CHAPTER 1: CHOOSING YOUR PRODUCT
BOX 1-3: CASE STUDY: INCENTIVES ALIGNMENT MODEL
BOX 1-4: CASE STUDY: “WHAT ARE THE HIDDEN COSTS OF GATES, LOCKUPS, AND SETTLEMENT PERIODS?”
CHAPTER 2: THE INVESTMENT PROCESS
CHAPTER 3: LEADERSHIP AND GOVERNANCE
- Examples of a business case will appear in my next book. For copyright reasons, it is available only by request.
- Examples of an investment policy statement will appear in my next book. For copyright reasons, it is available only by request.
- Examples of investment due diligence will appear in my next book. For copyright reasons, it is available only by request.
CHAPTER 4: ASSET TYPES
BOX 4-1: VXX VS. VIX
FIGURE 4-3: ILLIQUID ASSETS CONSTRAIN OTHER ALLOCATIONS
BOX 4-2: A CRYPTOCURRENCY ARBITRAGE EXAMPLE
CHAPTER 5: FINANCIAL DATA
ORGANIZING FINANCIAL DATA
- LARGE FILES AND BIG DATA https://www.mathworks.com/help/matlab/large-files-and-big-data.html
- SPLAYED DATA (CODE)
- SPLAYED DATA (DESCRIPTION) https://thinqkdb.wordpress.com/splayed-tables/
CAPITAL MARKETS ASSUMPTIONS
- FIDUCIENT CAPITAL MARKETS ASSUMPTIONS
- CODE TO CONVERT FIDUCENT CMAS TO OPTIMIZER INPUTS https://www.mathworks.com/matlabcentral/fileexchange/130689-scrape-fiducient-capital-markets-assumptions-and-other-table
- BLACKROCK CAPITAL MARKETS ASSUMPTIONS https://www.blackrock.com/institutions/en-us/insights/charts/capital-market-assumptions
- JPMORGAN CAPITAL MARKETS ASSUMPTIONS https://am.jpmorgan.com/us/en/asset-management/institutional/insights/portfolio-insights/ltcma/?gad=1&gclid=Cj0KCQjwj_ajBhCqARIsAA37s0yI3ylON-h7LtUJG-reVtYAdwZXUyanXLrLqo8WNuNANmSgiRcUfLsaAnTdEALw_wcB&gclsrc=aw.ds
ECONOMIC DATA
– NON-ARCHIVAL DATA
- BLOOMBERG ECONOMIC DATA
- CAPITIALIQ ECONOMIC DATA
- REFINITIV ECONOMIC DATA
– ARCHIVAL DATA
- ALFRED ECONOMIC DATA https://alfred.stlouisfed.org/
BULK AND DESCRIPTIVE DATA
- MORNINGSTAR DESCRIPTIVE DATA www.morningstar.com (Morningstar access is available in the business library on campus)
- BLOOMBERG DESCRIPTIVE DATA www.bloomberg.com (Bloomberg terminals are easy to find all over campus)
- REFINITIV DESCRIPTIVE DATA www.refinitiv.com (Refinitiv terminals can be download on your computer from the Columbia library website).
