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HOME SUPER CHOICE SUPERANNUATION SMSF FIND LOST SUPER FAQ PENSIONS FAQ ACTUARY FINANCIAL LITERACY INVESTMENT SECTORS INVESTMENT MODEL FINANCIAL PLANNING SHARE TRADING WHAT BANK ACCOUNT LIFE INSURANCE BOOKS & TOOLS PORTFOLIO SYSTEM ABOUT US WHY SUPEREASY SMSF BENEFITS SERVICES OVERVIEW FEES SMSF SET UP SMSF ADMIN SPECIAL OFFERS PORTFOLIO OVERVIEW CONTACT |
INVESTMENT SIMULATOR AUSTMOD - Stochastic and Historical Investment Simulation Model SuperEasy’s Actuarial Partners, Lynken Counsellors provide asset allocation and investment simulation services, through their qualified and experienced actuaries, Colin R. Grenfell and Ken G. Dance, using the Austmod simulation model. The model is an Excel workbook that displays up to 50 years of historical (past) and 40 years of simulated (future) investment performance for 15 “sectors”:
The model results are displayed in both table and chart forms. The simulated model scenarios depend on nominated assumptions for means, standard deviations, cross-correlations, auto-correlations, skewness, kurtosis, taxation and investment fees. The historical results are analysed and documented in Colin Grenfell’s September 2009 Institute of Actuaries of Australia (IAAust) paper “Australian Investment Performance 1959 to 2009 (and Investment Assumptions for Stochastic Models)”. Appendix A of Colin’s Oct/Nov 1997 IAAust paper “Uses of S.I.S. (Superannuation Investment Simulations)” has a specification of the then version O of Austmod. The latest model, version V, includes many new features, for example:
For the technically-minded - The model has an annual time scale. The mathematical structure of the underlying AUSTMODV algorithms is summarized below: 1. Normal. First, the model generates independent Normal random variables for each sector. 2. Cross-correlation. These random variables are then converted to dependent Normal random variables using the Cholesky decomposition formula (refer Wilkie A D, 1988, JIA 115. Part 1, page 51). 3. Skewness and kurtosis. These random variables may then be converted to dependent non-Normal random variables using formula [2] or [4] as described in Appendix A of “Australian Investment Performance 1959 to 2009 (and Investment Assumptions for Stochastic Models)”. 4. Shape. For sectors Q, F, G, J, L, N and C the shape of the distribution may then be improved by reducing both the skewness and kurtosis - refer paragraph A13 of “Australian Investment Performance 1959 to 2009 (and Investment Assumptions for Stochastic Models)”. 5. Taxation. The input for each sector includes two tax rates and information for imputation credits. The income tax rate is applied to the long term expected income yield and imputation credits. The deferred tax rate is applied to the total before tax yearly return less the long term expected income yield. This is equivalent to assuming, for tax purposes, that all fluctuations in investment returns are due to fluctuations in the capital appreciation component. The after tax standard deviation for each sector equals the before tax standard deviation * (1 - deferred tax rate). 6. Additional return. The before tax standard investment return for each investment sector may be increased (or decreased if negative) by adding an additional return. For tax purposes the additional return is treated as a capital appreciation component and taxed at the deferred tax rate. 7. Investment fees. The before tax investment fee for each sector is deducted from the before tax long term expected income yield; the result is then taxed at the income tax rate. 8. Forces. After allowing for taxation and any additional return and investment fees, the standardized random variables (denoted srv) from 4. above, are then converted to annual forces using the formula force = mu + sigma*srv. 9. Mixture. The annual force for the mixture or portfolio is then determined by weighting the sector forces by the proportions for each sector. The proportions may be specified individually, or default proportions for “Growth”, “Balanced” or “Capital Stable” may be used. 10. Rates. The annual forces are then converted to rates using the formula EXP(force) - 1. 11. Repeats. Steps 1 to 10 are repeated 108 times to give a 108-year single scenario with no auto-correlation. 12. Auto-correlation. A 40-year scenario with auto-correlation may then be generated using the methodology described in Appendix B, paragraphs B7 and B8, of “Australian Investment Performance 1959 to 2009 (and Investment Assumptions for Stochastic Models)”. 13. Lags. CPI and AWOTE may then be lagged (refer Section 14 and paragraphs B10 and B11 of the above paper). 14. Refinement. The CPI and AWOTE auto-correlations may be further improved by increasing their cross-correlation with the D sector by .12 (refer paragraph B11 of the above paper). For further information, contact Colin Grenfell on 03 9886 1091, or colin.grenfell@supereasy.com.au |
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SuperEasy Pty Ltd is not licensed to provide advice on investments, or legalities of the types of investments that you can have. SuperEasy® strongly recommends that you seek professional advice before making any investment choice or decision. |
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