Hello book friends, welcome to continue to be a guest in the little book boy's reading circle, today we continue to talk about the book noise, yesterday we said, the machine self-learning Xi, can be higher than human **, higher accuracy, the main thing is that he can find a lot of broken legs, such as everyone is analyzing the possibility of people going to the movies tonight, if you know, some people, just broke their legs, then how would you speculate?The reason is very simple, your previous ** has been completely overthrown, no matter how much this person loves watching movies, how attractive the movie is to him, as long as he knows that he broke his leg, it is impossible for him to go to the movie, the so-called broken leg situation is the situation of overthrowing the original ** model. In this regard, machines do a better job than humans, first, because they can obtain a larger amount of data to analyze the correlations between them, and secondly, they are more decisive in their judgments. It won't be like people, mother-in-law hesitates. For example, we set the machine, the highest point back 5-10%, that is, the trend is bad, should take profit and leave, the machine through self-study Xi, will find that it is possible that 8% of this data will be better, the probability of winning is greater, the investor loses the lowest, so he will decisively cut positions at the 8% take profit level. And people's judgment is likely to be unable to do it, and I always feel that this time will be different, whether I want to look at two more points. So artificial intelligence, is not magic, the machine is not more advanced than us, he is a set of recognition patterns, the so-called Xi ability, in fact, is to find correlation, and calculate high probability. It may take him some time to understand the model, but once he has determined it, it will be executed inhumanely. The computing power of human beings itself is very limited, and it is impossible to execute it inhumanely, so there is a large deviation between the two in terms of results.
Low-end artificial intelligence is to build a model and let the machine run on its own, which is not really intelligent. True artificial intelligence is to continuously collect data while the machine is running, and then establish market correlation, and finally calculate the maximum win rate, and follow the strategy of the maximum win rate to trade. Moreover, such a machine has the ability to learn on its own, and at the moment it is widely used in various fields. For example, artificial intelligence is used in human resource management to write recruitment software, and by having a machine algorithm pick out resumes, the chances of being accepted are increased by 14%. It's like we use fundamental quantification in investing, where the machine can quickly identify useful factors in the market, then search for more than 4,000** and find each factor. Then, the machine will sort according to the win rate to determine the ** size. Everything can be left to the program. In the future, hospitals may also introduce a large number of artificial intelligence, and machines can Xi themselves based on laboratory results, distinguish diseases, and even exceed doctors with accuracy. This will reduce the occurrence of misdiagnoses and greatly improve the efficiency of the hospital. It is possible that in the future, the medical institution will only be responsible for the examination, and the outpatient clinic will basically not be necessary.
One might think that algorithms can't make mistakesThis is certainly not possible. Algorithms can also make mistakes, and even some accidental human actions can mislead algorithms. But in general, the lesser of two evils. If an algorithm has a significantly lower error rate than humans, then it is a significant step forward. The greatest weakness of human beings is the tendency to trust their instincts, and many people are convinced of it and even satisfied. For example, when the market is **, people tend to want to run away right away, which is a gut reaction. Because we've been doing this for thousands of years of evolution, and when we encounter a crisis, we instinctively want to run away. In addition, we often have certain cognitive biases, and excessive arrogance often leads us down the wrong path. People always look forward to the ability of the future, however, in reality, this is just an unrealizable illusion. Because any ** means inevitable objective ignorance, especially in the unknown. While some people are pretentious and think they can go in the future, what they do is often very different from what is actually happening. As the book says, "long-term, meaningless". This phenomenon is prevalent in all fields.
For example, weather forecasters can't be accurate about future weather conditions. Even if they have years of experience, the accuracy rate is not higher than that of the average person. In addition, they can't ** how the weather is affected by various factors. Just like ***, the lack of accurate data and reliable models can make even experienced analysts miss out on opportunities. Property experts also can't be sure of the development prospects of a certain place, let alone they can't ** market volatility. is an extremely difficult task as there are multiple factors that need to be taken into account in any decision.
For sports experts, there is also a certain amount of uncertainty about their **. The analysis of football commentators is simply based on some data and logical reasoning. It's hard for them to pinpoint which team will win. Therefore, we cannot rely too much on the experts' **, otherwise we may face serious losses.
While the decision-making power of the model may be slightly better, we seem to be less receptive to this way of decision-making. We often tend to trust our own judgment, and this confidence often only has negative consequences. Many times, our decisions are based on subjective perceptions and emotions, rather than on objective data and analysis.