FUNDAMENTAL DATA
- BLOOMBERG FUNDAMENTAL DATA www.bloomberg.com
- PARSE BLOOMBERG PORT HOLDINGS TREND DATA (CODE) https://www.mathworks.com/matlabcentral/fileexchange/132358-parse-bloomberg-port-holdings-trend-report
- EDGAR FUNDAMENTAL DATA https://www.sec.gov/edgar/search-and-access
- CRSP/COMPUSTAT MERGED DATABASE – FUNDAMENTALS QUARTERLY https://wrds-www.wharton.upenn.edu/pages/get-data/center-research-security-prices-crsp/annual-update/crspcompustat-merged/fundamentals-quarterly/
- CRSP/COMPUSTAT MERGED – FUNDAMENTALS ANNUAL https://wrds-www.wharton.upenn.edu/pages/get-data/center-research-security-prices-crsp/quarterly-update/crspcompustat-merged/fundamentals-annual/
- CRSP/COMPUSTAT FUNDAMENTAL FIELDS
SURVEY DATA
SAMPLING AND SYNTHETIC DATA
- OVER- AND UNDERSAMPLING (E.G. SMOTE) SCRIPT
- GIBBS SAMPLER FOR HIGH-FREQUENCY GDP AND PREDICTION
MARKET DATA
- 3,500 ETF INVESTMENT UNIVERSE
- BLOOMBERG ADJUSTED PRICES https://www.mathworks.com/matlabcentral/fileexchange/130684-load-adjusted-prices-from-bloomberg
- BLOOMBERG ADJUSTED PRICES SCRIPT https://www.mathworks.com/matlabcentral/fileexchange/130729-load-large-bloomberg-excel-data-file
- LOAD LARGE BLOOMBERG EXCEL DATA FILE SCRIPT
- CRSP ADJUSTED PRICES
- CRSP ADJUSTED PRICES AND TOTAL RETURNS TO PRICESTT SCRIPT https://www.mathworks.com/matlabcentral/fileexchange/130674-crsp-to-matlab-adjusted-prices-and-total-returns
- YAHOO! ADJUSTED PRICES
- YAHOO! ADJUSTED PRICES SCRIPT https://www.mathworks.com/matlabcentral/fileexchange/130679-download-yahoo-adjusted-prices
- MORNINGSTAR ADJUSTED PRICES
- MORNINGSTAR ADJUSTED PRICES SCRIPT
- YCHARTS ADJUSTED PRICES
- YCHARTS ADJUSTED PRICES SCRIPT
MODEL PORTFOLIO HISTORY
- 101 ROBOADVISORS
- PROPRIETARY MODELS
- MARKET IMPLIED PORTFOLIOS
- BENCHMARK AND MODEL PERFORMANCE HISTORY
- ROLLING RETURNS AND YEARLY RETURNS SCRIPT https://www.mathworks.com/matlabcentral/fileexchange/130974-rolling-returns-and-yearly-returns
BENCHMARK HISTORY
- S&P 500 CONSTITUENT HISTORY
- MSCI ALL COUNTRY WORLD INDEX (ACWI ) CONSTITUENT HISTORY
- MSCI ALL COUNTRY WORLD INDEX (ACWI) SECTOR AND GEOGRAPHIC HISTORY
- PREQIN PRIVATE EQUITY DATA https://wrds-www.wharton.upenn.edu/pages/get-data/preqin/private-equity/
- PREQIN VENTURE CAPITAL DATA https://wrds-www.wharton.upenn.edu/pages/get-data/preqin/venture-capital/
MISSING DATA
SAMPLING AND SYNTHETIC DATA
BOX 5-2: USING A GIBBS SAMPLER TO CHANGE FREQUENCY
BOX 5-3: ROLL EXAMPLE
BOX 5-5 CASE STUDY: RIA DATA
- MTSS-GAN Derek Snow, MTSS-GAN”
- Time GAN: TimeGAN/tutorial_timegan.ipynb at master ú jsyoon0823/TimeGAN ú GitHub
- Cholesky Method https://www.mathworks.com/help/finance/portsim.html
- Monte Carlo with Copulas: https://www.mathworks.com/help/stats/copulas-generate-correlated-samples.html
HIGH FREQUENCY AND BIG DATA
- NYSE TAQ https://wrds-www.wharton.upenn.edu/pages/get-data/nyse-trade-and-quote/
- KDB+ 4/5 COLUMN UPLOAD SCRIPT
- HIGH-FREQUENCY TRANSACTIONS USING DATASTORE, TALL ARRAYS, AND THE KDB+ API”
- KDB+ WRDS/TAQ UPLOAD SCRIPT
CHAPTER 6: FEATURES
- SECTOR AND GEOGRAPHIC MAPS
- INFLATION PROTECTION FEATURES
- DIVIDEND GROWTH FEATURES
- QUALITY GROWTH FEATURES
- ESG FEATURES
- FIXED INCOME FEATURES
- TAX-LOSS HARVESTING FEATURES
“PREPROCESSING, MISSING DATA, & OUTLIERS”
- MISSING AND MINORITY DATA GENERATION USING BORDERLINE SMOTE
FEATURE EXTRACTION
TEMPORAL TRANSFORMATIONS
SYNTHETIC DATA GENERATION
- TIME-GANN SYNTHETIC FINANCIAL DATA GENERATION FOR MONTE CARLO ANALYSIS
CHAPTER 7: FINANCIAL AND ECONOMIC FACTORS
FEATURE COMPLEXITY AND HIERARCHY
