BRUNEAU Catherine

The research in this thesis focuses on two alternative markets: cryptocurrencies and oil products. Most alternative markets are far from efficient, and this generates many modeling challenges. Models based on Gaussian distributions are still the most popular choice for quantitative financial analysts and are implemented even in markets that are far from efficient. A robust modeling framework for alternative assets must start with a non-Gaussian distribution. Therefore, throughout this thesis, the general theme of all simulations and estimations is the use of generalized hyperbolic distributions. This approach has a dual justification. On the one hand, it is essential to develop a sharp quantitative framework beyond the Gaussian universe, testing the performance of the new model in real situations. On the other hand, the markets that are the subject of this research (oil products and cryptocurrencies) have neither the fundamentals nor the empirical behavior that could justify traditional modeling.

No summary available.

In this paper we propose a flexible tool to estimate the risk sensitivity of financial assets when exposed to any sort of risks, including extreme ones, from the financial markets and the real economy. This tool works with observations and a priori views. Our contribution is threefold. First, we combine copulas and factorial structures which allow us to capture the whole dependencies between the returns of a large number of assets of multiple classes. We build what we call a Cvine Risk Factors (CVRF) model, which can disentangle financial and explicitely economic like activity, inflation, emerging, etc, and more generally speaking real sphere related risks. Second, this model provides the way to extend the well known linear multibeta relationship in a non-linear version and to assess the exposures of any asset to several factorial risk directions in the cases where the risks are extreme. The exposure measures are relevant Cross Conditional Values at Risk (Cross-CVaR). Third, as an application of the methodology, we solve an optimization program to find portfolios that are the most diversified in capital while being immunized to extreme shocks to a given risk factorial direction. Varying the immunization constraint, we recover the portfolio strategies which are the most widely used today. For example, adopting the ERC (Equal Risk Contribution) rule insures optimal capital based diversification and immunization against inflation risk. Accordingly, we propose a unified view and a rationalization ex post of several current portfolio strategies that appear different at a first glance. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.

No summary available.

The objective of this thesis is to study what composition of the board of directors ensures the effectiveness of its monitoring and advisory functions. In Chapter 1, we investigate whether the presence of directors who are related to minority shareholders can be an effective corporate governance mechanism to limit expropriation by majority shareholders, without exacerbating risks. The empirical study in this chapter is conducted on a sample of banks with concentrated ownership. The results indicate that the presence of minority directors increases the effectiveness of the bank board insofar as it leads to higher market valuation without increasing risk. Chapter 2 complements the first chapter to determine the factors, both at the bank and country level, that may favor the presence of minority directors on bank boards. The results show that: (i) the importance of majority shareholders' voting rights, the quality of board recommendations in corporate governance codes and the level of shareholder protection are factors that favor the presence of minority directors on bank boards. (ii) strict supervisory regimes and high opacity reduce the presence of minority directors on bank boards. Our work suggests that banking authorities should recommend that banks with concentrated ownership include a minimum number of minority directors on their boards. In Chapter 3, we examine the impact of imposing a minimum quota of members of each gender on firms' performance and decisions, using the cases of Belgium, France and Italy as a natural experiment. Our statistical analysis shows that the percentage of women increases significantly and that the characteristics of board members change significantly after the quota is implemented. The empirical results show that quotas do not have a significant impact on firm performance and decisions. Our results support the implementation of a quota to ensure a balanced representation of men and women on corporate boards. However, they show that regulators create unrealistic expectations about the ability of women to improve firm performance, at least in the short run when the negative effects of imposing a quota are potentially the greatest.

The objective of this thesis is to examine both the supply and demand dimensions of financial inclusion. This research presents a comprehensive body of empirical evidence regarding access to financial services at both the macro and micro levels. The third chapter provides an exploration of this critical hypothesis. Using structural country data, it shows the effects of financial inclusion on reducing poverty and inequality. In addition, it shows the beneficial effects of new technologies on expanding financial inclusion and reducing poverty. The fourth chapter argues that financial literacy is an important determinant of household financial inclusion and well-being. Based on survey data, it further suggests that access to and use of new technologies increases the likelihood of financial inclusion. The objective of the fifth chapter is to determine whether the adoption of new technologies promotes financial inclusion among SMEs in Pakistan. The analysis reveals an association between ICT adoption and firm access to financial services, implying that firms with greater access to or use of new technologies are likely to derive greater benefits from financial markets than others.This research contributes to the literature on access to financial services by expanding the examination of several significant dimensions and complements studies on the impact of financial depth, financial stability, and financial literacy.

