An optimal prediction problem in financial modelling
Graph Chatbot
Chattez avec Graph Search
Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.
AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.
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 ...
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 ...
We develop a comprehensive mathematical framework for polynomial jump-diffusions in a semimartingale context, which nest affine jump-diffusions and have broad applications in finance. We show that the polynomial property is preserved under polynomial trans ...
Capital ages and must eventually be replaced. We propose a theory of financing in which firms borrow to finance investment and deleverage as capital ages to have enough financial slack to finance replacement investments. To achieve these dynamics, firms is ...
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 ...
In this paper, we study the compressibility of random processes and fields, called generalized Levy processes, that are solutions of stochastic differential equations driven by d-dimensional periodic Levy white noises. Our results are based on the estimati ...
The theory of sparse stochastic processes offers a broad class of statistical models to study signals, far beyond the more classical class of Gaussian processes. In this framework, signals are represented as realizations of random processes that are soluti ...
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 ...
The COVID-19 pandemic has demonstrated the importance and value of multi-period asset allocation strategies responding to rapid changes in market behavior. In this article, we formulate and solve a multi-stage stochastic optimization problem, choosing the ...
I started my PhD studies in August 2014 with a strong desire to push my own limits without knowing precisely the areas I wanted to cover in detail. To me, it was clear that I was interested by many different fields, however, I was particularly concerned wi ...
