Quantitative Portfolio Management. Michael Isichenko

      

      Table of Contents

      1  Cover

      2  Title Page

      3  Copyright

      4  List of Figures

      5  Code Listings

      6  Preface

      7  About this Book

      8  Abstract

      9  Acknowledgments

      10  Introduction

      11  Chapter 1: Market Data 1.1 Tick and bar data 1.2 Corporate actions and adjustment factor 1.3 Linear vs log returns

      12  Chapter 2: Forecasting 2.1 Data for forecasts 2.2 Technical forecasts 2.3 Basic concepts of statistical learning 2.4 Machine learning 2.5 Dynamical modeling 2.6 Alternative reality 2.7 Timeliness-significance tradeoff 2.8 Grouping 2.9 Conditioning 2.10 Pairwise predictors 2.11 Forecast for securities from their linear combinations 2.12 Forecast research vs simulation

      13  Chapter 3: Forecast Combining 3.1 Correlation and diversification 3.2 Portfolio combining 3.3 Mean-variance combination of forecasts 3.4 Combining features vs combining forecasts 3.5 Dimensionality reduction 3.6 Synthetic security view 3.7 Collaborative filtering 3.8 Alpha pool management

      14  Chapter 4: Risk 4.1 Value at risk and expected shortfall 4.2 Factor models 4.3 Types of risk factors 4.4 Return and risk decomposition 4.5 Weighted PCA 4.6 PCA transformation 4.7 Crowding and liquidation 4.8 Liquidity risk and short squeeze 4.9 Forecast uncertainty and alpha risk

      15  Chapter 5: Trading Costs and Market Elasticity 5.1 Slippage 5.2 Impact 5.3 Cost of carry 5.4 Market-wide impact and elasticity

      16  Chapter 6: Portfolio Construction 6.1 Hedged allocation 6.2 Forecast from rule-based strategy 6.3 Single-period vs multi-period mean-variance utility 6.4 Single-name multi-period optimization 6.5 Multi-period portfolio optimization 6.6 Portfolio capacity 6.7 Portfolio optimization with forecast revision 6.8 Portfolio optimization with forecast uncertainty 6.9 Kelly criterion and optimal leverage 6.10 Intraday optimization and execution

      17  Chapter 7: Simulation 7.1 Simulation vs production 7.2 Simulation and overfitting 7.3 Research and simulation efficiency 7.4 Paper trading 7.5 Bugs

      18  Afterword: Economic and Social Aspects of Quant Trading

      19  Appendix