Finding Alphas

Name: Finding Alphas | A Quantitative Approach to Building Trading Strategies
Brand: Wiley
Price: 37.99 EUR
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A Quantitative Approach to Building Trading Strategies

Igor Tulchinsky(Herausgeber*in)

Wiley (Verlag)

2. Auflage

Erschienen am 1. Oktober 2019

320 Seiten

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978-1-119-57125-4 (ISBN)

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Beschreibung

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Inhalt

Cover
Title Page
Copyright
Contents
Preface
Preface (to the Original Edition)
Acknowledgments
About the WebSim Website
PART I Introduction
1 Introduction to Alpha Design
Designing Alphas Based on Data
Defining Quality in Alphas
Alpha Construction, Step By Step
Conclusion
2 Perspectives on Alpha Research
PHDS on the Street
A New Industry
Statistical Arbitrage
Existence of Alphas
Implementation
Evaluation
Looking Back
The Opportunity
3 Cutting Losses
How to Apply the Principle of the Unrule to Cutting Losses
Summary
Part II Design and Evaluation
4 Alpha Design
Data Inputs to an Alpha
Alpha Universe
Alpha Prediction Frequency
Value of an Alpha
Practical Alpha Evaluation
Future Performance
Conclusion
5 How to Develop an Alpha: A Case Study
Conclusion
6 Data and Alpha Design
How we find Data for Alphas
Data Validation
Understand the Data Before Using it
Embrace the Big Data ERA
Conclusion
7 Turnover
Alpha Horizon
The Cost of a Trade
The Crossing Effect
Controlling Turnover
Examples
Tuning the Turnover
8 Alpha Correlation
Alpha PnL Correlation
Alpha Value Correlation
Correlation with Alpha Pool
Conclusion
9 Backtest - Signal or Overfitting?
Introduction
Statistical Arbitrage
Backtesting
Overfitting
How to Avoid Overfitting
Conclusion
10 Controlling Biases
Introduction
Categories of Bias
Systematic Biases
Behavioral Biases
Conclusion
11 The Triple-Axis Plan
The Tap
Implementing TAP
Conclusion
12 Techniques for Improving the Robustness of Alphas
Introduction
Methods for Robustness Improvement
Conclusion
13 Alpha and Risk Factors
14 Risk and Drawdowns
Estimating Risks
Drawdowns
Controlling Risks
Conclusion
15 Alphas from Automated Search
Efficiency and Scale
Input Data Should Not Come from Too Many Categories
Input Data and Unitless Ratios
Unnecessary Search Space
Intermediate Variables
Seas of Alphas, Not Single Alphas
Simple Alphas
Longer Backtesting Periods
Alpha Batch, Not Single Alpha Performance
Diversify the Alpha Batch
Sensitivity Tests and Significance Tests
Manual Alpha Search
Conclusion
16 Machine Learning in Alpha Research
Introduction
Machine Learning Methods
Conclusion
17 Thinking in Algorithms
Digital Filters
Optimization and Loss Function Design
The Bias-Variance Trade-Off
Dimensionality Reduction
Shrinkage Estimators
Parameter Optimization
Conclusion
Part III Extended Topics
18 Equity Price and Volume
Introduction
Seeking Profits Through Price and Volume
Conclusion
19 Financial Statement Analysis
Basics
The Balance Sheet
The Income Statement
The Cash Flow Statement
Growth
Corporate Governance
Negative Factors
Special Considerations
Factors as Screens
Converting Factors to Alphas
Conclusion
20 Fundamental Analysis and Alpha Research
Financial Statements
Financial Statement Analysis
Conclusion
21 Introduction to Momentum Alphas
Conclusion
22 The Impact of News and Social Media on Stock Returns
Introduction
News in Alphas
Academic Research
Sentiment
Novelty
Relevance
News Categories
Expected and Unexpected News
Headlines and Full Text
No News is Good News?
News Momentum
Social Media
Conclusion
23 Stock Returns Information from the Stock Options Market
Introduction
Volatility Skew
Volatility Spread
Options Trading Volume
Option Open Interest
Conclusion
24 Institutional Research 101: Analyst Reports
Accessing Analyst Research (For free, of Course)
So far, So Good. But Why should You Care?
Things to Watch Out for in Reading Analyst Reports
Why Do Stock Analysts Talk to the Financial Media?
Conclusion
25 Event-Driven Investing
Introduction
Merger Arbitrage
Spin-Offs, Split-Offs, and Carve-Outs
Distressed-Asset Investing
Index-Rebalancing Arbitrage
Capital Structure Arbitrage
Conclusion
26 Intraday Data in Alpha Research
Data in Market Microstructure
The Illiquidity Premium in Asset Prices
Market Microstructure and Expected Returns
Conclusion
27 Intraday Trading
Daily Trading Versus Intraday Trading
Different Types of Intraday Alphas
Making an Intraday Alpha
Conclusion
28 Finding an Index Alpha
Index Arbitrage in Practice
Market Impact from Index Changes
Other Index Anomalies
Conclusion
29 ETFs and Alpha Research
Merits of Investing in ETFS
Risks Behind These Instruments
Alpha Opportunities
Challenges in ETF Alpha Research
Conclusion
30 Finding Alphas on Futures and Forwards
Key Market Features
Underlying Factor Exposure
Consequences of Instrument Grouping
Basic Checklist for Alpha Testing
Conclusion
Part IV New Horizon - WebSim
31 Introduction to WebSim
Introduction
Why WebSim was Developed
How WebSim Is Used Globally
Who Uses WebSim
Where Alpha Ideas Come From
Sample Data Types
Creating an Alpha
Managing Simulation Settings
Analyzing Results
An Alpha Example
Conclusion
Part V A Final Word
32 The Seven Habits of Highly Successful Quants
1. Work Hard Without Even Realizing it
2. Set Ambitious Long-Term Targets but Attainable Weekly Goals
3. Prioritize Based on Risk and Reward
4. Stay Curious
5. Perform Value-Added Work - And Automate, Automate, Automate
6. Make Sensible Changes, and Beware of Overfitting
7. Form Synergistic Teams
References
Index
EULA

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