2. Secondly, choose the right trading software. Among them, the software of trading pioneer is the best programming, and many trading teams are basically using this software. Determine the account and transaction software.
3. What remains is how to write the strategy in programming language and input it into trading software. Programming is actually not difficult. In programmed transactions, programming only accounts for 30% of programmed transactions. Good programming can simplify the code, improve the running speed, increase the diversity and integrity of trading strategies, and realize some complex strategies.
4. If you don't have the programming ability in this field, you can take relevant training courses on futures trading. The other 70% is mainly the combination management of strategy, position setting, trading variety selection, programmed trading mentality control and network setting.
1, determination of strategy. The development process of a successful quantitative trading system must be appropriate. How to find a successful quantitative trading strategy is the basis of building a quantitative trading system. Both fundamentals and technical aspects can be analyzed by quantitative methods, and then a quantitative trading strategy can be obtained. For example, fundamentally speaking, the growth of GDP and the increase of currency circulation can be analyzed and described by quantitative methods. Technically, moving average and index smma are the sources of physical and chemical strategic thinking.
2. Classical theory. Many ideas of quantitative investment strategy come from the traditional classical investment theory, such as the technical analysis of classical commodity futures, which mainly includes the theoretical basis of technical analysis, Dow theory, chart introduction, the basic concept of trend, main reversal patterns, persistent patterns, trading volume and interest in holding positions, long-term charts and commodity indexes, moving averages, swing indexes and objections, intraday charts, three-point turning and optimization charts, Eliot wave theory, time period and so on. Some of these classical theories have specific indicators and specific application theories, while others only have theories. It is necessary to generate specific application indicators according to the theory to complete the strategy test. Therefore, the classical investment theory can quantify the specific logic in the theory into indicators or events to form trading signals through quantitative thinking, and realize the investment ideas of the classical theory through signal optimization testing. This method can effectively realize the classical theory, and at the same time, it can also derive the surrounding investment methods from the original classical theory, which is the mainstream model in the early stage of quantitative strategy development.
3. Logical reasoning. Most of the strategic thinking of logic comes from macro-basic information, and its quantitative strategic thinking is to sort out the quantitative model that conforms to macro-basic information through quantitative processing of macro-information. Typical quantitative strategies include industry rotation quantitative strategy, market sentiment rotation quantitative strategy, upstream and downstream supply and demand quantitative strategy and so on. The source of this strategy is very extensive, and the data is generally not standardized, so it is difficult to form a standard. At present, many hedge funds have similar ideas to generate quantitative strategy products.
4. Sum up experience. Experience summary is another main source of quantitative strategic thinking. Before trading with quantitative strategy, there were a large number of experienced investors in the market, many of whom were outstanding in long-term stable income. Therefore, their views on the market and trading ideas have become the imitation objects of quantitative strategy developers. Experienced traders are also willing to quantify some trading strategies that they feel are relatively solid and can obtain stable returns. Finally, they can trade with the machine automatically, just by monitoring the transaction. This can greatly reduce the energy consumed in the transaction. Under this premise, a quantitative strategy team emerged to cooperate with experienced traders.