SCAILLET Olivier

This paper proposes an original approach for backtesting systemic risk measures. This backtesting approach makes it possible to assess the systemic risk measure forecasts used to identify the financial institutions that contribute the most to the overall risk in the financial system. Our procedure is based on simple tests similar to those generally used to backtest the standard market risk measures such as value-at-risk or expected shortfall. We introduce a concept of violation associated with the marginal expected shortfall (MES), and we define unconditional coverage and independence tests for these violations. We can generalize these tests to any MES-based systemic risk measures such as the systemic expected shortfall (SES), the systemic risk measure (SRISK), or the delta conditional value-at-risk ([Formula: see text]CoVaR). We study their asymptotic properties in the presence of estimation risk and investigate their finite sample performance via Monte Carlo simulations. An empirical application to a panel of U.S. financial institutions is conducted to assess the validity of MES, SRISK, and [Formula: see text]CoVaR forecasts issued from a bivariate GARCH model with a dynamic conditional correlation structure. Our results show that this model provides valid forecasts for MES and SRISK when considering a medium-term horizon. Finally, we propose an early warning system indicator for future systemic crises deduced from these backtests. Our indicator quantifies how much is the measurement error issued by a systemic risk forecast at a given point in time which can serve for the early detection of global market reversals. This paper was accepted by Kay Giesecke, finance.

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The summary of this thesis and to evoke the various missions of the banking ALM as well as the financial risks which it takes in charge and recalled certain points of regulation, we propose to be interested in a subject rather characteristic of the questions raised by the trade of ALM, namely the management of the interest rate risk on the sight deposits within the framework of their remunerations. Let us recall that in a balance sheet, we distinguish between the Banking Book, a part devoted to the balance sheet of resources and uses linked to customers, i.e. the operational sphere. In fact, like many other departments of a bank, ALM has a return objective within certain risk limits. The stakes are relatively high for financial institutions. For example, retail banking has long been a stable and sustainable source of revenue for institutions, and the market attaches great importance to their ability to maintain this characteristic. On the other hand, items such as customer deposits constitute liquidity resources available at lower costs and this is not a point to be neglected in the particularly tense context since the 2008 crisis. Risk management is determined by the interest rate margins linked to a bank's sight deposits, the so-called Interest Rate Margin. This is defined as the difference between the market rate and the deposit rate to which a certain amount of deposits is multiplied. We assume that demand deposits are linked to both interest rates and commercial risk, which cannot be fully hedged in the financial markets. The dynamics of forward market rates follow a standard market model and take into account a certain risk premium associated with investing in long-term assets. Deposit rates in the US zone are determined by the M2 own rate, which is why the Fed is interested in the M2 own rate, which is calculated as the average rate of M2 resources weighted by the outstanding amounts. In the case of the Eurozone, this is referred to as the deposit rate or remuneration rate. The remuneration rates depend on the market rates and in particular the 3-month Euribor rates. We note in particular that when market rates are low, so are deposit rates. Deposit or remuneration rates are linked to market rates in a linear (or non-linear) fashion. We take the perspective of an asset-liability manager who focuses on the bank's net operating income in a given quarter under standard accounting rules, confronted with market incompleteness and dealing with interest rate derivatives, we distinguish between two types of hedging strategies: hedging in the quadratic sense, and hedging in the quantile and expected shortfall sense. For these two types of strategy, we consider two levels of information: one relating only to interest rate information and the other also including the current amount of demand deposits.

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This thesis examines financial decisions through the theory of American and Exotic options. First, we present a review of the literature on American-style options. The pricing of the standard American call option is revisited in order to provide the prerequisites. In the next step, a new type of option contract, called the Euro-American Strangle or Hybrid Strangle, has been introduced. Analytical formulas have been provided for their prices as well as their management parameters. A new method is proposed to compute the integrals that define the early exercise bounds. This method has been shown to be efficient, accurate and fast for pricing all types of Strangle and beyond. Next, we examined American-style Step options. We have shown that the properties of vanilla call options do not apply to Step options in certain situations. Valuation formulas and management parameters were determined. And finally, we considered the valuation of a firm holding simultaneously an option to abandon and an option to expand its activities under different market conditions (favorable or unfavorable). Critical decision thresholds were obtained. Analytical formulas for the value of the firm have been obtained. Simulations illustrate the behavior of these critical decision thresholds.

