• Analyzing each of the trading strategies covered in class, both conceptually, mathematically, and empirically using data.
• Understanding why strategies might work, and why they might not.
• Computing performance measures and critically evaluate the output.
• Simulating backtests of investment strategies.
• Computing execution costs, liquidity measures, and deriving the net returns in a backtest.
• Computing margin requirements, an investment strategy’s capital use, including knowledge of when it would receive a margin call.
• Applying regression analysis, including in return forecasting
• Identifying biases, including being able to avoid such pitfalls as look-ahead bias, selection bias, and survivorship bias.
• Knowledge of the historical events connected to asset management, hedge funds, and markets covered in class.
• Working independently on projects involving mathematical analysis and data analysis
• Generalizing arguments, methods, and concepts to problems that have not been analyzed explicitly throughout the course.
• Ability to reason independently about strategies that go beyond what is discussed explicitly in class, e.g., analyze the effects of a novel type of corporate action.

The class describes some of the main investment strategies used by active investors such as investment management firms, asset management divisions in banks, hedge funds, and proprietary traders. Further, the class provides a methodology to analyze these investment strategies. In class and through exercises, the strategies are illustrated using real data and students learn to use “backtesting” to evaluate a strategy. The class also covers institutional issues related to liquidity, margin requirements, risk management, and performance measurement.
 
The class discusses the main strategies used by active investors in individual equity markets (equity long-short, equity market neutral, dedicated short bias), in tactical asset allocation of equity indices, currencies, fixed-income, and commodities (global macro, managed futures), and in relative-value arbitrage strategies (event driven investments, convertible bond arbitrage, fixed income arbitrage).
 
To analyze these active investment strategies, the class applies tools for performance measurement, backtesting, regression analysis, managing transaction costs, market liquidity risk, funding a strategy, margin requirements, risk management, drawdown control, and portfolio optimization. Also, the class discusses the economics underlying these strategies, why certain strategies might work and why others might not.

The class is quantitative. As a result of the techniques used in state-of-the-art investments, the class requires the students to work independently, analyze and manipulate real data, and use mathematical modeling.

The course aims at teaching a broad set of active investment strategies from a rigorous academic perspective. The class is based on a recent book written by prof. Lasse Heje Pedersen titled “Efficiently Inefficient: How Smart Money Invests and Market Prices Are Determined.”; Princeton University Press, 2015, and may be supplemented with additional papers and/or case studies.