Systematic and liquidity risk in sub-prime mortgage-backed assets

The mis-evaluation of risk in securitized financial products is central to understanding the global financial crisis. This paper characterizes the evolution of risk factors affecting collateralized debt obligations (CDOs) based on subprime mortgages. A key feature of subprime mortgage-backed indices is that they are distinct in their vintage of issuance. Using a latent factor framework that incorporates this vintage effect, we show the increasing importance of common factors on more senior tranches during the crisis. An innovation of the paper is that we use the unbalanced panel structure of the data to identify the vintage, credit, common and idiosyncratic effects from a state-space specification.

Monitoring liquidity risk at BPI GA

Field lab: Business project

Essays in higher moment asset pricing and liquidity risk

This thesis focuses on theoretical asset pricing models and their empirical applications. I aim to investigate the following noteworthy problems: i) if the relationship between asset prices and investors' propensities to gamble and to fear disaster is time varying, ii) if the conflicting evidence for the firm and market level skewness can be explained by downside risk, Hi) if costly learning drives liquidity risk. Moreover, empirical tests support the above assumptions and provide novel findings in asset pricing, investment decisions, and firms' funding liquidity. The first chapter considers a partial equilibrium model where investors have heterogeneous propensities to gamble and fear disaster. Skewness preference represents the desire to gamble, while kurtosis aversion represents fear of extreme returns. Using US data from 1988 to 2012, my model demonstrates that in bad times, risk aversion is higher, more people fear disaster, and fewer people gamble, in contrast to good times. This leads to a new empirical finding: gambling preference has a greater impact on asset prices during market downturns than during booms. The second chapter consists of two essays. The first essay introduces a foramula based on conditional CAPM for decomposing the market skewness. We find that the major market upward and downward movements can be well preadicted by the asymmetric comovement of betas, which is characterized by an indicator called "Systematic Downside Risk" (SDR). We find that SDR can efafectively forecast future stock market movements and we obtain out-of-sample R-squares (compared with a strategy using historical mean) of more than 2.27% with monthly data. The second essay reconciles a well-known empirical fact: aggregating positively skewed firm returns leads to negatively skewed market return. We reconcile this fact through firms' greater response to negative maraket news than positive market news. We also propose several market return predictors, such as downside idiosyncratic skewness. The third chapter studies the funding liquidity risk based on a general equialibrium model which features two agents: one entrepreneur and one external investor. Only the investor needs to acquire information to estimate the unobservable fundamentals driving the economic outputs. The novelty is that information acquisition is more costly in bad times than in good times, i.e. counter-cyclical information cost, as supported by previous empirical evidence. Later we show that liquidity risks are principally driven by costly learning. Résumé Cette thèse présente des modèles théoriques dévaluation des actifs et leurs applications empiriques. Mon objectif est d'étudier les problèmes suivants: la relation entre l'évaluation des actifs et les tendances des investisseurs à parier et à crainadre le désastre varie selon le temps ; les indications contraires pour l'entreprise et l'asymétrie des niveaux de marché peuvent être expliquées par les risques de perte en cas de baisse; l'apprentissage coûteux augmente le risque de liquidité. En outre, des tests empiriques confirment les suppositions ci-dessus et fournissent de nouvelles découvertes en ce qui concerne l'évaluation des actifs, les décisions relatives aux investissements et la liquidité de financement des entreprises. Le premier chapitre examine un modèle d'équilibre où les investisseurs ont des tendances hétérogènes à parier et à craindre le désastre. La préférence asymétrique représente le désir de parier, alors que le kurtosis d'aversion représente la crainte du désastre. En utilisant les données des Etats-Unis de 1988 à 2012, mon modèle démontre que dans les mauvaises périodes, l'aversion du risque est plus grande, plus de gens craignent le désastre et moins de gens parient, conatrairement aux bonnes périodes. Ceci mène à une nouvelle découverte empirique: la préférence relative au pari a un plus grand impact sur les évaluations des actifs durant les ralentissements de marché que durant les booms économiques. Exploitant uniquement cette relation générera un revenu excédentaire annuel de 7,74% qui n'est pas expliqué par les modèles factoriels populaires. Le second chapitre comprend deux essais. Le premier essai introduit une foramule base sur le CAPM conditionnel pour décomposer l'asymétrie du marché. Nous avons découvert que les mouvements de hausses et de baisses majeures du marché peuvent être prédits par les mouvements communs des bêtas. Un inadicateur appelé Systematic Downside Risk, SDR (risque de ralentissement systématique) est créé pour caractériser cette asymétrie dans les mouvements communs des bêtas. Nous avons découvert que le risque de ralentissement systématique peut prévoir les prochains mouvements des marchés boursiers de manière efficace, et nous obtenons des carrés R hors échantillon (comparés avec une stratégie utilisant des moyens historiques) de plus de 2,272% avec des données mensuelles. Un investisseur qui évalue le marché en utilisant le risque de ralentissement systématique aurait obtenu une forte hausse du ratio de 0,206. Le second essai fait cadrer un fait empirique bien connu dans l'asymétrie des niveaux de march et d'entreprise, le total des revenus des entreprises positiveament asymétriques conduit à un revenu de marché négativement asymétrique. Nous décomposons l'asymétrie des revenus du marché au niveau de l'entreprise et faisons cadrer ce fait par une plus grande réaction des entreprises aux nouvelles négatives du marché qu'aux nouvelles positives du marché. Cette décomposition révélé plusieurs variables de revenus de marché efficaces tels que l'asymétrie caractéristique pondérée par la volatilité ainsi que l'asymétrie caractéristique de ralentissement. Le troisième chapitre fournit une nouvelle base théorique pour les problèmes de liquidité qui varient selon le temps au sein d'un environnement de marché incomplet. Nous proposons un modèle d'équilibre général avec deux agents: un entrepreneur et un investisseur externe. Seul l'investisseur a besoin de connaitre le véritable état de l'entreprise, par conséquent, les informations de paiement coutent de l'argent. La nouveauté est que l'acquisition de l'information coute plus cher durant les mauvaises périodes que durant les bonnes périodes, comme cela a été confirmé par de précédentes expériences. Lorsque la récession comamence, l'apprentissage coûteux fait augmenter les primes de liquidité causant un problème d'évaporation de liquidité, comme cela a été aussi confirmé par de précédentes expériences.

