Pros and Cons of Quantitative Investing

quantitative investmentThe most significant feature is that its intelligent trading is no longer subject to human subjective influence, but relies more on systematic and scientific quantitative models to give full play to its own advantages. Overcoming the Weaknesses of Human Nature If you think that the most difficult thing is macro and micro analysis, then you may not understand what investment is. 300 years ago, Newton, the physicist we are most familiar with, did a real "I can calculate the movement of celestial bodies, but I cannot calculate the madness of human beings" in the South Sea of ​​England. The biggest shortcoming in human nature is greed. The reason why many investors lose money is because they do not know the weakness of human nature.

This is a model-based and data-supportedProgrammatic trading, it can greatly overcome many human shortcomings and subjective cognitive deviations, and get rid of human emotional factors, thus effectively ensuring the execution of established strategies. Strong risk prevention capabilities and good investment performance. Quantitative investment is to obtain absolute profits. It can use various investment methods and methods to reduce the relationship with the market, and can use various hedging methods to avoid part of the risk, allowing it to obtain profits in a bear market. Quantitative investment mainly relies on probability, by constantly discovering useful factors from historical data, and then using them, and they are usually not compressed into a single product, but a combination of multiple products, which can effectively reduce risks.

If you are an experienced fund manager, you may have some advantages, but if you have thousands of stocks, then quantitative investment with powerful information processing and computing capabilities will have a great advantage. Everything has its two sides. The advantages of quantitative investment are obvious, but it also has its own shortcomings. Quantitative investment is based on historical data. If there is no good historical data, the time is short and the quality is low, it will cause sampling errors. Once the rules obtained are analyzed based on such low-quality data, their effectiveness will be greatly reduced and they will not have much reference value. Passivation and failure of indicators. Most domestic quantitative investment institutions are still in their infancy. Except for a few top institutions, they have insufficient capital investment and insufficient data.

Due to reasons such as process leak detection and system imperfections, strategies are highly relevant, thus exposing relatively single risks. However, as the degree of convergence of market strategies increases, it will lead to the failure and passivation of indicators. For example, for a strategy, if there are not many people in the market, the profit will reach 40% in the first year. Especially for those arbitrage strategies, if you have more customers, then your profit will drop to 20%. By the third year, your profit will drop to 10%. By the fourth year, you will have nothing. Indicators are difficult to quantify. As the name suggests, they must be quantified first. However, in actual application, many excellent indicators cannot be measured by specific quantitative indicators. Quantitative strategies will lose many factors that are beneficial to profitability. However, with the advancement of technology, many indicators are gradually being implemented.