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This article mainly introduces the relevant knowledge of "what are the knowledge points of Python quantitative transactions". The editor shows you the operation process through actual cases, the operation method is simple and fast, and it is practical. I hope this article "what are the knowledge points of Python quantitative transactions" can help you solve the problem.

I. Overview of quantitative transactions (algo-trading)

Algorithmic transactions are performed using automated systems, and these transactions are performed in a predictive manner through specific algorithms without any human intervention. The probability analysis of big data is carried out according to the mathematical model to maximize the long-term income expectation.

Quantify the benefits of the deal:

1. Historical assessment

The most important advantage of creating an automation strategy is that its performance can be determined by historical market data to represent future market data. This process is called Renewal Test backtesting. Backtesting can determine the (previous) statistical characteristics of the strategy and provide an insight into whether the strategy is likely to be profitable in the future.

two。 Efficiency

Algorithmic trading is more efficient than arbitrary methods. Fully automated systems do not require individuals or teams to continuously monitor the price market. This frees up time for the developers of the deal to do more research. In addition, automated trading can realize the automatic and stable systematic strategy of risk management and position adjustment process, and dynamically respond to market dynamics in real time.

3. No arbitrary input

One of the main advantages of an automated trading system is that there is no subsequent emotional input. In execution, fear and greed can be overwhelmingly free trading. In the case of system trading, there are few times when the ester situation changes the strategy. However, sometimes due to external factors, it is determined that the parameters of the strategy need to be modified or exit the implementation of the model.

4. Higher frequency

This is the inevitable result of the efficiency advantages discussed above. In a higher operational strategy automation environment, frequency in many markets becomes possible. Indeed, some of the most profitable trading strategies are the ultra-high frequency domain operation data on the limit order book limit or market order trading book. These strategies are impossible for human beings.

Quantify transaction disadvantages:

Capital requirements:

Algorithmic trading usually requires free trading of capital with a larger capital base than the capital base used for retail. In addition, the intraday quantification strategy for obtaining data feeds, especially if the use of futures contracts is not cheap for retailers. Depending on the latency requirement, it may be necessary to co-locate the server in the switch, which increases the monthly cost. More powerful Internet connections and powerful (and therefore expensive) desktop machines are also needed. Most importantly, because algorithmic trading seeks long-term expectations of returns, a larger amount of capital is needed to support short-term losses.

Second, trading system 1. Backtest-backtest

The function of pybacktest's. To this end, we return to the classic trading strategy moving average MA crossover.

Buy long when you wear the slow line on the MA fast line.

When you cross the slow line under the MA fast line, you will sell short.

The entry rule is also the exit rule, and the trading strategy is opposite to each other.

two。 Exchange

There are two types of orders that can be executed: market orders and limit orders. Market orders execute the transaction immediately, regardless of the available price. So a large transaction executed as a market order usually gets the price of each subsequent limit order mixed on the opposite side to be filled. Market orders will be seen as positive orders that will almost certainly be filled, despite potential unknown costs. Limit orders provide a mechanism for strategies to determine that the worst price transactions will be executed, while warning that transactions may not be partially or completely filled. Restricted orders are considered passive orders because they are usually vacant, but are guaranteed when they are prices.

3. Transaction fee

The most direct form of transaction cost generated by the transaction strategy is commission. All strategies require some form of access exchange, either directly or through a broker ("broker"). These services incur additional costs for each transaction called commission. Brokers usually provide a lot of services, although quantitative algorithms can only really achieve the use of switching infrastructure. As a result, brokerage commissions tend to be small on a per-transaction basis. Brokers also charge fees, which are fees for clearing and settling transactions. Further, this is a tax levied by regional or national governments. For example, stamp duty is paid on stock transactions in the UK.

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