Calculating a client's risk capacity and risk tolerance are foundation to a financial advice and investing framework, we go deeper into the academic understanding of these two main elements of risk.
Risk Tolerance
Individuals have preferences regarding tolerance for risk, and this is generally consistent across different contexts, including investments. Historically, personal preferences for risk (or risk tolerance) has driven most portfolio allocation within financial advice. While considerations of risk capacity may be equally important, it still is valuable to ascertain and apply individual preferences for risk tolerance to investment portfolios, as it is the indicator of ensuring the client is able to 'sleep at night' with their investments.
Demographics
Historically, demographics alone were used to determine tolerance for risk, and thus asset allocation. However, older people, and women, are not always less risk tolerant than others (Kannadhasan, 2015). These types of generalisations can result in clients becoming disempowered from the advice process.
Households that are younger male-led, more educated, who hold shares, with higher net wealth, are more likely to take financial risks (Huang, Xu, & Chiang, 2016). However, this is likely more a result of human capital and financial capital
(covered in the risk capacity section), than actual demographic trends.
It is these structural inequalities which often compound the impact of individual preference for risk on decreasing net wealth relative to others.
Risk Tolerance Components
The measurement of risk tolerance has existed in the psychological literature for decades, and covered a range of personal contexts.
While economists have often bundled risk tolerance with time preferences (Hanna et al., 2011; Claudia R. Sahm, 2012), psychologists see tolerance for risk as a personal and individual preference which may be impacted by context.
Components of risk tolerance calculations include the ranking of goals, emergency savings, emotions elicited during decision making, preferred risk-return trade-off, betting odds, and required rate of return (Cordell, 2002). The challenge is that people are not rational, and so each of the above components is different for everyone. The irrationality of investors has been studied extensively by authors who have found that we place excessive weight on small losses and highly value avoiding uncertainty (Tversky & Kahneman, 1992). We can also get addicted to risk taking behaviour, resulting in a positive feedback loop (Buckley, 2015). Our tolerance for risk also changes with our perception of economic conditions
(Claudia R Sahm, 2012).
Risk Tolerance Questionnaires
Investment risk tolerance questionnaires apply psychometric survey design principles to reliably and validly predict individual risk tolerance preferences (Hanna et al., 2011).
Authors have found that the responses to the surveys correlate strongly with investors perceptions of their own risk tolerance (Hallahan, Faff, & McKenzie, 2003). This means it is likely there is methodological error introduced into historical methods to ascertain risk tolerance, as it is not actual risk tolerance that is measured, rather, beliefs about one's own risk tolerance. The most accurate measure of assessing risk tolerance is of course to assess actual behaviour.
Historical Actions
What we actually do is a more accurate indicator of our beliefs than what we say we believe. This is also the case in assessing risk tolerance. It is possible to assess the responses to the risk tolerance survey with actual historical behaviours, and authors have found consistency in this analysis (Roszkowski & Grable, 2005; Yook & Everett, 2003).
Tolerance for Risk Studies
Individual preferences for risk has previously been studied in the Psychology literature as 'sensation seeking', which relates explicitly to risk taking behaviour
(Arnett, 1994; Zuckerman, Kolin, Price, & Zoob, 1964; Zuckerman & Neeb, 1980). Since this ground-breaking research was done there have been repeated tests and re-tests of tolerance for risk using empirical methodology.
There are a number of explicit behaviours which are associated with a high tolerance for risk such as smoking, driving fast (Zuckerman & Neeb, 1980), investing in stocks (Keller & Siegrist, 2006) and adventure tourism (Gilchrist, Povey, Dickinson, & Povey, 1995). However, authors have found that it is the responses to actual lotteries (with the client's own money) that elicit the best predictors of actual market responses (Pennings & Smidts, 2000).
Below is an example of using 'risk capacity' and 'risk tolerance' within a goalsbased investing framework.
Risk Capacity
Some authors consider risk capacity to be the most important component of a client's tolerance for financial risk (Davies, 2017). This is despite the fact that risk capacity is an objective calculation determined by a client's actual financial situation, rather than their ability to 'sleep at night' with their investment portfolio risk-return trade-off.
Risk capacity is the amount of risk that a client can take in their investments, depending on their situation. The critical components of risk capacity calculations are: liquidity, time horizon, net wealth, debt, net wealth calculation, and potential considerations for the risk capacity calculation.
Risk capacity is broadly comprised of human capital (our ability to generate wealth eg: our income or level of education), and financial capital (our current net wealth). While our human capital generally decreases as we age (as we have fewer earning years ahead of us), financial capital generally increases as we age.
Financial Capital
Netwealth
A critical component of risk capacity is net wealth, which when combined with liquidity etc, provides an indication of financial capital. While our current Western society is primarily concerned with financial wealth as an indicator of social status, thus net wealth is a critical indicator of risk capacity. This is because of the impacts on economic status and access to choices (Henretta & Campbell, 1978).
