Summary While trading ideas are certainly important—whether in arbitrage, relative value, or directional trading—the true determinant of profit and loss is risk control. Retail accounts are often cluttered with highly correlated assets. For retail investors, many institutional trading strategies are inapplicable due to transaction fees and exchange restrictions. While trading ideas are certainly important—whether in arbitrage, relative value, or directional trading—the true determinant of profit and loss (P&L) is risk control. This is precisely the aspect most retail investors overlook. According to a long-term study by the French Financial Markets Authority (AMF), 89% of retail investors lose money trading Contracts for Difference (CFDs) and Foreign Exchange (Forex). These systemic losses stem not from a disparity in IQ or severe information asymmetry, but from a fundamental misalignment in risk management logic. Contrary to the narratives depicted in films and television, where traders skyrocket to success by placing heavy bets, the institutional logic is not to achieve theoretically infinite returns in one or a few trades, but rather "survival first": only those who survive the arrival of a "black swan" live to "tell the tale", rather than "becoming history". Why Do Retail Investors Always Suffer Losses? Regarding risk control, the core difference between retail and institutional investors lies in the definition of "risk". In the eyes of retail investors, risk is typically defined as "I expected a rise, but the asset fell" or "I expected a fall and sold early, but the price rallied". However, for institutional traders, risk is defined by the "volatility" and "drawdown" of the investment portfolio. Retail investors often fall into a linear P&L fallacy (directional traders are particularly prone to this trap). Prospect Theory in behavioural finance suggests that retail investors tend to be risk-seeking when facing losses—essentially "holding on" in the hope of breaking even. However, this behavioural pattern is mathematically devastating: once a loss exceeds 20%, a return of at least 25% is required to break even; if the loss reaches 90%, the remaining capital requires a 900% return to recover. The non-linear growth required to recoup losses forces retail investors to take on excessive risk, leading ultimately to bankruptcy. Furthermore, there is the issue of correlation. Retail accounts are often cluttered with highly correlated assets (e.g., holding NVDA, AMD, and TSM simultaneously, or a basket of altcoins). This is not "diversification"; large quantities of highly correlated assets often move in lockstep. When the semiconductor sector declines, the entire portfolio faces significant losses. Similarly, the correlation amongst underlying assets in the altcoin market is typically maintained above 0.7, or even higher, meaning any single event can trigger a "systemic sell-off" across the board. Clearly, to ensure portfolio safety, retail investors must address two problems: How to execute stop-losses and achieve "antifragility" How to ensure the robustness of portfolio returns. How Do Institutions Manage Portfolios? In 1986, Gary P. Brinson and his colleagues reached a conclusion in their landmark paper "Determinants of Portfolio Performance" that is still regarded as the gold standard today: more than 90% of the variation in portfolio returns is attributed to asset allocation , rather than individual stock selection or market timing. Although subsequent research suggests that the fund manager's skill has a more substantial impact when illiquid strategies (such as private equity or real estate) are included, asset allocation remains the decisive factor governing portfolio returns. How do institutions utilise this? The answer lies in correlation. Global Macro Funds smooth their equity curves by constructing portfolios with low or even negative correlation. Long/Short Equity Funds utilise correlation to generate alpha beyond price movements. When banks manage their massive investment portfolios, asset correlation is often a primary parameter. Of course, correlation-based portfolio management is not without its challenges. In the current environment where leverage is ubiquitous, "leverage" itself has become a critical factor determining asset correlation. Deleveraging events often lead to a surge in correlation across different markets, while a return of risk appetite can drive a universal rise or fall in assets. Therefore, institutions not only continuously monitor correlations between assets but also focus on the correlation between different asset management strategies. Market-neutral strategies and Delta-neutral strategies typically maintain a low correlation with long-only strategies, serving as effective "stabilisers" within a portfolio. At the trading desk level, fund managers and traders adhere to a series of hard metrics. A widely applied metric is VaR (Value at Risk). It answers the question: "In 99% of cases, what is the maximum amount I could lose tomorrow?" If this figure exceeds the limit, algorithms force a liquidation, regardless of how bullish the trader may be. This prevents traders from "holding on" to losing positions and ensures the portfolio's losses are capped in worst-case scenarios. Additionally, Inverse Volatility Weighting