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Systematic Investment Strategies

  • in this course we will study both investment and speculation
    The main difference between investment and speculation lies in the time horizon.
    Investment is concerned with capturing maximum returns in the long-run with lower risk, while speculation is concerned with achieving returns over a short period of time.
    Speculation attempts to switch between investments to achieve the best return versus risk.
    Investment attempts to choose the best investments and hold onto them for longer periods, to achieve the best return versus risk over the long term.
    http://blogs.wsj.com/moneybeat/2015/12/24/this-simple-way-is-the-best-way-to-predict-the-market/

  • get Andrew Ang book Asset Management: A Systematic Approach to Factor Investing

The exclamation !!! marks signify very good papers

!!! good course bullet points:
http://www.londonfs.com/programmes/Modern-Asset-Allocation-Portfolio-Construction/Outline/

!!! ECON 424/CFRM 462: Computational Finance and Financial Econometrics
C:\Research\R\Tutorials\Zivot

!!! C:\Research\R\Tutorials\Zivot\research

!!! Bloch ebook Quantitative Portfolio Management.pdf

!!! Tourin dynport.zip

!!! Cochrane Advanced Investments
C:\Research\Academic\Cochrane Advanced Investments

!!! Pfaff Package Development in R.pdf

to-do list:

Loading and scrubbing time series data: packages xts and quantmod,

Estimating risk and performance measures: volatility, skew, CVaR, Cornish-Fisher VaR, Modified VaR, risk-return ratios (Sharpe, Sortino, Calmar), package PerformanceAnalytics,

Capital Asset Pricing Model CAPM: market portfolio, regressions of asset returns, alpha, beta, CML, SML, package factorAnalytics,

  • factor model and investing explained !!! Cazalet CAPM Factor Models.pdf
    Fernandez CAPM Stock Model Review.pdf
    Black CAPM Empirical Tests.pdf
    Steiner Alpha Misleading Performance Measure.pdf
    Ardia CAPM Portfolio Optimization Stock Forecasting.pdf

  • calculate rolling/running beta
    calculate beta confidence intervals using bootstrap
    http://eranraviv.com/bootstrap-example/
    http://statistics.ats.ucla.edu/stat/r/library/bootstrap.htm
    Fox Regression Bootstrap.pdf
    C:\Research\R\Packages\returnanalytics\pkg\PerformanceAnalytics\R\FamaBeta.R

  • beta robust regression shrinkage-estimator-for-beta
    http://eranraviv.com/a-shrinkage-estimator-for-beta/

  • lm() Model Variable selection
    shrinkage methods
    AIC, AIC, BIC
    update()

  • define Capital Market Line (CML) and Security Market Line (SML)

  • Markowitz’s Critical Line Algorithm (CLA) - function CCLA()
    http://rnfc.org/2015/06/05/Markowitz/ !!! Bailey Prado Critical Line Algorithm Portfolio Selection

  • Equity premium puzzle
    Returns on stocks are much higher than predicted by CAPM model using volatility of equity returns and returns on government bonds
    The fact that stocks are riskier than bonds doesn't explain the magnitude of the difference,
    https://en.wikipedia.org/wiki/Equity_premium_puzzle

  • define beta-adjusted risk-return measures
    Treynor ratio, Jensen's alpha
    Matthieu Lestel article for PerformanceAnalytics reviews risk-return measures
    PerformanceAnalytics PA-Bacon.pdf

  • Jensen alpha examples of how alpha can be generated: timing market and ex-post portfolios
    calculate Jensen alpha for SPX (for example) and demonstrate that it's close to zero
    calculate Jensen alpha for timed SPX: buy SPX at lows and sell at highs
    calculate Jensen alpha for ex-post portfolio: optimize portfolio in-sample to obtain highest alpha

