFLVR is essentially equivalent to the existence of an equivalent local martingale measure. The goal of this thesis is to review the theory of arbitrage pricing and the extension of this theory to include liquidity risk. At the current time, liquidity risk is a key challenge faced by investors. Consequently there is a need to develop more realistic pricing models that include liquidity risk. We present an approach to liquidity risk by Çetin, Jarrow and Protter [10]. In to this approach the liquidity risk is embedded into the classical theory of arbitrage pricing by having investors act as price takers, and assuming the existence of a supply curve where prices depend on trade size. This framework assumes that the quantity impact on the price transacted is momentary. Using trading strategies that are both continuous and of finite variation allows one to avoid liquidity costs. Therefore, the First and Second Fundamental Theorems of Asset Pricing and the Black-Scholes model can be extended.
AFRIKAANSE OPSOMMING: In moderne finansiële teorie speel die sogenaamde Eerste en Tweede Fundamentele Stellings van Bateprysbepaling ’n belangrike rol in die prysbepaling van opsies in arbitrage-vrye markte. Hierdie stellings gee nodig en voldoende voorwaardes vir ’n mark om vry van arbitrage te wees, en om volledig te wees. ’n Vroeë weergawe van die Eerste Fundamentele Stelling was deur Harrison en Kreps [30] bewys in die geval van ’n eindige waarskynlikheidsruimte. ’n Meer algemene weergawe was daarna gepubliseer deur Harrison en Pliska [31] in die geval van ’n eindige waarskynlikheidsruimte en diskrete tyd. In die geval van kontinue tyd het Delbaen en Schachermayer [19] ’n meer algemene konsep van arbitragevryheid ingelei, naamlik “No–Free–Lunch–With–Vanishing–Risk" (NFLVR), en aangetoon dat vir lokaalbegrensde semimartingaalprysprosesse NFLVR min of meer ekwivalent is aan die bestaan van ’n lokaal martingaalmaat. Die doel van hierdie tesis is om ’n oorsig te gee van beide klassieke arbitrageprysteorie, en ’n uitbreiding daarvan wat likideit in ag neem. Hedendaags is likiditeitsrisiko ’n vooraanstaande uitdaging wat beleggers die hoof moet bied. Gevolglik is dit noodsaaklik om meer realistiese modelle van prysbepaling wat ook likiditeitsrisiko insluit te ontwikkel. Ons bespreek die benadering van Çetin, Jarrow en Protter [10], waar likiditeitsrisiko in die klassieke arbitrageprysteorie ingesluit word deur die bestaan van ’n aanbodkromme aan te neem, waar pryse afhanklik is van handelsgrootte. In hierdie raamwerk word aangeneem dat die impak op die transaksieprys slegs tydelik is. Deur gebruik te maak van handelingsstrategië wat beide kontinu en van eindige variasie is, is dit dan moontlik om likiditeitskoste te vermy. Die Eerste en Tweede Fundamentele Stellings van Bateprysbepaling en die Black–Scholes model kan dus uitgebrei word om likiditeitsrisiko in te sluit.

This thesis presents empirical research into the project risk pricing decision undertaken by Australian project leaders for domestic project finance. It addresses questions about the relative importance of various project finance risks on the project risk pricing decision; the impact of risk interactions; and the degree of self-insight possessed by Australian project leaders when making this decision. Five project financing risk most frequently cited in the literature, namely: operating, environmental, market, political/regulation, and sponsors, were selected. Sixteen hypothetical risk pricing cases were structured, which were completed by twenty-five project leaders working in Sydney. The collected data was analysed, and the results show that the five project financing risks had strong impact on the project risk pricing decision. Among them, market risk is the most influential factor, followed by operating, sponsors, and political/regulation risks, while environmental risk was the factor with least effect. Very little support, however, was provided for the hypothesis that risk interactions impact the project risk pricing decision. Among the ten two-level risk interactions tested, only the interaction between sponsors and political/regulation was found to be significant. In relations to the degree of self-insight, various comparisons between subjective and objective weights demonstrated that the project leaders, in general, were quite insightful about their project finance risk pricing decisions
Master of Commerce (Hons)

Thesis (Ph.D.) -- University of Western Sydney, 2004.
"A thesis submitted in fulfilment of requirements for the degree of Doctor of Philosophy in Economics and Finance" Bibliography : leaves 211-226.

