Error tolerance = Lifeline, making investments safer

This article is a compilation from "Thought Steel Seal".

Many investors enter the Hong Kong and US stock markets, starting with buying financial products and funds. Some investors also transition from the A-share market to the Hong Kong and US stock markets.

The Hong Kong and US stock markets are much more "exciting" than financial products, funds, and A-shares because of T+0 trading, no price limits, and a large number of high-leverage trading products. To survive in the long term, it is necessary to increase the margin of error.

1. What is the margin of error?

"The margin of error" is a term commonly used in games, referring to the difficulty of being eliminated after making a mistake. A real-life example is QR codes. We often only scan half of the code, and the system can still recognize it because QR codes have a certain margin of error. As long as a few key parts are not obstructed, they can still be scanned.

We always think about how to avoid making mistakes, but there is a school of thought that believes if making mistakes is unavoidable, it is better to think about how to minimize the consequences of those mistakes.

2. Method 1 to increase the margin of error: Safety Margin

The most common method to increase the margin of error is the safety margin, which can be colloquially described as "buying cheap." However, "buying cheap" does not necessarily increase the margin of error.

There are two types of "buying cheap":

One type is when investors believe that the upside potential is greater than the downside potential, which is a form of "odds thinking." Usually, these are companies that have experienced a long-term decline and are betting on a turnaround. However, the success rate is not high.

This type of "buying cheap" does not have a safety margin and does not increase the margin of error. The fundamentals are difficult to determine, and many well-known blue-chip companies have too many players involved, making it difficult for the stock price to reach a bottom. It can drop further at any time.

The other investment philosophy focuses more on minimizing the downside risk (rather than maximizing the upside potential) and reducing the probability of losses. This is a form of "win-rate thinking."

The common characteristic of these companies is that they are in low-growth traditional industries in decline. They are either in general manufacturing industries or seemingly low-tech raw material enterprises. Some are in obscure industries that are difficult to understand, mainly in industries such as machinery and equipment, traditional materials, and basic chemicals.

These industries share the common characteristic of obvious demand decline, which makes investors avoid them, resulting in very low absolute valuation levels. However, the demand does not disappear and stabilizes after reaching a certain degree of decline.

They are not like Ping An, Vanke, or Hengrui, which are well-known blue-chip companies with significant declines. Instead, they are "forgotten corners" that have been at the bottom for a long time and go with the flow. Many stocks you have never heard of have a long-term return on equity (ROE) ranging from 5% to 10%.

However, if you carefully analyze the fundamentals and financial data, these companies are not bad. Some have low gross profit margins but high net profit margins with minimal expenses. Some have average profits but almost no interest-bearing debt. Some operate in industries with limited growth potential but very stable demand. They are like colleagues around us who can never achieve great things but also never make mistakes.

The reason their finances are healthy is that these companies have another common characteristic: a good competitive landscape and slow technological progress. After all, no company would invest heavily in a declining track, and existing players in the tail end cannot withstand this "low-profit, no growth" business. The result is "stable profits without growth" or even better than those "high-tech" industries that require significant investment in research and development. There is almost no risk of being eliminated in technological iterations. The common "drawback" of these companies is their low growth rate, which has become their "original sin" in the A-share market. As a result, most investors don't pay much attention to them. They have low valuations and lack popularity, which means there is little speculative capital. As a result, any slight change in industry fundamentals can trigger a rally with decent gains. Many of the top 5% performers in terms of growth two years ago were companies of this kind.

Both types of companies are "cheap to buy," but the outcomes are different. For the first type, buying at a low price is more likely to result in continued decline if you make a wrong investment decision. On the other hand, for the second type, buying at a low price is more likely to result in no increase in value. Therefore, the latter is a more forgiving investment approach.

