The purpose of this course is to equip you with the knowledge required to comprehend the financial statements of a company and understand the various transactions that take place in the stock market so that you can replicate the strategies discovered by the extant academic literature. The first part of the course provides a brief introduction to financial statements and various common filings of firms. You will learn how to obtain information regarding a company's performance from them and use the information to build trading strategies. Next, you are taught basic asset pricing theories so that you will be able to calculate the expected returns of a stock or a portfolio. Finally, you will be introduced to the actual functioning of asset markets, type of players in the market, different types of orders and the efficient ways and opportune time to execute them, trading costs and ways of minimizing them, the concept of liquidity .etc. This knowledge is required to develop efficient algorithm to execute various trading strategies.

This course covers two of the seven trading strategies that work in emerging markets. The seven include strategies based on momentum, momentum crashes, price reversal, persistence of earnings, quality of earnings, underlying business growth, behavioral biases and textual analysis of business reports about the company. In the first part of the course, you will learn how to read an academic paper. What parts to pay attention to and what parts to skim through will be discussed here. For every strategy, first you will be introduced to the original research and then how to implement the strategy. The first strategy, Piotroski F -score will be discussed in detail. You will be taught how to calculate the F - Score and how to use this score in a strategy. This is followed by the next strategy, Post earnings announcement drift (PEAD).

This course will provide back test results for all the strategies in developed and emerging markets. The learner will also be taught scientific ways of back testing without succumbing to either look ahead (or) survival bias. You will learn various methods of building a robust back testing system for the strategies discussed in the previous course. You will be taught how to differentiate between mere data mining and results based on solid empirical or theoretical foundation. Next, you will learn the ways and means of back testing the results and subjecting the back test results to stress tests. After which, you will learn the various ways in which transaction costs and other frictions could be incorporated in the back testing algorithm. Finally, you will learn techniques for measuring a strategies' performance and the concept of risk adjusted return. You will use some of the famous measures for risk adjusted returns such as Sharpe ratio, Treynor's Ratio and Jenson's Alpha. You will see how to pick an appropriate benchmark for a proposed fund.

This course integrates all the learning from the first three courses and guides the learner about ways of building a portfolio of strategies and integrating the same into a hedge fund. In the first part of the course, you will be taught ways of measuring the contribution of a strategy to a portfolio in terms of risk and return. You will be able to appreciate the consequences of including a strategy to a new as well an existing portfolio. Next, you are taught various ways of conducting the tilting analysis in order to determine the optimal weight to be placed on each strategy. After this you will learn to develop techniques for minimizing overall portfolio risk. You will also get a basic overview of the regulatory framework that is applicable to hedge funds. You will know about different types of investors and the expectations of each type of investors.