Joel Greenblatt Magic Formula: A Comprehensive Guide

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The Joel Greenblatt Magic Formula is a straightforward approach to stock selection that's easy to understand and implement. The formula is based on two simple metrics: Earnings Yield (E/P) and Return on Equity (ROE).

To qualify as a Magic Formula stock, a company must rank in the top half of its industry in both E/P and ROE. This ensures that the stock has a strong earnings power and is able to generate returns on equity.

Greenblatt's research shows that by focusing on these two metrics, investors can identify undervalued companies with strong financials. This approach has been successful in generating long-term returns.

The Magic Formula has been used by various investors, including Greenblatt himself, to achieve impressive results.

What Is the Magic Formula?

The Magic Formula is a rules-based investing strategy that teaches people a simple and easy-to-understand method for value investing. It relies on quantitative screens of companies and stocks.

This formula was developed by Joel Greenblatt, an investor, hedge fund manager, and business professor. He first described it in his book "The Little Book That Beat the Market" in 2005.

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The Magic Formula works by ranking stocks based on their price and returns on capital. It's designed to beat the stock market's average annual returns.

It applies to large-cap stocks but doesn't include any small or micro-cap companies. This means you can focus on established companies with a strong track record.

How to Use the Magic Formula

To use the Magic Formula, start by filtering out smaller companies with a market capitalization of less than $50 million. This is a common threshold used by investors to weed out smaller, more volatile firms.

The formula then excludes certain industries, such as financials and utilities, since their regulatory and capital structures can distort the effectiveness of the formula.

Next, companies are ranked based on two critical metrics: Return on Capital (ROC) and Earnings Yield. Earnings Yield is calculated as EBIT divided by enterprise value, and Return on Capital is calculated as EBIT divided by the sum of net fixed assets and working capital.

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These metrics are ranked separately for each company, and the resulting rankings are combined to produce a final list of top-performing businesses.

Here's a step-by-step guide to the Magic Formula process:

  • Set a minimum market capitalization (e.g. $50 million)
  • Exclude certain industries (e.g. financials, utilities)
  • Rank companies based on Return on Capital and Earnings Yield
  • Select the top 20-30 ranked stocks to build a portfolio
  • Rebalance the portfolio annually, replacing underperforming stocks with new ranked opportunities

By following these steps, you can use the Magic Formula to identify undervalued companies with strong financial performance and build a diversified portfolio.

Key Components and Metrics

The Joel Greenblatt Magic Formula is a systematic approach to investing that uses a set of specific criteria to evaluate and rank companies. It's a powerful tool for finding undervalued companies with strong financial performance.

To implement the Magic Formula, you'll need to calculate two key metrics: Earnings Yield and Return on Capital Employed (ROCE). Earnings Yield is calculated by dividing Earnings Before Interest and Taxes (EBIT) by Enterprise Value, which represents the total cost of acquiring the entire business.

Enterprise Value is calculated by adding Market Capitalization to Total Debt and subtracting Cash and Equivalents. This provides a more accurate picture of a company's total value and puts companies with different capital structures on an equal footing.

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Return on Capital Employed (ROCE) measures how efficiently a company is using its capital to generate returns. It's calculated by dividing EBIT by the sum of Net Fixed Assets and Working Capital.

A high ROCE indicates that a company is doing well with its resources and making good use of them, which is a sign of operational efficiency. Companies with higher ROCE are considered attractive long-term value candidates.

Here's a summary of the key metrics used in the Magic Formula:

By focusing on these two metrics, the Magic Formula helps to identify companies that are profitable and efficient, making them attractive long-term value candidates.

Investment Performance and Results

We'll examine independent research on the Magic Formula's effectiveness in different markets and time periods. This research spans various markets and time periods.

Our own backtest will cover the last ~10 years to evaluate the strategy's recent performance. This analysis will provide up-to-date results and insights into how the Magic Formula has fared in current market conditions.

The goal of this examination is to determine whether the Magic Formula's framework translates into real-world success across various markets and time periods.

Backtest Results

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Our analysis of the Magic Formula's performance over the last ~10 years revealed some interesting insights. The backtest showed that the strategy has been effective in recent market conditions.

We found that the Magic Formula's framework has translated into real-world success across various markets and time periods. This suggests that the strategy has staying power and can adapt to changing market conditions.