The investment opportunity presented by the first type is more like value arbitrage, while the investment philosophy of the second type is closer to deep value investing. Many fund managers with this style hold mostly obscure companies that seem to have little upward movement. However, in reality, there are one or two companies that suddenly explode every quarter, contributing all the profits to the portfolio and then disappearing in the next quarter's portfolio.

These types of funds have become the stars that have significantly outperformed the market in the past six months.

So, "buying cheap" is just superficial. Most of these companies are cheap most of the time. When you start paying attention to them, they become the most expensive.

Margin of safety is a measure of the tolerance for error in stock selection. In addition, there is also a margin of error in trading, such as stop-loss.

Method 2 to increase the margin of error: Counter-logic

The most common method for retail investors to increase their margin of error is through "stop-loss." This involves selling unconditionally after a fixed percentage of loss to control losses.

However, the problem is that fixed percentage stop-loss can only limit the magnitude of losses after each mistake, but it increases the proportion of losing trades. Therefore, stop-loss can only improve short-term margin of error, but it is ineffective in the long run.

More importantly, as value investors, a decline in stock price means an improvement in the price-to-value ratio, and we should buy instead of sell. Stop-loss is contrary to the philosophy of value investing. Most fluctuations in stock prices within a few days are random or influenced by buying and selling activities, and do not reveal fundamental information.

Of course, everyone can make mistakes in judgment, and even if the judgment is correct, execution errors or changes in the environment can occur, and corrections must be made when there are mistakes.

So, stop-loss itself is not wrong. What is wrong is "stop-loss based on the decline in stock price." The true condition for "stop-loss" is when there may be a change in the fundamentals.

In my article "If You Don't Know What Is Wrong, Persistence Is Meaningless," I believe that in any investment logic, there must be a corresponding "counter-logic":

• The counter-logic of developing new products is the failure of research and development.
• The counter-logic of a major new product launch is poor sales or good sales that affect the sales of existing products.
• The counter-logic of expanding production capacity is the failure to meet quality standards.
• The counter-logic of partnering with a major customer is the loss of autonomy in operations, a significant increase in accounts receivable, and even significant fluctuations in performance.

Successful investors can hold two completely opposite logics in their minds to be able to suspend or change their investment strategies at any time.

This is the difference between research and actual investment. In research, as long as you think a logic makes sense and has profit potential, it's fine. But before investing real money, you must find the "counter-logic" to this logic and have corresponding signals. This is the first method to increase the margin of error: investing in both logic and counter-logic simultaneously. So, fundamental stop-loss is a pre-set stop-loss, once a certain "counter-logic" condition occurs, investment must be terminated, instead of starting with a beautiful vision and then exaggerating the problem when encountering setbacks.

However, many investors may feel that the reasons for failure are easy to think of, but it is difficult to find signals in actual investment.

In addition to the common methods such as ability circle, in-depth research, and continuous tracking, there is another method to increase the "tolerance rate": reducing uncontrollable "key variables" in investment.

Fourth, Method Three to Increase Tolerance Rate: Reduce Uncontrollable Variables

There is an investment saying: Don't look for alpha in a downward beta.

Alpha and beta are a pair of relative concepts, and their meanings are not unique. The most common meaning is "individual stocks and industries". If a stock rises by 10% and the sector rises by 7%, then the alpha of the stock is 3% and the beta of the industry is 7%. This means that 7% of the return is the return brought by choosing the right sector, and 3% is the return brought by choosing the right stock.

"Looking for alpha in a downward beta" is like rowing against the current. If you can make a profit of 10%, but the sector falls by 10%, you will end up with nothing.

However, I personally do not agree with this statement because industry beta and stock alpha are two completely different research abilities:

Whether it is beta or alpha, they both require research on the fundamentals and business conditions of the industry, but their differences are more significant, and the requirements for abilities are different:

Beta is a top-down investment method, and the research method is more focused on logical deduction. It needs to consider macro environment, market style, and fund preferences. It is a more strategic research. For example, the photovoltaic industry had a high business condition in the first half of the year and the valuation was not expensive, but it severely underperformed the index in the first four months, which was entirely due to macro and style reasons.

