Exploring Large Caps Quality: A Three-Step Evaluation for Quality Value Stocks
In the following we describe the 3-step approach how the Large Caps Quality strategy was created. The portfolio can be seen here.
Step 1: Qualitative Filters
The first step is to apply qualitative filters to the universe of stocks. A stock is considered a buy if it meets the following criteria:
Market Cap bigger than 10B USD
Return on Equity (TTL) bigger than 10%
Gross Profit Margin (TTL) bigger than 35% or Operating Margin (TTL) bigger than 35%
Net Debt / EBIT (TTL) smaller than 400%
EV/FCF (TTL) smaller than 60
Operating Margin (TTL) bigger than 10%
Cash Return on Invested Capital (TTL) bigger than 10%
Growth rate of quarterly Revenues over 5 years bigger than 0%.
If a stock fails to meet any of these criteria, it is filtered out.
Step 2: Scoring System
The second step is to score the remaining stocks based on additional criteria. Stocks are awarded one point for each of the following criteria:
Gross Profit Margin (TTL) bigger than 50% or Operating Margin (TTL) bigger than 50%
Net Debt / EBIT (TTL) smaller than 100%
Return on Equity (TTL) bigger than 15%
Cash Return on Invested Capital (TTL) bigger than 15%
Price to Free Cash Flow (TTL) smaller than 30
Growth rate of quarterly Revenues over 5 years bigger than 10%
Operating Margin (TTL) bigger than 15%
Step 3: Total Score
The final step is to calculate the total score for each stock by summing up the points awarded in step 2. A stock is considered a buy if its total score is bigger than 5, otherwise it is filtered out.
List of filtered Stocks
Take a look at the snapshot of the dynamic stock list from May 9, 2023. On this particular day, a total of 79 stocks successfully passed our rigorous 3-step evaluation process. Among the well-known securities like Apple, Adobe, and Microsoft, you'll also find some hidden gems such as Aspen Technologies and Chesapeake Energy. In the accompanying screenshot, you can easily identify the score criteria marked with green or red icons, indicating whether each criterion was met or not.
Backtesting
The effectiveness of the Large Caps Quality strategy has been thoroughly verified through a comprehensive backtest spanning from August 2007 to March 2023. This extensive period covers significant market events such as the financial crisis in 2008, the COVID-19 pandemic in 2020, and the bearish year of 2022. The test was run with a daily rebalancing interval. The remarkable outcome of the backtest revealed an impressive 13.4% compound annual growth rate (CAGR) over the span of 15 years (see screenshot below).
Comparatively, the strategy's performance almost doubled that of the S&P 500 benchmark, which recorded a CAGR of 6.9%. During the onset of the COVID-19 pandemic, the portfolio experienced its largest drawdown, resulting in a decline of 28%. However, the portfolio showed resilience and managed to recover to its previous high within a period of three months. These compelling results firmly affirm the efficacy of the Large Caps Quality strategy as a smart investment approach.
Conclusion
In conclusion, the article provides insights into the 3-step approach of the quantitative Large Caps Quality strategy for stock investors. By applying qualitative filters and a scoring system based on specific criteria, the strategy aims to identify potential investment opportunities. The filtered stock list from May 9, 2023, showcases a diverse range of stocks, including well-known companies like Apple, Adobe, and Microsoft, as well as lesser-known gems such as Aspen Technologies and Chesapeake Energy.
The effectiveness of the strategy is further supported by thorough backtesting. The backtest, which covers a significant period from August 2007 to March 2023, including major market events, reveals an impressive compound annual growth rate (CAGR) of 13% over 15 years. This outperforms the CAGR of the S&P 500 benchmark, which stood at 7%. The portfolio recovered from the largest drawdown (28%) in the corona crisis within 3 months. It is important to note that these results are historical and do not serve as a guarantee for future performance.
The strategy was created using the Stock Screener tool from SimFin and was subjected to backtesting. Details on the quantitative criteria and the backtesting results can be viewed in detail here: https://app.simfin.com/portfolio/63d67599469e365d329af9c0
Disclaimer: The information in this article is for educational purposes only and should not be construed as financial advice. The author is not acting as a financial advisor, and readers are solely responsible for their investment decisions. The author and publisher disclaim any liability for losses or damages resulting from the use of this information. Investing carries risks, and past performance is not indicative of future results. It is essential to conduct thorough research and consult with a qualified financial professional before making any investment decisions. Readers should independently verify information and consider their own financial situation and risk tolerance.
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