Public Thesis defense - LIDAM

Essays on financial econometrics and quantitative finance by Linqi WANG

Pour l’obtention du grade de Docteur en sciences

Negative interest rates have significantly impacted multiple segments of financial markets and market participants' investment behavior. With nominal interest rates entering negative territory for the first time in history, a reassessment of the existing framework for interest rate modelling and derivative pricing is warranted. Moreover, lower bond yields induce investors to seek higher returns in other asset classes which are potentially associated with higher risks. Therefore, priority should be given to the development of new modelling solutions for the real-time monitoring of financial market volatility, correlation, and liquidity conditions given their central role in portfolio allocation and risk management.

This dissertation revolves around the development of modelling approaches with relevant applications to financial markets. In particular, Chapter 1 studies the implications of the negative interest rate environment for the modelling of short rates and the pricing of interest rate derivatives. In addition, we propose a model calibration approach that takes into account the whole implied forward rate distribution rather than sparse data points for derivative prices or implied volatilities. Chapter 2 focuses on the development of a Dynamic Conditional Score (DCS) model for the log correlation matrix which can accommodate fat tails in the conditional distributions and generalizes the Beta-t-EGARCH model of Harvey (2013), which uses the student-t distribution, to the multivariate case. In Chapter 3, we develop a new algorithm for dynamic portfolio selection which combines a Dynamic Conditional Correlation (DCC) model with nonlinear shrinkage for the dynamics of asset returns with LASSO-type penalization schemes to control for within- and between-group variations in portfolio weights. In the application, we consider US stocks whose sectoral classification is used for group assignment. Other applications could also be considered. For instance, this framework could be used to efficiently exploit the diversification opportunities across regions and asset classes arising in a negative rate environment. Finally, Chapter 4 proposes a new class of dynamic autoregressive liquidity models for the Amihud illiquidity measure to capture both the long-run trend in illiquidity series with a nonparametric component and short-run illiquidity dynamics with an autoregressive component. This allows us to provide real-time monitoring of liquidity conditions for asset classes which might constitute attractive diversification opportunities in a negative interest rate environment.

Jury members :

• Prof. Christian Hafner (UCLouvain), supervisor
• Prof. Frédéric Vrins (UCLouvain), supervisor
• Prof. Pierre Devolder (UCLouvain), chairperson
• Prof. Donatien Hainaut (UCLouvain), secretary
• Prof. Damiano Brigo (Imperial College London, UK)
• Prof. Oliver Linton (University of Cambridge, UK)

Pay attention :

The public defense of Linqi Wang scheduled for Wednesday 11 May at 3:00 p.m will also take place in the form of a video conference

Meeting ID: 852 2048 1160

Passcode: 932246

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