What is the Tolerance Rate?

"Tolerance rate" is a term often used in gaming, referring to the ability to make mistakes without facing immediate failure. A real-world example is QR codes, which can often be scanned even if only partially visible. This is because QR codes are designed with a tolerance rate, allowing them to be read as long as key parts are unobstructed.

In everyday life, we often focus on avoiding mistakes. However, a strategic approach suggests that if mistakes are inevitable, it might be more effective to consider how to minimize their consequences.

Method 1 to Improve Tolerance for Errors: Margin of Safety

A common way to enhance the tolerance rate is through the margin of safety, essentially "buying cheap." However, not all "cheap buys" improve the tolerance rate.

There are two types of "buying cheap":

Odds-Based Thinking: Investors believe the potential upside outweighs the downside. This often involves companies in distress after long declines, hoping for a turnaround. However, the success rate is low. These investments lack a true margin of safety because their fundamentals are unstable. Even well-known companies can drop further due to high competition and volatile prices.

Probability-Based Thinking: This approach focuses on limited downside risk, aiming for a low probability of loss. Companies in this category are often in low-growth, declining traditional industries, such as basic manufacturing or raw materials. These sectors, including machinery and basic chemicals, face declining demand, leading to low valuations. However, demand stabilizes at a certain point.

These companies are not the well-known giants but rather "forgotten corners" of the market, with consistent ROEs of 5-10%. A deeper analysis often reveals healthy fundamentals, such as low debt or stable demand, making them akin to reliable, if unremarkable, colleagues.

Their financial health is due to a favorable competitive landscape and slow technological progress. Few invest heavily in declining sectors, leading to stable profits without excessive competition or the risk of technological obsolescence.

While both strategies involve "buying cheap," the odds-based approach risks further decline, whereas the probability-based approach risks stagnation. The latter offers a higher tolerance rate and aligns with deep value investing. Fund managers using this strategy often hold lesser-known stocks that occasionally deliver significant gains.

These funds have outperformed the market recently, demonstrating that "buying cheap" is just the surface. When these companies gain attention, they may be at their priciest.

Margin of safety represents a stock selection tolerance rate, complemented by trading tolerance strategies like stop losses.

Method 2 for Enhancing Tolerance Rate: Counter-Logic

For individual investors, the most common way to enhance tolerance rate is through the "stop-loss method," which involves selling an asset unconditionally after it incurs a fixed percentage of losses to control downside risk.

However, the issue with fixed-percentage stop-losses is that while they limit the size of losses for each mistake, they also increase the frequency of losing trades. This means that stop-losses can improve short-term tolerance rates but are ineffective in the long run.

More importantly, for value investors, a price drop often means an improvement in valuation and a better buying opportunity—selling at this point goes against the principles of value investing. Most short-term price movements are random fluctuations or influenced by market liquidity, with little correlation to changes in the fundamentals.

That said, everyone is prone to making mistakes—whether it's a misjudgment, an execution error, or a change in external conditions. When mistakes occur, they must be corrected.

Thus, the problem is not with the concept of stop-losses itself, but with "stop-losses based on price drops." The real stop-loss condition should be tied to potential changes in the fundamentals.

Every investment thesis inherently contains a corresponding "counter-logic":

• When developing a new product, the counter-logic is the risk of R&D failure.
• When launching a blockbuster product, the counter-logic is poor sales performance or cannibalization of existing products.
• When expanding production capacity, the counter-logic is the risk of persistent low yield rates.
• When securing a major client, the counter-logic is the loss of operational autonomy, a surge in accounts receivable, or highly volatile earnings.

Successful investors are capable of holding two completely opposing logics in their minds, enabling them to stop or adjust their investment strategies at any time.

This is the key difference between research and actual investing. In research, as long as a thesis makes sense and shows profit potential, it suffices. But before committing real capital, it is essential to identify the "counter-logic" to the thesis and establish corresponding signals. This is the first method for enhancing the tolerance rate: simultaneously considering both the investment thesis and its counter-logic.

Fundamental stop-losses, therefore, are a preemptive measure. If a "counter-logic" signal materializes, the investment must be stopped immediately. This avoids starting with an overly optimistic outlook, only to overreact to minor setbacks later.

Of course, many investors might argue that while it's easy to identify potential failure scenarios, it is much harder to detect clear signals during actual investments.

