This is the set of homework I did for Computational Investing Part 1 (https://www.coursera.org/course/compinvesting1)
Why do the prices of some companies’ stocks seem to move up and down together while others move separately? What does portfolio “diversification” really mean and how important is it? What should the price of a stock be? How can we discover and exploit the relationships between equity prices automatically? We’ll examine these questions, and others, from a computational point of view. You will learn many of the principles and algorithms hedge funds and investment professionals use to maximize return and reduce risk in equity portfolios.
Week 1 Module 1: Course Overview Video 11*: Learning objectives of for the course [*need to reshoot to emphasize programming difficulty] Who is this course for? Logistics Instructor background Module 2: So you want to be a fund manager? Video 21: Module learning objectives Viewpoint of course Incentives for portfolio managers Two main types of hedge fund Video 22: Common metrics for assessing fund performance Annual return Risk Reward/Risk Video 23: Common metrics for assessing fund performance Sharpe Ratio Video 24: Demo Download historical data Manipulate historical data in Excel Module 3: Market Mechanics Video 31: Module objectives Major order types The order book How market orders drive prices up and down Live example Video 32: Order book recap How orders flow from trader to execution Colocated computing Mechanics of short selling Video 33: How hedge funds exploit market mechanics Order book-based trading Arbitrage Video 34: The computing inside a hedge fund Trading algos Optimizers Forecasters Module 4: Interview with Paul Jiganti Video 310: How your order gets to the market Part 1 Video 320: How your order gets to the market Part 2 Video 330: What happened with Knight Capital QUIZ: Market Mechanics
Week 2
Module 1: What is a Company Worth?
Video 41: Intrinsic value: Value of future dividends
Video 42: How and why news affects prices (Event Study)
Video 43: Fundamental analysis of company value
Module 2: Capital Assets Pricing Model
Video 71: Capital Assets Pricing Model
Video 72: CAPM: What is Beta
Video 73: How Hedge Funds use CAPM
Module 3: QSTK Software Overview
Video 61*: QSTK software overview
Video 63: Installing QSTK on a Mac
Video 81: Installing QSTK on Windows and testing QSTK on Windows
Module 4: Working with Historical Data* [need to add this module. Daily returns, cumulative returns, etc.]
Homework 0: Install QSTK
Week 3
Module 1: Manipulating Data in Python with Numpy
Video 51: Numpy Part 1
Video 52: Numpy Part 2
Video 53: Numpy Part 3
Module 2: Manipulating Data in QSTK
Video 171: QSTK Part 1
Video 172: QSTK Part 2
Video 173*: QSTK Part 3 [*show how to do major steps for HW1, discuss cached data]
Module 3: Homework 1: Analyze and Optimize a Portfolio
Video 181: Homework 1 Overview
Video 182: Homework 1 Excel example
Module 4: Interview with Tom Sosnoff
Video 340: Sosnoff Part 1
Video 350: Sosnoff Part 2
Video 360: Sosnoff Part 3
Homework 1: Create and analyze a portfolio
Week 4
Module 1: Efficient Markets Hypothesis and Event Studies
Video 91: Where does information come from? Arbitrage: Difference between real value and market price
Video 92: 3 Versions of Efficient Markets Hypothesis. Is EMH True?
Video 93: Event Studies
Video 94*: Event Studies Code Demo. Homework 2 Defined. (uses old code)
Module 2: Portfolio Optimization and the Efficient Frontier
Video 111: Module Objectives and Overview
Video 112: The Inputs and Outputs of a Portfolio Optimizer
Video 113: The Importance of Correlation and Covariance (in daily returns)
Video 114: The Efficient Frontier
Video 115: How Optimizers Work (In general, not just for portfolios)
Homework 2: Event Studies Week 5
Module 1: Digging Into Data
Video 121: Module Objectives and Overview (Review of the "Correct Answers" to the $5 Event Studies, Survivor Bias)
Video 122: Actual vs Adjusted Prices (Dividends & Splits)
Video 123: Data Scrubbing (Checking for Sanity)
Module 2: Overview of Homework 3
Video 131: How Next Two Homeworks Fit Together
Video 132: Specification for Homework 3
Video 133: Suggestions on Implementation of Homework 3
Homework 3*: Build a Market Simulator [clean up example data CSVs]
Week 6
Module 1: Overview of Homework 4
Video 161: Review of How to Assess Event Study
Video 162: Overview of Homework 4
Module 2: The Fundamental Law
Video 151: Coin Flipping
Video 152: Fundamental Law Part 1
Video 153: Fundamental Law Part 2
Module 3: CAPM for Portfolios: Managing Market Risk
Video 141: CAPM recap, overview for portfolios
Video 142: Example use of CAPM for long/short bet removing market risk
Homework 4: Event Study into Simulator
Week 7
Module 1: Information Feeds and Technical Analysis
Video 191: Example Information Feeds
Video 192: Intro to Technical Analysis
Video 193: Some Example Technical Indicators
Video 194: Bollinger Bands
Homework 5: Implement Bollinger Bands
Week 8
Module 1: Making a Better Market Simulator
Commissions
Market Impact (Slippage)
Module 2: Brief Introduction to Machine Learning
Parameterized models
Instance based models
Module 3: Arbitrage
Homework 6: Event Study with Bollinger Bands
Homework 7: Bollinger Band-based trading
Copyright 2013-2014 Varad Meru Released under the MIT and GPL Licenses.