What is Quantitative Trading?

Quantitative trading refers to the use of advanced mathematical models to replace human subjective judgments, and the use of computer technology to select a variety of "high probability" events that can bring excess returns from huge historical data to formulate strategies, greatly reducing investor sentiment The impact of volatility, to avoid making irrational investment decisions in extreme market enthusiasm or pessimism.

Quantitative trading

(Investment method)

Quantitative trading refers to the use of advanced mathematical models to replace human subjective judgments, and the use of computer technology to select a variety of "high probability" events that can bring excess returns from huge historical data to formulate strategies, greatly reducing investor sentiment The impact of volatility, to avoid making irrational investment decisions in extreme market enthusiasm or pessimism.

Quantitative investment and traditional qualitative investment are essentially the same, both are based on the theoretical basis of market inefficiency or weak efficiency. The difference between the two is that quantitative investment management is a "quantitative application of qualitative thinking", with more emphasis on data. Quantitative trading has the following characteristics:

1. Discipline. Make decisions based on the results of the model's operation, not by feeling. Discipline can restrain the weaknesses of greed, fear, and fluke in human nature, as well as overcome cognitive biases and can be tracked.

2. Systematic. The specific performance is "three more". First, there are multiple levels, including models at three levels of asset allocation, industry selection, and selection of specific assets. Second, there are multiple perspectives. The core idea of quantitative investment includes macro cycles, market structure, valuation, growth, and profitability. Quality, analyst profit forecast, market sentiment and other angles; the third is multi-data, that is, the processing of massive data.

3. Arbitrage ideas. Quantitative investment captures the opportunities brought by mispricing and misvaluation through comprehensive and systematic scanning, so as to find valuation depressions and profit by buying undervalued assets and selling overvalued assets.

4. Win with probability. First, quantitative investment is constantly mining and using prospective repeated laws from historical data; second, relying on portfolio assets to win, not individual assets.

Quantitative investment technology includes a variety of specific methods, which are widely used in the fields of investment variety selection, investment timing selection, stock index futures arbitrage, commodity futures arbitrage, statistical arbitrage and algorithmic trading. Here, statistical arbitrage and algorithmic trading are taken as examples for illustration.

1. Statistical Arbitrage ^[1]

Quantitative transactions are generally tested by means of massive data simulation tests and simulation operations, and positions and funds are allocated according to certain risk management algorithms to minimize risks and maximize returns. However, there are often certain potential risks. include:

1. Integrity of historical data. Incomplete market data may cause the model to not match market data. The style conversion of the market data itself may also cause the model to fail, such as transaction liquidity, price fluctuation range, price fluctuation frequency, etc., which is currently insurmountable for quantitative trading.

2. The position and fund allocation are not considered in the design of the model, and there is no safe risk assessment and preventive measures, which may lead to the mismatch of funds, positions and models, and the phenomenon of liquidation.

3. Network interruption and hardware failure may also affect quantitative transactions.

4. The homogeneous model generates risks caused by the phenomenon of competitive transactions.

5. Unpredictable risks caused by a single investment product.

In order to avoid or reduce the potential risks of quantitative trading, the strategies that can be adopted include: ensuring the integrity of historical data; adjusting model parameters online; selecting model types online; online risk monitoring and avoidance.

Quantitative strategy refers to using a computer as a tool to analyze, judge, and make decisions through a fixed set of logic. Quantitative strategies can be executed automatically or manually. ^[2]

What is included in a complete quantization strategy?

Quantification strategy

A complete strategy needs to include input, strategy processing logic, and output; strategy processing logic needs to consider factors such as stock selection, timing, position management, and take profit and loss.

Stock picking

Quantitative stock selection is to use a quantitative method to select a determined investment portfolio. It is expected that such a portfolio can obtain investment returns that exceed the market cap. Commonly used stock selection methods include multi-factor stock selection, industry rotating stock selection, and trend-following stock selection.

1 Multi-factor stock selection

Multi-factor stock selection is the most classic stock selection method. This method uses a series of factors (such as P / E ratio, P / B ratio, and P / S ratio) as stock selection criteria. Stocks that meet these factors are bought, and those that do not meet Sell. Value investors such as Buffett will buy low-PE stocks and sell them when PE returns.

2 Style Rotation Stock Pick

Style rotation stock selection is based on the use of market style characteristics to invest. The market prefers large-cap stocks and small-cap stocks at a certain moment. If you discover the law of market switching preferences and intervene in the early stage of style conversion, you may get a better Big gains.

3 Industry Rotation Stock Selection

The industry's rotating stock selection is due to the economic cycle. Some industries will follow other startups after starting. By discovering these following rules, we can buy the latter after the startup to obtain higher returns. Different macroeconomics Under the stage and monetary policy, different industry rotation characteristics may be produced.

4 Fund flow selection

Fund flow selection is to use the flow of funds to judge the stock trend. Buffett said that the stock market is a voting machine in the short term and must be a weighing machine in the long term. Short-term investor transactions are a form of voting behavior, and so-called votes are funds. If money flows in, the stock should rise, and if money flows out, the stock should fall. Therefore, a corresponding investment strategy can be constructed according to the flow of funds.

5 Momentum reverse stock selection

The momentum reversal stock selection method is an investment portfolio constructed using the characteristics of investors' investment behavior. Soros's so-called reflexivity theory emphasizes that the positive feedback effect of price increases will cause investors to continue to buy, which is the basic basis for momentum stock selection. Momentum effect means that the strong stocks in the previous period will continue to be strong in the future. When the positive feedback reaches an unsustainable stage, the price will collapse and return, and in this environment, a reversal characteristic will appear, that is, the stocks that were weak in the previous period will become stronger in the future.

6 Trend tracking strategies

Buying when the stock price is rising and selling when the stock price is down is essentially a strategy of chasing up and down. Many markets have more trends due to herd utility. If you can control When you make a good loss, you can continue to capture the trend, and in the long run, you can get additional income.

Timing

Quantitative timing refers to the quantitative determination of buying and selling points. If the judgment is up, buy and hold; if the judgment is down, sell and clear the position; if the judgment is shock, sell high and sell low.
Commonly used timing methods are: Quantitative timing of trends, Quantitative timing of market sentiment, Quantitative timing of effective funds, SVM, etc.

Position management

Position management is the technique of deciding how to enter the market in batches and how to stop profit and stop loss when you decide to invest in a certain stock portfolio.
Commonly used position management methods include: funnel position management method, rectangular position management method, pyramid position management method, etc.

Take Profit and Stop Loss

Take profit, as the name implies, sell in time when gains are made, and gain profit; stop loss, sell shares in time when the stock loses, to avoid greater losses.
Timely take profit and stop loss is an effective way to obtain stable returns.

The life cycle of a policy

A strategy often goes through several stages: generating ideas, implementing strategies, testing strategies, operating strategies, and strategy failures.

Generate ideas

Anyone may come up with a strategic idea at any time, either based on their own investment experience or on the successful experience of others.

Implementation strategy

Generating ideas to implementing strategies is the biggest leap. For implementing strategies, you can refer to the "What does a complete quantitative strategy include?"

Inspection strategy

After the strategy is implemented, it is necessary to pass the backtesting of historical data and the verification of simulated transactions. This is also the key link before the real offer, screening high-quality strategies and eliminating low-quality strategies.

Real trading

Invest in funds, test the effectiveness of strategies through the market, take risks, and earn income.

Strategy failure

The market is ever-changing, and the effectiveness of the strategy needs to be monitored in real time. Once the strategy fails, it needs to be stopped in time or the strategy should be further optimized.