Swiss Finance Institute @ EPFL

The Swiss Finance Institute @ EPFL has been created to foster research in finance and to develop a strong offering of programs in finance and financial engineering at the Ecole Polytechnique Fédérale de Lausanne. The focus is on the areas within finance that have a natural interaction with mathematics, statistics, engineering, and science, namely, mathematical finance, financial econometrics, and entrepreneurial finance.

The Swiss Finance Institute @ EPFL participates in two teaching programs, The Master in Financial Engineering at EPFL, which is a highly selective 2-year master program, and The PhD in Finance, which is organized jointly with the Swiss Finance Institute and the Universities of Geneva and Lausanne.

The Swiss Finance Institute @ EPFL benefits from the institutional support of the Swiss Finance Institute, a private foundation created in 2006 by Switzerland’s banking and finance community in cooperation with leading Swiss universities, and from Swissquote, who endowed the Swissquote Chair in Quantitative Finance.

The macroeconomics of announcement premium

Empirically, a large fraction of the market equity premium is realized immediately upon macroeconomic announcements, such as the FOMC announcements and the unemployment report. In contrast, macroeconomic quantities respond slowly to these announcements. We show  that the joint behavior of the reactions of capital markets and macroeconomic quantities with respect to macro announcements imposes strong restrictions on  the specification of preferences in macro and finance models. We present a quantitative general equilibrium model to jointly account for the announcement  premium in time series and in the cross section, as well the impulse responses of macroeconomic quantities with respect to these announcements.

By: Hengjie AI, Carlson School of Management, University of Minnesota

Career Risk and Market Discipline in Asset Management

We establish that the labor market helps discipline asset managers via the impact of fund liquidations on their careers. Using hand-collected data on 1,948 professionals, we find that top managers working for funds liquidated after persistently poor relative performance suffer demotion coupled with a significant loss in imputed compensation. Scarring effects are absent when liquidations are preceded by normal relative performance or involve mid-level employees. Seen through the lens of a model with moral hazard and adverse selection, these scarring effects can be ascribed to a drop in asset managers' reputation. The  findings suggest that performance-induced liquidations supplement compensation-based incentives.

By: Marco PAGANO, University of Naples Federico II, CSEF and EIEF

The Anatomy of a Cryptocurrency Pump-and-Dump Scheme

While pump-and-dump (P&D) schemes have attracted the attention of cryptocurrency observers and regulators alike, this paper is the first detailed study of P&D activities in cryptocurrency markets. We present a case study of a recent P&D event, investigate 220 P&D activities organized in Telegram channels from July 21, 2018 to November 18, 2018, and discover patterns in crypto-markets associated with P&D schemes. We then build a model that predicts the pump likelihood of all coins listed in an crypto-exchange prior to a pump. The model exhibits high precision as well as robustness, and can be used to create a simple, yet very effective trading strategy, which we empirically demonstrate can generate a return as high as 80% on small retail investment within a span of three weeks.
 

By: Java XU, PhD Candidate at Harvard Graduate School of Arts and Sciences and Institute of Insurance Economics I.VW-HSG


 

Swissquote Conference 2018 on Machine Learning in Finance

The ninth annual Swissquote Conference on Machine Learning in Finance took place at EPFL on 9 November 2018. The conference featured current research and insights on machine learning in finance provided by leading experts from academia a