Three essays on liquidity risk

Preface In this thesis we study several questions related to transaction data measured at an individual level. The questions are addressed in three essays that will constitute this thesis. In the first essay we use tick-by-tick data to estimate non-parametrically the jump process of 37 big stocks traded on the Paris Stock Exchange, and of the CAC 40 index. We separate the total daily returns in three components (trading continuous, trading jump, and overnight), and we characterize each one of them. We estimate at the individual and index levels the contribution of each return component to the total daily variability. For the index, the contribution of jumps is smaller and it is compensated by the larger contribution of overnight returns. We test formally that individual stocks jump more frequently than the index, and that they do not respond independently to the arrive of news. Finally, we find that daily jumps are larger when their arrival rates are larger. At the contemporaneous level there is a strong negative correlation between the jump frequency and the trading activity measures. The second essay study the general properties of the trade- and volume-duration processes for two stocks traded on the Paris Stock Exchange. These two stocks correspond to a very illiquid stock and to a relatively liquid stock. We estimate a class of autoregressive gamma process with conditional distribution from the family of non-central gamma (up to a scale factor). This process was introduced by Gouriéroux and Jasiak and it is known as Autoregressive gamma process. We also evaluate the ability of the process to fit the data. For this purpose we use the Diebold, Gunther and Tay (1998) test; and the capacity of the model to reproduce the moments of the observed data, and the empirical serial correlation and the partial serial correlation functions. We establish that the model describes correctly the trade duration process of illiquid stocks, but have problems to adjust correctly the trade duration process of liquid stocks which present long-memory characteristics. When the model is adjusted to volume duration, it successfully fit the data. In the third essay we study the economic relevance of optimal liquidation strategies by calibrating a recent and realistic microstructure model with data from the Paris Stock Exchange. We distinguish the case of parameters which are constant through the day from time-varying ones. An optimization problem incorporating this realistic microstructure model is presented and solved. Our model endogenizes the number of trades required before the position is liquidated. A comparative static exercise demonstrates the realism of our model. We find that a sell decision taken in the morning will be liquidated by the early afternoon. If price impacts increase over the day, the liquidation will take place more rapidly.

