Concept
Modèle d'évaluation par arbitrage
Publications associées (55)
Demand-based Asset Pricing: Theory, Estimation and Applications
This thesis investigates the relationship between investors' demand shocks and asset pricesthrough the use of data on portfolio holdings. In three chapters, I study the theory, estimation,and application of demand-based asset pricing models, which incorpor ...
EPFL2023Mortgage-backed securities
This paper reviews the mortgage-backed securities (MBS) market, with a particular emphasis on agency residential MBS in the United States. We discuss the institutional environment, security design, MBS risks and asset pricing, and the economic effects of m ...
Edward Elgar2023Principal Portfolios
We propose a new asset pricing framework in which all securities' signals predict each individual return. While the literature focuses on securities' own-signal predictability, assuming equal strength across securities, our framework includes cross-predict ...
WILEY2022Asset Pricing and Monetary Policy
Classical theory asserts that the formation of prices is the result of aggregated decisions ofeconomics agent such as households or corporation. However central banks are very importantagents that have often been neglected in asset pricing models. Central ...
EPFL2022Essays in Empirical Asset Pricing
This thesis consists of three applications of machine learning techniques to empirical asset pricing.In the first part, which is co-authored work with Oksana Bashchenko, we develop a new method that detects jumps nonparametrically in financial time series ...
EPFL2022A machine learning approach to portfolio pricing and risk management for high-dimensional problems
We present a general framework for portfolio risk management in discrete time, based on a replicating martingale. This martingale is learned from a finite sample in a supervised setting. Our method learns the features necessary for an effective low-dimensi ...
WILEY2022Conditional Synthetic Financial Time Series with Generative Adversarial Networks
The creation of high fidelity synthetic data has long been an important goal in machine learning, particularly in fields like finance where the lack of available training and test data make it impossible to utilize many of the deep learning techniques whic ...
2022Essays in Monetary Policy and Asset Pricing
This thesis uses machine learning techniques and text data to investigate the relationships that arise between the Fed and financial markets, and their consequences for asset prices.The first chapter, entitled Market Expectations and the Impact of Unconven ...
EPFL2022