Investment professionals have a fiduciary duty to analyze both the upside potential of a stock and its downside risks. And the most reliable method to fulfill this responsibility is by using data sciences, statistics and AI.

By Raymond M. Mullaney, CEO
January 10, 2025

Vital Questions for Statistical Analysis:

1) Price Movement Probability:

  • What’s the statistical frequency of price increases vs decreases?
  • How often do similar stocks move up/down in comparable market conditions?
  • What’s the historical volatility and price distribution?

2) Magnitude Assessment:

  • What’s the average size of upward vs downward moves?
  • What are the maximum historical gains/losses?
  • How do earnings/revenue changes correlate with price changes?

3) Risk Analysis:

  • What’s the current NPV vs Market Cap ratio?
  • How leveraged is the balance sheet?
  • What’s the cash burn or generation rate?

Current AI Adoption Barriers:

  1. Traditional reliance on human analysts
  2. Limited awareness of AI capabilities
  3. Resistance to quantitative approaches
  4. Investment industry inertia

Expected Timeline for AI Adoption:

  • Institutional investors: Already beginning
  • Financial advisors: 2-3 years
  • Retail investors: 3-5 years for widespread adoption

Three important facts for fiduciaries:

  1. Without statistical analysis of both upside and downside scenarios, investing becomes speculation rather than calculated risk-taking.
  2. Data sciences and AI tools can process vast amounts of historical data to generate these probabilities, making them invaluable for risk assessment.
  3. Data science will add tremendous value to your clients’ portfolios, your bottom line and both you and your clients’ peace of mind.