I recently read babyquant's "Brief Analysis of Arbitrage Strategies in the Big Pie Circle" and wrote about various arbitrage strategies. I will also talk about my own digital currency arbitrage strategy that has been running for about 2 years.

All of this is made public, firstly, because I no longer run these strategies, and I will summarize them myself after writing them; secondly, the logic of arbitrage strategies is not mysterious in the first place. What this industry competes for is execution, that is, the ability to write code, especially in high-frequency trading. The frequency of trading may not be very high, but you must react quickly and enter the market immediately when fluctuations occur. Of course, there is also the ability to specialize in research, because the competition for arbitrage is still relatively fierce, and the competition in the later period is even more fierce. You also need to have a certain ability to raise funds. After all, the profitability of arbitrage is limited. Only with sufficient funds can you make considerable profits. At least it must exceed your part-time income before it is worth doing it full-time. Of course, joining an institutional team is also a way.

Last night's market trend for Big Pie and Two Pie was really timely. It has not been such a smooth trend for a long time.

This time let’s talk about how to use B’s historical transaction records.

B'an officials have shared a lot of transaction data. There is a Github page where you can view in detail what categories of data are available and how to download them. Here I mainly introduce the download, organization and use of the aggregated transaction records aggTrades.

aggTrades is the transaction record after aggregation, that is, Binance aggregates several consecutive transactions executed at the same time, in the same direction, and at the same price into one record, similar to a K-line, but with only one price and no highest price. lowest price and so on. For example, if there is a large order placed at the market and many small orders are placed to eat it, then these orders that arrive at the same time in a very short time (milliseconds) will be aggregated together. Or it may be the order that the matching engine can match at one time.

Continuing from the previous three articles on programmatic trading real code:

Hard-core dry goods - details and thoughts on automated real-time trading of quantitative trading systems (1. Problems and difficulties)

Quantitative Trading System - Automated Firm Offer Details and Thoughts (2. Firm Offer Purpose)

Quantitative Trading System - Automated Real Offer Details and Thoughts (3. Processing Skills)

Here we will continue to talk about the multi-strategy trading system and the market center in the overall structure of the real offer code.

Preface

In the trading industry, especially futures contracts, several high-leverage trading masters will appear every once in a while, and the principal of 100,000 yuan can easily turn into tens of millions. However, almost all of these people were like meteors streaking across the night sky. After a brief dazzling moment, they disappeared silently.

Continuing from the previous two articles on matters needing attention in programmatic trading:

Hard-core dry goods - details and thoughts on automated real-time trading of quantitative trading systems (1. Problems and difficulties)

Quantitative Trading System - Automated Firm Offer Details and Thoughts (2. Firm Offer Purpose)

Here we will continue to talk about some detailed handling skills in code design.

database

As mentioned in the previous two articles, the status record of a more complex strategy combination is very important and requires the use of a database.

In fact, most programming businesses can be classified into the CRUD category, that is, the core process is just adding, deleting, modifying and checking the database. Trading codes are no exception. Medium and low-frequency secondary market trading behavior is actually not much different from when people go shopping on a certain treasure. They are both buying and selling. The focus of automated trading lies in the management of strategic status.

The previous article, Hard-Core Information - Details and Thoughts on Automated Real Offering of Quantitative Trading System (I. Problems and Difficulties), talked about some basic problems of real trading in the currency circle. This article talks about the main purpose of the firm offer.

I think there are four main ones:

1. Implement the established logic of the strategy

There is no doubt about this. When there is a signal, corresponding operations must be made, opening and closing positions. This point requires that you try not to use limit orders. Otherwise, if the transaction cannot be completed, you will have to pursue the order. The price may have already gone too far. In the end, whether to pursue the order is also a question.

In the long run, the slippage caused by using market orders is roughly similar to the slippage caused by occasionally missing limit orders but chasing orders, so it is better to enter and exit the market directly, unless your strategy is very special.

What we are mainly talking about here is the implementation of programmed real-time code for medium and low-frequency trading strategies.

Strategy

The birth of a quantitative trading strategy is generally based on observing and understanding the market, generating a strategy idea, then designing the specific details of the strategy, and then back-testing multiple varieties of data to obtain and verify the effect of specific parameter values. If the effect is good and has universal applicability, then the next step is to test the real market with small funds. If the out-of-sample real offer is feasible, you can eventually increase funds and run it for a long time.

In order to prevent leverage, let me explain that of course there are other methods to generate strategies, such as data mining, digging, digging, digging factors. There are also automatic generation factors such as machine learning and reinforcement learning. However, this kind of black box method is difficult to keep running during the strategy retracement period, because you don’t know when and why these dug-up factors failed. When doing quantitative trading, the most important thing is to insist on firm trading. If the market is not good, you can shrink your position, but you cannot shut down. No one can know when the big market will break out. If you miss it, your previous retracement will be in vain.

This article mainly discusses the quantitative trading system. For subjective trading, because the market feeling and shape are difficult to quantify, it is also difficult to systematize and automate, so it is not included in the discussion.

What is a system

Trading systems, like transportation systems, engineering systems, and legal systems in reality, help us live better in an uncertain world by establishing a series of rules. The trading system accompanies you in various secondary markets and is your most important talisman for survival. It protects your position and allows it to continuously shuttle through the exchange's matching engine, and ultimately the capital curve fluctuates upward.