However, people often fall into the trap of hindsight. They always think that their decisions are the right one because they have seen the results. However, many times, they do not really understand the situation at the time and do not even recognize the existence of uncertainty. It is only in hindsight, when we recall the decisions of the time, that we realize that they were not so accurate.
Therefore, we need to be more cautious. Instead of simply relying on the judgment of experts, we should pay more attention to objective facts and figures. Only then will we be able to make more informed decisions and avoid unnecessary losses. There is a direct relationship between cooking at home and no longer being hungry. Usually, when you feel hungry, you make an immediate decision to eat. Therefore, the close connection between these two factors does not necessarily mean that there is a necessary causal relationship between them. On the other hand, sometimes you cook food at home and you don't eat it, and you still feel hungry, because there is a correlation between them, but that doesn't mean it's causation. If we think of these associations as causality, then we can easily fall into some false assumptions.
For example, when we see a central bank raise interest rates, we usually infer that it will. Although there is a correlation between these two factors, we cannot take it as a corollary. In fact, there are also cases where central banks may raise interest rates. There are also examples from everyday life where the relationship between reading more books and success is not a causal relationship, but a correlation link. People who read more are more likely to succeed, but it cannot be asserted that this is because of the reading. Some people may be biased, such as seeing a tall man and thinking that he must be a basketball player, but in fact the proportion of basketball players is much smaller than that of the average office worker.
In addition, our perception sometimes shows some obvious biases, such as seeing an old man with gray hair and thinking that he is a doctor, but this is actually wrong. Similarly, many people have misconceptions about the safety of flying, so they have a Xi of sending a message after disembarking, even if they don't usually do it. However, in reality, airplanes are one of the safest modes of transportation, much safer than self-driving.
Finally, some ** will take advantage of our common cognitive bias, such as pretending to be a middle-aged person on TV, wearing traditional Chinese clothes, claiming to be an old Chinese medicine doctor, and providing false medical care. These** take advantage of our biases and make us more susceptible to scams. Therefore, when dealing with related issues, we must keep a clear head and clearly recognize which factors are related to each other and which are not causal. MLM organizations are able to deceive people because they are good at taking advantage of people's aspirations for a future life. Some people will convey to the elderly that chronic diseases are an inevitable consequence of human aging, and that the medical profession is helpless about it. However, these ** did not stop for this, but claimed that there is a mysterious medicine that can rejuvenate people, ** these diseases. Although the elderly are not stupid, they have a deep desire for a miracle medicine that can solve their suffering. Therefore, they involuntarily fall into this trap.
Whether you have a high level of knowledge or not, you can still easily fall part of this trap. For example, the author himself, who once spent a lot of intellectual resources to find effective ** ways because of long-term gastrointestinal discomfort, although he knew that these drugs were useless, he was eager to try them. This is the effect of cognitive biases, where you are always inclined to accept arguments that support your beliefs, even if they are false.
In addition, there are two types of psychological biases: anchor bias and excessive consistency bias. Anchoring bias is all about influencing your judgment through a value anchor, just as when you get off a Rolls-Royce, others will think you are very rich. This value anchor can be your first car, a mansion you've lived in, or designer clothing you're wearing. Over-agreement bias is when you draw a straight conclusion based on past experience and then stick to that point of view to the end. For example, the impression you make when you first meet can have a huge impact on your judgment later on, and this impression is often fixed and difficult to change.
When a group of people with the same psychological bias get together, the discussion often goes wrong. A good example of this is when market risk increases, and everyone panics, and their judgment has been severely impaired. No matter how hard you try to stay calm, the end result may be on the pessimistic side. On the contrary, when the market improves, everyone's optimism tends to make the results deviate from reality.
Therefore, we must understand that the existence of these psychological biases is inevitable, but as long as we recognize their existence, we can better avoid being taken advantage of. How can non-Taiwan shine on people?"Only when we look at the world with a clear heart can we better face the challenges of life. Our view is always consistent that in ***, understanding market sentiment is crucial. When the market is hot, performance** should be viewed according to the idea of seven folds, and when the market is down, the credibility of the earnings report will be higher. After all, researchers are naturally cautious and reluctant to make a big deal out of it, which also reassures us. Tomorrow, let's work together on how to build a scientific system that addresses this potential bias.