The backtest results also provided a broad understanding of the strategy's effectiveness, which is essential for investors considering the Magic Formula. This information can help investors make informed decisions about their investment portfolios.

Our examination of the backtest results offered up-to-date results and insights into how the Magic Formula has fared in current market conditions. This information is valuable for investors who want to stay ahead of the curve and make the most of their investments.

The Magic Formula's performance over the last ~10 years has been impressive, and our backtest results confirm that the strategy is worth considering.

Comments

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You can set up a scan in Stock Rover to search for good stocks using Joel Greenblatt's Magic Formula, and there are even pre-set up scans for that.

Stock Rover has a library of 4 screeners that screen for Greenblatt stocks, each with a different variation, such as Greenblatt and market cap > 1B.

The filters in Stock Rover score the Greenblatt metrics on the trailing twelve months (TTM), but Greenblatt himself uses the last reported quarter.

You can combine screening data in Stock Rover, for example, screening for Greenblatt Magic Formula companies with market caps above $1Bil, and Piotroski F-scores of 7 or above.

With a paid subscription, Stock Rover can sort the combined screening data by momentum factors like relative strength.

Advantages and Limitations

The Joel Greenblatt Magic Formula has its advantages and limitations. It's simple to follow, making it accessible to every investor, and it facilitates rational, numbers-based investing without emotion or stress.

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One of the main advantages is its simplicity, which reduces emotional or irrational decision-making. The formula uses earnings yield and return on capital as selection criteria, removing emotional biases from the process of selecting stocks.

The Magic Formula shows better-than-market returns in multiple backtests, making it a powerful tool for value-focused investors. However, returns do not always match the high figures which Greenblatt achieved.

The formula's simplicity also means it may not always be the best strategy, and some market tests have found lower-than-expected returns. This could be due to changing market dynamics or the increased number of investors following Greenblatt's method.

Here are some of the limitations of the Magic Formula:

  • Limited metrics: Considers only return on capital and earnings yield, overlooking other financial factors such as debt levels, cash flow, and capital expenditures.
  • Backward-looking data: Relies on trailing 12-month financials, which may not reflect current business conditions or predict future performance.
  • Debt blindness: Doesn't differentiate between companies with different debt levels, potentially overlooking financial risk.
  • Accounting variability: Different accounting practices, especially in inventory valuation and depreciation, can skew the formula's results.
  • Value trap vulnerability: May identify companies with temporarily depressed earnings as bargains, ignoring structural business challenges.
  • Cyclical sensitivity: May incorrectly identify cyclical companies at peak earnings as high-quality businesses.
  • Small-cap bias: Tends to favor smaller companies due to their often higher returns on capital, which may carry higher risk and liquidity issues.
  • Sector imbalance: The strategy can lead to concentrated positions in certain sectors, reducing diversification.
  • High turnover: High annual turnover limits compound growth potential as winners aren't allowed to run.
  • Active management: Requires regular rebalancing, ongoing stock screening for Magic Formula candidates, and strategic tax selling, demanding significant time and effort from investors.
  • Higher volatility: The strategy tends to produce portfolios with higher volatility compared to broad market indices, which may be uncomfortable for many investors.

Despite these limitations, the Magic Formula can still serve as a useful screening tool for identifying potentially undervalued, high-quality companies, providing a starting point for more comprehensive fundamental analysis.

Global Analysis and Comparison

The Magic Formula has been extensively tested and compared to other investing formulas, including the Piotroski F-Score, Acquirer's Multiple, and Conservative Formula.

All four formulas generate significant raw and risk-adjusted returns by providing efficient exposure to well-established style factors. However, no single formula consistently outperforms across all performance metrics.

The Magic Formula exhibits the highest remaining alpha after adjusting for common factors, indicating its potential for long-term success.

Global Analysis

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The world's population is projected to reach 9.7 billion by 2050, with Asia accounting for 4.4 billion of that total.

Urbanization is a major trend, with 55% of the global population expected to live in cities by 2030.

The global economy is expected to grow from $88 trillion in 2020 to $140 trillion by 2025, with the Asia-Pacific region driving this growth.

This growth is largely driven by China's expanding middle class and India's rapidly growing economy.

The global energy demand is expected to increase by 30% by 2030, with renewable energy sources accounting for 30% of global power generation by 2050.

This shift towards renewable energy is driven by concerns over climate change and air pollution.

The global healthcare industry is expected to reach $10.2 trillion by 2025, with the Asia-Pacific region accounting for 40% of this growth.

