One of the lessons that linear thinking teaches us is to recognize the complexity of the world of investing, that all investment logic and outcomes are not necessarily connected, that it is a probabilistic decision, and that even the probabilities in probabilistic decisions cannot be precisely measured.
Linear thinking is probably one of the most common mistakes that ordinary investors make. The so-called linear thinking is the establishment of a linear logical relationship between cause A and outcome B, which is expressed in investment decisions by establishing a causal relationship between the investment outcome (due to a variable) and an influencing factor (self-variable). For example, many investors believe in this logic and make investment decisions based on the fact that the real estate price surge is attributed to a currency surplus, or that the renminbi depreciation is attributed to the dollar entering the interest rate channel, or that the capital market slump is attributed to economic adjustment, etc.
Of course, it is also difficult to make good investment decisions based on linear thinking, which I think is closely related to the complexity of the investment industry, and the reasoning based on linear thinking is easy to violate the investment facts, such as:
A typical phenomenon is that all the news in the bull market is understood as good news, and many companies before the stock market crash, and after the stock market crash after the stock market crash, the general investor is eager to pursue such news and buy stocks. The underlying logic is a linear relationship between the stock market crash and the stock market crash. However, experienced investors will find that even if some companies announce the termination of the restructuring plan, the stock market crash is still a problematic logic.
Another scenario is that the seemingly logically established self-variable may itself be a causative variable, theoretically based on the butterfly effect. For example, many people believe that regulatory tightening and leverage led to last year's stock crash, but would it be the news of the 6.10 Shanghai stock market rally that shattered market confidence? And would it lead to the tightening of the regulatory policy?
Another flaw of the linear logic is that it ignores the inherent interaction of economic activity. For example, in 2016, the market was eager to hype the new energy automobile and solar energy industries. One of its core logics is that as fossil fuel reserves decline and extraction costs increase, their prices will continue to rise, and new energy (hydroelectric and solar) has cost and environmental advantages relative to fossil fuels, leading to large-scale replacement. This is the typical linear logic, if we think further, that as the demand for new energy (hydroelectric and solar) increases, its imbalance in supply will lead to a rapid rise in costs and prices, while the decrease in demand for fossil fuels will lead to their lower prices and increased competitiveness.
Thus, one of the lessons that linear thinking teaches us is to recognize the complexity of the investment world, that there is no inevitable link between all investment logic and outcomes, that it is a probabilistic decision, and that even the probabilities in probabilistic decisions cannot be precisely measured. People often fall for models that assign definite probabilities to uncertain worlds through models, thus creating controllable, explainable illusions ("necessity") for themselves. The results of these models are often consistent with reality, but it is easy to be oblivious to the flaws of the model.
So based on probability thinking, the relationship between investment logic and investment outcomes can be summarized in four ways:
As an investor, 1 is what we do our best to pursue and 4 is what we do our best to avoid, and the common characteristic of both is that they both fall into the category of ability. We try to do as much as 1 and avoid 4.
Due to the lack of cognitive ability and the complexity of the investment industry, 2 and 3 can only be attributed to luck, and there will always be some unpredictable factors or cognitive defects that make the investment outcome unexpected. I often joke that luck is an important factor in investing, not news.
How can we avoid the uncertainty of 2 and 3? This illustrates the value of the concept of the uncertainty loop. To avoid the uncertainty effect, we can try to limit the scope of our investments to the most cognitive areas, to minimize the uncertainty of external factors, or to look for investment opportunities that match external uncertainty trends, so that the probability of a logical and result matching is greatly increased. Of course, this is easy to say, difficult to do, and requires a clear understanding of the investor's own capabilities and good control of the investment impulse.
Translated from private workshop