This thesis is about interest rate modelling with applications in pricing and risk management of interest rate derivatives and portfolios. The first part of the thesis is developed within the random field framework suggested by Kennedy (1994). The framework is rich enough to be used for both pricing and risk management, but we believe its real value lies in the latter. Our main objective is to construct infinite-factor Gaussian field models that can fit the sample covariance matrices observed in the market. This task has not previously been addressed by the work on field methodology. We develop three methodologies for constructing strictly positive definite covariance functions, characterising infinite-factor Gaussian fields. We test all three constructions on the sample covariance and correlation matrices obtained from US and Japanese bond market data. The empirical and numerical tests suggest that these classes of field models present very satisfactory solutions to the posed problem. The models we develop make the random field methodology a much more practical tool. They allow calibration of field models to key market information, namely the covariation of the yields. The second part of the thesis deals with pricing kernel (potential) models ofthe term structure. These were first introduced by Constantinides (1992), but were subsequently overshadowed by the market models, which were developed by Miltersen et al. (1997), and Brace et al. (1997), and are very popular among the practitioners. Our objective is to construct a class of arbitrage-free term structure models that enjoy the same ease of calibration as the market models, but do not suffer from non-Markov evolution as is the case with the market models. We develop a class of models the within pricing kernel framework. I.e., we model the pricing kernel directly, and not a particular interest rate or a set of rates. The construction of the kernel is explicitly linked to the calibrating set of instruments. Thus, once the kernel is constructed it will price correctly the chosen set of instruments, and have a low-dimensional Markov structure. We test our model on yield, at-the-money cap, caplet implied volatility surface, and swaption data. We achieve a very good quality of fit.

We consider three topics. The topics are: Exact pricing of discretely-sampled variance derivatives (Chapter 2), No Good Deals - No Bad Models (Chapter 4) and Risk sharing in international economies and market incompleteness (Chapter 5). The unifying themes are: Incomplete markets, asset pricing and ambiguity aversion (or model uncertainty).

This thesis investigates three issues related to risk-neutral pricing. The first aspect investigated is the effect of discretization and truncation errors on risk-neutral moments, as defined in Bakshi, Kapadia and Madan (2003). It proposes exact solutions for the finite integrals in the volatility, cubic and quartic contracts and compares its accuracy approach with the interpolation-extrapolation approach. It yields more accurate estimates for risk-neutral skewness and kurtosis for those assets which exhibit the volatility smirk. By contrast, for those assets dominated by the forward skew, the exact approach outperforms the interpolation-extrapolation approach for skewness only. The second issue investigated is the skewness preference. It seeks to explain the positive skewness preference through heterogeneous beliefs and overconfidence. An overconfident group longs more skewness in the positively skewed portfolio, over-estimates the value of this portfolio, causes heterogeneous beliefs and yields a positive skewness preference. The final issue investigated is the relation between risk-neutral kurtosis and returns. The relation can be either positive or concave and cannot be explained bu heterogeneous beliefs and overconfidence. There are important causality effects between skewness and kurtosis and evidence is presented that the relation between kurtosis and returns may not be independent.

This thesis presents empirical research into the project risk pricing decision undertaken by Australian project leaders for domestic project finance. It addresses questions about the relative importance of various project finance risks on the project risk pricing decision; the impact of risk interactions; and the degree of self-insight possessed by Australian project leaders when making this decision. Five project financing risk most frequently cited in the literature, namely: operating, environmental, market, political/regulation, and sponsors, were selected. Sixteen hypothetical risk pricing cases were structured, which were completed by twenty-five project leaders working in Sydney. The collected data was analysed, and the results show that the five project financing risks had strong impact on the project risk pricing decision. Among them, market risk is the most influential factor, followed by operating, sponsors, and political/regulation risks, while environmental risk was the factor with least effect. Very little support, however, was provided for the hypothesis that risk interactions impact the project risk pricing decision. Among the ten two-level risk interactions tested, only the interaction between sponsors and political/regulation was found to be significant. In relations to the degree of self-insight, various comparisons between subjective and objective weights demonstrated that the project leaders, in general, were quite insightful about their project finance risk pricing decisions

Thesis (M.Comm. (Hons.)) -- University of Western Sydney, 2002.
"An empirical study of the project finance risk pricing decision made by Australian project leaders in terms of project finance risk weighting and degree of self-insight" Bibliography : leaves 98-105.

