We have all heard the saying: the growth of corporate net profit will definitely promote the rise of stock price. But how long does it take for a “certain” to appear? No one knows, just say “long-term”, this “long-term” is the same as the divination of gypsies, it cannot be falsified.
At the same time, many people believe that when the PE is very low, if the net profit rises, it will push the PE to rise and achieve Davis’ double-click. If the stock price does not rise or falls, it is due to market irrationality.
Even Peter Lynch said this:
This passage means that net profit and stock price present a stable correlation. It seems that there is a stable anchor point between the two. Buy below this anchor point and sell above the anchor point. What a perfect timing strategy.
This strategy is to use engineering thinking. In engineering, if you want to control the fluctuation of a certain characteristic (Y), you need to identify the key factors that affect Y. Assuming that there is only one factor X, you can establish Y through statistical data regression or laboratory data. =F(X), the controllability of the final characteristics is achieved through the control factor.
For example: rice cooker. The key parameters affecting the quality of rice (soft and waxy, raw and cooked) include water volume, temperature, pressure and time, establish the functional relationship between quality Y and the four factors, and achieve the optimal quality of rice by controlling the factors, and control the cooked rice every time consistency without having to cook the rice to know if it is good or not.
So the question is, is this engineering thinking applicable to stock price forecasting? Is it applicable to predicting the relationship between stock price and net profit?
Let’s first look at the regression relationship between Kweichow Moutai’s year-end stock price and net profit in the last 10 years:
The horizontal axis is the net profit per share, and the vertical axis is the stock price at the end of the year.
The straight line and the arc are fitted according to the linear relationship and the exponential relationship respectively. The closer the R2 value is to 1, the closer the fitted curve is to the input data, and it seems that the exponential relationship fits better.
And it is. In the past 10 years, Moutai’s stock price has risen 10 times, of which net profit has increased by 3.9 times, and PE has increased by 2.5 times. The typical Davis double-click is also what Peter Lynch said. The stock price rises faster than the net profit rises.
Finally, we use real data to verify these two formulas, predict the stock price at the end of 2022, and see if the formula is the holy grail of investment: We know that the net profit per share in 2022 is 50 yuan, and we substitute these two formulas respectively, and the stock price is 2391 respectively. Yuan and 4713 yuan.
However, the actual stock price in 2022 is 1727 yuan. The position of the red dot in the figure is far from the two fitting curves. Then the stock price of 1727 is below the fitting line, is it the price that Peter Lynch said can be bought?
Frankly, I’m not confident.
Look at the fitting curve of another company, Overseas Chinese Town, over the past 10 years:
The conclusion given by this fitting line is that there is no correlation between OCT’s stock price and net profit, and net profit is not a factor affecting OCT’s stock price (the slope is basically 0).
So if you look at this statistical method, even if the past stock price and net profit data fit very well, it is not accurate to predict the future, and even the stock price and net profit of some companies do not show correlation.
Why doesn’t this kind of thinking apply? There are two main reasons:
One is the influence of uncontrollable noise factors.
In engineering, the noise factor is very small, and part of the noise factor is also controllable, and will not cause too much interference to Y. If you don’t believe me, you can imagine the noise factors that affect the cooking of rice cookers.
The stock price is different. The stock price is the reaction of the expectations and emotions of countless participants in the market. The behavior of each participant is like the particles of Brownian motion, which is irregular, uncontrollable, and unpredictable. Each participant is a noise factor, they respond differently to each piece of information, each individual’s behavior is insignificant, but together determine the stock price.
At the same time, the behavior of these individuals is also affected by uncontrollable external information. The nature of the world is chaos. What kind of information will appear in the future? Is the information good or bad? No one can know in advance.
Therefore, the factor of net profit appears insignificant under the influence of noise factors.
The second is the defect of the regression equation.
The formation of the regression equation is based on past data, and the horizontal axis of the data has a range interval, and the prediction is only credible within this range interval (repeated data verification).
Kweichow Moutai’s net profit per share of 5 billion exceeds the range of historical data. Even without the influence of noise factors and other factors, it is illogical to apply the fitting formula (without historical data verification).
Therefore, I tend to think that there is no formula, or a holy grail, that can predict future stock price trends, because no one relies on the formula to get rich. If there is, how much will this formula be worth?
If you base your investment on stock price forecasts, no matter whether the forecast is based on fundamental information such as net profit or the graphics formed by past stock price fluctuations, they are as unreliable as sand. Garbage in, garbage out.
Give up the obsession with stock price forecasts, and before every purchase, ask yourself: If the stock market is closed for 5 years, if this is not a listed company, would I buy it?
If the judgment on the ability and moat of a company to generate real money is correct, even if it is not listed, the owner of the company can still rely on the operation of the company to make a lot of money, which is the logic of tens of thousands of businessmen getting rich in our reality.
What if the stock price of this company continues to fall in the future? That’s just lucky because we’ll earn more, it’s a matter of math.
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