- FOOTNOTE 4 & FIGURE 7-1: LAYERING MODELS IN AN ECONOMICALLY INTUITIVE HIERARCH
DESCRIPTIVE FEATURES
BLOOMBERG DESCRIPTIVE FEATURES
MORNINGSTAR DESCRIPTIVE FEATURES
ECONOMIC FEATURES
- FOOTNOTE 8: GIBBS SAMPLER
CROSS-ASSET FEATURES
ASSET AND MARKET FEATURES
- FOOTNOTE 17: ECONOMIC SURPRISE
ALTERNATIVE FEATURES
EXECUTION FEATURES
FEATURE CONDITIONING AND TIMING
FACTOR EFFICACY
MECHANISTIC TRANSFORMATIONS
CHAPTER 8: CREATING FACTOR FORECASTS
CAPITAL MARKETS ASSUMPTIONS
STRATEGIC FORECASTING
TACTICAL FORECASTING
RISK PREMIA
FIXED INCOME PREMIA
- FOOTNOTE 13: PAR YIELD CURVE
EQUITY PREMIA
OTHER PREMIA
CHAPTER 9: STRATEGY, OBJECTIVE, & CONDITIONS
REMOVING TIME DEPENDENCE
FIXED HORIZON VERSUS PATH DEPENDENCY
“ALLOCATION, SELECTION, DIRECTION, TIMING, AND QUANTITY”
CHAPTER 10: TIME SERIES & CROSS-SECTIONAL ANALYSIS
- ECONOMETRICS MODELLER APP https://www.mathworks.com/help/econ/econometric-modeler-overview.html
- REGRESSION LEARNER APP https://www.mathworks.com/help/stats/regression-learner-app.html
- CLASSIFICATION LEARNER APP https://www.mathworks.com/help/stats/classificationlearner-app.html
- DEEP NETWORK DESIGNER APP https://www.mathworks.com/help/deeplearning/deep-network-designer-app.html
- REINFORCEMENT LEARNING DESIGNER APP https://www.mathworks.com/help/reinforcement-learning/ug/design-dqn-using-rl-designer.html
CHAPTER 11: ALPHA AND RISK MODELS
CHAPTER 12: ASSET ALLOCATION
- PORTFOLIO OPTIMIZATION OBJECT (INCLUDING CVAR OPTIMIZATION
- BLACK-LITTERMAN PORTFOLIO OPTIMIZATION USING FACTORS https://www.mathworks.com/help/finance/asset-allocation-and-portfolio-optimization.html
CHAPTER 13: SECURITY SELECTION
- ECONOMETRICS FOR SECURITY SELECTION
- REGRESSION LEARNER FOR SECURITY SELECTION
- CLASSIFICATION LEARNER FOR SECURITY SELECTION
- DEEP LEARNING FOR SECURITY SELECTION
- REINFORCEMENT LEARNER FOR SECURITY SELECTION
- UEC (ENVIRONMENTAL SOCIAL & GOVERNANCE (ESG) HEDGE FUND) DATA & SCREENS
CHAPTER 14: BACKTESTING
- BACKTESTING FRAMEWORK
- EMSC ORDER SIMULATION OBJECT AND TEST CODE
- ENHANCED BACKTESTING OBJECT
CHAPTER 15: TRANSACTION COSTS & FEES
- ENHANCED TCA OBJECT
- ENHANCED KX/KDB+/Q OBJECT
- TRANSACTION COST ANALYSIS DATABASE BUILDER
- TRANSACTION COST ANALYSIS FORECAST
- TRANSACTION COST ANALYSIS POST-ANALYSIS
- TRANSACTION COST ANALYSIS RECALIBRATION TOOL
CHAPTER 16: REBALANCING AND TAXES
- TAX-LOSS HARVESTING PERFORMANCE CALCULATOR
- TAX-LOSS HARVESTING TRADE RECOMMENDATION
CASE STUDY: PERFORMANCE OF THE LARGEST 101 ROBOADVISORS
CHAPTER 17: TIME SERIES & CROSS-SECTIONAL ANALYSIS
CASE STUDY: VECTOR ERROR CORRECTING (VEC) VS DYNAMIC STOCHASTIC GENERAL EQUILIBRIUM MODEL (DSGE)
- VECTOR ERROR CORRECTING (VEC)
- DYNAMIC STOCHASTIC GENERAL EQUILIBRIUM MODEL (DSGE)
CHAPTER 18: PERFORMANCE & RISK MANAGEMENT
CHAPTER 19: INVESTMENT, RISK, & CASH MANAGEMENT
CASE STUDIES
CASE STUDY: FEE ENGINEERING
CASE STUDY: GATES, LOCKUPS, AND SETTLEMENT PERIODS
CASE STUDY: CONTAGION
CASE STUDY: ECONOMIC SURPRISE
CASE STUDY: QUANTEMENTAL GTAA
CASE STUDY: ESG TAA
CASE STUDY: SOUTH AFRICAN TAA
CASE STUDY: LAZY (OPPORTUNISTIC) REBALANCING
OTHER RESOURCES
TEXTBOOK
* http://www.quantitativeassetmanagement.com/
DATA
* Datasets: Obtain a WRDS account https://www8.gsb.columbia.edu/itg/faculty/research_at_cbs/database/wrdsrequest
* CRSP/COMPUSTAT MERGED DATABASE – SECURITIES DAILY https://wrds-www.wharton.upenn.edu/pages/get-data/center-research-security-prices-crsp/annual-update/crspcompustat-merged/security-daily/
