Publications associées à Out of Sample Forecasts of Quadratic Variation

Machine Learning for Modeling Stock Returns

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

How Integrated are Credit and Equity Markets? Evidence from Index Options

Pierre Collin Dufresne, Jan Benjamin Junge

We study the extent to which credit index (CDX) options are priced consistent with S&P 500 (SPX) equity index options. We derive analytical expressions for CDX and SPX options within a structural credit-risk model with stochastic volatility and jumps using ...

Wiley2024

Challenges of COVID-19 Case Forecasting in the US, 2020-2021

Joseph Chadi Benoit Lemaitre, Pan Xu, Myungjin Kim, Shan Yu, Lei Gao, Weitong Zhang, Wei Cao, Xinyi Li

During the COVID-19 pandemic, forecasting COVID-19 trends to support planning and response was a priority for scientists and decision makers alike. In the United States, COVID-19 forecasting was coordinated by a large group of universities, companies, and ...

Public Library Science2024

Towards Motion Forecasting with Real-World Perception Inputs: Are End-to-End Approaches Competitive?

Alexandre Massoud Alahi

Motion forecasting is crucial in enabling autonomous vehicles to anticipate the future trajectories of surrounding agents. To do so, it requires solving mapping, detection, tracking, and then forecasting problems, in a multi-step pipeline. In this complex ...

2024

Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations

Nicola Parolini, Ntorina Thanou, David Kraus, Andrea Kraus, Daniel Lopez, Markus Scholz, Benjamin Bejar Haro, Daniel Rodrigo Lopez, Ekaterina Krymova, Tao Sun

Background:Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive p ...

eLIFE SCIENCES PUBL LTD2023

Improved extended-range prediction of persistent stratospheric perturbations using machine learning

Raphaël Gérard Théodore Michel Marie de Deloÿe et Fourcade de Fondeville, Guillaume Romain Obozinski

On average every 2 years, the stratospheric polar vortex exhibits extreme perturbations known as sudden stratospheric warmings (SSWs). The impact of these events is not limited to the stratosphere: but they can also influence the weather at the surface of ...

Copernicus Gesellschaft Mbh2023

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

Inference and Computation for Sparsely Sampled Random Surfaces

Victor Panaretos, Tomas Rubin, Tomas Masák

Nonparametric inference for functional data over two-dimensional domains entails additional computational and statistical challenges, compared to the one-dimensional case. Separability of the covariance is commonly assumed to address these issues in the de ...

TAYLOR & FRANCIS INC2022

Covariance Estimation for Random Surfaces beyond Separability

Tomas Masák

This thesis focuses on non-parametric covariance estimation for random surfaces, i.e.~functional data on a two-dimensional domain. Non-parametric covariance estimation lies at the heart of functional data analysis, and considerations of statistical and com ...

EPFL2022

Essays in Monetary Policy and Asset Pricing

Benoit Vincent Sylvain Cornet

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 Unconv ...

EPFL2022

National and subnational short-term forecasting of COVID-19 in Germany and Poland during early 2021

Markus Scholz, Ekaterina Krymova

Background During the COVID-19 pandemic there has been a strong interest in forecasts of the short-term development of epidemiological indicators to inform decision makers. In this study we evaluate probabilistic real-time predictions of confirmed cases an ...

Springernature2022

Skew-Brownian motion and pricing European exchange options br

Puneet Pasricha

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 on the Role of Policy and Venture Financing in Clean Technology Innovation

Matthias David van den Heuvel

This thesis aims to provide novel analyses and data that improve the understanding of the financing of investments in clean technologies. In particular, this thesis explores the role that private and public actors play in supporting young innovative firms. ...

EPFL2022

FABRICATION AND ANALYSIS OF THIN FILM LITHUM NIOBATE RESONATORS FOR 5GHz FREQUENCY AND LARGE k(t)(2) APPLICATIONS

Victor Plessky, Luis Guillermo Villanueva Torrijo, Seniz Esra Küçük, Soumya Yandrapalli

This work presents the fabrication and analysis of suspended thin film Lithium Niobate resonators. The yield of the new fabrication process presented below is >90% showing devices with high k(t)(2) of 28% resonators at 5GHz, making them suitable for high f ...

IEEE2021

Numerical Weather Prediction and Artificial Neural Network Coupling for Wind Energy Forecast

Jiannong Fang, Fernando Porté Agel, Lorenzo Donadio

In the past two decades, wind energy has been under fast development worldwide. The dramatic increase of wind power penetration in electricity production has posed a big challenge to grid integration due to the high uncertainty of wind power. Accurate real ...

2021

Re-evaluating natural resource investments under uncertainty: An alternative to limited traditional approaches

Sebastian Maier

The need to evaluate natural resource investments under uncertainty has given rise to the development of real options valuation; however, the analysis of such investments has been restricted by the capabilities of existing valuation approaches. We re-visit ...

2021

Informed Trading in the Stock Market and Option Price Discovery

Pierre Collin Dufresne

When activist shareholders file Schedule 13D filings, the average excess return on target stocks is 6% and stock price volatility drops by about 10%. Prior to filing days, volatility (price) information is reflected in option (stock) prices. Using a compre ...

2021

Waste collection inventory routing with non-stationary stochastic demands

Sacha Varone, Michel Bierlaire, Iliya Dimitrov Markov, Mohammad Yousef Maknoon

We solve a rich routing problem inspired from practice, in which a heterogeneous fixed fleet is used for collecting recyclable waste from large containers over a finite planning horizon. Each container is equipped with a sensor that communicates its level ...

PERGAMON-ELSEVIER SCIENCE LTD2020

Small-Signal Approach for Precise Evaluation of Gate Losses in Soft-Switched Wide-Band-Gap Transistors

Elison de Nazareth Matioli, Armin Jafari, Palliyage Srilak Nirmana Perera, Furkan Karakaya

High-frequency switching is favorable for fast transient response, small size of passive components and superior power density, especially in soft-switching topologies. At high frequencies, power dissipation due to consecutive charging/discharging of gate ...

IEEE2020

Wide band-pass FSS with reduced periodicity for energy efficient windows at higher frequencies

Josef Andreas Schuler, Luc Burnier, Jérémy Jacques Antonin Fleury

A simulation model and an experimental characterization of energy saving glazing transparent to mobile communication frequency up to 40 GHz is presented. A previous study showed that laser structured energy efficient windows with a frequency selective surf ...

SPRINGER HEIDELBERG2020