While the primary contributor to net wealth is traditionally the family home (CostaFont, Frank, & Swartz, 2018; Pfeiffer, 2017), this is generally not converted to income in retirement (Poterba, Venti, & Wise, 1994), and thus should be excluded from new wealth calculations for the purposes of portfolio allocation.
Home ownership is on the decline, as a result of changing family sociodemographics, particularly those who are married (Drew, 2015; Mundra & Uwaifo Oyelere, 2018), as well as declines in taxation incentives (Rosen, Bank, Eckstein, Stern, & Tcheau, 2017), gender, race and education challenges (Bourassa & Shi, 2017), and access to credit (Bourassa & Shi, 2017; Spader, McCue, & Herbert, 2016).
Property investment, even for a family home, is a very risky asset class according to the academic literature (Costa-Font et al., 2018; Teye, Haan, Elsinga, Bondinuba, & Gbadegesin, 2017; Wei, Zhang, & Liu, 2017).
Net wealth needs to be considered alongside actual historical behaviour to fully account for risk capacity (Sarlija, Bensic, & Zekic-Susac, 2009).
The net wealth calculation needs to measure investible assets (versus Jetski's and plasma screen TV's) as a proportion of net wealth (Davies, 2017). This is because it ensures that in a financial shock, lifestyle is not jeopardised (Davies, 2017).
Liquidity
When a client holds more liquid assets, this contributes positively to risk capacity because they are able to utilise their assets if needed (Davies, 2017), for either risk management or taking advantage of opportunities (Green, Melzer, Parker, & Rojas, 2016). Both a qualitative (eg. the holiday home is a family heirloom) and quantitative (eg. cash is more liquid than property) aspects of liquidity need to be considered, although it's calculation may pose some challenges.
Time Horizon
Investment time horizon is unique for each client, and each goal the client holds. Hence, goal specific time-horizon is also unique for each client. It is intuitive that the investment time horizon for each goal would impact on the clients capacity to take financial risk (Roszkowski & Grable, 2005).
Historically, researchers considered which life phase a client was in to determine time horizon (Cordell, 2001), and indeed the default superannuation funds generally still follow this approach. We now follow a much more sophisticated approach which considers the unique time horizon for each goal.
The literature on investing according to the life-cycle is very thorough (Basu & Drew, 2007, 2009; Chai, 2009; Li & Yao, 2007; Shefrin & Thaler, 1988; Viceira, 2007).
The time horizon for each goal, combined with the importance of each goal to the client, will impact the risk capacity calculation. Generally, a longer goal time-horizon will result in a higher risk capacity for that goal.
Human Capital
Human capital is our ability to generate wealth through income. In societies with high education standards and consistent wages across occupations (or marginal taxation structures to generate this effect), most wealth is stored as human capital rather than financial capital (Hanna et al., 2011).
In general, calculations of human capital include income volatility, education, occupational level (eg. manager), and years to retirement (more years to retirement, means higher human capital).
Debt
In the West there is a global trend of increasing over-indebtedness (Amadi, 2012; Gathergood, 2012; Nottage, 2013; Ottaviani & Vandone, 2011). Debt is risky because the result of financial stress, such as job loss, can have significant drops in consumer consumption (Baker, 2018). The financial implications of debt are that it can result in higher exposure to external negative contexts such as increasing interest rates or falling property prices (Kim, 2016).
Risk Capacity Calculation
Risk capacity is a scale (Cordell, 2002), which takes into account the equal contributors of financial capital and human capital (Hanna et al., 2011). Desired financial returns and psychological risk tolerance components should not be included in risk capacity calculations, but rather be stand-alone considerations
(Davies, 2017).
Insurance needs are included in this calculation, as it is the wealth protection component of the clients financial situation (Cordell, 2001). As does the relative size of each goal as a proportion of existing wealth (Davies, 2017).
References
Dr Katherine Hunt (BPsychSc, B Comm (Financial Planning), Honours in Finance
(University Medal). PhD}
Dr Katherine has been working with a.i. to develop a digital Risk Profile Questionnaire within the a.i. software platform, consisting of extensive academic research that enables advisers to have a robust foundation in determining risk for their clients, aligning their clients to the right asset allocation in line with their goals and life aspirations.
Dr Katherine has a Bachelor of Psychological Science, Bachelor of Commerce
(Financial Planning), and Bachelor of Finance (First Class Honours, University Medal).
You can also read one of the most extensive research reports carried out in Australia on Investment Risk Profiling: Lessons from Psychology by Dr Katherine, published in the Financial Planning Research Journal.
Research references as part of Dr Katherine's work:
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