No summary available.

No summary available.

The demographics of developed economies show a rapid aging of their populations, and this process has begun in emerging countries. Demographic aging is due to three phenomena: the postponement of the age of first childbirth, the decline in fertility and the increase in life expectancy. This phenomenon has important economic consequences, notably through the rise in the dependency ratio, defined as the number of retirees in relation to the working age population. This thesis focuses on the consequences of demographic aging on the price of capital and on the financing of pensions in the face of the financial crisis. In the first chapter, we study the effect of the dynamics of the demographic structure on the price of capital in a nested-generation model with capital adjustment costs. The findings indicate that the price of assets increases and then decreases as the demographic structure changes. The second chapter focuses on the performance of a large portfolio during financial market stress. Using copula theory, we develop a methodology to analyze the exposure of a portfolio to different extreme market risks. The third chapter deals with the analysis of the sensitivity of the financial situation of pension funds to market risks, using the methodology developed in the previous chapter. We find that the assets and liabilities of a pension fund's balance sheet are vulnerable to volatile movements in financial markets.

While there is an abundant literature on office market modelling, only few studies focus on the Greater Paris case, which stands as the largest office market in Europe. This article aims at contributing to the understanding of the Parisian rental office market underlying mechanisms. We use cointegration techniques including Gregory–Hansen structural break approach to model the market over the period 1990–2013. We employ a two-stage error correction framework to identify the long-run equilibrium rent as well as the short-run adjustments in rent, vacancy rate and stock. The findings show that once allowances are made for a regime shift in the long-run rent relationship, the specified model explains relatively well the Parisian market. The long-run results confirm the role of employment and total stock as long-run determinants of rental values. Yet, in the short-run, due to the inertia arising from the intrinsic features of the office market, lagged dependent variables appear to be drifting rents away from their equilibrium.

This paper investigates the impact of extreme shocks on stock and bond markets on listed European banks. The originality of our approach consists in dealing jointly with stock and bond markets and taking into account their interdependencies in case of extreme events by using a specific CVRF (CVine Risk Factor) model which combines copulas and a factorial structure. Moreover, contrary to what is generally done in the literature, we do not focus only on the responses of the stock returns but we also examine the response of the balance sheets of the banks and particularly of their short term assets in order to assess their fragility in terms of liquidity. Our main findings are the following: 1) the nature of the banks' fragility has changed: today, the interest rate risk should be the first concern before the equity risk, as the banks have extensively increased their exposition to bond market due to flight-to-quality reactions and to large investments in governments bonds after the rescue operations the banks have benefited. 2) in case of a surge in the interest rate and in the links between stock and bond returns, the portfolios of the biggest banks in Europe would experience very severe shortfalls for both equity and liquidity buffers. Accordingly regulators should monitor the evolution of dependencies between assets and should pay utmost attention to the positive links between stock and bond returns.

In this paper, we propose a flexible tool to estimate the risk sensitivity of a high-dimensional portfolio composed of different classes of assets, especially in extreme risk circumstances. We build a so-called Cvine Risk Factors Model (CRFM), which is a non-linear version of a risk factor model in a copula framework. Our tool allows us to decompose the risk of any asset and any portfolio into specific risk directions depending on the context. As an application, we compare the sensitivity of different types of portfolios to extreme risks. We also give an example of a view-type analysis as usually performed by portfolio managers who examine what their portfolio becomes under specific circumstances: here we examine the case of a low inflation context. These analyses allow us to detect changes in the diversification opportunities over time.

This thesis on office markets is presented in three articles. The first one aims at identifying the persistent and transitory determinants of the evolution of office rents in the Paris region, based on analyses of co-integration properties and structural breaks. The second article examines the interactions between the dynamics of the five sub-markets that make up the Central Paris office market. More precisely, the methodology adopted allows us to define the nature of the interactions in terms of substitutability, complementarity or independence between sub-markets. The third paper contributes to the study of the real estate market from a financial point of view by analyzing the determinants of the rate of return of the UK office market. A non-linear regime-switching model is used to measure the relative impact of these determinants on the rate of return as a function of the monetary and financial environment.

No summary available.