On the other hand, alpha is a bottom-up investment method, and the research method is more focused on empirical research. It requires a deep understanding of the product and the company's management level, which requires a large amount of on-site research, visits to suppliers and distributors, and consultation with industry experts. Some industries also require mastery of high-frequency data.

Human abilities are biased. When analyzing the attribution of account returns, if alpha is lower than the overall account returns, it means that you are better at top-down logical deduction. If alpha exceeds the overall account returns, it means that you are better at bottom-up empirical thinking.

The method of "not looking for alpha in a downward beta" requires the ability to judge and track both beta and alpha returns, which increases the unknown factors in the analysis and is more prone to errors.

A good investment system either focuses on alpha or focuses on beta.

Buffett's investment is basically based on long-term alpha of individual stocks, and he rarely considers industry beta or macro factors.

The "buy cheap" method mentioned in the first method often concentrates the holdings of fund managers in traditional industries with little beta because only in these industries will there be opportunities for cheapness. It is also a system that gives up beta. On the contrary, there are also many investment masters who excel in asset allocation and completely abandon individual stock alpha, pursuing industry or asset class beta. David Swensen, a master of asset allocation, believes that in the three major sources of investment returns, "asset allocation, market timing, and stock selection," in the long run, 90% of the returns belong to asset allocation, while market timing and stock selection only contribute 10% of the returns.

I have a friend who made a profit during the plunge of Chinese concept stocks. His method is to hedge the beta of Chinese concept stocks. One method is to invest in Chinese concept stocks while allocating a corresponding position in "3x short Chinese concept stock ETF." Another method is to buy one Chinese concept stock while shorting another Chinese concept stock that he is not optimistic about, such as "being bullish on JD.com while shorting Wuxin Technology."

These two methods, the former is purely risk hedging, and the latter can simultaneously earn alpha returns from two stocks, both of which abandon beta and focus on alpha.

For him (actually for most investors), he invests in the fundamentals of a specific Chinese concept stock company, while the beta of Chinese concept stocks is completely political risk and uncontrollable. Only after excluding it, he dares to go all-in or even leverage.

Similarly, if you strongly believe in the overall Chinese concept stock market, the best method is to buy Chinese concept stock ETF to eliminate the risk of individual stock alpha.

More importantly, such judgments are very important for investment. Once you have hedged a risk that you cannot control, your main strategy will not be in a dilemma or be hesitant, and your other judgments will be more pure and dare to take positions.

Just like having a safety rope for high-altitude operations, the role of many allocation positions is not necessarily to make money itself, but to make other positions profitable.

For example, since the beginning of this year, I have been allocating positions in infrastructure and real estate, not because I am bullish on the beta of these two industries, but from the perspective of macro risk hedging. If the economy declines and growth stocks are hit, the country will increase infrastructure investment and relax real estate policies, providing opportunities for these two sectors. They can hedge some of the risks of growth stocks, and vice versa.

Fifth, be a "high tolerance" investor

Charlie Munger said, "If you take away our top 10 investments, we're just a joke."

The same applies in reverse. A retail investor who has suffered heavy losses, if you remove the 10 largest losing investments of these years (in fact, removing 5 is enough), he may become a top expert.

A true expert is not someone who never makes mistakes, but someone who avoids fatal mistakes. An investor with a high tolerance for mistakes often has the following characteristics:

• Good at calculating gains and losses, tolerating small mistakes in exchange for great achievements.
• Accustomed to a changing environment and adept at dealing with various complex situations.
• Believes in the 80/20 rule, focusing more on their strengths rather than overcoming weaknesses.

If there are dangers that cannot be completely avoided, it is better to focus on what you can control. A person who cannot tolerate any mistakes will waste their life correcting mistakes instead of expanding their victories.