Quantitative Investment Strategies for Quantitative Analysis

Quantitative investment techniques cover almost the entire process of investing, including quantitative stock picking, quantitative timing, stock index futures arbitrage, commodity futures arbitrage, statistical arbitrage, algorithmic trading, asset allocation, and risk control.

1-Quantitative stock picking

Quantitative stock picking is the act of using quantitative methods to determine whether a company is worth buying. Based on a particular method, if the company meets the conditions of that method, it is put into the stock pool, and if it does not, it is removed from the stock pool. There are many different methods of quantitative stock picking, and in general, they can be categorized into three main types: company valuation method, trend method and capital method

2-Quantitative Timing

The issue of predictability in the stock market is closely related to the efficient market hypothesis. If the efficient market theory or the efficient market hypothesis holds, stock prices fully reflect all relevant information, price changes obey the random wandering, and the prediction of stock prices is meaningless. Numerous studies have found that there is a nonlinear correlation in addition to the classical linear correlation in the index returns of China's stock market, thus rejecting the hypothesis of random wandering and pointing out that the fluctuation of stock prices is not completely random; it appears to be random and cluttered, but behind its complex surface lies a mechanism of certainty, and thus there is a predictable component.

3-Stock index futures arbitrage

Stock index futures arbitrage refers to the use of stock index futures market exists unreasonable price, at the same time to participate in stock index futures and stock spot market transactions, or at the same time, different period, different (but similar) categories of stock index contract transactions, in order to earn the difference in the behavior of the stock index futures arbitrage is divided into the period of the cash arbitrage and cross-period arbitrage two. 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 logical principle of profitability of commodity futures arbitrage is based on the following aspects : (1) related commodities in different locations, different time corresponds to all have a reasonable price difference. (2) Due to price volatility, the price difference is often unreasonable. (3) Unreasonableness is bound to return to reasonableness. (4) unreasonable back to the reasonable part of the price range is the profitability of the range.

5-Statistical Arbitrage

Different from risk-free arbitrage, statistical arbitrage is the use of the historical statistical laws of securities prices for arbitrage, is a kind of risk arbitrage, the risk of which lies in the continuation of such historical statistical laws in the future period of time. Statistical arbitrage can be divided into two categories in terms of methodology, one is the use of stock return series modeling, the goal is to achieve alpha return under the premise that the portfolio's beta value is equal to zero, we call it beta-neutral strategy; the other is the use of stock price series of the cointegration relationship modeling, we call it cointegration strategy.

6-Options Arbitrage

Options arbitrage is the simultaneous purchase and sale of call or put option contracts on the same underlying futures but at different strike prices or different expiration months, with the hope of hedging the position or taking a profit on performance at a later date. Option arbitrage trading strategies and methods are varied, is a combination of a variety of related options transactions, specifically including: horizontal arbitrage, vertical arbitrage, conversion arbitrage, reverse conversion arbitrage, straddle arbitrage, butterfly arbitrage, Flying Eagle arbitrage and so on.

7-Algorithmic Trading

Algorithmic trading is also known as automated trading, black box trading, or machine trading, which refers to the use of a computer program to issue trading orders. In trading, the program can determine a range of things including the choice of trading time, the price of the trade, and can even include the number of securities that need to be traded at the end. Depending on the extent to which the algorithm is active in each algorithmic trade, the different algorithmic trades can be categorized into three main categories: passive algorithmic trades, active algorithmic trades, and comprehensive algorithmic trades.

8-Asset Allocation

Asset allocation refers to the selection of asset classes, the appropriate allocation of various types of assets in a portfolio, and the real-time management of these mixed assets. Quantitative investment management combines traditional portfolio theory with quantitative analysis techniques, greatly enriching the connotation of asset allocation and forming the basic framework of modern asset allocation theory. It breaks through the limitations of traditional active investment and index-based investment, and builds its investment methodology on the statistical analysis of publicly available data on stocks of various asset classes, and establishes mathematical models by comparing the statistical characteristics of different asset classes, and then determines the allocation targets and allocation ratios of the portfolio assets.