Abstract
This paper introduces the Santiago1000 Strategy, a novel stock selection method that integrates growth, momentum, and fundamental analysis to identify high-performing stocks. By combining criteria from the Twin Momentum and P/B Growth strategies, it targets stocks with low book-to-market ratios, high price momentum, strong fundamentals (G_SCORE ≥ 6), improving ROA/ROE trends, and positive free cash flow. The methodology involves a multi-step filtering process applied to NYSE and Nasdaq stocks. Results suggest that this strategy can potentially outperform traditional approaches by leveraging multiple return predictors. The study discusses implications, limitations, and future research directions, contributing to the field of investment strategy development.
Keywords
Santiago1000 Strategy, stock selection, growth stocks, momentum investing, fundamental analysis
Introduction
Stock selection remains a critical challenge in investment management, with various strategies aiming to maximise risk-adjusted returns. The Santiago1000 Strategy, developed by Antonio Walter Santiago, integrates elements of the Twin Momentum and P/B Growth strategies to create a comprehensive approach. This study aims to explain and defend the Santiago1000 Strategy, addressing the question: How can growth and momentum be effectively combined to select high-performing stocks? The paper builds on existing literature in momentum and growth investing, offering a new framework for investors.
Literature Review
The literature on stock selection highlights the efficacy of momentum and growth strategies. Jegadeesh and Titman (1993) established that stocks with high past returns tend to continue performing well, a phenomenon known as price momentum. Chan, Karceski, and Lakonishok (2003) demonstrated that fundamental trends predict returns, supporting the use of financial metrics in stock selection. Mohanram (2005) extended this to growth stocks, using the G_SCORE to differentiate winners from losers among low book-to-market (BM) firms, achieving significant excess returns. Huang et al. (2019) showed that combining price and fundamental momentum (based on trends in ROE, ROA, etc.) yields monthly average returns of 2.16%, outperforming standalone strategies. However, a gap exists in integrating these approaches into a unified strategy that balances growth, momentum, and financial health. The Santiago1000 Strategy addresses this gap by merging these dimensions.
Methodology
The Santiago1000 Strategy employs a five-step filtering process to select stocks:
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Low Book-to-Market Ratio: Select stocks in the bottom 20% of the book-to-market (BM) ratio, identifying growth stocks with high market value relative to book value.
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High Price Momentum: From this subset, choose stocks in the top 20% of 12-month returns, capturing price momentum.
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Strong Fundamental Metrics (G_SCORE): Filter for stocks with a G_SCORE ≥ 6, based on eight signals (ROA, CFROA, earnings variability, R&D intensity, etc.), as per Mohanram (2005).
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Fundamental Momentum: Ensure ROA and ROE have been improving over the past 3 years, aligning with the fundamental momentum component of Twin Momentum, which uses trends in seven variables (ROE, ROA, EARN, APE, CPA, GPA, NPY).
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Positive Free Cash Flow: Include only stocks with positive free cash flow in the latest fiscal year, defined as operating cash flow minus capital expenditures > 0, ensuring financial health.
The sample consists of stocks listed on the NYSE and Nasdaq, with data sourced from platforms like Finviz and Yahoo Finance. The analysis is theoretical, relying on historical performance patterns and expected outcomes based on prior research.
Results
Although this study is theoretical, expected results are inferred from prior research. Mohanram (2005) demonstrated that G_SCORE-based strategies generate excess returns, while Huang et al. (2019) showed that Twin Momentum outperforms standalone strategies. The integration suggests that Santiago1000 may offer superior returns, particularly in bull markets, due to its diversified criteria. Applying the strategy to NYSE and Nasdaq stocks, examples include Apple (AAPL), Microsoft (MSFT), Amazon (AMZN), Nvidia (NVDA), and Tesla (TSLA), which often meet the criteria (low BM, high returns, high G_SCORE, improving ROA/ROE, positive free cash flow). A sample list of
20 stocks is provided below:
|
Ticker
|
Name
|
Exchange
|
Sector
|
|---|---|---|---|
|
AAPL
|
Apple Inc.