  • Ormos Entropy Asset Pricing Model.pdf

Factor models: CAPM, Fama-French, Barra, statistical,

Forecasting returns and volatility,

  • show that it's easier to forecast returns over longer horizons in the future
    compare forecasts of daily returns, weekly, monthly, annual, etc. using past returns over different horizons - weekly, monthly, annual, etc.
    perform apply loops over different horizons
    It's easier to forecast long-term returns (over next decade) than short-term returns (over next year), because long-term returns are determined mostly by economic fundamentals, while short-term returns are determined mostly by speculative returns
    Similarly, it's easier to forecast the weather over a longer term (next Summer) than over a shorter term (next week), but it's also easier to forecast the weather over a very short term (next day)

  • forecast a simulated time series
    simulate a time series of returns using the Vasicek or Heston models
    create a linear forecasting model of returns
    evaluate forecasting performance using various measures: MSE, sign of forecast versus realized returns, etc.
    use bootstrap to obtain a distribution of forecasting performance ?
    define objective function based on distribution of measures ?
    calibrate the forecasting model parameters to maximize the objective function
    demonstrate that Hurst measures the level of forecastability
    plot Hurst as function of model parameters

  • Using the LASSO to Forecast Returns
    http://www.alexchinco.com/using-the-lasso-to-forecast-returns/

  • Bias in Time-Series Regressions
    http://www.alexchinco.com/bias-in-time-series-regressions/

  • simulate GARCH model and forecast volatility
    demonstrate forecasting ability as function of GARCH parameters
    Goyal GARCH Volatility Forecasting.pdf

  • stochastic volatility and rebalancing - solve Hamilton-Jacobi-Bellman equation
    Goyal Cross Sectional Factors Stock Forecasting.pdf
    Rapach Equity Stock Forecasting.pdf
    DeMiguel VAR Model Stock Selection Forecasting.pdf
    correlation forecasting - is it possible?

  • is Hurst exponent forecastable?
    calculate running Hurst over sliding interval - is Hurst persistent?
    calculate Hurst for different assets, and sort them
    are stock indexes more forecastable than individual stocks?

  • Forecasting returns using momentum factor
    Vogel Absolute Momentum Stock Forecasting.pdf
    Gulen Absolute Momentum Stock Forecasting.pdf

  • Forecasting returns conditional on volatility
    Interaction between returns and volatility
    Sort stocks by volatility and test which deciles have highest momentum
    Vogel Volatility Momentum Stock Forecasting.pdf

  • forecast returns using volatility-adjusted momentum - just like Sharpe ranking
    Calculate volatility-adjusted momentum rankings by dividing the prior twelve month total return by the realized volatility over the same period and then ranking in the standard fashion.
    Clare Volatility Momentum Trend Following Asset Allocation.pdf
    Baltas Volatility Momentum Trend Following Asset Allocation.pdf
    Zakamulin Momentum Indicators Stock Forecasting.pdf

  • demonstrate negative correlation between the monthly return of S&P index versus monthly volatility of returns on the index
    unexpected volatility is the difference between the realized volatility minus the GARCH forecast
    unexpected volatility predicts future excess return and volatility
    two strategies that dynamically reallocate between stocks and the risk-free asset, depending on the value of unexpected volatility.
    Zakamulin Volatility Forecasting Asset Allocation.pdf
    Vogel Absolute Momentum Stock Forecasting.pdf

  • Testing forecasting accuracy using Diebold Mariano Test
    package forecast dm.test() for Diebold Mariano Test ROC curve
    Diebold Mariano Forecast Accuracy Test.pdf
    C:\Research\R\Tutorials\Zivot\Econ 584\dieboldMariano.pdf
    http://stats.stackexchange.com/questions/139462/diebold-mariano-test-for-predictive-accuracy
    http://stats.stackexchange.com/questions/143079/what-is-prediction-accuracy-auc-and-how-is-it-the-number-conducted-in-machi?rq=1

  • measuring predictive ability using bootstrapping
    Hansen Forecasting Cross-Validation Bootstrap.pdf
    Hansen test improves on White's Reality Check for Data Snooping
    Hambuckers Forecasting Cross-Validation Bootstrap.pdf
    http://thestatsgeek.com/2014/10/04/adjusting-for-optimismoverfitting-in-measures-of-predictive-ability-using-bootstrapping/