In addition to relying on common practices like staying within one's circle of competence, conducting in-depth research, and maintaining ongoing monitoring, there is another way to enhance the tolerance rate: reduce the number of uncontrollable "critical variables" in your investments.

Method 3 for Enhancing Tolerance Rate: Reducing Uncontrollable Variables

There’s an investment saying: “Don’t look for upward alpha in downward beta.”

Alpha and beta are relative concepts, with multiple interpretations. The most common definition refers to stocks versus industries. For instance, if a stock rises by 10% while its sector increases by 7%, the stock’s alpha is 3%, and the sector’s beta is 7%. This means that 7% of the return comes from the sector’s overall performance, while 3% is generated by the stock’s unique attributes.

The idea of “looking for alpha in downward beta” is akin to rowing against the tide: even if your stock selection generates a 10% gain, a 10% decline in the sector’s beta could erase all profits, leaving you with nothing.

However, I personally disagree with this saying. The reason lies in the fact that industry beta and stock alpha require entirely different research skills:

• Beta represents a top-down investment approach, focusing on logical reasoning and macro analysis. It involves assessing the broader economic environment, market trends, and capital flows, making it more strategy-oriented.
• Alpha, on the other hand, is a bottom-up approach that relies heavily on empirical research. It requires a deep understanding of products and corporate management, often involving extensive fieldwork, supplier and distributor visits, consultations with industry experts, and sometimes high-frequency data analysis.

Since individual capabilities tend to lean toward one of these approaches, analyzing portfolio returns can reveal which skill set an investor excels at:

• If your alpha contribution is less than your overall portfolio returns, you’re likely better at top-down reasoning and beta analysis.
• If your alpha contribution exceeds your portfolio returns, you’re likely stronger in bottom-up empirical research.

The saying “Don’t look for upward alpha in downward beta” assumes that investors can simultaneously track and manage both alpha and beta returns. However, this dual focus introduces uncontrollable variables, increasing the likelihood of errors.

A robust investment system should focus on either alpha or beta, but not both.

For example, Warren Buffett’s investment philosophy is primarily based on long-term stock-specific alpha, with little regard for industry beta or macroeconomic factors. Similarly, the “buying cheap” strategy mentioned in the first method often involves focusing on traditional industries with minimal beta exposure, as these sectors provide the best opportunities for undervalued investments.

Conversely, many asset allocation experts completely ignore stock-specific alpha and instead pursue industry or broader asset-class beta. David Swensen, the legendary asset allocation master, argued that 90% of long-term investment returns come from asset allocation, while stock selection and market timing contribute only 10%.

Both approaches—whether focusing purely on alpha or exclusively on beta—offer distinct advantages:

• The former is essentially risk hedging, allowing investors to avoid uncontrollable beta risks while doubling down on alpha opportunities.
• The latter seeks to eliminate alpha risks, enabling investors to capture broader beta-driven returns with tools like ETFs.

For most investors, the principle is clear:

• Suppose you’re investing in a specific Chinese stock, but the sector’s beta is heavily influenced by uncontrollable political risks. In that case, you should only go all-in (or use leverage) after eliminating those beta risks.
• Similarly, if you’re bullish on the entire Chinese stock sector, the best approach is to buy a Chinese stock ETF, thereby removing the risks associated with individual stock alpha.

This distinction is critical for investment success. When uncontrollable risks are hedged, your primary strategy becomes more focused and confident, enabling you to allocate capital with greater conviction.

Just like how a safety harness allows workers to operate at heights, certain hedging positions may not directly generate profits but are essential for enabling other positions to succeed.

Becoming a High-Tolerance Investor

Charlie Munger once said, “If you remove our ten most successful investments, we’d be nothing but a joke.”

This statement can also apply to retail investors: if you remove their ten largest losing trades (or even just five), they might suddenly appear to be top-tier investors.

The hallmark of a great investor isn’t the absence of mistakes, but the ability to avoid catastrophic ones. High-tolerance investors often share the following traits:

• Skillful at calculating gains and losses, willing to tolerate small errors in exchange for significant achievements.
• Adaptable to changing environments, capable of navigating complex situations with ease.
• Focused on their strengths, adhering to the 80/20 rule by prioritizing their areas of expertise rather than obsessing over weaknesses.

If certain risks cannot be completely avoided, it’s better to concentrate on what you can control. Investors who strive to eliminate all errors often waste their energy correcting mistakes rather than amplifying their successes.