What are the advantages of quantitative investment strategies

What are the advantages of quantitative investment strategiesMany people who first come into contact with this "term" do not know about quantitative investment, and Micro pointed out that quantitative investment strategy has the following five advantages, mainly including discipline, systematic, timeliness, accuracy, decentralization, etc.

1) Discipline: Strictly implement the investment recommendations given by the quantitative investment model, rather than changing them arbitrarily as investor sentiment changes. The benefits of discipline are many, overcoming human weaknesses such as greed, fear, and luck, as well as cognitive biases, and behavioral finance theory has much to say about this.

2) Systematic: The systematic characteristics of quantitative investment mainly include multi-level quantitative models, multi-angle observation and observation of massive data. The multi-level model mainly includes the asset allocation model and the industry selection model.

type, selected ** model and so on. The multi-angle observation mainly includes the analysis of macro cycles, market structure, valuation, growth, earnings quality, analyst earnings**, market sentiment and other perspectives.

3) Timeliness: Track market changes in a timely and fast manner, constantly discover new statistical models that can provide excess returns, and look for new trading opportunities.

4) Accuracy: Accurately and objectively evaluate trading opportunities, overcome subjective emotional biases, and properly use the idea of arbitrage. Quantitative investment is looking for valuation depressions, and capturing the opportunities brought about by mispricing and misvaluation through comprehensive and systematic scanning.

Unlike qualitative investment managers, quantitative investment managers spend most of their energy on analyzing which varieties are undervalued, undervalued, and overvalued.

5) Diversification: Under the condition of controlling risks, it acts as a tool to accurately achieve the goal of diversification. Diversification can also be said that quantitative investing relies on probability to win. This is manifested in two aspects, one is the continuous development of quantitative investment.

History excavates historical laws that are expected to be repeated in the future and makes use of them, and these historical laws are strategies with a high probability of winning. The second is to rely on screening out the best combinations to win, rather than one or several ** votes to win, from.

1. Advantages of quantification:

It helps to avoid blind spots and control risks.

Quantification is based on the analysis of a large number of historical data, comprehensively considering a variety of investment methods, and then with the help of computer and data analysis to statistically develop an investment model suitable for the current market, and make investment decisions based on the investment model.

In fact, the core is to control risks through quantitative investment strategies, and the strategy of active investment can obtain excess returns in the market under the condition of controllable risks.

In addition, quantitative** breaks through the limitations of traditional and exponential investment, and can also become a fixed income product when it is not good.

Second, the disadvantages of quantifying **:

Weak adaptability.

If there is a systemic risk situation, when the whole market is trending, and then falls sharply, quantification cannot avoid the situation, because quantification requires a period of time to optimize and adjust the algorithm, and its adaptability is not strong, and it is relatively slow and sluggish.

In addition, there is no way to pursue a fairly high amount of income after taking the amount of fiber mining, and the quantitative ** is generally concerned with long-term performance, if investors want to invest in the short term, then the quantification ** may be difficult to have a high return in the short term.

Extended Information: What does quantification mean?

Quantification is actually a kind of quantitative investment, which is a kind of management that guides investment by using statistical and mathematical methods and in strict accordance with the quantitative model constructed by these strategies, of which quantification can also be subdivided into the following three types:

1. Index-enhanced**, which wants to provide investment performance that is higher than the return level of the underlying index.

2. Hedging type**, which hedges the risk of the market by going long and short, in order to obtain a more stable absolute return.

3. Active management, which is similar to the concept of active management, obtains excess returns through active management.

At the same time, investors can consider the following aspects when choosing quantitative**:

1. Scale.

** Too small and at risk of liquidation; When the scale is too large, it becomes more difficult for the manager to operate.

2. **Manager.

When it comes to quantification, it's best to have a background in mathematics, financial engineering, or statistics.

The details are as follows:1Alpha Hedging (**+**), Call Auction Stock Selection (**), Multi-factor Stock Selection (**), Grid Trading (**), Index Enhancement (**), Cross-Variety Arbitrage (**), Intertemporal Arbitrage (**), Intraday Rotation Trading (**), Market Maker Trading (**), Turtle Trading (**), Industry Rotation (**), Machine Learning (**).

Extended Information:1It is easier to achieve quantitative pattern breakthroughs, including fractals, narrow sideways breakouts, various ** combinations, double bottoms and double tops, and entanglement three buys and three sells; It is difficult to achieve quantitative patterns with good breakouts, there are trend lines, arc tops and bottoms, flags, diamonds, triangles and other classic technical analysis patterns, the trend is followed by consolidation, and the consolidation is followed by the trend.

The trading strategy of sideways breakout fully embodies the law of volatility in the volatility cycle. What we need to do is to reasonably quantify the definition of the consolidation of the divination family, such as the period span and the amplitude of fluctuations.

2.Yesterday's high, yesterday's low, yesterday's ** price, and today's opening price can be called the four prices of Fiali. It is the main breakout trading reference system adopted by the Japanese ** champion Fiali real market.