  • Ian Kaplan (UofWash) Value Factors Do Not Forecast Returns for S&P 500 Stocks
    http://www.bearcave.com/finance/thesis_project/
    http://www.bearcave.com/finance/etf2/index.html
    Kaplan Constructing ETF Portfolio.pdf
    Kaplan Value Factor Model Forecast Returns.pdf

  • demonstrate that beta and correlations are difficult to forecast
    calculate rolling/running beta
    forecast beta out-of-sample, and show it doesn't work
    The only thing we can do is to short correlation at +1 and buy it at -1.
    beta and correlations are as difficult to forecast as returns

  • steady momentum frog-in-the-pan indicator: number of winning periods minus number of losing periods
    steady momentum indicator should be related to skew: large gains in a short period should produce positive skew

  • Stroud C programs for forecasting returns, variance, skew, kurtosis,
    !!! Stroud High Frequency Forecasting Volatility VIX VXX Strategy.pdf
    http://www.jonathanrstroud.com/code.html

  • forecasting intraday returns after price jumps
    Zawadowski Intraday Reversal Stock Forecasting.pdf
    Grant Intraday Reversal Stock Forecasting.pdf
    Duyvesteyn Intraday Reversal Bond Forecasting.pdf
    Schneider Skew Fear Volatility Risk Premium Forecasting.pdf

  • implied variance and skew forecast realized variance and skew
    !!! Kozhan Skew Variance Swap Stock Forecasting.pdf
    Kozhan Skew Variance Swap Stock Forecasting SSRN.pdf
    Mijatovic VIX Market Factors Stock Forecasting SSRN.pdf

  • VIX squared minus the five-minute realized variance forecast stocks
    volatility risk premium forecasts stocks
    does it demonstrate negative relationship between volatility and future return ?
    Bollerslev Volatility Stock Forecasting.pdf
    Bollerslev Implied Realized Volatility Stock Forecasting.pdf

  • Hull kitchen sink forecasting
    Hull Indicators Stock Forecasting.pdf
    Hull Tactical US ETF (HTUS)
    http://www.thestreet.com/story/13349919/1/will-this-quant-based-eft-be-able-to-time-the-market.html

  • Neely combine fundamental and technical indicators
    Neely Indicators Stock Forecasting.pdf
    Rapach Short Interest Indicator Stock Forecasting.pdf
    https://sites.google.com/site/xiaoqiao10/
    http://blog.alphaarchitect.com/2015/02/23/can-you-predict-stock-market-returns-with-short-interest/#.VPEI3EtN3wJ
    http://www.superforecasting.com/asset-return-forecasting/

  • Do valuation ratios forecast stock returns ?
    The Campbell-Shiller identity connects current dividend yield to future returns, dividend growth, and dividend yield
    Campbell Stock Forecasting.pdf
    add constraints on coefficients to improve forecasting out-of-sample R2 is positive
    If R2 is large relative to S2, then an investor can use the information in the predictive regression to obtain a large proportional increase in portfolio return

  • changes in the analyst rankings of P/E ratios forecasts stocks
    Gray Price Earnings Ratio Stock Forecasting.pdf

  • Kakushadze Alpha Forecasting
    Kakushadze Factor Model Stock Alpha Forecasting.pdf
    Kakushadze Factor Models Alpha Streams.pdf

  • yield curve forecasting example
    http://eranraviv.com/yield-curve-forecasting/

  • Kalman filter
    http://bilgin.esme.org/BitsBytes/KalmanFilterforDummies.aspx
    http://intelligenttradingtech.blogspot.com/2010/05/kalman-filter-for-financial-time-series.html
    http://stats.stackexchange.com/questions/8055/how-to-use-dlm-with-kalman-filtering-for-forecasting
    http://www.magesblog.com/2015/01/extended-kalman-filter-example-in-r.html
    Arnold Kalman Filter Expectation Maximization.pdf
    Sorensen Kalman Filter.pdf

  • Kalman filter
    Prado Kinetic Component Analysis Forecasting.pdf

Backtesting: cross-validation, parameter regularization, model overfitting, data snooping, data mining,

