Selected Course Syllabi

Global Asset Allocation and Management

Prof. Tony Berrada, Prof. Ines Chaieb

The objective of this course is to understand the process of portfolio construction and acquire skills to implement these processes. As globalization is a major trend affecting the asset management industry, we will also discuss international diversification of portfolios and currency hedging. Should investors invest globally? What would happen if all investors diversified their portfolios internationally? Do investors actually invest globally? Are there special diversification opportunities for international investors for example from investing in partially integrated markets such as emerging financial markets?
Traditional asset management focuses on equities and fixed income. In this course, we will also discuss currencies as an asset class and explore carry trade strategies.

Risk Management in Private Banking

Dr. Michel Crouhy, Prof. Dan Galai, Prof. Olivier Scaillet, Prof. Fabio Trojani

The objective of this course is to provide an overall presentation of best practice and acquire key data-analytic tools for risk management. In a first step, the course discusses Risk Management in Private Banking in light of what has been learned from past disasters such as Orange County and Long-Term Capital Management (LTCM) as well as the subprime and sovereign debt crises. We present the typology of risk types and the various potential exposures of companies to types of uncertainties, for both financial as well as non-financial corporations whose debt and equity constitute the main assets of investment portfolios. We address wealth management, corporate governance issues, liquidity risk in periods of market turmoil and, finally, financing and risk management issues specific to start-up.

In a second step, the course emphasizes risk-modelling tools used in the industry to monitor risks both at the bank level and at the client level in wealth management. A crucial theme is the modelling and measuring of the dependence among risks. Using an intuitive teaching approach with interactive training sessions based on case studies solved through a web platform allowing for online data analysis, we explain key data-analytic tools for risk management in a non-technical way and we demonstrate their application in selected real-data problems.

Wealth Management in Practice

Dr. Michel Girardin, Prof. Jean-Charles Rochet

The objective of this course is to know how to define an investment policy based on the clients’ needs and objectives and, thanks to on-site visits and practical illustration, to be introduced to how Wealth Management is carried out in the Swiss Private Banking industry, with special emphasis on the New trends such as Impact Investing, Robo-advisors and Behavioral / Neuro-finance.

Specifically, we will address the goals of private clients (High and Ultra-High Net Worth Individuals) and see how they may differ from those of institutional clients (Corporate firms and Pension Funds). Once we define the optimal strategic asset allocation, and provide a toolkit on the best measures of investments’ risk-adjusted returns which enable the portfolios’ performance analysis and attribution.

Data Analysis and Advanced Modeling for Finance

Prof. Olivier Scaillet, Prof. Fabio Trojani

The objective of this course is to understand the underlying instruments and the application of various quantitative investment strategies, which are consistently used by modern professional investors to optimize the risk-return trade of in wealth management. We introduce important data-analytic tools for measuring existing risk-return trade-offs in financial markets. We adopt an intuitive teaching approach supported by interactive training sessions on a web platform. In this way, we explain the properties of key data-analytic tools for portfolio management in a non-technical way, and we demonstrate their practical relevance in selected real-data problems.

The first part of the course introduces important types of financial data structures and their properties. In the second part of the course, we focus on different linear models, highlighting return predictability structures that might be difficult to detect in periods of distressed financial markets, the identification of "smart" risk-premium components in cross-sections of assets, and the joint return dynamics of bond of different maturities. The third part addresses the measurement, the modeling and the prediction of time-varying financial risks. The fourth part of the course focuses on practically relevant nonparametric methods to characterize the joint randomness of returns and volatilities and to uncover potentially nonlinear predictability structures for returns.

Alternative Investments

Prof. Rajna Gibson Brandon, Prof. Harald Hau, Prof. Martin Hoesli, Prof. Philipp Krueger

The objective of this course is to present the main characteristics, valuation and performance attributes of three important categories of alternative investments, namely hedge funds, private equity and sustainable investments.

The first part presents the main strategies used by hedge funds, analyze their risk-return trade-offs and assess their ability to generate positive performance (alpha). The course will draw on the most recent academic research on hedge funds and its relation to industry practice. Additionally, some empirical case studies conducted by the students will help them to get familiar with this specific type of alternative investments. The second part will discuss how and when private equity investors can create shareholder value by restructuring and reorganization for both profitable and distressed corporations. The emphasis will be on understanding the source of value creation or value transfer for the private equity firm. Finally, the course will explore how sustainability issues are incorporated into traditional investment management and how sustainability relates to environmental, social, and governance (ESG) issues. Students will also be exposed to recent product innovations and carry out an empirical case study learning how sustainability data can be used in portfolio construction.