1 quantitative stock selection
Quantitative stock selection is an act of judging whether a company is worth buying by quantitative methods. According to a certain method, if the company meets the conditions of this method, it will be put into the stock pool, and if it does not, it will be removed from the stock pool. There are many ways to quantify stock selection. Generally speaking, it can be divided into three categories: company valuation method, trend method and capital method.
2. Quantitative timing
The predictability of the stock market is closely related to the efficient market hypothesis. If the efficient market theory or efficient market hypothesis is established, the stock price fully reflects all relevant information, and the price changes follow a random walk, so it is meaningless to predict the stock price. Many studies have found that there is a nonlinear correlation in the index return of China stock market besides the classical linear correlation, thus denying the hypothesis of random walk, and pointing out that the fluctuation of stock price is not completely random, which seems to be random and chaotic, but behind its complex surface, there is a deterministic mechanism, so there is a predictable component.
3. Stock index futures arbitrage
Arbitrage of stock index futures refers to the behavior of taking advantage of the unreasonable price of stock index futures market, participating in the trading of stock index futures and stock spot market at the same time, or trading different (but similar) types of stock index contracts at the same time to earn the difference. The arbitrage of stock index futures is mainly divided into two types: spot arbitrage and intertemporal arbitrage. The research of stock index futures arbitrage mainly includes spot construction, arbitrage pricing, margin management, impact cost, component stock adjustment and so on.
4. Commodity futures arbitrage
The logic principle of arbitrage profit of commodity futures is based on the following aspects: (1) There is a reasonable price difference between related commodities in different places and at different times. (2) Due to price fluctuation, the price difference is often unreasonable. (3) Unreasonable must return to reasonable. (4) Unreasonable return to a reasonable price range is the profit range.
5. Statistical arbitrage
Different from risk-free arbitrage, statistical arbitrage is a kind of risk arbitrage by using the historical statistical law of securities prices, and its risk lies in whether this historical statistical law will continue to exist in the future. Statistical arbitrage can be divided into two categories in terms of methods. One is to model with stock return sequence, and the goal is to realize α return on the premise that the β value of portfolio is equal to zero, which we call β neutral strategy; The other is to use the cointegration relationship of stock price series to model, which we call cointegration strategy.
6. Option arbitrage
Option arbitrage trading refers to buying and selling call or put option contracts with the same related futures but different execution prices or different maturity months at the same time, hoping to make a profit when hedging trading positions or performing contracts in the future. There are various trading strategies and methods of option arbitrage, which are a combination of various related options trading, including: horizontal arbitrage, vertical arbitrage, conversion arbitrage, reverse conversion arbitrage, cross arbitrage, butterfly arbitrage, flying eagle arbitrage and so on.
7. algorithmic trading
Algorithm trading, also known as automatic trading, black box trading or machine trading, refers to the use of computer programs to issue trading instructions. In trading, the scope that the program can decide includes the choice of trading time, the price of trading, and even the number of securities that need to be traded in the end. According to the different degree of initiative in each algorithm transaction, different algorithm transactions can be divided into three categories: passive algorithm transactions, active algorithm transactions and comprehensive algorithm transactions.
8. Asset allocation
Asset allocation refers to the selection of asset categories, proper allocation of various assets in the portfolio, and real-time management of these mixed assets. Quantitative investment management combines traditional portfolio theory with quantitative analysis technology, which greatly enriches the connotation of asset allocation and forms the basic framework of modern asset allocation theory. It breaks through the limitations of traditional active investment and index investment, and its investment method is based on the statistical analysis of public data of various asset classes. By comparing the statistical characteristics of different asset categories, a mathematical model is established, and then the allocation target and proportion of portfolio assets are determined.