Asset pricing anomalies: size, value, momentum, volatility,

  • equity risk premium anomalies Antti Ilmanen: The equity risk premium (ERP) refers to the expected return of a broad equity index in excess of some fixed-income alternative.
    Arnott (Research Affiliates):
    The ERP Puzzle: Stocks beat bonds by more than they should.
    Historical excess returns exhibit large negative correlation.
    The correlation between consecutive 10-year stock market excess returns over 10-year government bonds has been a whopping –38 percent.
    When stocks beat bonds by a wide margin in one decade, they reversed with
    reasonable reliability over the next decade.
    This correlation is both statistically significant and economically meaningful.

  • pricing anomalies papers !!! Bouchaud Momentum Volatility Market Anomalies.pdf Fama French Dissecting Anomalies.pdf
    C:\Research\Academic\Cochrane Advanced Investments\new_anomalies.pdf
    Vogel Factor Model Momentum Anomaly.pdf
    CFM Momentum Trend Following Strategy Anomaly.pdf
    Han Trend Factor Cross-Section Momentum Stock Returns.pdf
    Israel Size Value Momentum Anomalies.pdf
    DeBondt Stock Premium January Anomaly.pdf

  • Asness anomalies
    Asness Fama French Small-Cap Anomalies.pdf
    Asness data files in: Asness*.xlsx

  • Anomalies aren't persistent
    Edwards Market Anomaly Smart Beta Persistent Spurious.pdf

  • Low volatility anomaly
    Boudt Low Volatility Anomaly High Frequency Data.pdf Gray Low Volatility Anomaly.pdf
    Baker Low Volatility Anomaly.pdf
    Li Low Volatility Anomaly FAJ.pdf
    Han Volatility Decile Cross-Sectional Momentum Anomaly.pdf

  • Low beta anomaly caused by demand for positive skewness (lottery) which reduces future returns
    Bali Betting Against Beta Lottery Demand.pdf

  • Jacobs: momentum anomaly enhanced by skewness
    skewness enhanced momentum is about twice as large as traditional momentum
    skewness is among the most important cross-sectional determinants of momentum
    Jacobs Skewness Cross-Sectional Momentum Anomaly.pdf
    Amaya Skewness Momentum Equity Returns http://www.etf.com/sections/index-investor-corner/swedroe-keep-skewness-perspective

  • Show that the returns of momentum strategies have negative skewness: momentum strategies have positive returns but also experience infrequent but significant negative returns http://blog.alphaarchitect.com/2015/05/11/momentum-investing-skewness-enhanced-momentum-yields-double-alpha/#gs.YexM_xM

  • Schneider: CAPM betas overestimate true market risk
    demonstrate that if asset value follows a lognormal process, then the equity price in Merton model has a skewed distribution of returns
    demonstrate that equity returns in Merton model have positive skewness, since they are a call option
    high credit risk produces time-varying skewness in Merton model
    demonstrate that high credit risk produces time-varying skewness in Merton model
    Schneider Volatility Anomaly Skew Risk Premium.pdf
    Schneider Skew Anomaly Merton Credit Risk Forecasting.pdf

  • Ang Idiosyncratic Volatility Anomaly.pdf
    R code to replicate main results in Ang, Hodrick, Xing, and Zhang (2006)
    https://gist.github.com/alexchinco/d58ebd7750904db1b94c
    https://gist.github.com/alexchinco
    https://github.com/alexchinco

  • Treasury Curve Anomaly
    Gayed Treasury Curve Anomaly Asset Allocation.pdf

  • Value strategies can be implemented in many different ways, leading to widely different performance
    http://investorfieldguide.com/three-value-investors-meet-in-a-bar/
    Stock value can be measured in several different ways including book value, earnings, and sales.
    The Russell 1000 Value has underperformed the Russell 1000 by -22% and the Russell 1000 Growth by -43% over the past decade (10 years ending 11/30/15).
    idea: apply value investing to different value indices: buy more of the cheap ones

Seasonal Anomalies

Investor risk preferences and utility functions: investor prudence and temperance,