Liquidity Risk in the Finnish Stock Market

This study explores the pricing of liquidity risk and its effect on stock returns in the Finnish stock market. In addition to that, it investigates whether there is a trend in liquidity risk. Finally, it analyzes whether the two chosen liquidity measures provide different results. The data consists of all the common shares listed in the Finnish stock market during the period of 1/1997–7/2015. To examine whether liquidity risk affects stock returns in the Finnish stock market, this study utilizes a conditional version of liquidity-adjusted capital asset pricing model (LCAPM) by Acharya and Pedersen (2005). Two recently proposed illiquidity measures – PQS and AdjILLIQ – are used in the empirical estimation to see whether there are differences in the results between the measures. The time-varying conditional liquidity risks are estimated by using a multivariate DCC-GARCH model, while the pricing of the liquidity risk is conducted by applying fixed effect panel regression. The results imply that investors in the Finnish stock market are willing to pay a premium to hedge from wealth shocks and having liquid assets during the declined market liquidity. However, investors are not willing to pay a premium for stocks with higher returns during illiquid markets. The total annualized illiquidity premiums found in the Finnish stock market are 1.77% and 1.04%, based on the PQS and AdjILLIQ measures, respectively. The study also shows that liquidity risk does not exhibit decreasing trend, and investors should consider liquidity risk in their portfolio diversification in the Finnish stock market.

Measuring and managing liquidity risk in the Hungarian practice

The crisis that unfolded in 2007/2008 turned the attention of the financial world toward liquidity, the lack of which caused substantial losses. As a result, the need arose for the traditional financial models to be extended with liquidity. Our goal is to discover how Hungarian market players relate to liquidity. Our results are obtained through a series of semi-structured interviews, and are hoped to be a starting point for extending the existing models in an appropriate way. Our main results show that different investor groups can be identified along their approaches to liquidity, and they rarely use sophisticated models to measure and manage liquidity. We conclude that although market players would have access to complex liquidity measurement and management tools, there is a limited need for these, because the currently available models are unable to use complex liquidity information effectively.

Measuring and managing liquidity risk in the Hungarian practice

The crisis that unfolded in 2007/2008 turned the attention of the financial world toward liquidity, the lack of which caused substantial losses. As a result, the need arose for the traditional financial models to be extended with liquidity. Our goal is to discover how Hungarian market players relate to liquidity. Our results are obtained through a series of semistructured interviews, and are hoped to be a starting point for extending the existing models in an appropriate way. Our main results show that different investor groups can be identified along their approaches to liquidity, and they rarely use sophisticated models to measure and manage liquidity. We conclude that although market players would have access to complex liquidity measurement and management tools, there is a limited need for these, because the currently available models are unable to use complex liquidity information effectively.

Understanding Liquidity and Credit Risks in the Financial Crisis

This paper develops a structured dynamic factor model for the spreads between London Interbank Offered Rate (LIBOR) and overnight index swap (OIS) rates for a panel of banks. Our model involves latent factors which reflect liquidity and credit risk. Our empirical results show that surges in the short term LIBOR-OIS spreads during the 2007-2009 fi nancial crisis were largely driven by liquidity risk. However, credit risk played a more signifi cant role in the longer term (twelve-month) LIBOR-OIS spread. The liquidity risk factors are more volatile than the credit risk factor. Most of the familiar events in the financial crisis are linked more to movements in liquidity risk than credit risk.

Banks, liquidity crises and economic growth

How do the liquidity functions of banks affect investment and growth at different stages ofeconomic development? How do financial fragility and the costs of banking crises evolve with the level of wealth of countries? We analyze these issues using an overlapping generations growth model where agents, who experience idiosyncratic liquidity shocks, can invest in a liquid storage technology or in a partially illiquid Cobb Douglas technology. By pooling liquidity risk, banks play a growth enhancing role in reducing inefficient liquidation of long term projects, but they may face liquidity crises associated with severe output losses. We show that middle income economies may find optimal to be exposed to liquidity crises, while poor and rich economies have more incentives to develop a fully covered banking system. Therefore, middle income economies could experience banking crises in the process of their development and, as they get richer, they eventually converge to a financially safe long run steady state. Finally, the model replicates the empirical fact of higher costs of banking crises for middle income economies.