In sharp contrast to the basic risk-return assumption of theoretical finance, the empirical evidence shows that distressed firms underperform non-distressed firms (e.g. Dichev, 1998; Agarwal and Taffler, 2008b). Existing literature argues that a shareholder advantage effect (Garlappi and Yan, 2011), limits of arbitrage (Shleifer and Vishny, 1997) or gambling retail investor (Kumar, 2009) could drive the underperformance. Herein, I test these potential explanations and explore the drivers of distress risk. In order to do so, I require a clean measure of distress risk. Measures of distress risk have usually been accounting-based, market-based or hybrids using both information sources. I provide the first comprehensive study that employs a variety of performance tests on different prediction models. Cont/d.

Financial practitioners use models in order to price, hedge and measure risk. These models are reliant on assumptions and are prone to ”model risk”. Increased innovation in complex financial products has lead to increased risk exposure and has spurred research into understanding model risk and its underlying factors. This dissertation quantifies model risk inherent in Value-at-Risk (VaR) on a variety of portfolios comprised of European options written on the ALSI futures index across various maturities. The European options under consideration will be modelled using the Black-Scholes, Heston and Variance-Gamma models.

This dissertation explores issues related to asset pricing anomalies by focusing on options market. It consists of 3 chapters. In Chapter 1, we find that firms’ left-tail risk is a strong positive predictor of future bear spread returns, suggesting that the options market underreacts to firms’ left-tail risk and the downside protection provided by bear spreads is not adequately priced. We provide a behavioral explanation for this phenomenon. We find that the underreaction to firms’ left-tail risk is stronger when the underlying stocks experience larger recent losses, are closer to their 52-week lows, and have higher information uncertainty. The options market’s underreaction to firms’ left-tail risk mainly happens in high investor sentiment periods. In Chapter 2, we decompose and analyze the straddle returns around firms' earnings announcements. Previous study shows that delta-neutral straddles earn positive returns around earnings announcements, indicating an underpricing of earnings-induced risk. This study uses a volatility-jump decomposition to analyze the driving components of the delta-neutral straddle returns. We find that the volatility component consistently generates positive returns. The jump component’s return is positive over the pre-announcement period and becomes negative after announcement. Our findings suggest that options market anticipates earnings-induced jumps. The overall pattern of delta-neutral straddle’s cumulative return is mainly driven by its jump component but the positive cumulative return after announcement is mainly driven by its volatility component. In Chapter 3, we propose a gambling activity measure by jointly considering open interest and moneyness of out-of-the-money individual equity call options. The new measure, CallMoney, captures excessive optimism during the dot-com bubble, the oil price bubble, and the pre-GFC stock market bubble. CallMoney robustly and negatively predicts both out-of-the-money and at-the-money call option returns cross-sectionally. The option return predictability of CallMoney is stronger when stock price is further from its 52-week high, capital gains overhang is lower, and when information uncertainty of the underlying stock is higher. CallMoney also robustly and negatively predicts cross-sectional stock returns. Comparing to lottery-like-payoffs based (indirect) gambling measures, CallMoney performs better at predicting both option and stock returns.

Into the Thesis, the author will try to give the basis of risk management and asset pricing. Both of them are fundamental elements to understand how the financial models work; this topic is judged important in the perspective of successive studies in financial math: having clear the starting point makes things easier. From the title it is clear that modern and more complex models will be only touched upon. We decide to divide the dissertation in two different parts because, in our opinion, it is more evident that two different ways to approach at credit risk exist: on one side we try to quantify the risk deriving from giving credit, on the other we will establish a strategy that allows us to invest money with the aim to pay the other part of the agreement. Everything became more clear chapter by chapter. Financial institutions like banks are exposed at both of this type of risk. Chapters 1 and 5 are the center of this thesis: they represent the zero point from which the modern models were originated.

