Asset Allocation and Portfolio Construction

Day One

Review of MPT and Traditional Asset Allocation Practice

• The impact of the Financial Crisis and the low-yield environment on investment management
• Review of Modern Portfolio Theory (MPT) - discussion of pre-course readings and questions
  • The many definitions of “risk”
  • A reinterpretation of Two-Fund-Separation as factor investing advice
  • MPT applications: surplus management, active management relative to a benchmark
• Issues of traditional asset allocation industry practice
  • Pseudo asset classes & diversification
  • Risk characteristics of fixed weight policy portfolios
  • Drivers of the success of rebalancing strategies
  • Industry Trend: Factor-based asset allocation

Exercise: Factor risk budgeting in a mean-variance framework

An Overview of Newer Approaches to Asset Allocation

• Investment horizons and time-variable risk and return characteristics
• The case for flexible asset allocations: moving from static portfolio risk to managing portfolio risk and return dynamically over time
• Industry Trend “Smart Beta”: Is it a strategy, a product or a distribution approach?

Expected Returns & Return-Based Asset Allocation

• Return-Based Strategies:
  • Market-cap-weighted passive & adaptive asset allocation
  • Tactical asset allocation, strategic asset allocation
• Estimating expected returns
  • Scenario-based approaches to return estimation: Markov-Regime switching models and approaches used in the industry
  • Alpha estimation: benchmark-implied returns, Treynor/Black portfolios, Information Coefficient
  • The Black/Litterman model & introduction to Bayesian Expectations
  • Denoising with the James Stein return estimator
• Turning forecast scores into portfolio allocations without optimizers
  • Turning rankings into scores
  • Deriving risk-adjusted scores
  • Taking into account restrictions: tactical bands, turnover, general linear constraints

Exercise: A macroeconomic scenario-based approach to risk and return estimation

Day Two

Risk Expectations and Risk-Based Investing

• Risk-based investment strategies
  • Minimum variance
  • Risk parity
  • Risk budgeting
  • Equal-weighted
  • Most-diversified, maximum diversification
  • Drivers of the success of low risk investment strategies: interest rate regimes, market anomalies or factor risk premium?
• Time-varying risk characteristics
  • Autocorrelation & volatility clustering
  • Comparison of volatilities and correlation dynamics
  • Understanding the positive relationship between risk and return
• Volatility and correlation matrix estimation
  • Historical estimators, rolling and exponentially-weighted implementations, introduction to GARCH
  • Properties of a valid correlation matrix, consequences of invalid correlation matrices
  • Robust correlation estimators: average correlation matric, Bayesian shrinkage estimators (the Ledoit/Wolf approach)
  • Handling asymmetrical dependencies and tail-risk dependence

Exercise: Developing a quantitative volatility trading strategy

Estimation Risk and Its Management

• A scenario-approach to explicitly taking into account uncertainty in expected returns and correlations
• The statistical nature of the efficient frontier: from confidence bands to the Resampled Efficient Frontier™
• Distorted risk and return: the impact of illiquidity, survivorship bias
• Robust portfolio construction approaches: minimizing regret

Exercise: Decision making under uncertainty in a scenario framework

Quantitative Portfolio Construction beyond Mean and Variance

• Overview of risk measures beyond volatility
  • Downside risk measurement: semi-variance, LPM, VaR/CVaR
  • Interim risk: drawdown measures (max drawdown, drawdown-at-risk)
• Higher moments
  • Skewness and kurtosis as tail risk characteristics
  • Their use in risk measurement and portfolio construction and estimation risk issues
• CVaR and LPM/UPM optimization: exact solutions and approximations
• Behavioural Portfolio Construction: Applying insights from Prospect Theory
• Random portfolios & convex hulls
• Understanding the advanced optimization algorithms: threshold accepting, simulated annealing, genetic optimizer
• Multi-criteria portfolio optimization: taking into account sustainability scores in the construction of ESG portfolio
• The use of AI (Artificial Intelligence), Machine Learning, Big Data Approaches in portfolio construction

Day Three

Selected Topics in Quantitative Analysis

• Tail risk management
  • Understanding the normal distribution assumption
  • Non-normal distributions: Cornish-Fisher, NIG, normal mixtures
  • Tail risk contributions, risk budgeting with Modified VaR/CVaR
  • Modelling fat portfolio tails with elliptical distributions
• Overdiversification and diworsification
• Taking into accounting asymmetries in correlations: equities, bonds and gold

Exercise: Downside, upside, average and tail correlation measurement

Currency Management

• Risk, return and exposure analytics for unhedged and hedged currency exposures
• Approaches to currency management: active management versus hedging
• Optimal currency hedging: optimization approaches (1-stage, 2-stage) and practitioner approaches (strategic and tactical hedge quotas, currency overlay portfolios)

Exercise: 1-stage versus 2-stage optimization in currency management

Model Risk Management

• Forecast risk = model risk + parameter estimation risk
• Backtesting: in-sample versus out-of-sample, overfitting issues
• Elements of a buy-side model risk management framework