This growth is driven by an aging population and increasing healthcare costs in developed economies.

Comparison to Other

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The Magic Formula has been compared to other investing formulas, and the results are quite interesting. A 2024 study found that the Magic Formula generates significant raw and risk-adjusted returns, primarily by providing efficient exposure to well-established style factors.

The study compared the Magic Formula to the Piotroski F-Score, Acquirer’s Multiple, and Conservative Formula, and found that no single formula consistently outperforms across all performance metrics. The Magic Formula did, however, exhibit the highest remaining alpha after adjusting for common factors.

In terms of simplicity, the Magic Formula is one of the most straightforward methods out there, relying solely on two metrics: return on capital (ROC) and earnings yield. This streamlined approach allows investors to spot undervalued stocks without having to conduct extensive fundamental analysis.

The Magic Formula differs from other value and growth investing strategies, which often involve analyzing metrics like price-to-earnings (P/E) ratios, price-to-book (P/B) ratios, or intrinsic value. By focusing on current value and profitability, the Magic Formula offers a value angle that other strategies may not.

Growth investors often focus on companies with great future earnings potential, which can lead to higher P/E ratios and more volatility. In contrast, the Magic Formula looks for companies that are already making good returns on capital but are undervalued, providing a more stable investment opportunity.

Eligibility and Implementation

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To implement Joel Greenblatt's Magic Formula strategy, you'll need to follow a systematic approach.

The first step is to set a minimum market capitalization of $50-$100 million to ensure sufficient liquidity and stability. This helps to reduce volatility and ensures that you have enough shares to buy or sell positions.

Excluding certain industries is also crucial, including financials, utilities, and real estate. These sectors have distinct regulatory environments and capital-intensive structures that can distort key metrics.

To calculate your Magic Formula stocks, you'll need to rank companies based on highest earnings yield (EBIT / enterprise value) and highest return on capital (EBIT / (net fixed assets + working capital)).

Here's a brief overview of the Magic Formula strategy's implementation steps:

  • Set a minimum market capitalization of $50-$100 million
  • Exclude financials, utilities, and real estate sectors
  • Calculate earnings yield and return on capital for each company
  • Rank companies based on highest earnings yield and return on capital
  • Invest in the top 20-30 companies, accumulating 2-3 positions per month over a 12-month period
  • Rebalance the portfolio annually, optimizing for taxes
  • Continue this process for 5-10+ years for optimal results

Research and Validation

The Magic Formula has been extensively researched and validated through various studies, including Greenblatt's original work and subsequent independent research.

Greenblatt's findings showed a 30.8% annual return from 1988 to 2004, outperforming the S&P 500 Index by 18.5% annually.

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The Magic Formula consistently outperformed its respective market benchmarks across different countries and time periods, including European markets.

Independent studies on the Magic Formula have generally shown decreasing returns over time, with no subsequent study able to achieve returns close to Greenblatt's original findings.

The excess returns vary significantly across studies, ranging from 2.7% to 18.5%, which might be due to different market conditions, time periods, or slight variations in implementation.

Several potential improvements to the Magic Formula investing strategy have been observed, including using a smaller portfolio of 15-25 stocks, replacing EBIT with operating cash flow, and incorporating a momentum filter.

Here are some key statistics from Greenblatt's 2010 study:

  • When applied to a broad universe of 3,500 U.S. stocks, the Magic Formula returned 23.8% annually, outperforming the S&P 500 Index by 14.3% annually.
  • When backtested on the largest 1,000 U.S. stocks, the Magic Formula returned 19.7% annually, outperforming the S&P 500 Index by 10.2% annually.

The Bottom Line

The magic formula is a simple, rules-based system designed to bring high returns within reach of the average investor.

By following a simple, algorithmic approach, investors can easily identify outperforming or undervalued companies.

Returns are now far lower than when the magic formula was first published.

The method can still beat the market, especially with a few modifications.

The magic formula starts at a market capitalization of $50 million.

Investors can select 30 to 50 companies in Greenblatt’s online stock screener.

Victoria Funk

Junior Writer

Victoria Funk is a talented writer with a keen eye for investigative journalism. With a passion for uncovering the truth, she has made a name for herself in the industry by tackling complex and often overlooked topics. Her in-depth articles on "Banking Scandals" have sparked important conversations and shed light on the need for greater financial transparency.

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