The main objective of this paper is to prove that liquidity costs do exist in option pricingtheory. To achieve this goal, a martingale approach to option pricing theory is usedand, from a model by Jarrow and Protter [JP], a sound theoretical model is derived toshow that liquidity risk exists. This model, derived and tested in this extended theory,allows for liquidity costs to arise. The expression liquidity cost is used in this paper tomeasure liquidity risk relative to the option price.

Electricity prices in competitive markets are extremely volatile with salient features such as mean-reversion and jumps and spikes. Modeling electricity spot prices is essential for asset and project valuation as well as risk management. I introduce the mean-reversion feature into a classical variance gamma model to model the electricity price dynamics as a mean-reverting variance gamma (MRVG) process. Derivative pricing formulae are derived through transform analysis and model parameters are estimated by the generalized method of moments and the Markov Chain Monte Carlo method. A real option approach is proposed to value a tolling contract incorporating operational characteristics of the generation asset and contractual constraints. Two simulation-based methods are proposed to solve the valuation problem. The effects of different electricity price assumptions on the valuation of tolling contracts are examined. Based on the valuation model, I also propose a heuristic scheme for hedging tolling contracts and demonstrate the validity of the hedging scheme through numerical examples. Autoregressive Conditional Heteroscedasticity (ARCH) and Generalized ARCH (GARCH) models are widely used to model price volatility in financial markets. Considering a GARCH model with heavy-tailed innovations for electricity price, I characterize the limiting distribution of a Value-at-Risk (VaR) estimator of the conditional electricity price distribution, which corresponds to the extremal quantile of the conditional distribution of the GARCH price process. I propose two methods, the normal approximation method and the data tilting method, for constructing confidence intervals for the conditional VaR estimator and assess their accuracies by simulation studies. The proposed approach is applied to electricity spot price data taken from the Pennsylvania-New Jersey-Maryland market to obtain confidence intervals of the empirically estimated Value-at-Risk of electricity prices. Several directions that deserve further investigation are pointed out for future research.

This thesis investigates the pricing of sovereign credit risk in the bond and credit default swap (CDS) market for Turkey. Using daily data, CDS premiums and Emerging Market Bond Index (EMBI) are examined over the period 1, January 2001- 20, June 2012. Firstly, the short-run and long-run determinants of CDS premiums are compared with those of EMBI, employing the Autoregressive Distributed Lag (ARDL) bounds testing approach. Then, the basis, the difference between CDS and EMBI spreads is analyzed seeking the factors which drive the two markets apart. Empirical results reveal that the CDS and bond market price credit events differently and hence, two spreads deviates in the short run. On the other hand, cointegration analysis shows that two prices move together in the long run, as theory predicts. Applying VECM analysis, the findings suggest that CDS spreads move ahead of the EMBI in the terms of price adjustment.

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.

This thesis is an empirical credit risk study, developing a multi-factor quadratic term structure model in discrete time and investigating credit risk. There are three main contributions. First, I examine the corporate credit default swap premia. I estimate parameters using an extended Kalman filter. The results show that the discrete quadratic term structure model is able to avoid some of the drawbacks associated with continuous models and affine term structure models. In addition, it was found that two state variables are enough to explain most of the variation in corporate credit spread. Second, I use an empirical study to analyze how market priced default component and nondefault component were incorporated into corporate bonds during 2005 - 2009. I jointly model the corporate bonds and credit default swaps using a three-factor quadratic term structure model and an extended Kalman filter. The evidence shows that the default component is not the major part of the corporate spread for most firms in my dataset, rather it is the time-varying nondefault component. Lastly, I study a large range of sovereign and bank credit default swap premia. I use a quadratic term structure model to define credit risk and decompose bank credit default swap premia into three factors: sovereign, common and bank-specific factors. The results indicate that banks in the dataset in all countries outside the United States (US) are very sensitive to common factors, and relatively sensitive to sovereign factors. The US banks, however, show more sensitivity to sovereign factors. Although sovereign and common factors explain a large portion of bank credit default swap premia, bank- specific factors played a major role, especially after the Lehman's failure. I also examine how the market priced the default component in both the dollar and sterling LIBOR (London Interbank Offered Rate). The evidence shows that the default component of LIBOR no longer reflects the panel banks' credit risks. Before September 2008, the default component of LIBOR was mainly driven by the coeffects of the sovereign and common factors. After that, both dollar and sterling LIBOR were reduced to an historic low. The sterling LIBOR are almost driven by sovereign factors while the dollar LIBOR reflects an even smaller credit risk than the sovereign risk. This evidence confirms market participants' thoughts that the dollar LIBOR should be higher than the observed rate.

