1 / 18

Mixing Asset Allocation Techniques for Alternative Investments

Value-added from Hedge Funds. PAST PERFORMANCE IS NOT NECESSARILY INDICATIVE OF FUTURE RESULTS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

amalie
Download Presentation

Mixing Asset Allocation Techniques for Alternative Investments

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


    1. Mixing Asset Allocation Techniques for Alternative Investments Mark S. Rzepczynski President & CIO

    2. Value-added from Hedge Funds

    3. Frontiers Sensitive to Environment Returns and volatility not stable Distributional biases The case of collapsing frontier Volatility shocks correlations increase Price declines correlations increase

    4. Optimizer Misses Unique Factors Hedge fund data issues Style differences Distributional differences Conditional events Non-linear pay-offs

    5. Hedge Funds have Data Problems Survivorship bias Errors in variables Sampling problem Non-linear behavior

    6. Convergent vs. Divergent Styles Convergent styles World knowable Stable world Mean-reverting Short volatility Arbitrage-based Divergent styles World uncertain Unstable world Mean-fleeing Long volatility Trend-following

    7. Non-normal Problem Significant Skew effects distribution Sharpe ratios distorted Optimizer will have biases

    8. Conditional Events Important Alternative exposure serves as protection Style allocation is conditional on events Hence, mix will change with event view

    9. Non-linear Pay-offs Present Dynamic styles have flexible betas Managed futures as look-back straddles Merger arbitrage as short puts Market neutral as short volatility strategy

    10. What are Possible Solutions? New estimation techniques Constraint-based solutions State dependency allocations Inclusion of preference analysis

    11. Estimation Technique Solutions Historical analysis has limits Alternative techniques Long-run (global) mean analysis Shrinkage estimators Bayesian estimators

    12. Constraints Improve Allocations Eliminate concentration issue Impose style diversification Account for qualitative judgment

    13. State Dependency Adds Value Allow for current environment Extreme correlation issue Styles match with state of the world The case for managed futures The case for merger arbitrage

    14. Preference Disclosure Issues Risk aversion should account for skew Downside protection accounts for regret Time horizon provides perspective

    15. “Characteristics vs. Covariances?” Quantitative approach has limits Data sensitivity problems Qualitative approach gives unique insight Style analysis finds opportunities Combination approach adds value

    16. References Brooks, Chris and Harry Kat, “The Statistical Properties of Hedge Fund Index Returns and Their Implications for Investors” ISMA Working Paper October 2001. Clarke, Roger and Harindra de Silva, “State-Dependent Asset Allocation” Journal of Portfolio Management Winter 1998 (Vol. 24, No. 2) pp. 57-64. Daniel, Kent and Sheridan Titman “Characteristics or Covariances” Journal of Portfolio Management Summer 1998 (Vol. 24, No.4) pp. 24-33 Edwards, Franklin and Mustafa Onur Caglayan, Hedge Fund and Commodity Fund Investments in Bull and Bear Markets”, Journal of Portfolio Management Summer 2001 (Vol. 27, No. 4) pp. 71-82. Eichhorn, David, Francis Gupta, and Eric Stubbs, “Using Constraints to Improve the Robustness of Asset Allocation” Journal of Portfolio Management Spring 1998 (Vol. 24, No. 3) pp. 41-48. Larsen Glen and Bruce Resnick, “ Parameter Estimation Techniques, Optimization frequency, and Portfolio Return Enhancements” Journal of Portfolio Management Summer 2001 (Vol. 27, No. 4) pp. 27-34. Lo, Andrew “The Three P’s of Total Risk Management” Financial Analysts Journal Jan/Feb 1999 (Vol. 55, No.1) pp. 13-26. Lo, Andrew “Risk Management for Hedge Funds: Introduction and Overview” Financial Analysts Journal Nov/Dec 2001 (Vol. 57, No 6) pp. 16-33. Leland, Hayne, “Beyond Mean-Variance: Performance Measurement in a Nonsymmetrical World” Jan/Feb 1999 (Vol. 55, No.1) pp. 27-36. Rzepczynski Mark S. “Market Vision and Investment Styles: Convergent Versus Divergent Trading” Journal of Alternative Investments Winter 1999 (Vol. 2, No. 3) pp. 77-82. Rzepczynski Mark S. and Franklin Neubauer “Adding Hedge Funds to a Traditional Asset Portfolio:What Can We Learn?” Alternative Investment Management Association Newsletter September 2001 No. 48 pp. 33-34.

    17. Notes

    18. Notes

More Related