By Jim Hennington, Fellow of the Institute of Actuaries Australia
Content level: Advanced
Stochastic modelling is a technique that looks at the probability different outcomes may occur. For example, when projecting the value of a share portfolio, there is uncertainty around what the investment returns will be each year. Markets are subject to some randomness.
A stochastic model looks at the statistical distribution of the unknown variable(s) that impact the results of the model. For investments, the main unknown is the performance of different asset classes (e.g. returns on cash, shares, property, government bonds etc).
For retirees, another key unknown is your lifespan – which could be anywhere from today (if you got hit by a bus) until the end of the life tables.
Stochastic modelling at ‘product’ level
In the financial services sector, insurers, banks, superannuation funds, investment managers use this technique to quantify risks and optimise outcomes. Monte Carlo simulation is a common example of stochastic modelling. It generates thousands of probability weighted sequences for future market returns. A portfolio or strategy can be tested through all of these scenarios to identify the probability weighted range of possible outcomes that might be observed in the future. We refer to this as stochastic modelling at product level. It can be used to estimate the chance a particular investment achieves (or fails to achieve) a desired goal.
Households, however, often have many different financial arrangements and cashflows going on at once. This can include where each spouse holds multiple assets and investments plus social security entitlements they might be entitled to (which can be subject to means testing). The way a household manages its finances in retirement will often adapt to their experience each year. For example, in years where investment income is better than expected, a household may save some of their surplus income. And in a year where returns are negative, they may need to draw on their savings to meet their living costs. The allocation of their assets to/from their various holdings therefore can be dynamic.
Stochastic modelling at ‘household’ level
Modern retirement models like ours take stochastic simulation modelling beyond ‘product’ level and apply it to the household’s full financial situation.
In Australia, most retirees become entitled to an income from the government Age Pension at some point in retirement – either when they first reach eligibility age or later on in retirement as they spend down their savings over time. For those whose wealth falls within the means-testing bands, the annual income they receive from social security can be highly irregular. It goes up (or down) as your asset values move with market returns and drawings. These complex interactions can only be modelled using stochastic modelling.
Another issue is that human lifespans are random variables too. This impacts how long people’s savings need to last. Retirees generally seek to avoid outliving their savings and this means their spending levels need to allow for the probability they could live to an advanced age. In addition, when one spouse of a couple passes away, the household’s financial situation experiences a step-change. Their income from social security usually reduces and their living costs are also likely to reduce. This event, with it’s timing subject to randomness, has a material impact that should be modelled carefully as part of any retirement adequacy calculations.
With a household-level model, all significant assets, liabilities, and incomes of the household are projected and stress tested through a full range of market sequences, inflation scenarios and lifespan scenarios (for both spouses). The approach projects and models the complex interdependencies between assets, holdings and cashflows for the houshoeld each year, taking into account the user’s lifestyle needs over time.
Only then can a household plan retirement with a high degree of confidence that their living standard (i.e. regular spending level) can be sustained for life. For example, a household can identify what level of spending they can enjoy and be 95% sure it will last for life, no matter what markets do or how long they might live.
Advanced stochastic models at household level can also model employment patterns, career breaks, savings shapes, investment strategies, debts, product fees, part time work, pensions, annuities, tax and legislative rules, social security rules, property downsizing (or upsizing), inheritances, bequests, spending plans, lump sum transactions etc.
Users can then test whether they’ll be able to achieve their desired retirement lifestyle with a high degree of confidence.
- If not: the model can enable the user to explore alternative decisions with the aim of either achieving the target, or adjusting down their expectations (which may involve decisions like working for longer, saving more, spending less or downsizing).
- If so: the model can explore what additional spending the retiree can enjoy in addition. For example, this may include luxury spending items, buying ‘toys’ or gifting money to children or grand-children.
Jubilacion’s actuaries have developed a methodology for preparing and presenting stochastic results in a way that’s intuitive, clear and has been proven to empower confident decision making.
Jubilacion would love to hear from you and help you plan for your retirement. We genuinely love hearing about people’s retirement stories and discussing how modelling helps to make confident, fully informed decision making about what matters to you. You can call us on (03) 6240 1575, fill out our contact form on our website www.jubilacion.com.au or email us at email@example.com.
Actuary Jim Hennington has been working in retirement planning and financial software for 20 years. He’s an active member of the Institute’s Retirement Incomes Working Group and has been involved in their submissions on Regulating Digital Product Advice, the Retirement Income Covenant, the Retirement Incomes Review, Quality of Advice Review and Innovative Retirement Income Stream (IRIS) Legislative Considerations. He was actively involved in producing the Institute’s guidance notes on Good Practice Principles for Retirement Modelling and Innovative Income Streams.
Jim co-authored the papers ‘10 Good Practice Principles for Retirement Modelling’ in 2016, a paper ‘We asked how 2,500 planners formulate retirement income advice’ in 2018 and ‘A Framework for Maximising Retirement Income’ in 2021.