1. What is a quantitative trading system?
Quantitative trading refers to the use of advanced mathematical models to replace human subjective judgments, and the use of computer technology to select multiple "high probability" events that can bring excess returns from huge historical data to formulate strategies, which greatly reduces investor sentiment The impact of volatility, to avoid making irrational investment decisions when the market is extremely fanatical or pessimistic.
The main functions of the quantitative trading system are: the signal system for buying and selling; the direction of the bull market or the bear market; position management and fund management; risk control and investment portfolio.
Two, the two major trading methods of the quantitative trading system
The two major trading methods of the quantitative trading system are:
1. Statistical arbitrage
Statistical arbitrage is an arbitrage based on the historical statistical law of asset prices. It is a kind of risk arbitrage. The risk lies in whether this historical statistical law will continue to exist in the future.
2. Algorithmic trading.
Algorithmic trading, also known as automatic trading, black box trading or machine trading, refers to a method of issuing trading instructions through computer programs through designing algorithms. In trading, the range that the program can determine includes the choice of trading time, the price of the transaction, and even the number of assets that need to be traded in the end.
The main types are:
(1) Passive algorithmic trading, also called structured algorithmic trading. In addition to using historical data to estimate the key parameters of the trading model, the trading algorithm will not actively choose trading timing and the number of transactions based on market conditions, but will conduct transactions in accordance with an established trading policy.
(2) Active algorithmic trading, also known as opportunity algorithmic trading. This type of trading algorithm makes real-time decisions based on market conditions, judging whether to trade, the number of transactions, and the price of the transaction.
(3) Comprehensive algorithmic trading, which is a combination of the former two. The common method of this type of algorithm is to first disassemble the trading instructions and distribute them to several time periods, and how to trade in each time period is determined by the active trading algorithm. The combination of the two can achieve effects that a single algorithm cannot achieve.
Trading strategies are:
1. Reduce transaction costs:
2. Arbitrage:
3. Market making.
3. The characteristics of the quantitative trading system:
(1) Wide investment perspective. Relying on the computer to process the sea star information efficiently and accurately, to find a wider range of investment opportunities in all markets.
(2) Discipline. Strict discipline is an important feature that distinguishes quantitative trading from active investment. Discipline has many benefits. It can overcome the weaknesses of human nature, such as fear, greed, fluke, and can also overcome cognitive biases.
(3) Systematic. Multi-level models mainly include industry selection models, major asset allocation models, and selected individual stock models. Multi-angle observations mainly include analysis from multiple perspectives such as macro cycle, valuation, growth, earnings quality, market structure, analyst earnings forecasts, and market sentiment.
(4) Timeliness. Track market changes in a timely and rapid manner, constantly discover new statistical models that can provide huge profits, and look for new trading opportunities.