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Applying the HJM-approach when volatility is stochastic

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Machine Learning for Modeling Stock Returns

Teng Andrea Xu

Throughout history, the pace of knowledge and information sharing has evolved into an unthinkable speed and media. At the end of the XVII century, in Europe, the ideas that would shape the "Age of Enlightenment" were slowly being developed in coffeehouses, ...

EPFL2024

Takeover Protections and Asset Prices

Erwan Morellec

We study the effects of takeover feasibility on asset prices and returns in a unified framework. We show theoretically that takeover protections increase equity risk, stock returns, and bond yields by removing a valuable put option to sell the firm, notabl ...

Catonsville2024

Stripping the Swiss discount curve using kernel ridge regression

Damir Filipovic

We analyze and implement the kernel ridge regression (KR) method developed in Filipovic et al. (Stripping the discount curve-a robust machine learning approach. Swiss Finance Institute Research Paper No. 22-24. SSRN. https://ssrn.com/abstract=4058150, 2022 ...

Springer Heidelberg2024

Tiers of joy? Reserve tiering and bank behavior in a negative-rate environment

Andreas Fuster

Negative interest rate regimes typically involve reserve tiering to exempt a portion of bank reserves from negative rates. We study the effects on bank behavior of a large and unanticipated change in reserve tiering by the Swiss National Bank that generate ...

2024

In this thesis we present three closed form approximation methods for portfolio valuation and risk management.The first chapter is titled ``Kernel methods for portfolio valuation and risk management'', and is a joint work with Damir Filipovi'c (SFI and EP ...

EPFL2023

Discount models

Damir Filipovic

Discount is the difference between the face value of a bond and its present value. We propose an arbitrage-free dynamic framework for discount models, which provides an alternative to the Heath-Jarrow-Morton framework for forward rates. We derive general c ...

Heidelberg2023

Demand-based Asset Pricing: Theory, Estimation and Applications

Philippe van der Beck

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 ...

EPFL2023

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

This article derives a closed-form pricing formula for European exchange options under a non-Gaussianframework for the underlying assets, intending to resolve mispricing associated with a geometric Brownianmotion. The dynamics of each of the two correlated ...

ELSEVIER SCIENCE INC2022

Essays in Empirical Asset Pricing

Alexis Arilès Marchal

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 ...

EPFL2022