If the market fluctuates, you can make money.
20 1 1 At the end of the year, the fluctuation of the international commodity market showed the importance of funds more and more, rather than the traditional fundamentals determining the market fluctuation. This new change makes investors rely more and more on the analysis of funds to make decisions, which also promotes the development of quantitative hedging transactions to some extent.
The so-called quantitative investment, its essence is to use data and models to make investment decisions. Ding Peng, a senior analyst in orient securities, said that quantitative hedging is still in its infancy in China, but there have been many successful cases in the international market. Take the United States as an example. The Medallion Fund managed by james simons, the king of hedge funds, has made an average annual profit of 35% for 20 consecutive years. Simmons' main strategy is to use powerful mathematical models and computer software to predict the future through the correlation analysis of historical data, and make high-frequency transactions in different products in the global market to earn small fluctuations, so as to obtain stable and sustained income.
Ding Peng pointed out that hedging is a relatively neutral strategy, which is less affected by the bull and bear market environment and can make money as long as it fluctuates. He believes that the era of profiteering in investment is over. In the era of derivatives, although the market operation is much more difficult, steady profit will become the core competitiveness of asset management, and absolute income products will also become the pursuit of high-net-worth customers. Therefore, quantitative hedging transactions will become the core of obtaining absolute returns.
Ding Peng said that at present, spot arbitrage trading is still widely used in the domestic market, but in fact, quantitative concepts include futures, option arbitrage and algorithmic trading. Taking stock index futures arbitrage as an example, its basic concept refers to the behavior of taking advantage of the unreasonable price in the stock index futures market, participating in stock index futures and stock spot market trading at the same time, or trading stock index contracts with different maturities and different (but similar) categories at the same time to earn the difference. Its main methods include spot arbitrage, intertemporal arbitrage, cross-market arbitrage and cross-variety arbitrage.
The advantage of option arbitrage is unlimited income, but limited risk loss. Therefore, in many cases, using options instead of futures to short and carry out arbitrage trading is less risky and has higher yield than simply using futures arbitrage. Its main methods include stock option arbitrage, conversion arbitrage, span arbitrage, long-span arbitrage, "butterfly" arbitrage and "eagle" arbitrage.
▌ Quantitative hedging three trading strategies
Liquidity rebate transaction
In order to win more trading orders, all the stock exchanges in the United States provide brokers who create liquidity with a certain transaction fee rebate, usually 0.25 cents per share. No matter whether the bill is paid or sold, as long as the transaction is successful, the exchange will pay kickbacks to the original brokers who provide liquidity, and at the same time charge higher fees to the brokers who use liquidity for trading. With the popularity of this incentive mechanism, more and more trading strategies for the purpose of obtaining trading kickbacks have emerged.
For example, suppose the psychological transaction price of institutional investors is 30-30.05 USD. If the first buyer in the trading system (such as 100 shares) is successfully paired, the transaction will be made at $30. In this way, the second order (such as 500 shares) in the trading system will be displayed. Assuming that the purchase order is also matched successfully, the transaction is completed at $30. According to the above trading information, the computer system of high-frequency traders specializing in liquidity rebate strategy may detect the existence of other subsequent $30 purchases by institutional investors, so they quickly took action and quoted 65,438+000 shares at a price of 30.0 1 USD. There is no doubt that those brokers who sell their stocks at $30 are more willing to sell them to kickbacks at $ 30.0438+0.
After the transaction is successful, the rebate dealer immediately adjusts the trading direction and sells the newly bought 100 shares at the price of 30.0 1 USD, that is, 30.0 1 USD. Since the stock price of $30 no longer exists, the selling order is likely to be accepted by institutional investors.
In this way, although the rebate trader did not make a profit in the whole trading process, he got a rebate commission of 0.25 cents per share provided by the exchange because the second active selling order provided liquidity for the market. It goes without saying that the profit of 0.25 cents per share earned by rebate dealers is at the cost of 1.0 cents paid by institutional investors.
Algorithm trading of prey
In the United States, more than half of institutional investors follow the national best bidding principle. According to this principle, when the priority of one order is higher than that of another order, in order to close the second order, the stock price is often adjusted to ensure consistency with the former. In fact, the algorithmic quotation of a stock often keeps up with each other at a very fast speed, which makes the stock price show a phased change trend from high to low and from low to high, which is why in actual trading, a limited number of 100 shares or 500 small transactions are often seen, which often pushes the stock price up or down by ten cents to dozens of cents.
The so-called prey algorithm trading strategy is designed on the basis of studying the historical law of the above-mentioned stock price changes, that is, by creating artificial prices, institutional investors are induced to increase their buying prices or reduce their selling prices, thus locking in trading profits.
For example, suppose institutional investors follow the national best bidding principle, and the psychological transaction price is 30-30.05 USD. Just like the liquidity rebate trader in the above example, prey algorithm traders use very similar procedures and techniques to find potential continuous algorithm orders from other investors. After the computer confirmed that there was an algorithmic bill with a price of $30, the prey algorithmic trading program launched an attack: the bill with a price of $30.065438 +0 was quoted, forcing institutional investors to quickly raise the price of subsequent bills to $30.065438 +0. Then the prey algorithm traders further pushed the price to $30.02, inducing institutional investors to continue chasing.
By analogy, the prey algorithm trader instantly pushes the price to the upper limit of $30.05 acceptable to institutional investors and sells the stock to the latter at this price. Traders know that the artificial price of $30.05 is generally difficult to maintain, so they make up their positions when the price falls.
Automatic market maker trading
The main function of market makers is to provide trading liquidity for trading centers. Like ordinary market makers, high-frequency traders of automatic market makers improve liquidity by providing orders to the market. The difference is that they usually operate in the opposite direction to investors. The high-speed computer system of automatic market makers and high-frequency traders has the ability to discover the investment intentions of other investors by issuing ultra-fast instructions. For example, after an order to buy or sell is issued at a very fast speed, if the position is not closed quickly, the order will be cancelled immediately. However, if the transaction is completed, the system can capture a lot of information about the existence of potential and hidden orders.
Example: suppose an institutional investor sends a series of bills with the price between 30.0 1-30.03 USD to its algorithmic trading system, and no one outside knows about it. In order to find the existence of potential orders, the high-speed computer system of automatic market makers and high-frequency traders issued a sell order for 100 shares at a price of $30.05. The order was cancelled because the price was higher than the investor's price ceiling and did not cause any reaction; The computer tried again with $30.04, but there was still no response, and the order was cancelled. The computer tried again at $30.03 and the transaction was successful.
Based on this, the computer system realizes that there are a certain number of hidden bills with a price ceiling of $30.03. As a result, the computer system with powerful computing function immediately issued a bill of 30.0 1 USD, and made use of its technical advantages to clinch a deal before institutional investors, and then sold it back to institutional investors at the price of 30.03 USD.