The Investor Profile from DataPoints

To request a copy of our upcoming research paper on the Investor Profile to be presented at the CFP Academic Colloquium (see citation below), please email research @ datapoints.com. Copies of the paper will be emailed after the presentation in November.

Fallaw, S. S. & Grable, J. E. (2021). A Competency Modeling Approach to Assessing Psychological Risk Tolerance. Paper to be presented at the 2021 CFP Board Academic Colloquium, November 16, 2021.

Below is a summary of the technical information on the Investor Profile from DataPoints, an assessment designed to help you understand your client’s psychological risk tolerance. To learn more about the Investor Profile, please download our overview or our white paper here. Advisors working with DataPoints can access the full technical report in our Knowledge Base.

Psychological risk tolerance is a complex set of individual differences characteristics that can impact how an investor feels or behaves related to volatility in either the client’s portfolio, financial markets in general, or some combination of the two. The Investor Profile assessment is a psychometrically-sound assessment of constructs related to the behaviors that can be used by individuals and financial professionals as a measure of psychological risk tolerance. It improves upon past attempts at measuring risk tolerance by using a biodata-based approach to measurement, being applicable to investors with a wide range of investment or financial experience and providing factor-level information that can aid in coaching and development. The assessment can be used by individuals or by financial professionals providing investment advice to clients to help guide the creation of a portfolio that will be appropriate given their psychological risk tolerance and to provide recommendations for improving or maintaining certain financial behaviors that may improve the likelihood of sticking with a long-term investment strategy.

Test Components

The Investor Profile assessment provides advisors with three different types of information.

  • The Investor Profile score, an overall score that can be used as an assessment of risk tolerance to provide information on how advisors have allocated similarly profiled clients. This information is provided by DataPoints’ partnership with the Financial Planning Performance Lab.
  • Factor scores: Risk Preference, Investor Confidence, Volatility Composure, Investor Judgment, and Risk Personality.
  • Action score, designed to predict investment-related behavior during downturns in the market.

Test Development

The factors for the Investor Profile assessment were created using a competency modeling approach. Items for the Investor Profile were written to measure the factors uncovered from the competency modeling effort. Items were written using both biodata and other item writing techniques. After compiling all potential items, the item writing team reviewed all items and removed items that were (a) unclear and/or potentially low on readability, (b) measuring more than one construct, (c) an item that would require investing-related experience, or (d) not relevant to financial or investment-related tasks/topics.

Studies

Multiple studies served as the basis for the creation of the Investor Profile assessment factor, composite, and predictor scores. The studies were designed to gather data to examine the underlying factors related to investor-related behaviors and characteristics, to assess the construct and criterion-related validity of the factor scores, and to cross-validate the empirically-keyed scores and the factor structure of the remainder of the factors. Specifically, the studies examined:

  • The factor structure of the investor-related items, to establish the empirical key for a predictor of investor-related outcomes, and to examine the criterion-related validity of the test.
  • The construct validity of the individual factors and the Investor Profile score. Construct validation provides evidence that the factors and/or scores are measuring what they purport to measure by relating scores and factors to other similar measures.
  • The validity of the empirical key of the Investor Profile factor and the cross-validation of the factor scores with outcome measures in a new sample. Specifically, a concurrent validation strategy was employed using the scale scores and empirically-keyed scales. The importance of cross-validation is to ensure that (1) the empirical keys for the Investor Profile and Client Retention scores are similar across samples, and (2) the correlations among the variables are similar across samples.
  • The validity of the scales in individual investor and financial planning client populations.

Summary of Reliability Analyses

Internal consistency reliability was calculated for each of the factors. The goal was to create reliable measures with a minimum number of items in order to shorten the length of the test. Most of the factors met or exceeded the .70 threshold.

Summary of Validation Analyses

Criterion-Related Validation

A concurrent validation strategy was employed in two separate studies to examine the relationship between the various scores and the criteria of interest. This type of strategy is often employed in personnel selection scenarios, whereby an assessment is validated with an employment-population in order for it to be used in the selection of future employees who may or may not have experience with the job in question. Likewise, this strategy was used by Grable and Lytton (1999) in the creation of their risk tolerance assessment. By way of example, the results for Study 1 examining the relationship between the Investor Profile scores and criteria of interest are contained in Table 1.

