Applying the Free Energy Principle to Investing
Applying the Free Energy Principle (FEP) to investing can provide insights into how investors manage uncertainty and make decisions to optimize outcomes in uncertain environments, such as the stock market or cryptocurrency. Let’s break down the core ideas of the FEP and apply them to investing with real-world examples.
1. Prediction and Uncertainty in Investing
In investing, making decisions involves predicting future market movements, asset prices, or company performance. Investors, like the brain, are constantly trying to reduce uncertainty by refining their predictions using new information (news, earnings reports, economic data).
Real-World Example:
An investor in the stock market might predict that the price of Apple Inc. (AAPL) will increase based on historical performance, product launches, or earnings reports. However, new information, like a tech market downturn or geopolitical instability, could affect that prediction. The investor needs to update their beliefs (model) to account for the new information, thereby reducing their uncertainty (prediction error).
2. Minimizing Free Energy: Reducing Prediction Error
In investing, minimizing free energy is akin to minimizing the difference between expected returns and actual returns (prediction error). Investors aim to develop strategies that reduce the gap between what they predict (future price of an asset) and what actually happens (real market prices).
- In the Free Energy Principle, the brain minimizes the gap between expectations and reality.
- In investing, this could be done through risk management strategies, diversification, or hedging to protect against unexpected market movements.
Real-World Example:
Consider an investor who follows a dollar-cost averaging (DCA) strategy. By investing a fixed amount of money at regular intervals (regardless of price), they reduce the risk of trying to predict the best time to buy. Over time, this strategy minimizes prediction error by smoothing out volatility, as the investor buys both when prices are high and when prices are low, reducing the overall surprise (uncertainty) in portfolio returns.
3. Action and Perception: Adapting Investment Strategies
Just like the brain adjusts its predictions and behaviors to minimize free energy, investors adjust their portfolios in response to changing market conditions. If new data (e.g., economic reports or company earnings) contradicts an investor’s initial thesis, they might take action by rebalancing their portfolio, selling assets, or diversifying into safer investments.
- Perception: An investor’s view of the market changes with new information.
- Action: The investor rebalances their portfolio to align with this updated perception.
Real-World Example:
An investor may have a portfolio heavy in technology stocks. If they start seeing signs of a tech bubble bursting (e.g., high valuations, rising interest rates affecting growth stocks), they may perceive this as a risk to their portfolio. To minimize their prediction error, they might shift some assets into value stocks, bonds, or commodities, acting to minimize risk and stabilize returns.
4. Homeostasis and Survival: Risk Management
In biological systems, homeostasis refers to maintaining a stable internal state. In investing, homeostasis can be understood as the preservation of capital and long-term portfolio growth. To survive in the unpredictable world of investing, investors must avoid major losses and ensure their portfolios remain balanced.
The Free Energy Principle suggests that systems take actions to reduce “surprises.” In investing, risk management is critical for reducing surprises that could destabilize a portfolio (e.g., large market downturns, inflation, recessions).
Real-World Example:
Investors often use stop-loss orders to sell an asset automatically when it drops to a certain price, preventing major losses. Another strategy could involve investing in dividend-paying stocks or bonds to provide a steady income stream and reduce the impact of volatile market movements. This approach helps maintain a portfolio’s “homeostasis” and keeps it within desired bounds of performance.
5. Gradient Descent in Investing: Learning and Portfolio Optimization
In the Free Energy Principle, the brain minimizes free energy through a process called gradient descent, where it continuously updates its beliefs and predictions. In investing, this is analogous to portfolio optimization, where investors adjust their portfolios over time, learning from past mistakes and market performance.
Real-World Example:
An investor may start with a portfolio heavily weighted in growth stocks, expecting high returns. Over time, if they notice that their portfolio is underperforming during economic downturns, they might learn to optimize their asset allocation by adding more defensive assets like bonds, commodities, or dividend-paying stocks, thereby reducing risk. This is akin to gradient descent, where each adjustment brings the portfolio closer to optimal performance.
6. Surprisal in Investing: Market Shocks and Corrections
In FEP, surprisal refers to unexpected outcomes that are highly improbable. In investing, surprisal could represent unexpected market shocks, such as economic recessions, geopolitical events, or corporate scandals that dramatically affect asset prices.
Investors aim to reduce these surprises through careful analysis and diversification, but since some events are inherently unpredictable (black swan events), they must build resilient portfolios that can withstand these shocks.
Real-World Example:
The COVID-19 pandemic in early 2020 led to a massive market selloff, surprising even seasoned investors. Those who had diversified portfolios, including cash reserves, gold, and other defensive assets, were better positioned to weather the shock. By reducing exposure to high-volatility stocks and increasing exposure to more stable investments, these investors reduced the “surprisal” effect on their portfolios.
7. Variational Free Energy: Active Investing vs. Passive Investing
The concept of variational free energy in FEP can be applied to active versus passive investing. Passive investors, who follow strategies like index investing, might be seen as minimizing free energy by aligning their portfolio with the market as a whole, reducing the effort required to constantly update predictions. Active investors, on the other hand, take a more hands-on approach, continuously updating their models and trying to outperform the market.
Real-World Example:
A passive investor might invest in an S&P 500 index fund, accepting market performance as their benchmark, thereby minimizing the need to constantly adjust their portfolio and reducing free energy in a simple way. An active investor might instead pick individual stocks, requiring more updates and adjustments (and potentially higher returns), but with more risk.
Conclusion
The Free Energy Principle offers a compelling way to think about how investors operate in uncertain financial markets. Just as the brain constantly updates its model of the world to minimize surprises and maintain stability, investors adjust their portfolios to reduce risk, manage uncertainty, and optimize returns. By understanding how concepts like prediction error, surprisal, and gradient descent apply to investing, we can better navigate complex financial environments and make more informed decisions.
In practical terms, strategies like diversification, risk management, and constant learning (portfolio optimization) can help minimize uncertainty, reduce surprises, and improve long-term investment success.