is applied to portfolio management. Instead of an equal-weighted model, institutions allocate capital based on risk. Strict position limits are imposed on high-volatility assets (such as altcoins), whilst relatively looser limits are granted to assets with lower volatility. Do Institutions Speculate? "Rollercoaster" P&L curves are not welcomed by investors. Through the solutions mentioned above, institutions effectively control portfolio volatility and maximum drawdown. However, this does not mean institutions are perpetually "risk-averse". In certain scenarios, institutional risk appetite rises significantly, and they do engage in speculative trading. Generally speaking, however, institutions speculate with a portion of accumulated profits; they do not speculate with the principal capital. Institutional speculation follows the principle of "Asymmetric Payoff". Institutions only engage in speculative trading when the following conditions are met: The odds are sufficiently high: Institutions rarely participate in 1:1 wagers; the typical odds favoured by traders and fund managers are 1:3 or even 1:5. This implies that even with a win rate of only 30%, they remain profitable in the long run. There is a clear event driver: Institutions usually deploy a small amount of capital to speculate around major events. For example, Federal Reserve interest rate decisions, M&A restructuring, FDA drug approvals, and implied events in derivatives data (such as "deleveraging") are prime opportunities for trading. Conversely, when the market is relatively calm, institutions usually "remain on the sidelines"; they do not incur unnecessary costs gambling on short-term technical analysis. There are appropriate tools: Institutions typically use options as insurance, but they also use them for speculation at specific times. The "hard stop-loss" attribute of options is the primary reason institutions favour them over Delta 1 leverage. In extreme cases, it is difficult to execute timely stop-losses with Delta 1 contracts, whereas options have the maximum loss locked into the model from the outset. Although various auxiliary tools based on Delta 1 (such as smart stop-loss and smart execution) are prevalent, they cannot solve liquidity issues, whereas options largely resolve this problem. The Evolution of the Retail Investor: How to Manage Your Money Like a Professional Fund？ For retail investors, many institutional trading strategies are inapplicable due to transaction fees and exchange restrictions. However, risk control strategies are largely universal; one does not need a Bloomberg Terminal to emulate institutional risk management thinking. ETFs significantly lower the barrier to portfolio allocation. ETF issuers have already pre-packaged assets; with just an IBKR or Robinhood account, retail investors can simultaneously purchase ETFs with significantly different risk levels, volatility profiles, and correlations, such as GLD, TLT, IBIT, IWM, SPY, and SVOL. With the proliferation of AI, investors can use AI to assist in formulating a robust ETF portfolio based on their risk appetite. Therefore, when investing, prioritise ETFs over underlying assets; trading a few ETFs is far more convenient than managing dozens of individual assets. Simple institutional risk control schemes can be incorporated into daily routines. For instance, the "2% Rule" (which states that the potential loss of any single trade must not exceed 2% of the total account equity) effectively controls potential portfolio losses. Furthermore, technical analysis indicators based on volatility, such as the Average True Range ((ATR)), can be integrated into the risk control system to set reasonably logical stop-loss boundaries. Do not forget stress testing. Although retail investors cannot easily build a stress testing system akin to a professional risk matrix, simple stress tests should still be considered. For example, calculate daily: "If BTC rises/falls by 10%, how much will my account profit or lose? If I do not adjust my existing altcoin portfolio, what is my maximum drawdown if altcoins are cut in half?" Such calculations and self-inquiry effectively help investors understand their account's risk exposure and prepare for potential fluctuations in their balance. There is an old saying on the streets: "There are old traders, and there are bold traders, but there are no bold, old traders." The essence of institutional risk control is acknowledging the unpredictability of the future. The advantage of institutions lies not in predicting the future but in building a deterministic survival capability within an uncertain market through strict risk control systems and mathematical rules, thereby "surviving when wrong and profiting when right". For retail investors, evolving from a "prayer" to a "risk manager" is a mandatory module in the course of investing. After all, before the miracle of compound interest can occur, you must first ensure you are still at the table. Disclaimer: The information provided herein does not constitute investment advice, financial advice, trading advice, or any other sort of advice, and should not be treated as such. All content set out below is for informational purposes only. Original Post Editor's Note: The summary bullets for this article were chosen by Seeking Alpha editors.