A large number of home loan defaults and the collapse of the housing market led to the failure of several investment banks in the United States. These factors also triggered the latest financial crisis. These events have given rise to a body of work that seeks to explain the factors determining the simultaneous failures of real estate lending. This thesis provides additional evidence of the importance of default dependence in the management of real estate loan portfolios. This thesis consists of three chapters identifying the key factors determining the dependence of home loan defaults and home prices. We show that a more accurate measure of credit risk is possible by taking into account the factors mentioned below. In chapter 1, we analyze the variation in the dependence of 13 regional price indices. We estimate a multivariate hidden Markov chain with two equidistant regimes. We model the transition probability using the growth of the interest rate and the loan-to-value ratio. Our results show that the average regional dependence of house prices varies over time. Moreover, this trend is related to changes in the interest rate and the loan-to-value ratio. Considering a subsample of metropolitan regions, we also show that a decrease in the loan-to-value ratio is associated with a higher probability of being in a high-dependence regime as described by a canonical tree copula. In Chapter 2, we use a composite likelihood copula and a mathematical function to analyze the pairwise default dependence of a set of securitized subprime mortgages from the Los Angeles area between 2000 and 2011. Our results show that default dependence is affected by the geographic distance between loans, the mean, and the dyadic differences in variables such as loan-to-value ratio, FICO credit scoring, and income at the borough level. In addition, we identify a contagion effect or a negative regional house price change index and a high default rate increases default dependence. Finally, our model gives a good estimate of the Value at Risk of the number of defaults in a block of securitized loans. In chapter 3, we analyze the efficiency of a portfolio of subprime mortgages. We estimate the spread and variance of returns using default probabilities obtained from a pairwise default dependence model. We analyze the 13 largest blocks of real estate loans, securitized between 2001 and 2005. Our results show that the diversification of loan blocks was not optimal. Moreover, we show that it is possible to further reduce the risk associated with loan pools by taking into account non-geographic risks.

This thesis presents several extensions to positive affine interest rate models. A first chapter introduces the concepts related to the models used in the following chapters. It details the definition of so-called affine processes, and the construction of asset price models obtained by non-arbitrage. Chapter 2 proposes a new estimation and filtering method for linear-quadratic state-space models. The next chapter applies this estimation method to the modeling of interbank spreads in the Eurozone, in order to decompose the fluctuations related to default and liquidity risk. Chapter 4 develops a new technique to create multivariate affine processes from their univariate counterparts, without imposing conditional independence between their components. The last chapter applies this method and derives a multivariate affine process in which some components can remain at zero for extended periods. Incorporated into an interest rate model, this process can efficiently account for zero-bottom rates.

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This thesis studies several aspects of the dynamics of asset returns. The first three chapters focus on price formation in the art market. The first chapter establishes that prices can temporarily, and partially predictably, deviate from fundamental value. This article was published in Economics Letters (Volume 122, Issue 3, pp. 432-434) and was written with Christophe Spaenjers and Luc Renneboog. Chapter 2 studies the speed of information transmission in aggregate art market prices. Chapter 3 analyzes the correlation between price and volume and supports evidence consistent with a bubble hypothesis. It was written with Luc Renneboog. Chapter 4 focuses on empirical modeling of the predictability of stock market indices in fifteen industrialized countries. It proposes to combine the information given by each country in order to improve the predictive power.

In this thesis, we examine the important contributions of dependence modeling by copula theory in the context of problems related to the management of financial portfolios and structured credit products.The first part of this thesis is devoted to the management of financial portfolios. The first part of this thesis is devoted to the management of financial portfolios. We first study the relationship that can be established between the level of diversification of the portfolio and the choice of the copula that best describes the dependency structure. The objective is to identify a characteristic in the portfolios allowing a simpler selection of the appropriate copula. In a second chapter, we propose to study the impact of a misspecification of the copula model on the estimates of conventional risk measures such as Value-at-Risk and Expected-Shortfall. The idea is to verify the usefulness of developing these estimates under the true copula model. In a third chapter, we study the impact of a misspecification of the copula model in the context of an optimal portfolio allocation problem. The main objective is to identify the sensitivity of investors, according to their degree of risk aversion (losses), for one or the other component of the copula model. We propose to establish a bridge between the teachings of behavioral finance theories and the modeling of dependence by the copula theory.The second part of the thesis deals with structured credit products. We study, in a first chapter, the contribution of an actuarial model, using copula functions in the modeling of the dependence structure between default times, in the context of the estimation process of risk measures. Finally, in a last chapter we revisit the notion of the "Diversity Score", developed by the rating agency Moody's in order to assign the quality of structured credit products in terms of diversification. We discuss the analogy of this measure with that of the copula approach, and we demonstrate its adequacy with some families of copula functions.

The first chapter is a presentation of the main concepts and results concerning corporate finance in the light of some recent developments in labor economics.The second chapter aims at establishing the optimality properties concerning the investment and hiring of a firm within the framework of linear utility maximization.The third chapter deals with the (possible) problem of disinvestment and layoffs. In particular, we study the optimal decision problems of the manager facing either a market growth or a fall in demand for his product.The fourth chapter reconsiders the question by taking into account specifically an upper bound on the quantity that can be really sold.The fifth chapter considers the possible phenomena of mean reversion of the unit price of the product sold.The sixth and last chapter reconsiders the optimal decision problems for different possible forms of debt.

