Magic Formula Investing
Magic Formula Investing is an investment strategy which advocates simplified, systematic stock selection that promises sound returns. Developed by Joel Greenblatt, a renowned investor and founder of Gotham Asset Management, the strategy is outlined in his book “The Little Book That Still Beats the Market.” Magic Formula Investing leverages financial metrics to rank stocks and build a diversified portfolio, aiming for high returns with minimal effort.
Principles of Magic Formula Investing
The core principle of Magic Formula Investing relies on two main financial metrics: Earnings Yield and Return on Capital (ROC). Let’s break down each component:
Earnings Yield
Earnings Yield measures the relationship between a company’s earnings and its market valuation, expressed as the inverse of the Price-to-Earnings (P/E) ratio. It offers a gauge of how much profit a company generates per dollar invested. The formula for Earnings Yield is:
[ \text{Earnings Yield} = \frac{EBIT}{Enterprise Value} ]
Where:
- EBIT stands for Earnings Before Interest and Taxes, reflecting earnings before the influence of interest expenses and taxes.
- Enterprise Value (EV) represents the market value of the entire business, calculated as market capitalization plus debt minus cash.
Return on Capital (ROC)
Return on Capital measures the efficiency with which a company generates profits from its capital, reflecting how well the company utilizes its operations to create value for shareholders. The formula for ROC is:
[ \text{ROC} = \frac{EBIT}{Net Working Capital + Net Fixed Assets} ]
Where:
- Net Working Capital includes a company’s short-term assets minus short-term liabilities.
- Net Fixed Assets represent the long-term assets required for operations, like property, plant, and equipment.
Greenblatt’s Magic Formula ranks companies based on these two metrics, prioritizing those with high Earnings Yield and high Return on Capital.
Steps to Implement Magic Formula Investing
Implementing Magic Formula Investing involves a systematic approach:
1. Establishing the Universe of Stocks
First, determine the universe of stocks to consider. A typical screening might include:
- Companies with a market capitalization above a certain threshold (e.g., over $100 million).
- Publicly traded companies listed on major exchanges.
- Exclusion of financials and utilities, as their financial structures could complicate the calculation.
2. Calculate Earnings Yield and Return on Capital
For each stock in the universe, calculate both the Earnings Yield and Return on Capital:
- Calculate EBIT from the company’s income statement.
- Determine Enterprise Value using the latest market data.
- Compute Net Working Capital and Net Fixed Assets from the balance sheet.
3. Rank Stocks
Rank all companies based on their Earnings Yield and Return on Capital separately and then combine the rankings to form a composite score. The companies with the best composite scores become the most attractive investments.
4. Create the Portfolio
Form a diversified portfolio by selecting the top-ranked stocks (typically 20-30).
5. Hold and Rebalance
Hold the selected stocks for a year, then review and rebalance the portfolio annually based on updated rankings.
Example of Magic Formula Investing in Action
Let’s consider an example to visualize the theoretical application of Magic Formula Investing. Assume a simplified market with five stocks:
| Stock | EBIT | Enterprise Value (EV) | Return on Capital | Composite Rank |
|---|---|---|---|---|
| A | 200 | 2000 | 0.1 | 2 |
| B | 300 | 6000 | 0.05 | 5 |
| C | 150 | 1000 | 0.15 | 1 |
| D | 220 | 2500 | 0.088 | 3 |
| E | 180 | 2200 | 0.082 | 4 |
Ranked by combined Earnings Yield and ROC, stocks C, A, and D make it to the top. These would be the stocks to be included in the portfolio.
Historical Performance of Magic Formula Investing
According to studies and Greenblatt’s own observations, Magic Formula Investing has exhibited strong historical performance, often beating market benchmarks over long periods. However, like any strategy, it may underperform in certain market conditions. Historical backtesting of the strategy, spanning several decades, has revealed average annual returns often surpassing 10-15%, far outpacing typical indices.
Criticisms and Challenges
Magic Formula Investing, while simple and historically effective, is not without criticisms and challenges:
Market Efficiency
Critics argue that markets are generally efficient, meaning consistent outperformance might not be sustainable over time. As more investors adopt similar strategies, the potential for excess returns could diminish.
Behavioral Biases
Investors might struggle with the discipline required for a systematic strategy, abandoning it during periods of underperformance. Sticking to the formula during downturns can be psychologically challenging.
Data Accuracy
The accuracy of financial data (EBIT, Enterprise Value, etc.) is crucial. Discrepancies or outdated information can skew rankings and compromise the strategy’s effectiveness.
Impact Costs
Implementing the strategy across a diversified set of stocks may incur significant trading costs, especially in less liquid markets. These costs can eat into the excess returns.
Automating Magic Formula Investing
With technological advancements, automating Magic Formula Investing has become feasible. Algorithmic trading systems can streamline the formula’s implementation, minimizing manual labor and potential errors. Here’s how:
1. Data Integration
Integrate real-time financial data from reliable sources (e.g., Bloomberg, Yahoo Finance).
2. Calculation Algorithms
Develop algorithms to calculate Earnings Yield and ROC automatically.
3. Stock Ranking
Automate the ranking process, updating scores based on the latest financial data.
4. Portfolio Management
Implement rules for portfolio selection, rebalancing, and risk management. Consider trading platforms like Interactive Brokers to automate buying and selling.
Case Study: Quantopian
Quantopian, before its closure, was a platform allowing individuals to automate and backtest trading strategies, including Magic Formula Investing. Tools like these, despite their end, underscore the feasibility of automated investing strategies.
Conclusion
Magic Formula Investing, with its foundation on robust financial metrics, offers a systematic approach to stock selection, aiming to provide high returns with reduced complexity. Despite its simplicity, the strategy requires discipline and careful consideration of market conditions, trading costs, and data accuracy. Automatization provides a promising avenue, leveraging modern technology to streamline execution and maintain rigor in following the strategy.
For those interested in dual assurances of mathematical soundness and systematic execution, Magic Formula Investing serves as an attractive, historically proven methodology worth considering in a diverse investment framework.