* CRSP MUTUAL FUNDS – HOLDINGS https://wrds-www.wharton.upenn.edu/pages/get-data/center-research-security-prices-crsp/quarterly-update/mutual-funds/portfolio-holdings/
* FINANCIAL RATIOS https://wrds-www.wharton.upenn.edu/pages/get-data/financial-ratios-suite-wrds/
* INTRADAY INDICATORS https://wrds-www.wharton.upenn.edu/pages/get-data/intraday-indicators-wrds/
* VENTURE CAPITAL https://wrds-www.wharton.upenn.edu/pages/get-data/wrds-venture-capital/
* FACTORS https://wrds-www.wharton.upenn.edu/pages/get-data/wrds-factors/
* SEC ANALYTICS https://wrds-www.wharton.upenn.edu/pages/get-data/wrds-sec-analytics-suite/
* I/B/E/S ANALYSTS’ FORCAST DETAIL HISTORY https://wrds-www.wharton.upenn.edu/pages/get-data/ibes-thomson-reuters/ibes-academic/detail-history/detail/
* THOMSON REUTERS MUTUAL FUND HOLDINGS – S12 MASTER FILE https://wrds-www.wharton.upenn.edu/pages/get-data/thomson-reuters/mutual-fund-holdings-s12/s12-master-file/
* THOMPSON/REFINITIV DATASTREAM DAILY INDEX CONSTITUENTS https://wrds-www.wharton.upenn.edu/pages/get-data/thomson-reuters/datastream/equities-data/dly_index_const/
* NEW YORK STOCK EXCHANGE & AMERICAN STOCK EXCHANGE & NASDAQ NATIONAL MARKET SYSTEM MILLISECOND TRADE AND QUOTE DATABASE https://wrds-www.wharton.upenn.edu/pages/get-data/nyse-trade-and-quote/
SOFTWARE
* Install MATLAB https://www.mathworks.com/academia/tah-portal/columbia-university-650045.html
BIG DATA
* Review and run this example: https://www.mathworks.com/help/matlab/large-files-and-big-data.html
* Review and run the examples at the BOTTOM of this page: https://www.mathworks.com/products/datafeed.html
BACKTESTING
* Review and run this example: https://www.mathworks.com/help/finance/portfolio-backtest-framework.html?s_tid=CRUX_lftnav
* Review and run this example: https://www.mathworks.com/videos/backtesting-strategy-framework-in-financial-toolbox-1606119787183.html
* Review and run this example: https://www.mathworks.com/help/finance/backtest-investment-strategies.html
* Review and run this example: https://www.mathworks.com/help/finance/backtest-investment-strategies-with-trading-signals.html
* Review and run this example: https://www.mathworks.com/help/finance/backtesting-using-risk-based-equity-indexation.html
* Review and run this example: https://www.mathworks.com/help/finance/backtest-strategies-using-deep-learning.html
* Review available code here: http://www.quantitativeassetmanagement.com/computercode/
TRADING
* Read https://www.mathworks.com/help/datafeed/bloomberg-emsx.html
* Read https://www.schwab.com/learn/story/stock-order-types-and-conditions-overview
* Have a quick look at https://emsx-api-doc.readthedocs.io/en/latest/
* Read https://www.backtrader.com/docu/
* Watch https://www.mathworks.com/videos/series/getting-started-with-trading-toolbox-94461.html
MARKET IMPACT
* Source data from papers like https://arxiv.org/abs/1705.03233
* Source data from Github like https://github.com/rorysroes/SGX-Full-OrderBook-Tick-Data-Trading-Strategy
* Source data from WRDS (you need an account from the library) https://wrds-www.wharton.upenn.edu/
* Source data from paid services (e.g. LOBSTER) https://lobsterdata.com/
* Look for open-source data like https://awesomeopensource.com/projects/orderbook
* Contact X and ask for data from LOBSTER
* Review and run this example: https://www.mathworks.com/videos/feature-extraction-using-diagnostic-feature-designer-app-1551178861512.html?s_tid=srchtitle_learner%20app_6
* Review and run this example: https://www.mathworks.com/videos/classify-data-using-the-classification-learner-app-106171.html