Financial institutions are confronted with various risks in the performance of their functions, including credit risk, market risk and operational risk. The instability of these factors weakens these institutions and makes them vulnerable to financial risks which, for their survival, they must be able to identify, analyze, quantify and manage appropriately. Among these risks, the one linked to credit is the most feared by banks, given its capacity to generate a systemic crisis. The probability of an individual moving from a non-risky state to a risky state is thus at the heart of many economic questions. In credit institutions, this issue is expressed in terms of the probability that a borrower will move from a "good risk" state to a "bad risk" state. For this quantification, credit institutions are increasingly using credit scoring models. This thesis focuses on current credit-scoring techniques adapted to the needs of a credit institution, the CFCAL-bank, specialized in mortgage-backed loans. In particular, we present two non-parametric models (SVM and GAM) whose performance in terms of classification is compared with that of the logit model traditionally used in banks. Our results show that SVMs perform better if we are only interested in the global predictive capacity. However, they exhibit lower sensitivities than the logit and GAM models. In other words, they predict defaulting borrowers less well. In the current state of our research, we advocate GAM models, which admittedly have lower overall predictive ability than SVMs, but give more balanced sensitivities, specificities, and predictive performance. By highlighting targeted credit scoring models, applying them to real mortgage data, and comparing them through their classification performance, this thesis makes an empirical contribution to the research on credit scoring models.

This thesis contributes to academic research in real estate by providing a risk assessment for commercial real estate investment management. Real estate investment has many specificities such as location, liquidity, investment size or obsolescence and requires active management. These specificities make traditional risk measurement approaches difficult to apply. This research work is presented in the form of four academic papers dealing with portfolio management and risk in real estate. This work is built on the existing academic literature and is based on previous publications. First, it analyzes tenant exit options contained in commercial leases in continental Europe and studies their impacts on portfolio value, management and risk. In the first paper, we consider tenant exit options included in commercial leases in continental Europe to better assess the value and risk of a real estate portfolio. This is achieved through the simultaneous use of Monte-Carlo simulations and option theory. The second article deals with the optimal holding period of a real estate portfolio when options contained in the leases are taken into account. The third article focuses on Value at Risk and proposes a model that takes into account the non-normality of real estate returns. This is obtained by combining the use of the Cornish-Fisher development and rearrangement procedures. Finally, in a last article, we present a model specially developed for the calculation of Value at Risk in real estate. This model has the particularity of taking into account the specificities of real estate and the parameters that have a greater influence on the value of assets.

This thesis investigates the theoretical and empirical consequences of considering socially responsible indicators in traditional portfolio selection. The first chapter studies the significance of the loss of mean-variance efficiency of a sovereign bond portfolio when a constraint is introduced on the average socially responsible rating of governments. Using a sample of developed government bonds over the period 1995-2008, we show that it is possible to significantly increase the average socially responsible rating without losing significantly in terms of diversification. The second chapter proposes a theoretical analysis of the effect on the efficient frontier of a constraint on the socially responsible rating of the portfolio. We highlight the different scenarios that can occur depending on the correlation between expected returns and socially responsible ratings and the investor's risk aversion. Finally, since the question of the efficiency of portfolios invested according to socially responsible criteria is debated in the financial literature, a last chapter proposes a new mean-variance efficiency test in the realistic case where no risk-free asset is available.

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In this thesis we have been interested in models to characterize long memory in terms of fractional integration and threshold effects. These models allow us to decide whether the observed persistence is best represented by a fractional integration or nonlinearity property. Thus, we were interested in TIMA models with contemporaneous asymmetry that generalize TIMA models with delayed asymmetry. The introduction of a contemporaneous asymmetry implies that the shocks are no longer characterized by a noise according to the usual representation. This type of asymmetry excludes an estimation of the model parameters by standard methods. We have therefore developed an indirect simulated inference method that we have implemented after having studied its performance from simulations. We have also studied ARFIMA threshold models which allow to model simultaneously threshold effects in the fractional integration parameter and the autoregressive parameters. The threshold effect is introduced separately and then jointly in the long memory parameter and in the autoregressive parameters. We have proposed a procedure to test both types of threshold effects simultaneously by showing how tests conducted separately to analyze each of the two types of threshold effect could lead to spurious results. The application of the methodology developed in our thesis shows that the joint test is decisive to validate the presence of threshold effects when the individual tests do not allow to conclude.

This work consists of five chapters and examines two aspects of term structure modeling: the valuation of interest rate derivative assets and the inference of models typically used in this valuation. The first chapter consists of an introduction to continuous-time models and their arbitrage valuation. The second chapter focuses on the valuation of options in a particular affine model. The estimation of diffusion processes describing the dynamics of state variables is analyzed in chapter iii and consists in a presentation of a method based on simulations. In chapter iv, non-nested hypothesis tests using simulation-based procedures and a notion of indirect embedding are described. Two applications are proposed in chapter v. The first is the presentation of a method for estimating bond prices from term structure models. The second application concerns the estimation and comparison of several models usually used for the instantaneous short rate.