This thesis highlights the asymmetric aspect of the output elasticity of unemployment in the United States and in Europe. The first part of this empirical work returns to an estimate of the "true" value of the Okun coefficient corrected for publication bias. We use a meta-analysis and show that an important aspect of the distortion of the coefficient lies in the choice of the endogenous variable. In the second chapter, we show that Okun's law implies in its foundations a procyclical behavior of productivity generated by the practice of labor retention. The US economy shows a significant deformation of the Okun coefficient during recessions and recoveries since the mid-1980s, when productivity lost its procyclical character. In Germany and France, on the other hand, the Okun coefficient deforms little over the cycle. This European specificity could be due to the nature of macroeconomic fluctuations. Thus, the German economy experiences macroeconomic shocks with a strong transitory and persistent character. Nevertheless, the rest of the European countries have shocks of a permanent nature. In the last chapter, we show that real GDP and unemployment can share an asymmetric cointegration relationship that seems to be associated with an asymmetric Phillips curve.

We investigate the presence of self-fulfilling dynamics during the European sovereign crisis in the light of a theoretical model that we bring to the data. Our empirical framework allows us to empirically test the presence of self-fulfilling dynamics and to identify what may have driven the market sentiment during this crisis. To do so we estimate the probability of default of five European “peripheral” countries during January 2006 to September 2011 with a panel smooth threshold regression. Our estimation results suggest that (1) both the fundamentals and “animal spirit” ignited the European sovereign crisis. (2) we isolate the risk indicator through which investors’ belief coordinate.

This paper reinvestigates the presence and the causes of the underwriting cycle in the French property-liability insurance industry as displayed by the combined ratio for the 1963-2008 period. The question is still a timely issue if we refer to regulation issues and the recent proposals in the Sovency framework to take into account the fluctuations of the profitability in specifying the solvency capital requirement. In the literature, two approaches are traditionally adopted to investigate the underwriting cycle : the first one refers to an endogeneous characterization of the cyclical properties from an AR(2) model. The second one claims that the cycle in the property-liability insurance has exogeneous sources related to the financial markets and the general economy. In this article, we reconcile the two approaches by using a smooth transition regression (STR) model. This model shows that the AR(2) model is relevant in a first regime where the capacity constraint is binding. In contrast, the fluctuations in the combined ratio are positively influenced by the lagged stock market return in a second regime where the capacity is not constrained, as for the most recent period. Moreover, we find that the current capacity is related to the lagged inflation rate in the latter case. These results confirm the idea that the European rules regarding the solvency capital requirement for insurance companies should take into account the state of the economy and the financial markets.

The interaction between the financial and real spheres has long been neglected in macroeconomic models, which generally assume that the former is neutral. The recent subprime crisis demonstrates that this is not the case. This thesis proposes three essays on the role of the financial sector, and more particularly the banking sector, in the light of the latest crisis. The first is to give a formal framework to the exceptional nature of the crisis by abandoning the assumption of normality of 'residual events'. Our results refute the 'normal' character of the crisis but, more importantly, highlight the biases in terms of economic diagnoses to consider it as such.Furthermore, one of the exceptional effects of this crisis was the use of unconventional monetary policies. The second part of the thesis suggests that uncertainty in the interbank markets is a probable reason for the ineffectiveness of conventional monetary policies. The third part of the thesis proposes a study of the impact of the new Basel III regulations on the real sector. The lack of positive externalities between the implementation of the capitalization constraint and the LCR further accentuates the output gap between SMEs and large firms, leading to an even more significant overall recessionary impact. A slower and perfectly announced implementation of the new regulatory standards could nevertheless mitigate these effects.

Despite the substantial costs associated with holding capital, the level of capital observed in the non-life insurance sector is well above regulatory standards. This thesis sheds new light on capitalization policy and studies the effect of uncertainty about risk factors on investment policy. These questions are addressed using innovative theoretical and empirical approaches that favor a global and multi-period analysis framework. The first part of the paper focuses on the development of equilibrium models that take into account the randomness and uncertainty of risks. A second part empirically examines the adjustment relationships between capitalization, risk-taking and reinsurance policies. A third part evaluates the efficiency of the level of capital in a multi-period framework. Equilibrium models show that simultaneous choice of capital and risk is more beneficial to insurers than separate adjustment of one of the decisions. The empirical results confirm the strong interdependence between the different financial decisions. The capitalization policy converges towards a long-term target level in line with the performance objectives of insurance companies. The relationship between capital and risk is the most significant and reflects both the anchoring of the concept of economic capital in the functioning of insurance companies and the effectiveness of the capital adequacy rule. This relationship directly influences solvency and contributes to the creation of value. Finally, the analysis of multi-period efficiency shows that the capitalization policy responds less to considerations of passive capital accumulation than to sub-optimal behavior dictated by market imperfections.

