Pilot Study — Phase 1

Measuring the cognitive biases
that shape financial decisions

Sigmalign is a behavioural finance research initiative developing a psychometric instrument to identify and quantify the biases that influence investor behaviour. We are currently conducting a 60-day pilot study with financial advisors and their clients in Canada.

Loss Aversion · Overconfidence · Herding Susceptibility · Anchoring · Recency Bias

A pilot study in behavioural wealth intelligence

Despite decades of research establishing that cognitive biases systematically distort financial decisions, the advisory industry lacks a standardised, validated instrument for measuring these biases at the individual client level.

The Sigmalign Pilot Study is a 60-day observational study designed to establish the feasibility and early reliability data needed to develop such an instrument. We work directly with licensed financial advisors and their consenting clients in a naturalistic advisory setting.

Phase 1 is not a claim to validity. It is the structured, pre-registered data collection effort required to eventually make one.

60
Day study period
2
Assessment waves
25
Instrument items
5
Bias dimensions
Score + Debrief

Advisors receive the Sigmalign Score report and conduct a structured debrief conversation. Behavioural events are logged throughout the study period.

Score Only

Advisors receive the score report with no structured debrief protocol. Provides a comparison condition for evaluating the role of the debrief conversation.

The Sigmalign Score — plainly explained

The Sigmalign Score is a psychometric assessment that measures five cognitive biases known to influence financial decision-making. It is grounded in behavioural economics and prospect theory, drawing on the published work of Kahneman, Tversky, Thaler, Odean, and others.

How it works

Clients complete 25 scenario-based questions, each presenting a realistic financial situation and four possible responses. There is no "right" answer — responses are scored for the degree of bias they reflect, not financial knowledge.

Each of the five bias dimensions is scored independently on a continuous scale. The composite Sigmalign Score is the unweighted mean of those five scores.

What it measures

  • Loss Aversion (LAS) — tendency to weight potential losses more heavily than equivalent gains
  • Overconfidence (OS) — tendency to overestimate personal financial knowledge or predictive ability
  • Herding Susceptibility (HSS) — tendency to follow peers, media, or market trends rather than a personal plan
  • Anchoring (AS) — tendency to over-weight an initial reference point when making hold, sell, or rebalancing decisions
  • Recency Bias (RBS) — tendency to over-weight recent events when forming expectations about future returns

What Phase 1 is designed to establish

  • Internal consistency (Cronbach's alpha) for each dimension
  • Test-retest reliability across the 60-day window
  • Face validity from client self-report
  • Feasibility of advisor-facilitated administration
  • Preliminary advisor-client behavioural event data

What this study does not claim

Phase 1 is not a validation study. With a sample of 10–30 clients across 3–5 advisors, it cannot establish construct validity, predictive validity, or published test-retest reliability. A formal study protocol is available on request.

Sigmalign Score Bands
Band Score Range Interpretation
Calibrated 5.0 – 9.9 Bias strength is low. Client is likely to respond to advisor guidance in a plan-consistent manner under moderate stress.
Active 10.0 – 13.9 Bias is present and likely to influence decisions under stress. Structured communication is recommended.
Reactive 14.0 – 17.9 Bias is elevated. Client is at meaningful risk of plan-inconsistent decisions during market events.
Critical 18.0 – 20.0 Bias is severe. Proactive advisor engagement and a documented coaching plan are strongly recommended.

Band designations are descriptive, not diagnostic. They do not constitute investment advice, suitability determinations, or clinical assessments. Thresholds are provisional and will be empirically calibrated using Phase 1 and Phase 2 data.

Kris Podolski, Founder & CEO of Sigmalign Behavioural Intelligence

Kris Podolski

CFP® CIM® — Founder & CEO
Sigmalign Behavioural Intelligence Inc.
Toronto, Ontario

Kris Podolski brings twenty years of practice as a financial planner to this research. Holding both the Certified Financial Planner (CFP®) and Chartered Investment Manager (CIM®) designations, he has spent two decades observing how cognitive patterns — rather than financial knowledge — determine whether clients follow their own financial plans under stress.

That observation is the origin of Sigmalign. The existing tools available to advisors — risk tolerance questionnaires, KYC forms, suitability assessments — measure stated preferences and financial knowledge. None of them measure the bias profiles that predict how a client will actually behave when markets move against them.

Sigmalign is an attempt to build that instrument properly: grounded in behavioural science, designed for the advisory context, and developed through a structured research process rather than intuition.

Kris welcomes dialogue with academic researchers working in behavioural finance, financial decision-making, and psychometric instrument development.

Interested in the research?

We are actively seeking academic researchers with expertise in behavioural finance, psychometric instrument development, financial decision-making, or related fields. Collaboration may take several forms:

  • Instrument design review and item-level feedback
  • Statistical consultation for Phase 1 analysis
  • Co-authorship on research outputs from Phase 2 onward
  • Academic advisory and ethics oversight roles

A full study protocol is available on request. We are happy to share it in advance of any conversation.

Get in touch

Reach out directly by email. Please include your research area and affiliation — we will respond within two business days.

Email Kris Podolski
kris@sigmalign.ca · sigmalign.ca