关于量化系统开发逻辑讲解及合约量化策略系统开发技术方案（详细分析）

关于量化、怎么解释跟开发逻辑是怎样？今天刘毅为你们讲解下，

一、开发一套量化V+系（StPv888）统应该具备什么要素呢？

应该具备如下要素：

1，大数据

2，算法模型

3，入场择时

4，仓位管理

5，风险控制

6，检验策略，策略的历史数据回测等数据进行检验
　　

二、一些比较常见的量化买卖是什么呢？

Features of Quantitative Trading Robot:

1.The most obvious feature of quantitative trading is to reduce the impact of investor sentiment fluctuations and avoid making irrational investment decisions in the case of extreme market fanaticism or pessimism,while quantitative trading robots avoid subjective assumptions and use programs to turn their ideas into quantifiable strategies,using only computing strategies and trading strategies through computers;

2.History back test,realized by computer program,can verify the rationality of trading strategy by quantifying trading ideas;

3.It can ensure the execution of transactions/profits,especially the quantitative analysis of medium and low frequency,without the need to mark the market

跟单这块具体有哪些功能呢?
　　

1.交易员：This is the core.The platform can accommodate traders and provide a recommendation mechanism for traders.The users he invites are divided into more.

2.推荐制度：The recommendation system joining platform can be designed according to the specific situation of the project.

3.交易所选择：Multiple exchanges can be connected through the API system,allowing users to choose traders or platforms to follow orders independently;Of course,if the project has a plan to build an exchange to master the resources,it is also possible.

4.其他功能：You can add many such as market list,registration parameter setting,dividend mechanism,and other games and social networking.

区块链是承载Web3.0应用组织演化和利益分配的核心载体，对于Web3.0应用是不可或缺的部分，Web3.0需要区块链。

区块链是一个去中心化计算协议，约定了不同的利益主体如何分散的创建和维护一个分布式的计算基础设施，从而实现“基础设施管理权”与“用户数据控制权”之间的分离，防止单一平台通过计算基础设施管理权力，实现对用户数据、用户资产和用户身份的控制。区块链还是一个透明可信的权利确认与追溯系统，一份权利一旦数字化为区块链上的通证，可以得到可靠的确权，并且可全程追踪其流转、交易、转换、变形的全过程。区块链是协议创造和自动执行平台。智能合约是这一能力的集中体现。通过智能合约，权利与价值的分配协议可以无需借助可信第三方，即得到高效、准确、可信的执行，并且全过程可审计。

for i in range(int(time_len)24):#由于返回的是小时制，所以总数据等于天数24

time_stamp=coin_data[‘prices’][0]/1000#返回的是毫秒级时间戳所以除以1000转换成秒级进行处理

time_local=time.localtime(time_stamp)#转换成本地时间

dt=time.strftime(“%Y-%m-%d%H:%M:%S”,time_local)#进行数据的转换方便观察

coin_time.append(dt)#存入时间队列

coin_price.append(coin_data[‘prices’][1])#存入价格队列

plt.plot(coin_time,coin_price,linewidth=2)#图标绘制，第一个参数是x轴，第二个参数是y轴

plt.title(id+‘’+time_len+‘days table’,fontsize=14)

plt.xlabel(“time”,fontsize=14)

plt.ylabel(“usd”,fontsize=14)

plt.show()