* Review and run this example: https://www.mathworks.com/help/matlab/large-files-and-big-data.html
* Review and run this example: https://www.mathworks.com/videos/forecast-electrical-load-using-the-regression-learner-app-1536231842528.html?s_tid=srchtitle_regression%20learner%20app_1
* Run this code: https://www.mathworks.com/help/finance/deep-reinforcement-learning-for-optimal-trade-execution.html
PORTFOLIO CONSTRUCTION
* Review and run this example: https://www.mathworks.com/help/finance/portfolio-optimization-examples.html
* Review and run this example: https://www.mathworks.com/help/finance/portfolio-optimization-against-a-benchmark.html
* Review and run this example: https://www.mathworks.com/help/finance/backtest-investment-strategies.html
* Review and run this example: https://www.mathworks.com/help/finance/backtest-investment-strategies.html
* Review and run this example: https://www.mathworks.com/help/finance/backtest-investment-strategies-with-trading-signals.html
* Review and run this example: https://www.mathworks.com/help/finance/backtest-strategies-using-deep-learning.html
* Review and run this example: https://www.mathworks.com/help/finance/portfolio-optimization-using-social-constraints.html
* Review and run this example: https://www.mathworks.com/help/finance/diversification-of-esg-portfolios.html
* Review and run this example: https://www.mathworks.com/help/finance/backtesting-using-risk-based-equity-indexation.html
* Review and run this example: https://www.mathworks.com/help/finance/create-hierarchical-risk-parity-portfolio.html
* Review and run this example: https://www.mathworks.com/help/finance/diversify-portfolio-using-custom-objective-function.html
* Review and run this examplehttps://www.mathworks.com/help/finance/custom-objective-function-for-min-variance-with-tracking-error-penalty.html
* Review and run this example: https://www.mathworks.com/help/finance/black-litterman-portfolio-optimization.html
* Review and run this example: https://www.mathworks.com/help/finance/portfolio-optimization-using-factor-models.html
* Review and run this example: https://www.mathworks.com/help/finance/asset-allocation-case-study.html
* Review and run this example: https://www.mathworks.com/help/finance/create-risk-budgeting-portfolio.html
* Review and run this example: https://www.mathworks.com/help/finance/using-custom-objective-function-for-min-tracking-return-with-net-return-constraint.html
* Review and run this example: https://www.mathworks.com/help/finance/hedging-using-cvar-portfolio-optimization.html
* Review and run this example: https://www.mathworks.com/help/finance/compute-maximum-reward-to-risk-using-cvar-portfolio-optimization.html
* Review and run this example: https://www.mathworks.com/help/finance/mixed-integer-mad-portfolio-optimization-problem.html
* Review and run this example: https://www.mathworks.com/help/finance/index.html?s_tid=CRUX_topnav
* Review available code here: http://www.quantitativeassetmanagement.com/computercode/
PERFORMANCE
* Read about GICS: https://www.msci.com/our-solutions/indexes/gics
* Review and run this example: https://www.mathworks.com/help/finance/investment-performance-metrics-1.html
SCENARIOS AND STRESS
“* Read https://www.bloomberg.com/professional/blog/whats-worst-nightmare-heres-find-portfolio-ready/#:~:text=Bloomberg%27s%20scenario%20analysis%20tool%20in,a%20group%20of%20risk%20factors.”
* Review and run this example: https://www.mathworks.com/help/finance/investment-performance-metrics-1.html