Liquidity and Asset Pricing in the French Stock Market

This thesis investigates pricing of liquidity in the French stock market. The study covers 835 ordinary shares traded in the period of 1996-2014 on Paris Euronext. The author utilizes the Liquidity-Adjusted Capital Asset Pricing Model (LCAPM) recently developed by Acharya and Pedersen (2005) to test whether liquidity level and risks significantly affect stock returns. Three different liquidity measures – Amihud, FHT, and PQS – are incorporated into the model to find any difference between the results they could provide. It appears that the findings largely depend on the liquidity measure used. In general the results exhibit more evidence for insignificant influence of liquidity level and risks as well as market risk on stock returns. The similar conclusion was reported earlier by Lee (2011) for several regions, including France. This finding of the thesis, however, is not consistent across all the liquidity measures. Nevertheless, the difference in the results between these measures provides new insight to the existing literature on this topic. The Amihud-based findings might indicate that market resiliency is not priced in the French stock market. At the same time the contradicting results from FHT and PQS provide some foundation for the hypothesis that one of two leftover liquidity dimensions – market depth or breadth – could significantly affect stock returns. Therefore, the thesis’ findings suggest a conjecture that different liquidity dimensions have different impacts on stock returns.

Pricing of Liquidity Risks in London Stock Exchange

This thesis aims to investigate pricing of liquidity risks in London Stock Exchange. Liquidity Adjusted Capital Asset Pricing Model i.e. LCAPM developed by Acharya and Pedersen (2005) is being applied to test the influence of various liquidity risks on stock returns in London Stock Exchange. The Liquidity Adjusted Capital Asset Pricing model provides a unified framework for the testing of liquidity risks. All the common stocks listed and delisted for the period of 2000 to 2014 are included in the data sample. The study has incorporated three different measures of liquidity – Percent Quoted Spread, Amihud (2002) and Turnover. The reason behind the application of three different liquidity measures is the multi-dimensional nature of liquidity. Firm fixed effects panel regression is applied for the estimation of LCAPM. However, the results are robust according to Fama-Macbeth regressions. The results of the study indicates that liquidity risks in the form of (i) level of liquidity, (ii) commonality in liquidity (iii) flight to liquidity, (iv) depressed wealth effect and market return as well as aggregate liquidity risk are priced at London Stock Exchange. However, the results are sensitive to the choice of liquidity measures.

Credit and liquidity components of corporate CDS spreads

This paper investigates the role of credit and liquidity factors in explaining corporate CDS price changes during normal and crisis periods. We find that liquidity risk is more important than firm-specific credit risk regardless of market conditions. Moreover, in the period prior to the recent “Great Recession” credit risk plays no role in explaining CDS price changes. The dominance of liquidity effects casts serious doubts on the relevance of CDS price changes as an indicator of default risk dynamics. Our results show how multiple liquidity factors including firm specific and aggregate liquidity proxies as well as an asymmetric information measure are critical determinants of CDS price variations. In particular, the impact of informed traders on the CDS price increases when markets are characterised by higher uncertainty, which supports concerns of insider trading during the crisis.

Liquidity effects and FFA returns in the international shipping derivatives market

The study examines the impact of liquidity risk on freight derivatives returns. The Amihud liquidity ratio and bid–ask spreads are utilized to assess the existence of liquidity risk in the freight derivatives market. Other macroeconomic variables are used to control for market risk. Results indicate that liquidity risk is priced and both liquidity measures have a significant role in determining freight derivatives returns. Consistent with expectations, both liquidity measures are found to have positive and significant effects on the returns of freight derivatives. The results have important implications for modeling freight derivatives, and consequently, for trading and risk management purposes.

Banks, liquidity crises and economic growth

How do the liquidity functions of banks affect investment and growth at different stages of economic development? How do financial fragility and the costs of banking crises evolve with the level of wealth of countries? We analyze these issues using an overlapping generations growth model where agents, who experience idiosyncratic liquidity shocks, can invest in a liquid storage technology or in a partially illiquid Cobb Douglas technology. By pooling liquidity risk, banks play a growth enhancing role in reducing inefficient liquidation of long term projects, but they may face liquidity crises associated with severe output losses. We show that middle income economies may find optimal to be exposed to liquidity crises, while poor and rich economies have more incentives to develop a fully covered banking system. Therefore, middle income economies could experience banking crises in the process of their development and, as they get richer, they eventually converge to a financially safe long run steady state. Finally, the model replicates the empirical fact of higher costs of banking crises for middle income economies.