|
Nasdaq
|
Technology
|
|
MSFT
|
Microsoft Corp.
|
Nasdaq
|
Technology
|
|
AMZN
|
Amazon.com Inc.
|
Nasdaq
|
Consumer Discretionary
|
|
NVDA
|
Nvidia Corp.
|
Nasdaq
|
Technology
|
|
TSLA
|
Tesla Inc.
|
Nasdaq
|
Consumer Discretionary
|
|
GOOGL
|
Alphabet Inc.
|
Nasdaq
|
Communication
|
|
META
|
Meta Platforms Inc.
|
Nasdaq
|
Communication
|
|
NFLX
|
Netflix Inc.
|
Nasdaq
|
Consumer Discretionary
|
|
ADBE
|
Adobe Inc.
|
Nasdaq
|
Technology
|
|
CRM
|
Salesforce.com Inc.
|
NYSE
|
Technology
|
|
AVGO
|
Broadcom Inc.
|
Nasdaq
|
Technology
|
|
AMAT
|
Applied Materials Inc.
|
Nasdaq
|
Technology
|
|
LRCX
|
Lam Research Corp.
|
Nasdaq
|
Technology
|
|
KLAC
|
KLA Corp.
|
Nasdaq
|
Technology
|
|
INTU
|
Intuit Inc.
|
Nasdaq
|
Technology
|
|
BKNG
|
Booking Holdings Inc.
|
Nasdaq
|
Consumer Discretionary
|
|
MAR
|
Marriott Intl Inc.
|
Nasdaq
|
Consumer Discretionary
|
|
ABNB
|
Airbnb Inc.
|
Nasdaq
|
Consumer Discretionary
|
|
MRNA
|
Moderna Inc.
|
Nasdaq
|
Healthcare
|
|
PANW
|
Palo Alto Networks Inc.
|
Nasdaq
|
Technology
|
This list is illustrative, and real-time data verification is recommended.
Discussion
The Santiago1000 Strategy offers several advantages:
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Diversified Criteria: It combines growth (low BM), momentum (price and fundamental), and financial health, reducing reliance on a single factor.
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Potential for Higher Returns: By integrating multiple return predictors, it may outperform traditional strategies, especially in volatile markets.
-
Risk Management: The requirement for positive free cash flow and a high G_SCORE ensures the selection of financially sound companies, mitigating risks of overvaluation.
However, limitations include: -
Complexity: The strategy requires detailed financial data and calculations like G_SCORE, which may be challenging for individual investors.
-
Risk of Overfitting: Multiple criteria may lead to overfitting, particularly without out-of-sample validation.
-
Transaction Costs: Frequent adjustments to maintain criteria may increase costs, impacting net returns.
Future research could involve backtesting over extended periods, comparing performance against benchmark indices, and analysing sensitivity to market conditions.
Conclusion
The Santiago1000 Strategy presents a comprehensive approach to stock selection, integrating growth, momentum, and fundamental strength. By combining the best elements of the P/B Growth and Twin Momentum strategies, it aims to identify stocks with superior return potential while managing risks through rigorous criteria. This strategy is a valuable tool for investors seeking to build high-performing portfolios based on robust financial analysis, updated as of 30 March 2025.
References
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Mohanram, P. S. (2005). Separating Winners from Losers among Low Book-to-Market Stocks using Financial Statement Analysis. Review of Accounting Studies, 10(2-3), 133-170.
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Huang, D., Zhang, H., & Zhou, G. (2019). Twin Momentum: Fundamental Trends Matter. SSRN. Available at: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2894068
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Jegadeesh, N., & Titman, S. (1993). Returns to buying winners and selling losers: Implications for stock market efficiency. The Journal of Finance, 48(1), 65-91.
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Chan, L. K. C., Karceski, J., & Lakonishok, J. (2003). The level and persistence of growth rates. The Journal of Finance, 58(2), 643-684.
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Piotroski, J. D. (2000). Value investing: The use of historical financial statement information to separate winners from losers. Journal of Accounting Research, 38(Supplement), 1-41.
Santiago1000 Strategy
