Risk-Based Investment Strategies

Smart Beta, Robust Risk Parity and Risk Budgeting

Agenda Program
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Prague, NH Hotel Prague
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This course offers a detailed discussion of risk-based investment strategies, covering portfolio construction principles, success factors and conceptual issues and recent industry trends like Smart Beta and Risk Parity.

Attend this intensive 2-day training and learn to:
  • Overview of investment risk analytics: A fresh perspective on established concepts like volatility and an introduction to modern risk concepts like conditional value-at-risk, drawdown-at-risk, lower partial moments, copulas and non-normal distribution modeling.
  • Risk-Based Investment Strategies: Risk-based portfolio construction approaches (e.g. Risk Parity, Smart Beta) and their success factors.
  • Estimating Risk: Use of various estimators to derive the necessary inputs
  • Risk Analysis in practice: Model risk and its management. Stress testing and scenario analysis for investment portfolios. Issues in backtesting investment strategies
Who should attend?
The course is not only for specialists but for a wider audience including investment managers, asset management executives of all levels, institutional investors and research analysts. This course has been designed for the benefit of:
  • Investment officers
  • Research analysts
  • Portfolio managers
  • Risk managers
  • Fund analysts
  • Institutional investors
  • Quantitative investment analysts
The training consists of classroom-based teaching combined with selected group exercises and spreadsheet-based example calculations.

Delegates will receive printouts of all slides and electronic access to Excel spreadsheets used during the course, plus an Excel add-in to perform more complex computations for one year.
Participants are encouraged to bring their own notebook with MS Excel to maximize the interaction, practical examples and benefit from the seminar.

Program of the seminar: Risk-Based Investment Strategies

The seminar timetable follows Central European Time (CET).

Day One

09.00 - 09.15 Welcome and Introduction

09.15 - 12.30

Investment Risk in Context

  • The philosophy of risk
  • The psychology of risk
  • The economics of risk

Introduction to Risk-Based Investment Strategies

  • Risk-based versus return-based investing
  • Target volatility versus constant asset allocation strategies
  • The empirical case for managing risk to improve return, risk and risk-adjusted returns
  • How to use risk as a trading signal
  • Understanding the demand for risk-based strategies

Minimum Variance Portfolio Investing

  • Portfolio Construction
  • Risk and return characteristics, success factors
  • Empirical characteristics

12.30 - 13.30 Lunch

13.30 - 17.30

Risk Parity, Robust Risk Parity and Risk Budgeting

  • Portfolio Construction
  • Risk and return characteristics, success factors
  • Empirical characteristics

Equal-Weighted Investing

  • Portfolio Construction
  • Risk and return characteristics, success factors
  • Empirical characteristics

The Most Diversified Portfolio

  • Portfolio Construction
  • Risk and return characteristics, success factors
  • Empirical characteristics

Day Two

09.00 - 12.30

Volatility Risk

  • Calculating volatility
  • Annualizing volatility
  • The psychology of volatility
  • Statistical tests
  • Limitations of volatility
  • Robust alternatives to volatility
  • The impact of leverage
  • Volatility as the lowest common denominator: UCITS

Loss-Based Risk Measures beyond Volatility

  • Semi-variance, Lower Partial Moments, VaR, CVaR, Maximum Drawdown, Drawdown-At-Risk and Conditional Drawdown-At-Risk

12.30 - 13.30 Lunch

13.30 - 17.30

Applied Risk Measurement

  • Some stylized facts about financial return time series
  • Historical approaches
    • Dynamic risk analysis: rolling statistics, exponentially-weighted statistics, introduction to GARCH
    • Covariance estimators: Shrinkage estimators (Ledoit/Wolf, Jorion), using random matrix theory to remove noise
    • Using economic and statistical factor models (PCA)
    • On the relative importance of correlations
  • Parametric approaches
    • Distributions: NIG, normal mixtures
    • Bootstrapping, resampling
    • The Cornish-Fisher approximation and its limitations
  • Scenario-based estimation of risk
  • Handling estimation risk
  • Applied Stress Testing and Scenario Analysis
    • The historical versus the parametric approach
    • Tweaking volatilities and correlations
    • Handling low probability scenarios

General Topics in Quantitative Portfolio Construction

  • Backtesting issues
  • Rebalancing strategies
  • Turnover analysis
  • Benchmarking issues
  • Evaluating results: Performance and risk measures to consider
  • On numerical optimization
  • Using Excel and VBA
  • Handling time series data from illiquid assets

Evaluation and Termination of the Seminar

Training catalogue in PDF
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