Econometric models of financial risks

The goal of this dissertation is to use statistical tools to analyze specific financial risks that have played dominant roles in the US financial crisis of 2008-2009. The first risk relates to the level of aggregate stress in the financial markets. I estimate the impact of financial stress on economic activity and monetary policy using structural VAR analysis. The second set of risks concerns the US housing market. There are in fact two prominent risks associated with a US mortgage, as borrowers can both prepay or default on a mortgage. I test the existence of unobservable heterogeneity in the borrower's decision to default or prepay on his mortgage by estimating a multinomial logit model with borrower-specific random coefficients.

Topics in financial econometrics

In the first chapter, we consider the joint estimation of objective and risk-neutral parameters for SV option pricing models. We propose a strategy which exploits the information contained in large heterogeneous panels of options, and we apply it to S&P 500 index and index call options data. Our approach breaks the stochastic singularity between contemporaneous option prices by assuming that every observation is affected by measurement error. We evaluate the likelihood function by using a MC-IS strategy combined with a Particle Filter algorithm. The second chapter examines the impact of different categories of traders on market transactions. We estimate a model which takes into account traders’ identities at the transaction level, and we find that the stock prices follow the direction of institutional trading. These results are carried out with data from an anonymous market. To explain our estimates, we examine the informativeness of a wide set of market variables and we find that most of them are unambiguously significant to infer the identity of traders. The third chapter investigates the relationship between the categories of market traders and three definitions of financial durations. We consider trade, price and volume durations, and we adopt a Log-ACD model where we include information on traders at the transaction level. As to trade durations, we observe an increase of the trading frequency when informed traders and the liquidity provider intensify their presence in the market. For price and volume durations, we find the same effect to depend on the state of the market activity. The fourth chapter proposes a strategy to express order aggressiveness in quantitative terms. We consider a simultaneous equation model to examine price and volume aggressiveness at Euronext Paris, and we analyse the impact of a wide set of order book variables on the price-quantity decision.

The Structure of Financial Supervision: Consolidation or Fragmentation for Financial Regulators?

This research was designed to answer the question of which direction the restructuring of financial regulators should take – consolidation or fragmentation. This research began by examining the need for financial regulation and its related costs. It then continued to describe what types of regulatory structures exist in the world; surveying the regulatory structures in 15 jurisdictions, comparing them and discussing their strengths and weaknesses. This research analyzed the possible regulatory structures using three methodological tools: Game-Theory, Institutional-Design, and Network-Effects. The incentives for regulatory action were examined in Chapter Four using game theory concepts. This chapter predicted how two regulators with overlapping supervisory mandates will behave in two different states of the world (where they can stand to benefit from regulating and where they stand to lose). The insights derived from the games described in this chapter were then used to analyze the different supervisory models that exist in the world. The problem of information-flow was discussed in Chapter Five using tools from institutional design. The idea is based on the need for the right kind of information to reach the hands of the decision maker in the shortest time possible in order to predict, mitigate or stop a financial crisis from occurring. Network effects and congestion in the context of financial regulation were discussed in Chapter Six which applied the literature referring to network effects in general in an attempt to conclude whether consolidating financial regulatory standards on a global level might also yield other positive network effects. Returning to the main research question, this research concluded that in general the fragmented model should be preferable to the consolidated model in most cases as it allows for greater diversity and information-flow. However, in cases in which close cooperation between two authorities is essential, the consolidated model should be used.

Estimation of Quasi-Rational DSGE Models

Small-scale dynamic stochastic general equilibrium have been treated as the benchmark of much of the monetary policy literature, given their ability to explain the impact of monetary policy on output, inflation and financial markets. One cause of the empirical failure of New Keynesian models is partially due to the Rational Expectations (RE) paradigm, which entails a tight structure on the dynamics of the system. Under this hypothesis, the agents are assumed to know the data genereting process. In this paper, we propose the econometric analysis of New Keynesian DSGE models under an alternative expectations generating paradigm, which can be regarded as an intermediate position between rational expectations and learning, nameley an adapted version of the "Quasi-Rational" Expectatations (QRE) hypothesis. Given the agents' statistical model, we build a pseudo-structural form from the baseline system of Euler equations, imposing that the length of the reduced form is the same as in the `best' statistical model.