In this thesis, we analyze the contribution of the options market to the informational efficiency and stability of the French equity market listed on Euronext-LIFFE for the period 1996-2006, and we propose to define to what extent the merger of Euronext with Liffe in 2002 and the macroeconomic conditions of 1996-2006 influence this contribution.The study of the introduction of options on the characteristics of stocks reveals (i) the absence of impact on both volatility and systematic risk of stocks measured by beta, (ii) a negative price effect that remains statistically insignificant in the majority of sessions, (iii) a significant increase in volume, (iv) a decrease in the price range The VAR modeling shows that the introduction of the option strengthens the adjustment of volume to stock volatility significantly only at the 10% threshold. Furthermore, the proportion of informed agents in the stock market is not higher following the introduction of options.The Log-ACD (Autoregressive Conditionnal Duration) modeling augmented by the introduction of liquidity as an explanatory variable does not detect any effect of the introduction of the option on the informational reinforcement of stocks.Furthermore, our study highlights that the objective of the options market is hedging (respectively speculation and/or arbitrage) in periods of high (respectively low) volatility. The merger of Euronext with Liffe in 2002 does not introduce any significant change in the improvement of the process of price adjustment to news. The overall result of the lack of effect of the introduction of the stock option is explained by the current volatility-based trading in France. This reduces the predictive power of options.

The purpose of this thesis is to make a methodological contribution to the empirical literature on financial stability. It consists of three chapters. The first chapter studies the convergence of financial systems in the euro area by estimating a household credit demand equation in different countries. Using the ARDL model proposed in particular by Pesaran et al (1999), we highlight the convergence of the long-run determinants of credit demand within the largest countries, while the short-run dynamics remain heterogeneous. The second chapter contributes to the literature on financial fragility by studying how macroeconomic shocks affect supply and demand in the corporate debt market. We consider the effect of the competitive environment, as well as the level of risk, as measured by the default rate of firms. We measure the effects of large macroeconomic shocks on the debt market equilibrium. The third chapter studies the interactions between macroeconomic shocks and firms' financial fragility. It analyzes the interactions in both directions, i.e. whether corporate failures are affected by macroeconomic variables and whether, in the opposite direction, failures can determine the business cycle. Bankruptcy forecasting equations are estimated using the approach of Shumway (2001). The modeling of the joint dynamics of insolvencies and macroeconomic variables allows for the measurement of "second round effects". The model is used to perform stress tests.

Despite the considerable amount of theoretical and empirical work aimed at analyzing non-life insurance underwriting cycles. No single clear conclusion seems to emerge. The lack of consensus seemed to us to be due to the inadequacy of the adapted linear modeling and the neglect of the cointegration properties applied to both time series and panel data. This thesis has therefore aimed at re-examining the underwriting cycles while focusing on the dynamics of the combined ratio and on the determinants of premiums for the case of France and for other countries. In the first chapter, we presented a review of the literature on the subject. In the second chapter, we analyzed the underwriting cycles and the determinants of premiums for the French aggregate sector using non-linear time series econometrics. In the third chapter, we used recent developments in panel data econometrics, taking into account non-stationarity and non-linearity, to conduct a disaggregated analysis by French line of underwriting cycles and premium determinants, and to conduct a comparative analysis of premium determinants in an international framework. The results obtained for the French aggregate sector led us to conclude that the cyclical phenomenon disappeared in France as early as 1989 and that the dynamics of the combined ratio is instead modeled by a smooth transition regression (STR) model. The pricing of premiums seems to change from 1985 onwards and the growth rate of premiums seems to be represented by a smooth transition error correction model (STECM). Second, the estimation of static and dynamic panels allowed us to detect similarities in the dynamics of the combined ratios of the non-life insurance lines. Similarly, the estimation of cointegration relationships on panel data allowed us to identify differences in the determinants of premiums of non-life insurance lines. Finally, the comparative analysis by country showed that the growth rates of the countries' premiums are reproduced by a smooth transition error correction model on panel data (PSTECM).