In this thesis, efforts are devoted to the stochastic modeling, measurement and evaluation of credit risks, the development of mathematical and statistical tools to estimate and predict these risks, and methods for solving the significant computational problems arising in this context. The reduced-form intensity based credit risk models are studied. A new type of reduced-form intensity-based model is introduced, which can incorporate the impacts of both observable trigger events and economic environment on corporate defaults. The key idea of the model is to augment a Cox process with trigger events. In addition, this thesis focuses on the relationship between structural firm value model and reduced-form intensity based model. A continuous time structural asset value model for the asset value of two correlated firms with a two-dimensional Brownian motion is studied. With the incomplete information introduced, the information set available to the market participants includes the default time of each firm and the periodic asset value reports. The original structural model is first transformed into a reduced-form model. Then the conditional distribution of the default time as well as the asset value of each name are derived. The existence of the intensity processes of default times is proven and explicit form of intensity processes is given in this thesis. Discrete-time Markovian models in credit crisis are considered. Markovian models are proposed to capture the default correlation in a multi-sector economy. The main idea is to describe the infection (defaults) in various sectors by using an epidemic model. Green’s model, an epidemic model, is applied to characterize the infectious effect in each sector and dependence structures among various sectors are also proposed. The models are then applied to the computation of Crisis Value-at-Risk (CVaR) and Crisis Expected Shortfall (CES). The relationship between correlated defaults of different industrial sectors and business cycles as well as the impacts of business cycles on modeling and predicting correlated defaults is investigated using the Probabilistic Boolean Network (PBN). The idea is to model the credit default process by a PBN and the network structure can be inferred by using Markov chain theory and real-world data. A reduced-form model for economic and recorded default times is proposed and the probability distributions of these two default times are derived. The numerical study on the difference between these two shows that our proposed model can both capture the features and fit the empirical data. A simple and efficient method, based on the ordered default rate, is derived to compute the ordered default time distributions in both the homogeneous case and the two-group heterogeneous case under the interacting intensity default contagion model. Analytical expressions for the ordered default time distributions with recursive formulas for the coefficients are given, which makes the calculation fast and efficient in finding rates of basket CDSs.
published_or_final_version
Mathematics
Doctoral
Doctor of Philosophy

This thesis examines the relationship between foreign exchange (FX) volatility and excess returns from the currency market. We argue that FX volatility plays an important role in explaining the excess returns from the currency market so as in partially explaining the long stranding unsolved puzzles in FX market: the uncovered interest rate parity (UIP) puzzle and the purchasing power parity (PPP) puzzle. There are two empirical parts in this thesis. In the first part, we take the FX volatility risk as risk factors to price the cross sectional excess returns from the carry trade in three different settings, the unconditional ICAPM model, the conditional ICAPM model and a model separating the volatility risk into a persistent volatility risk factor and a less persistent volatility risk factor. For all three models, we find that the excess returns from the carry trade are negatively correlated with the FX volatility risk factors. The volatility risk factors are negatively priced and can explain about 90% cross sectional excess returns from the carry trade. We argue that the excess returns from the carry trade are compensations for bearing volatility risks, especially during high volatility risk period and regardless whether the volatility risks are persistent or not. In the second part, we investigate the puzzles in FX market under different FX volatility regimes. We find that the carry trade suffers from losses during high volatility period is because both the UIP and the PPP tends to reassert themselves under high volatility period, at least to some extent. Thus if we switch from the carry trade strategy to a PPP implied trading strategy during high volatility period, we could avoid the losses from the carry trade and have higher average excess returns. More importantly, we could make this “mixed” strategy tradable by using last period’s FX volatility state to forecast this period’s volatility state.

