ruscigno/computational-investing-pt-1

The HW code

COMPUTATIONAL INVESTING HOMEWORK

This is the set of homework I did for Computational Investing Part 1 (https://www.coursera.org/course/compinvesting1)

COURSERA'S COMPUTATIONAL INVESTING PART-1 COURSE

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.

SYLLABUS

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 

LICENSE

Copyright 2013-2014 Varad Meru Released under the MIT and GPL Licenses.