The objective of this thesis is to study different methods of predicting business failure in both static and dynamic approaches. More precisely, in the static approach, we have resorted to the methods of selection of the discriminating variables by using neural networks. The first one, based on the HVS criterion, entitled HVS-AUC, allowed us i) to build a more parsimonious model compared to the ADL . ii) to identify a set of stable variables that are both non-cyclical and with a high explanatory power. In contrast, the second technique is based on the forward procedure or, more precisely, on forward-AUC. This method produces results comparable to the LDA but with fewer explanatory variables. We also used Bayesian network structure learning methods to try to improve the classification performance of the companies. We mobilized a technique called "Max-Min Hill-Climbing" or MMHC. We analyzed the classification performance of a combined algorithm between MMHC and the basic model of a naive Bayesian network (BN). This new method has been named BN-MMHC (Naive Bayes augmented by MMHC). In the second dynamic approach, we put more emphasis on factors that cannot be measured a priori and on explanatory factors that cannot be understood in a static framework. In the first part, we mobilized macroeconomic variables to better estimate the risk of default. In the second part, we used an alternative model that allows us to correctly assess the shocks that firms may experience over time. In this way, we have evaluated the effect of the propagation of these shocks.

The objective of this thesis is to study the impact of macroeconomic factors on credit risk. In this thesis, we use two types of models that allow us to exploit a large number of series. The first model used refers to the GVAR model (Global Vector AutoRegressive model) developed by Pesaran et al. (2004). We consider a fictitious portfolio of 83 firms covering 16 developed countries. We find that default probabilities increase significantly during recessions but do not decrease during growth periods. We also confirm the fact that companies with a good rating are less sensitive to changes in economic conditions than those with a poor rating. The second model studied is the dynamic factor model of the FAVAR type (Factor Augmented Vector Autoregressive Model), proposed by Stock and Watson (2005). We propose two empirical applications, one focused on the United States, the other on the Eurozone. We find that common factors explain relatively little of the default rates of firms. This result demonstrates the importance of risk diversification. We also find that the most explanatory factor of the default rate is the factor related to real activity, such as production and employment. Another important explanatory factor is the one related to stock market indices. Finally, we find that monetary policy is far from being the dominant factor in determining changes in the default rate. Changes in the FeD's policy rate do not therefore appear to be one of the causes of the subprime crisis.

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.

We implement modeling strategies consistent with the problems raised by the study of the euro zone and the concerns of a central bank. We seek to verify the operational usefulness of exploiting a heterogeneous and large body of information to forecast inflation, and to extract the economic fluctuations responsible for inter-economic developments. To this end, we have made use of the latest developments in statistical theory regarding factor models, which allow us to apply these models to a large amount of non-stationary data. The main methodological aim of the thesis is to distinguish between common and country-specific effects, and between short- and medium-term phenomena and long-term phenomena. The predictive power of this synthesis of inflation information is also examined and compared in particular with that of a model based on economic theory.

While many empirical exercises show that the dynamics of flexible exchange rates are the result of purely speculative phenomena, this thesis highlights, on the contrary, that these fluctuations are not decoupled from any macroeconomic determinant. These results are established on the basis of an econometric study of the case of the monthly real exchange rate of the yen/dollar. Our approach emphasizes the interaction between financial and macroeconomic variables in the determination of currency exchange rates, with reference to international portfolio choice theory. In addition, we focus on the study of persistent linkages between exchange rates and their fundamentals-which we characterize as cointegrating relationships-and the influence of these linkages on the short-term dynamics of these variables. An essential contribution of this thesis lies in taking into account, both in economic modeling and in statistical measurement, the influence of structural breaks, i.e. unpredictable shocks that durably affect the structure of the economy studied, in a system of non-stationary series. In particular, we show that the uncertainty on the parameters of the true model that agents face after a regime change leads to systematic forecast errors on their part during a learning period. Finally, we develop an econometric tool that allows us to characterize the long-run properties of a multivariate cointegrated dynamic system in the presence of such breaks.

We study the causality between time series from an econometric point of view. As such, we adopt the characterization proposed by Feigl (1953) who characterizes causality as a property, experimentally confirmed, of improved forecasting, in accordance with laws that define the economic frame of reference of the analysis. We approach the analysis of causality as an impulse analysis, considering two notions of impulse, deterministic and stochastic, characterized respectively as modifications of the initial conditions (or average characteristics of the dynamics) and canonical innovations. We show that causality, characterized in terms of improved forecasting at all horizons, (Lütkepohl (1990) can be analyzed by studying the propagation of deterministic impulses. We formalize precisely the notion of indirect unidirectional link and give a necessary and sufficient condition to exclude all direct and indirect causal links between two series extracted from a stationary VAR model. The effects of stochastic impulses are characterized, following the principles advocated by Sims (1980) and are associated with the characterization of causality in the sense of this author. When we study persistent causality between integrated series, we choose to analyze this property by developing a stochastic impulse analysis, because persistence is stochastic in nature. The formalization of persistent causality that we adopt can be interpreted in terms of improved forecasting over an infinite horizon, which allows us to finally propose a causal reading.