The intertemporal risk-return tradeoff is the cornerstone of modern empirical finance and has been the focus of much debate over the years. The reason for this is because extant literature cannot agree as to the very nature of this important relation. This is troublesome in terms of academic theory given that it challenges the notion that investors are risk-averse agents and is furthermore troublesome in practice given that market participants expect to be rewarded with higher expected returns in order to take on higher risks. The motivation for this thesis stems from the conflicting and inconclusive empirical evidence regarding the risk-return tradeoff. Through each of the chapters, it sheds new light on possible reasons as to why extant studies offer conflicting evidence and, given the enhancements and innovative approaches proposed here, it provides empirical evidence in support of a positive intertemporal risk-return tradeoff when examining several international stock markets. The research questions this thesis addresses are as follow. Firstly, is it possible that extant conflicting evidence is manifested in the use of historical realized returns to proxy for investors’ forward-looking expected returns? Secondly, can accounting for shifts in investment opportunities (i.e. intertemporal risk) better explain investors’ risk aversion and changes in the dynamic risk premium? Thirdly, is it possible that conflicting findings are the result of neglecting to account for the possibility that there exist heterogeneous investors in the stock market with divergent expectations? The empirical findings can be summarized as follows; firstly, there is a strong possibility that many existing studies cannot find a positive risk-return relation because they are relying on ex post historical realized returns as a proxy for investors’ forward-looking expected returns. Secondly, there is evidence in favor of the Merton (1973) notion that there exists intertemporal risk which impacts investors and that this type of risk should be considered. This has been also another reason why extant literature cannot agree on the nature of the intertemporal risk-return tradeoff. Finally, even after accounting for investor heterogeneity, the findings provide support for the Merton (1973) theoretical Intertemporal Capital Asset Pricing Model. Namely, in contrast to existing studies on the matter, there is evidence of fundamental traders over longer horizons and no evidence of feedback traders at such horizons. Although this sheds new light on some of the driving forces behind stock prices, the nature of investors’ degree of risk aversion seems to be best supported by the Merton (1973) theoretical Intertemporal Capital Asset Pricing Model.

The presented dissertation is focused on the applications of statistical methods and ap-proaches applied in the energy business. The need for the modeling of energy risks arose only recently when the energy business was opened to competition. Therefore, the prima-ry aim of the dissertation is to clarify the main principles of the energy business which are necessary for understanding both risk principles and motivation of the proposed models. I am largely focused on retail risks, i.e., the risks associated with delivery to end-consumers. In particular, I deal with energy contracts providing volume flexibility, recalled as swing options in the literature. Therefore, the second issue on which I am focusing is a group of demand-driven swing options whose more systematic analysis in the portfolio context has not been published so far. Examining the risk, I apply the deductive (probabil-istic) analysis which reveals interesting relations between correlations. The practical ap-plications also require inductive considerations resulting in the construction of statistical estimators relying on historical data. I propose an estimator of the volumetric correlation based on a classical theory whose bias is investigated via MC simulation. To analyze a par-ticular volume-price correlation, I introduced the notion of robust dependency. Applying bootstrap procedures, robust dependency can be used both for testing purposes and for sensitivity analysis of the sample correlation. There are many works available devoted to energy price models which are different from the price models applied on financial markets. Therefore, the third target of the dis-sertation is an empirical statistical analysis of both power and natural gas Czech spot pric-es which can serve as a basis for the development of price models adapted to the Czech market environment. Finally, the fourth aim is the evaluation of power contracts which is very specific. The outputs of the model are both a synthetic market price and a hedging strategy. The model is designed to provide flexibility in practical applications.

This thesis is built around the development and use of asset pricing factors and addresses pricing anomalies. It investigates the idiosyncratic volatility (IV) anomaly in China and applies the resale option theory first documented by Scheinkman and Xiong (2003). The research confirms that the IV anomaly in China and shown that the resale option theory can be quite helpful in deciphering the IV effect. Confirmation of the IV anomaly in China is a contribution to current literature; more importantly, the adoption of resale option theory to explain the IV effect in China is believed to be new. It also investigates the impact of being a state-owned enterprise (SOE), it shows that the SOE factor is useful in understanding of the asset pricing mechanism in China. The construction of an SOE factor and the concept of building a “true-to-label” risk factor by neutralizing the SOE effect are new contributions. This thesis investigates how risk-factor premia can be captured when investments are restricted to long-only positions (i.e., securities can only be purchased, not sold, short). Further it extends the asset pricing factor portfolio using a multifactor rotation technique, with the goals of isolating the cyclicality of the factor’s behavior and varying its exposure to different factors to improve the return, also with long-only constraints.

