Interests and Research
I am interested in finding structure in financial markets. My research focus is on methods to recover information that is not directly observable with the most innocuous assumptions possible. I try to learn every day about old and new techniques from engineering and mathematics, to keep myself informed about politics, and to enjoy and play music as much as possible.
Contact
USI Lugano
Via G. Buffi 13
CH-6900 Lugano
Paul Schneider
Working Papers
Fast empirical scenarios. with M. Multerer and R. Sen
Adaptive joint distribution learning. with D. Filipovic and M. Multerer
International arbitrage premia. with M. Sandulescu
Ross recovery with time series information and economic constraints.
Option trading under uncertainty.
Fear Trading. with Fabio Trojani
Refereed Journal Articles
Optimal Investment and Equilibrium Pricing under Ambiguity. forthcoming Review of Finance (2024), with M. Anthropelos
Constrained polynomial likelihood. forthcoming Journal of Business & Economic Statistics (2023), with C. Almeida and R. Masini
Dispersion of Beliefs Bounds: Sentimental Recovery. forthcoming Management Science (2023), with A. Pazarbasi and G. Vilkov
On the nature of jump risk premia. forthcoming Management Science (2022), with P. Orlowski and F. Trojani
Low Risk Anomalies?. Journal of Finance (2020) 75, 2673-2718 with Christian Wagner and Josef Zechner
An Anatomy of the Market Return. Journal of Financial Economics (2019) 132, 325-350
(Almost) Model-Free Recovery. Journal of Finance (2019) 74, 323-370, with Fabio Trojani
Divergence and the Price of Uncertainty. Journal of Financial Econometrics (2018) 9, 1-56, with Fabio Trojani
The Economic Value of Predicting Bond Risk Premia: Can Anything Beat the Expectations Hypothesis. Journal of Empirical Finance (2016) 37, 247-267, with Lucio Sarno and Christian Wagner
Generalized Risk Premia. Journal of Financial Economics (2015) 116, 487-504
Asset Pricing with Nonlinear Risk Premia. Journal of Financial Econometrics (2014) 12, 479-506, with Aleksandar Mijatovic
The Skew Risk Premium in the Equity Index Market. Review of Financial Studies (2013) 26, 2174-2203, with Roman Kozhan and Anthony Neuberger
Density Approximations for Multivariate Affine Jump-Diffusion Processes. Journal of Econometrics (2013) 176, 93-111, with Damir Filipovic and Eberhard Mayerhofer
Properties of Foreign Exchange Risk Premia. Journal of Financial Economics (2012) 105, 279-310, with Lucio Sarno and Christian Wagner
Flexing the Default Barrier. Quantitative Finance (2011) 11, 1729-1743, with Gregor Dorfleitner and Tanja Veza
Bayesian Inference of Discretely Sampled Markov Processes with Closed-Form Likelihood Expansions. Journal of Financial Econometrics (2010) 8, 450-480, with Osnat Stramer and Matthew Bognar
Globally Optimal Parameter Estimates for Nonlinear Diffusion Processes with Expected Likelihood. Annals of Statistics (2010) 8, 215-245, with Aleksandar Mijatovic
The Economic Role of Jumps and Recovery Rates in the Market for Corporate Default Risk. Journal of Financial and Quantitative Analysis (2010) 45, 1517-1547, with Leopold Soegner and Tanja Veza
Pricing Options with Green's Functions when Volatility, Interest Rate, and Barriers Depend on Time. Quantitative Finance (2008) 8, 119-133, with Gregor Dorfleitner, Arne Buch and Kurt Hawlitschek
Useful Stuff
Latex Templates
JF2018 A template for preparing an accepted paper for publication in the Journal of Finance. Reuses parts of Richard Stanton's packages. Contains a main text as well as an internet appendix with examples of equations, figures, and references.
JFE2018 My paper 'An Anatomy of the Market Return' which was accepted by the copy editor of the Journal of Financial Economics. Contains a main text as well as an internet appendix. Note that the first submission to the copy editor must be made single page which you can achieve by commenting the first line and un-commenting the second line in the main document JFEmaintext.tex
R Packages
DIconvex, with Liudmila Karagyaur. Ever worked with cross sections of options and wondering whether bid ask spreads admit at least one arbitrage-free path of option prices? Look no further. DIconvex maximizes the number of options you can keep such that at least one set of monotonic and convex prices exists within bid ask spreads. A mixed integer linear program does all the work. Fast, scalable and robust.