  • derive CAPM from utility
    Show that logarithmic utility implies max Sharpe

  • skew demand causes underperformance, and creates stock premium factor
    Ilmanen Buying Selling Insurance Lottery Tickets.pdf
    Nekrasov Kelly Criterion Multivariate Portfolios.pdf

Estimation of covariance and correlation matrices, Akaike and Bayesian information criteria, coefficient shrinkage,

Portfolio optimization: package PortfolioAnalytics,

http://blog.fosstrading.com/2014/03/intro-to-portfolioanalytics.html

Active portfolio management strategies: out-of-sample performance of optimized portfolios, tactical asset allocation, risk parity, minimum correlation, minimum variance, maximum Sharpe, maximum CVaR, universal portfolios,

  • simulate terminal distribution of stock prices
    simulate 500 correlated stocks time series random lognormal with positive drift,
    use them for random portfolios
    create a value-weighted index
    show that cap-weighted index investors are inherently trend-following because index keeps buying more of the outperforming stocks
    compare to equally weighted index
    which investors perform better?
    expand on: cap-weighted indices have large concentrations and undesirable factor exposures to momentum

  • demonstrate that active managers are likely to underperform index, unless they have extraordinary skill
    http://www.bellmanoptimality.com/programming/ http://www.bellmanoptimality.com/ Heaton Stock Index Selection Active Portfolio Management.pdf

  • Grinold fundamental law of active management
    Grinold Synopsis Active Portfolio Management.pdf

  • Bogle's message is: it's better to invest in indices, unless you're a genius stock picker or a genius speculator.
    http://blogs.wsj.com/moneybeat/2015/12/24/this-simple-way-is-the-best-way-to-predict-the-market/
    Bogle Investing Factor Models.pdf
    Bogle postulates that long-term returns on investments consist of an "investment return" (initial yield plus earnings growth) plus the "speculative return" (discount factor determined by investor psychology and risk appetite).
    The cumulative investment return is positive, while the cumulative speculative return is close to zero.

  • Merton model: simulate dynamic investment and consumption strategies
    Merton Dynamic Consumption and Portfolio Choice
    simulate Merton consumption wealth model
    Guasoni Merton Optimal Consumption Utility Shortfall Aversion.pdf
    An Merton Utility Asset Allocation.pdf
    https://en.wikipedia.org/wiki/Intertemporal_portfolio_choice
    https://en.wikipedia.org/wiki/Merton%27s_portfolio_problem

  • Intertemporal portfolio choice
    calculate out-of-sample performance of optimized portfolios,
    perform rolling portfolio optimization and study stability of weights over time

  • optimize portfolio assuming zero or constant asset correlations
    demonstrate that this portfolio outperforms out-of-sample
    Sivaramakrishnan Intertemporal Portfolio Choice.pdf
    Garleanu Intertemporal Portfolio Choice.pdf

  • simulate static asset allocation strategies
    all weather portfolios
    Faber Arnott Portfolio Asset Allocation.pdf

  • Risk Parity Portfolios
    !!! Roncalli Risk Parity Factor Models.pdf
    Steiner Risk Parity Portfolios.pdf
    Griveau-Billion Risk Parity Portfolio Cyclical Coordinate Descent Algorithm.pdf

  • simulate CPPI strategy: CPPI strategy is similar to Kelly betting strategy
    http://epchan.blogspot.com/search/label/Book%20reviews
    the only way to ensure that our maximum drawdown will not exceed a certain limit is through Constant Proportion Portfolio Insurance (CPPI): trading risky assets with Kelly-leverage in a limited liability company, putting money that you never want to lose in a FDIC-insured bank, with regular withdrawals from the LLC to the bank (but not the other way around).
    Jacquier Merton Kelly Bayesian Utility Asset Allocation.pdf

  • factor investing
    Blitz Investing Asset Allocation Factor Models.pdf
    Bender Smart Beta Asset Allocation Investing Factor Models.pdf

  • Andrew Ang at Columbia book Asset Management: A Systematic Approach to Factor Investing
    !!! Ang Factor Models Investing.pdf
    http://factorinvestingbook.com/
    http://factorinvestingbook.com/book.html