Thesis: S.M. in Management Research, Massachusetts Institute of Technology, Sloan School of Management, 2019
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 21-22).
I study the effects of US Macroeconomic surprises on the pricing of sovereign risk of sixty-six countries in the period 2002-2017 using daily CDS data. I also explore how a country spread's sensitivity to these shocks depends on a wide range of country characteristics. I discuss potential transmission mechanisms of sovereign distress to the real economy by studying the cross-sectional response of security prices (corporate CDS spreads and stock returns) to global shocks. I find that positive macroeconomic surprises in the US systematically reduce sovereign spreads consistent with the view that global investors price sovereign risk. However, I find that both the size and the sign of the effect depend on the business cycle in the US. During contractionary periods the positive effect of news is greatly reduced, often erased, and sometimes reversed. I also find evidence of asymmetric and non-linear effects. Moreover, I find that country characteristics such as its credit rating, its debt-to-GDP ratio, and measures of economic integration play a crucial role in determining the country's response to US shocks.
by Leonardo Ariel Elias.
S.M. in Management Research
S.M.inManagementResearch Massachusetts Institute of Technology, Sloan School of Management

In this dissertation, I consider a range of topics in bankruptcy, credit risk and asset pricing. The first chapter proposes a structural-equilibrium model to examine some economic implications arising from voluntary filing of Chapter 11. The results suggest that conflict of interests (between debtors and creditors) arising from the voluntary filing option causes countercyclical losses in firm value. The base calibration shows that these losses amount to approximately 5% of the ex-ante firm value and are twice those produced by a model without incorporating the business cycles. Furthermore, besides countercyclical liquidation costs as in Chen (2010) and Bhamra, Kuehn and Strebulaev (2010), countercyclical pre-liquidation distress costs and the conflict of interests help to generate reasonable credit spreads, levered equity premium and leverage ratios. The framework nests several important models and prices the firm's contingent claims in closed-form. The second chapter proposes a structural credit risk model with stochastic asset volatility for explaining the credit spread puzzle. The base calibration indicates that the model helps explain the credit spread puzzle with a reasonable volatility risk premium. The model fits well to the dynamics of CDS spreads and equity volatility in the data. The third chapter develops a consumption-based learning model to study the interactions among aggregate liquidity, asset prices and macroeconomic variables in the economy. The model generates reasonable risk-free rates, equity premium, real yield curve, and asset prices in equity and bond markets. The base calibration implies a long-term yield spread of around 185 basis points and a liquidity premium of around 55 basis points for an average firm in the economy. The calibrated yield spread and liquidity premium are consistent with the empirical estimates.

A decision maker who is facing a random demand for a perishable product, such as newspapers, decides how many units to order for a single selling period. This single-period inventory problem is often referred to as the \classic newsvendor problem", in which the selling price is ¯xed, the order must be made before the selling period, and the decision maker is risk-neutral. If the decision maker orders too many (overage), the inventory cost will be too high. If the decision maker orders too few (underage), the potential pro¯t will be lost. The optimal order quantity is a balance between the expected costs of overage and underage. This thesis investigates an extension of the classic newsvendor problem. In this extension the demand depends on the selling price, the decision maker may obtain an additional order at a higher price during the selling period, and the decision maker is risk-averse (not risk-neutral). The problem is to ¯nd optimal order quantity and selling price so that the expected utility of the risk-averse decision maker is maximized. This thesis examines the relationship between the order quantity and the sell- ing price for di®erent risk-averse decision makers in this extended newsvendor problem de¯ned above. The result shows that the relationships are consistent for some decision makers but not for others. For example, if the decision maker exhibits a constant absolute risk aversion (CARA), the optimal order quantity will decline when the selling price increases. If the decision maker has constant relative risk aversion (CRRA), the relationship is complex. This thesis ¯nds that if it is just known that the decision maker is risk-averse, the optimal order quantity placed is less than that made by a risk-neutral decision maker. Further more, the risk-averse decision maker's optimal order quantity falls when her/his risk aversion increases. However, the relationship between order quantity and selling price is still indeterminate in this case. This extension of the classic newsvendor problem provides a more realistic dy- namic setting than before, therefore providing an excellent framework for exam- ining how the inventory problem interacting with the marketing issue (selling price) will in°uence decision makers at the ¯rm level. It also provides an inte- grated framework for investigating di®erent variations of newsvendor problems. Thus, this thesis will motivate and encourage more applications of the newsven- dor problem which is a foundation of many supply chain management problems.