Additional validation studies included examining the incremental validity of the Action score in the prediction of actions during a downturn in the market as well as comfort in investing above and beyond income, net worth, and self-reported preference. In multiple studies (including a cross-validation study), the Action score added incrementally to the prediction of investor behavior beyond simple risk preference.

Table 1: Correlations Among Investor Profile Scores and Criteria of Interest for Study 1

AgeIncomeNet WorthAction During Last DownturnComfort with Past Decline in Value of InvestmentsComfort Investing in Stocks
Investor Profile Score-.08.25**.29**.29**.33**.67**
Risk Preferences-0.040.18**0.13*0.13*0.25**0.48**
Investor Confidence-0.12*0.19**0.26**0.14*0.17**0.60**
Investor Judgment0.11*0.080.20**0.25**0.13*0.18**
Investor Composure-0.050.19**0.26**0.24**0.23**0.38**
Risk Personality-0.17**0.08-0.040.040.23**0.31**
Action Score-0.040.24*0.37*0.34**0.28**0.68**

*p < .05      ** p < .01

Construct Validation

The Investor Profile overall composite score and factor scores significantly relate to other measures of investor-related personality, including the scales listed in Table 2. The results of these analyses provided initial evidence of the construct validity of the scales. Specifically, the results supported the construct validation of the Investor Profile scores:

  • The Investor Profile, Investor Confidence, and Action scores related to Risk Tolerance
  • Investor Judgment was related to Education level and the Financial Knowledge measure
  • Investor Composure was negatively related to Personalization of Loss
  • Risk Personality was related to Risk Attitude and Sensation-Seeking measures

These findings generally support the construct validity of the Investor Profile composite and factor score. Future research should examine the relationships and validity using an approach to discern validity using multiple methods of measurement (e.g., multitrait-multimethod matrix, which can be used to establish both convergent and discriminant validation (Campbell & Fiske, 1959).

Table 2: Scales Included in Construct Validation Analyses for the Investor Profile

ConstructSourceDescription
Risk ToleranceGrable & Lytton, 200313-item scale measuring the multi-dimensional constructs of (1) investment risk, (2) risk comfort and experience, and (3) speculative risk with multiple-choice questions.
EducationMeasure of education level
Financial KnowledgeGrable & Joo, 200410 item (true/false) scale assessing financial knowledge. A composite score is developed by adding the number of correct responses per participant.
Sensation-SeekingGrable & Joo, 20045 items that ask the participant to circle the option closest to their personality trait, adapted from Arnett (1994). Responses are summed, with a higher score indicating greater propensity for risk-taking.
Investment HorizonWood & Zaichkowsky, 20044 items rated on a 7-point Likert scale (strongly disagree to strongly agree), with higher scores indicative of the length of time an investor expects to hold a portfolio.
Risk AttitudeWood & Zaichkowsky, 20042 items rated on a 7-point Likert scale (strongly disagree to strongly agree), with higher scores indicative of more comfort in possible initial financial losses.
Personalization of LossWood & Zaichkowsky, 20042 items rated on a 7-point Likert scale (strongly disagree to strongly agree), with higher scores indicative of greater self-doubt and internalization of loss when it does occur.

Application & Use of the Investor Profile from DataPoints

The DataPoints Investor Profile assessment is appropriate for adult populations who manage their household affairs. Specifically, the assessment is appropriate for individuals who are responsible for some aspect of leadership within their household. It should be noted that this assessment is not designed to be a clinical measure of money-related disorders, such as hoarding behavior, compulsive gambling, or other similar types of psychological disorders.

Test takers (clients) should complete the Investor Profile on their own, preferably in a quiet location free from distractions. The test should be completed in one sitting, and each client should complete the assessment him or herself (versus having one household complete a single assessment).

The Investor Profile can be readministered to examine changes in a client’s factor scores or overall score over time. Note that because the factors measured by the test are relatively stable, DataPoints recommends waiting a period of at least six months before retesting.


To learn more about the Investor Profile from DataPoints, please download our overview or our white paper here. Advisors working with DataPoints can access the full technical report in our Knowledge Base.