Types of Quantitative Trading Strategies

Quantification refers to digitizing time and signals in behavioral patterns and analyzing them using a series of logic, rather than just relying on human senses and instincts. Quantitative methods are generally automated, but manual operations can also be used. For example, using technical indicators or financial indicators to select stocks is actually a kind ofQuantitative strategies, but the execution part may be artificial. when atrading strategyIt is written into the code and program. This is the so-called quantitative trading. All transactions will be carried out automatically, including futures, funds, Forex, etc.

In the final analysis,Automated trading strategiesIt's easy to implement, but automated trading strategies are completely different from developing efficient trading patterns. The biggest advantage of quantitative trading is that it can avoid emotional fluctuations, thereby reducing impulsive trading caused by subjective consciousness. The types of quantitative investment strategies can be divided into stocks, CTA, options, SOS and other types. CTA is a quantitative trading strategy for stock index futures, treasury bond futures and commodity futures trading. It is currently the most commonly used trading strategy in the market. SOS diversifies funds into different funds to further diversify its risks on the basis of diversified investments. The advantage of this strategy is that it can combine the advantages and advantageous strategies of fund managers with different investment styles, gather the interests of all investors, and quantify them according to the income model.

Trading strategies include unilateral strategy, long-short strategy, arbitrage strategy, arbitrage strategy, arbitrage strategy, etc.A single long-short strategy refers to a strategy that achieves profits through unilateral buying or unilateral selling under the premise of comprehensive economic cycles, macro trends, political events, historical data and other factors. Through the combination of multiple single long-short strategies, the purpose of arbitrage or hedging can be achieved, and the purpose of risk aversion can be achieved. Market-neutral arbitrage strategy refers to buying and selling the same or substantially the same type of financial product at the same price in different markets and at different times at a higher price. If this is the case, then investors can sell or buy the same or essentially the same financial product at the same time. The basic logic of this strategy is profit, and its core is mean reversion. Hedging is a financial and statistical correlation.

When buying and selling financial instruments, the prices of these two types of financial products are related to market trends. The prices are inverse, the trading volume is equal, and the profits and losses are compared. The basic principle of the hedging strategy is to avoid risks that investors are unwilling to take by conducting risk management on the securities portfolio, focusing on balancing risks, and buying, selling, and buying stock index futures and corresponding stocks at the same time. A hedging strategy is a stock market neutral strategy that combines a single long-short strategy for multiple stocks and can also be considered a hedge. According to different strategy signals, quantitative strategies include multi-factor strategies, mean reversion strategies, momentum return strategies, 28-year rotation strategies, turtle strategies, and continuous learning strategies. According to different transaction rates, quantitative investment strategies can be divided into two types: high frequency and low frequency. High-frequency strategies usually use advanced computer technology and systematic analysis to conduct transactions and complete transactions within a day.

The position holding algorithm is a high-frequency strategy, and strategies with long holding times and long swap cycles, such as certain stocks that are held for a long time and adjusted weekly or quarterly, can classify multi-factor strategies into non-high-frequency strategies. In addition, with the in-depth cooperation in computer technology, mathematics, physics, finance and other disciplines, more excellent teaching methods will be developed to provide investors with better investment decisions.