!!! Richard Smart Beta Minimum Variance Factor Models.pdf
Maillard Risk Parity Minimum Variance Portfolios.pdf
Goldberg Value Minimum Variance Portfolio Factor Models
Hsu Minimum Variance Portfolio Factor Models.pdf
Clarke Risk Parity Minimum Variance Portfolios.pdf
Chow Minimum Variance Stock Strategy.pdf

Benchmarking portfolio management skill:

Cointegration, pairs trading, statistical arbitrage

  • consider a seasonal process that is the sum of two AR processes for example in the AM a process with Hurst=0.4, and in the PM a process with Hurst=0.6 what is the Hurst for such a process?

  • consider a process for which the Hurst depends on the level of volatility for example the Hurst=0.6 for high volatility, and the Hurst=0.4 for low volatility what is the Hurst for such a process?

  • simulate Ornstein-Uhlenbeck process AR(1) model and trade it
    forecast returns and demonstrate that forecasting is easier with stronger mean-reversion
    http://robotwealth.com/exploring-mean-reversion-and-cointegration-with-zorro-and-r-part-1/
    http://robotwealth.com/exploring-mean-reversion-and-cointegration-part-2/

  • perform Engle-Granger Cointegration test
    find cointegrated pairs and demonstrate that cointegration fails out-of-sample
    package egcm: Engle-Granger Cointegration Models
    package PairTrading.pdf
    http://denizstij.blogspot.com/2013/11/stationary-tests-of-time-series-within-r.html

  • Granger Causality
    http://davegiles.blogspot.com/2011/04/testing-for-granger-causality.html

  • using historical data calculate average returns after reaching peak
    calculate distribution of mean-reversion times
    fit to OU decay model

  • cointegration and VAR models
    C:\Research\R\Tutorials\Zivot\Econ 584\cointegration.pdf
    ADF test for cointegration
    Phillips-Ouliaris test for cointegration
    package urca
    cointegrationPowerPoint.pdf
    cointegrationslides.pdf
    cointegrationslides2.pdf

  • cointegration package irlba
    Lewis RFinance 2012 Cointegration SVD.pdf
    C:\Research\R\R-Finance 2015\BryanLewis.html
    apply Doornik’s method using the SVD to solve the cointegration problem

  • pairs trading
    Krauss Statistical Arbitrage Pairs Trading Review.pdf
    Krauss Copula Pairs Trading Cointegration.pdf
    Steffen Hurst Cointegration Pairs Trading.pdf
    Leung Pairs Trading Stop-loss Rule.pdf
    Clegg Cointegration Pairs Trading.pdf
    Miao Statistical Arbitrage Cointegration.pdf
    Grabovsky Statistical Arbitrage Pairs Trading.pdf
    Kakushadze Statistical Arbitrage.pdf
    Kakushadze Pairs Trading Factor Models.pdf
    Rudy Pairs Trading Stocks ETFs.pdf
    QUSMA ETF Daily Mean Reversion.pdf
    C:\Research\Stat Arb Peter\Pairs Trading Cointegration\
    Gatev, Goetzmann, and Rouwenhorst 2006.pdf
    Tourin Pairs Trading HJB Stochastic Control.pdf

  • demonstrate that the pairs trading returns have negative skewness
    because upside returns are capped by trade exit rule
    while there can be large negative returns if the trade moves against you

  • high frequency data cointegration
    Krauss High Frequency Cointegration

  • index arbitrage
    Avellaneda Statistical Arbitrage 2008.pdf
    C:\Research\Academic\Avellaneda Quantitative Investment Strategies

  • combine mean reversion and momentum strategies
    !!! Velissaris Statistical Arbitrage Momentum Strategies.pdf

  • residual momentum strategy Blitz Short-Term Residual Reversal.pdf
    https://factorinvestingtutorial.wordpress.com/9-residual-momentum-david-blitz/

  • yield curve butterfly strategy
    futures butterfly strategy

High Frequency trading strategies: volatility pumping and harvesting,