AI with VantagePoint
How AI with VantagePoint Fits into Our Process
October Effect Limited uses AI-enabled analytics provided by VantagePoint as part of its investment research and ongoing portfolio review process.
These tools are designed to analyze large volumes of market data and may help identify developing trends, shifts in market conditions, and potential risk signals that warrant further review.
The technology is used as one input among many within a broader investment process. Artificial intelligence does not replace disciplined portfolio construction, risk management principles, or professional judgment. All investment decisions remain subject to human evaluation and oversight.
AI-driven analytics rely on mathematical models and historical market data. Market conditions can change unexpectedly, and no technology or methodology can predict market movements with certainty. Investment strategies are implemented in alignment with client objectives, time horizons, and risk tolerance.
Artificial intelligence tools are used as part of the research and monitoring process. No technology can eliminate investment risk. All investing involves risk, including the possible loss of principal. Past performance does not guarantee future results.
Understanding Investment Performance Reporting
Investment performance reporting is highly regulated and inherently complex. Presenting performance information in a clear, fair, and compliant manner requires adherence to established calculation methodologies, disclosure standards, and regulatory requirements.
Performance results must be calculated consistently and presented with appropriate context. This includes identifying the relevant time periods, explaining underlying assumptions, disclosing material limitations, and clearly stating whether returns are shown net or gross of fees and expenses. Without this context, performance information can be incomplete or potentially misleading.
Regulatory guidance under the SEC Marketing Rule establishes standards for how performance may be presented in advertising and client communications. These standards are designed to promote transparency and to help ensure that investors receive balanced information that reflects both potential benefits and material risks.
Investors should understand that market returns fluctuate over time, and no reporting format eliminates uncertainty. Past performance does not guarantee future results. Hypothetical, backtested, or model-based performance—if presented—has inherent limitations and may differ from actual trading results. All investing involves risk, including the possible loss of principal.
Because of these complexities, performance reporting must meet a high standard of accuracy, documentation, and disclosure before it is shared with clients or prospective investors.
A Brief History of Technology in Investment Analysis
In this short video, Frank shares a practical history of how technology has evolved within investment management — from early computer-driven modeling to modern artificial intelligence systems.
Decades ago, investment professionals began using computer-based statistical modeling to better understand risk and probability. One of the most widely known examples is the Monte Carlo simulation — a method that runs thousands of hypothetical market scenarios to evaluate how a portfolio might behave under different conditions. Rather than predicting a single outcome, Monte Carlo analysis evaluates a range of possible outcomes based on historical patterns and probability assumptions.
As computing power expanded, so did the ability to process increasingly complex datasets. What once required mainframe systems can now be executed in seconds. Over time, mathematical modeling evolved into machine learning techniques capable of identifying patterns within large volumes of financial data.
Artificial intelligence represents the next stage of that evolution. Modern AI systems analyze historical market behavior, price relationships, and trend dynamics at a scale and speed that would not be possible manually. However, like earlier statistical models, AI relies on assumptions, historical data, and structured algorithms. It does not eliminate uncertainty.
In this video, Frank explains how these tools developed over time and how they fit into a disciplined investment process today.
This video is for educational purposes only. This content does not constitute investment advice, and references to specific platforms are not endorsements or recommendations. Investing involves risk, including the possible loss of principal.
Independent Performance Tracking Through Theta Research
Theta Research is an independent third-party firm that specializes in performance tracking and reporting for boutique investment advisory firms and individual retirement account (IRA) strategies. The firm provides standardized reporting tools designed to calculate and present investment results using consistent methodologies.
Third-party performance tracking can provide an additional layer of structure and documentation in the reporting process. Independent calculation and reconciliation help promote transparency and consistency in how performance data is compiled and displayed.
Theta Research is not affiliated with October Effect Limited, and the firm does not provide investment advice to October Effect clients. Its role is limited to performance calculation and reporting services.
Individuals who wish to review performance reporting through Theta Research may request guest access, if available, or obtain their own subscription directly through Theta Research.
For a guest pass to ThetaResearch please call the office at (757) 390-3341.
Third-party services referenced are independent organizations.
References do not constitute an endorsement or guarantee of services.
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