The main purpose of this work is to find a proper way to evaluate the catastrophe risk and to price CAT bonds. In other do so , we will do a presentation of catastrophe risk and instruments used to hedge this risk such as CAT bonds.Next we will do state of the differents pricing approaches and use available data to implement the calibrated model

This dissertation provides evidence on the risk factors that are priced in bank equities. Alternative empirical models with precedent in the nonfinancial asset pricing literature are tested, including the single-factor Capital Asset Pricing Model (CAPM), three-factor Fama-French model, and Intertemporal Capital Asset Pricing Model (ICAPM). The empirical results indicate that an unconditional two-factor Intertemporal Capital Asset Pricing Model (ICAPM) model, that includes the stock market excess return and shocks to the slope of the yield curve, is useful in explaining the cross-section of bank stock returns. I find no evidence, however, that firm specific factors, such as size and book-to-market ratios, are priced in bank stock returns. These results have a number of practical implications for event studies of banking firms, estimation of bank cost of capital and investment performance, as well as regulatory initiatives to utilize market discipline to evaluate bank risk under Basel II.

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics
ETFs are a relatively new investment product that allows investors to achieve the diversification of a mutual fund with the trading flexibility of a stock. This and other advantages have been drastically attracting investors over the last years; however, the price of this product is a topic that remains little explored. In this paper I introduce a panel data analysis of premiums/discounts of ETFs with similar characteristics. I find that some of these characteristics are significant explanations to ETF pricing inefficiencies.

In this dissertation, I study the performance of asset-pricing models in explaining the cross section of expected stock returns. The finance literature has uncovered several potential failings of the Capital Asset Pricing Model (CAPM). I investigate the ability of additional risk factors, which are not considered by the CAPM, to explain these problems. In particular, I examine intertemporal risk and long-run risk in the cross section of returns. In addition, I develop a firm-level test to refine and reassess the cross-sectional evidence against the CAPM. In the first chapter, I test the cross-sectional implications of the Intertemporal CAPM (ICAPM) of Merton (1973) and Campbell (1993, 1996) using a new firm-level approach. I find that the ICAPM performs well in explaining returns. Consistent with theoretical predictions, investors require a large positive premium for taking on market risk and zero-beta assets earn the risk-free rate. Moreover, investors accept lower returns on assets that hedge against adverse shifts in the investment opportunity set. The ICAPM explains more cross-sectional variation in average returns than either the CAPM or Fama-French (1993) model. I also investigate whether the SMB and HML factors of the Fama-French model proxy for intertemporal risk and find little evidence in favor of this conjecture. In the second chapter, we propose an intertemporal asset-pricing model that simultaneously resolves the puzzling negative relations between expected stock return and analysts' forecast dispersion, idiosyncratic volatility, and credit risk. All three effects emerge in a long-run risk economy accommodating a formal cross section of firms characterized by mean-reverting expected dividend growth. Higher cash flow duration firms exhibit higher exposure to economic growth shocks while they are less sensitive to firm-specific news. Such firms command higher risk premiums but exhibit lower measures of idiosyncratic risk. Empirical evidence broadly supports our model's predictions, as higher dispersion, idiosyncratic volatility, and credit risk firms display lower exposure to long-run risk along with higher firm-specific risk. Lastly, in the third chapter, we examine asset-pricing anomalies at the firm level. Portfolio-level tests linking CAPM alphas to a large number of firm characteristics suggest that the CAPM fails across multiple dimensions. There are, however, concerns that underlying firm-level associations may be distorted at the portfolio level. In this paper we use a hierarchical Bayes approach to model conditional firm-level alphas as a function of firm characteristics. Our empirical results indicate that much of the portfolio-based evidence against the CAPM is overstated. Anomalies are primarily confined to small stocks, few characteristics are robustly associated with CAPM alphas out of sample, and most firm characteristics do not contain unique information about abnormal returns.