Third-Party Research & Methodology Only

This section shares summaries of third-party academic research and descriptions of quantitative models. The content represents the findings of the original researchers, not the opinions or recommendations of Foxholm Financial. Foxholm Financial does not publish hypothetical or backtested performance metrics on its quantitative research pages. All content is restricted to methodology, signal construction, factor logic, and risk architecture. SEC rules require that investment advisers not present misleading performance data, and our methodology-only approach reflects that standard and the firm's fiduciary obligations.

Concepts

Core Quantitative Investing Concepts

The building blocks behind quantitative investing. These pages cover the ideas that show up across many different models and strategies: how risk is measured, what factors are, why backtests can mislead, and how trading costs eat into returns. Each concept stands on its own but connects to the models and research that depend on it.

Risk & Return Measurement

How to tell whether a strategy is actually good, not just lucky. These concepts cover the standard tools for comparing strategies on equal footing by accounting for risk.

Risk-Adjusted Returns
Metrics like the Sharpe ratio that measure how much extra return a strategy earns for each unit of risk taken.
Signal Decay
Why trading signals lose their edge over time as more investors discover and act on the same patterns.
Transaction Costs and Execution
The hidden costs of trading, including commissions, bid-ask spreads, and the price impact of large orders.

Factor & Model Construction

How quantitative models are built and tested. These concepts explain the process of turning raw market data into investable strategies, and the mistakes that can make a model look better than it really is.

How Factor Models Are Built
How researchers isolate characteristics like value, momentum, and quality from raw market data.
Overfitting and Data Snooping
When a model mistakes noise for signal by fitting too closely to past data, making it useless for the future.
Backtesting Pitfalls
Common mistakes that make a strategy look better in testing than it actually is, including survivorship bias and look-ahead bias.

Portfolio & Market Dynamics

How different investments interact with each other and how market conditions shift over time. These concepts underpin portfolio construction and risk management.

Correlation and Diversification
The math behind why combining investments reduces risk, and why diversification can fail when you need it most.
Market Regime Detection
Methods for identifying whether markets are in a calm, trending, or turbulent state, and why strategies perform differently in each.
Tail Risk and Fat Tails
Why extreme market events happen far more often than standard models predict, and what that means for portfolio protection.
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Disclaimer

This content is for educational and informational purposes only and does not constitute an offer to sell or a solicitation of an offer to buy any securities. Nothing herein constitutes investment advice or recommendations tailored to your individual situation. All investments involve risk, including the potential loss of principal. Past performance is no guarantee of future results. Information presented is believed to be factual and up-to-date, but Foxholm Financial does not guarantee its accuracy and it should not be regarded as a complete analysis of the subjects discussed. Before making investment decisions, consult with a qualified financial advisor who can evaluate your specific circumstances.