Key Takeaways
- The notion that any successful investment strategy can be universally replicated overlooks the profound impact of individual behavioural biases, which are often the primary driver of underperformance.
- Structural differences in capital size, time horizon, and personal liabilities create unique constraints that render a one-size-fits-all approach impractical and often suboptimal.
- The true skill of a seasoned investor is not a static set of rules but an adaptive framework that evolves with market regimes; this adaptability is exceptionally difficult to codify and copy.
- Aspiring investors should focus on deconstructing the principles behind a successful process—such as risk management and emotional discipline—and tailoring them to their own context, rather than attempting to mimic specific trades or allocations.
In the modern financial arena, awash with democratised data and low-cost execution, a seductive notion persists: that the path to success is a replicable blueprint. This idea, championed by figures like the investor known as TheLongInvest, suggests that any diligent individual can mirror the actions of a successful practitioner and achieve similar results. While this perspective is rooted in an admirable ideal of empowerment, it collides with the intractable realities of human psychology, structural market asymmetries, and the simple, inconvenient fact that no two investors share the same circumstances.
The Behavioural Gulf Between Knowledge and Action
The most significant chasm between a professional’s strategy and an individual’s attempt to replicate it is not informational, but behavioural. The architecture of a sound investment plan may be simple to understand—diversify, maintain a long-term perspective, rebalance periodically—but it is fiendishly difficult to execute under duress. The field of behavioural finance is littered with the documented costs of these failures.
Studies consistently reveal a “behaviour gap,” representing the delta between the performance of investment funds and the actual returns realised by the investors in those funds. This gap is the tangible cost of ill-timed decisions: selling in a panic during a downturn or piling into an asset at its peak out of a fear of missing out. The data paints a stark picture of this self-inflicted damage.
The Quantified Cost of Investor Behaviour
Analysis by firms like DALBAR in its annual Quantitative Analysis of Investor Behavior report has repeatedly shown that the average equity fund investor significantly underperforms the S&P 500 index over long periods. This is not because their chosen funds were poor, but because their timing of entries and exits was suboptimal.
| Time Period (Ending 31 Dec 2022) | S&P 500 Annualised Return | Average Equity Fund Investor Annualised Return | Behaviour Gap (Annualised Underperformance) |
|---|---|---|---|
| 20 Years | 9.65% | 7.13% | -2.52% |
| 30 Years | 9.65% | 6.81% | -2.84% |
Source: Adapted from DALBAR, Inc. QAIB 2023. Data is illustrative of long-term trends.
This persistent underperformance is a direct consequence of biases such as loss aversion, herding, and the disposition effect (the tendency to sell winners too early and hold losers too long). A strategy that looks elegant on paper disintegrates when confronted with the emotional reality of watching a portfolio decline by 20%. The discipline to “do nothing” is perhaps the most underrated and hardest-to-replicate skill in investing.
Structural Constraints: Why Your Map is Not Theirs
Beyond psychology, structural factors make the mimicry of an investment strategy a flawed exercise. The context in which capital is deployed is as important as the strategy itself.
Capital Size and Time Horizon
An investor managing a substantial portfolio can achieve a level of diversification and absorb transaction costs in a way that someone with a small capital base cannot. A strategy involving dozens of individual equity positions or the use of complex derivatives may be perfectly logical for a multi-million-pound portfolio but is entirely impractical for an individual building wealth with a few hundred pounds per month. Furthermore, the ability to withstand volatility is directly linked to one’s financial runway. A 30-year-old professional can view a market crash as a long-term buying opportunity; for a 60-year-old nearing retirement, the same event could be catastrophic, forcing a liquidation of assets at the worst possible moment to meet living expenses.
The Evolving Strategy Fallacy
A more subtle error is to assume a successful investor’s strategy is static. What is publicly articulated is often a snapshot in time, a reflection of a particular market regime. The truly skilled practitioner is not applying a fixed set of rules but is constantly adapting their framework. A strategy that thrived in the zero-interest-rate environment of the 2010s, for example, required significant recalibration for the inflationary, higher-rate world that followed. Jim Mellon, a British investor, has noted how market landscapes can shift, requiring investors to pivot between sectors like technology and biotechnology based on evolving macro trends. The ability to discern these regime shifts and adjust accordingly is the real “alpha,” and it is a dynamic skill, not a static blueprint.
Conclusion: Deconstructing the Process, Not Copying the Playbook
The assertion that “everything I do can be done by everyone” contains a partial truth: the principles of sound investing, such as discipline and fundamental analysis, are indeed accessible to all. However, the application is deeply personal and context-dependent. The path to competent self-directed investing is not through mimicry but through adaptation. It involves a rigorous self-assessment of one’s own behavioural tendencies, risk tolerance, and financial circumstances.
Instead of copying an investor’s portfolio, one should seek to deconstruct their decision-making process. Why did they buy that asset? What was their risk management thesis? How did they behave during the last market drawdown? Answering these questions provides a transferable methodology, whereas a list of tickers provides only a fleeting and context-free signal.
Perhaps the next phase of market evolution will not reward those who follow gurus, but those who leverage technology for hyper-personalisation. The speculative frontier may involve AI-driven platforms that do more than suggest assets; they could act as behavioural coaches, creating personalised “frictions” to prevent impulsive trades or dynamically adjusting risk exposure based on an individual’s predefined life goals and emotional triggers. Success, in that future, would be a function not of copying another’s genius, but of building a better, more disciplined version of oneself.
References
- @TheLongInvest. (2024, May 29). [Everything I do can be done by everyone I’m showing that it can be done]. Retrieved from https://x.com/TheLongInvest/status/1933031614873022484
- BlackRock. (n.d.). Weekly Commentary. BlackRock Investment Institute. Retrieved from https://www.blackrock.com/us/individual/insights/blackrock-investment-institute/weekly-commentary
- DALBAR, Inc. (2023). Quantitative Analysis of Investor Behavior (QAIB).
- LPL Financial. (n.d.). Research. Retrieved from https://www.lpl.com/research.html
- Mellon, J. (2024). Interview with Jim Mellon: Insights on the 2025 Market Landscape and Investment Strategies. Share-Talk. Retrieved from https://www.share-talk.com/interview-with-jim-mellon-insights-on-the-2025-market-landscape-and-investment-strategies/