In addition, the mode of subjective mind trading of Infiali determines that it also combines and uses a large number of "resistance and overflow lines" in actual trading, that is, resistance lines and support lines.

3.As a popular breakout trading strategy in the foreign exchange market, hans123 breaks through the highs and lows of N-root** after its concise opening as a criterion for trading signal triggering. This is also a trading mode that enters the market earlier, and with filtering technologies such as envelope, time confirmation, and volatility, it may improve its chances of winning.

4.The ORB breakout trade was first proposed in 1988 by Toby, a manager in the United States. He measures the smaller of the distance between the opening price and the most ** and the lowest price, and the breakthrough range is the failure, and once the market exceeds this range, it is considered to be a real breakthrough.

In practical applications, the breakthrough in the morning and the breakthrough after the narrow range can be used as an effective filtering condition.

Quantitative investing is the application of mathematics, statistics, information technology and other knowledge in the investment process. Investors will collect the best data, and then rely on the powerful information processing power of the computer system to replace manual subjective judgment with advanced mathematical models, so as to achieve maximum returns under the premise of controlling risks.

Quantitative investing has many advantages, for example, investment strategies are based on large-scale data, execution is not affected by investor sentiment, cognitive biases can be effectively overcome, market changes can be fast-tracked, new statistical models are constantly searched for to provide excess returns, and new trading opportunities can be found. Quantitative investment, as a prerequisite for effective risk control, can be used as a tool for investment diversification. For example, quantitative investing can dig out certain patterns from historical data and use them.

These rules can result in a greater probability of return on investment.

In the process of quantitative trading, the application of quantitative investment thinking covers almost the entire process of investment, from the selection of investment objectives, the analysis of portfolio strategies, the implementation of strategies to investment objectives, and finally to the risk control and feedback of investment strategies. Several concepts related to optimal strategies, including trend strategies, quantitative hedging strategies, arbitrage strategies, high-frequency strategies, and algorithmic trading, are particularly worrying.

The reason for the popularity of quantitative investment, even with subjective investment trends, must have the advantages of quantitative investment. All in all, there are the following: it is based on mathematical statistics, closer to a science, making the future easier** and perceived, allowing all markets and transactions to be monitored in real time throughout the year, which humans cannot.

It avoids human emotion, is completely automated by machines, and strictly enforces discipline. Processes and risks are more controllable. These advantages have gradually brought quantitative investing into our field of vision and are being accepted by more and more investors.

It refers to the use of mathematics, information technology, and statistics in the investment process. To understand large-scale data, we must also have quantitative investment thinking, pay attention to the provisions of investment objectives, have a portfolio strategy, understand the implementation of the strategy, and also have quantitative decision-making, and pay attention to the trend strategy.

Quantitative investing means that calculations are made by a computer, and then long-term investments are made through the results. The more common quantitative strategy is to invest according to the data of the computer, invest according to the results of the computer, invest according to the financial capacity and data, and also select stocks according to the quantitative results.

Quantitative investment refers to the relevant knowledge that will be used in investment, and a lot of data can be collected, such as returnee trading strategy, alpha strategy, multi-factor stock selection, double ** strategy, index enhancement strategy, and network trading, all of which are common quantitative investment strategies.

Quantitative investment refers to the trading method that issues buy and sell orders through quantitative methods and computer programs for the purpose of obtaining stable returns, and requires the use of mathematics, statistics, information technology and other knowledge in the process of investment.

The quantitative strategy in the market includes two parts: market long trend and market performance neutrality, the market long trend includes two parts: index enhancement and active quantification, and market performance neutral includes quantitative hedging, which is the so-called alpha strategy ( strategy).

Strategy refers to the use of financial derivatives to hedge market risks, to obtain relatively stable returns, such products have also achieved relatively large development in the past few years. Quant is actually a very broad concept, involving a variety of different asset classes, such as commodities**, quant has a series of CTA strategies, in addition, there are multi-strategy quants.

From the perspective of public offerings, there are three main types of mainstream quantitative strategies in the market:

The first type is the active quantitative strategy.

The active quantitative strategy is to select stocks in a quantitative way, and then combine it with active fundamental screening to build such a strategy that combines active and quantitative strength.

The second type is the exponential enhancement strategy.

Index enhancement refers to the first tracking of a certain index, which is generally a mainstream broad-based index in the market, such as the CSI 300 or CSI 500 or even the CSI 1000 index, on the basis of which the long-term stable excess return will be pursued, that is, the enhanced alpha part.

The third type of alpha strategy for quantitative hedging.

The core of the alpha strategy of quantitative hedging is still the combination of index enhancement to obtain excess returns relative to the index, but at the same time, the stock index ** will be introduced as hedging, stripping away the volatility of the market or what we call the index, and obtaining relatively stable alpha returns.

This type of strategy has also grown in size over the past five years, especially in the last two to three years. From about 15 billion in 2015, the scale has grown to about 65 billion now, and it is also a very mainstream strategy in public offerings.