虚拟货币(BTC、ETH)炒币量化系统项目。在一版本的基础上加入了趋势判断

Overview

🎉 第二版本 🎉 (现货趋势网格)


介绍

在第一版本的基础上

趋势判断,不在固定点位开单,选择更优的开仓点位

优势: 🎉

  1. 简单易上手
  2. 安全(不用将api_secret告诉他人)

如何启动

  1. 修改app目录下的authorization文件
api_key='你的key'
api_secret='你的secret'

dingding_token = '申请钉钉群助手的token'   # 强烈建议您使用 (若不会申请,请加我个人微信)

如果你还没有币安账号: 注册页面交易返佣40%(系统返佣20%,id私发给我,微信每周返佣20%,长期有效)

免翻墙地址

申请api_key地址: 币安API管理页面

  1. 修改data/data.json配置文件 根据
{
    "runBet": {
        "next_buy_price": 350,      <- 下次开仓价   (你下一仓位买入价)
      
        "grid_sell_price": 375      <- 当前止盈价  (你的当前仓位卖出价)
        "step":0                    <- 当前仓位  (0:仓位为空)
    },
    "config": {
        "profit_ratio": 5,         <- 止盈比率      (卖出价调整比率。如:设置为5,当前买入价为100,那么下次卖出价为105)
        "double_throw_ratio": 5,   <- 补仓比率      (买入价调整比率。如:设置为5,当前买入价为100,那么下次买入价为95)
        "cointype": "ETHUSDT",     <- 交易对        (你要进行交易的交易对,请参考币安现货。如:BTC 填入 BTC/USDT)
        "quantity": [1,2,3]        <- 交易数量       (第一手买入1,第二手买入2...超过第三手以后的仓位均按照最后一位数量(3)买入)
        
    }
}

  1. 安装依赖包 ''' pip install requests json '''
  2. 运行主文件
# python eth-run.py 这是带有钉钉通知的主文件(推荐使用钉钉模式启动👍)

注意事项(一定要看)

  • 由于交易所的api在大陆无法访问(如果没有条件,可以使用api.binance.cc)
    • 您需要选择修改binanceAPI.py文件
# 修改为cc域名
class BinanceAPI(object):
    BASE_URL = "https://www.binance.cc/api/v1"
    FUTURE_URL = "https://fapi.binance.cc"
    BASE_URL_V3 = "https://api.binance.cc/api/v3"
    PUBLIC_URL = "https://www.binance.cc/exchange/public/product"
  • 如果您使用的交易所为币安,那么请保证账户里有足够的bnb

    • 手续费足够低
    • 确保购买的币种完整(如果没有bnb,比如购买1个eth,其中你只会得到0.999。其中0.001作为手续费支付了)
  • 第一版本现货账户保证有足够的U

  • 由于补仓比率是动态的,目前默认最小为5%。如果您认为过大,建议您修改文件夹data下的RunbetData.py文件

    def set_ratio(self,symbol):
        '''修改补仓止盈比率'''
        data_json = self._get_json_data()
        ratio_24hr = binan.get_ticker_24hour(symbol) #
        index = abs(ratio_24hr)

        if abs(ratio_24hr) >  **6** : # 今日24小时波动比率
            if ratio_24hr > 0 : # 单边上涨,补仓比率不变
                data_json['config']['profit_ratio'] =  **7** + self.get_step()/4  #
                data_json['config']['double_throw_ratio'] = **5**
            else: # 单边下跌
                data_json['config']['double_throw_ratio'] =  **7** + self.get_step()/4
                data_json['config']['profit_ratio'] =  **5**

        else: # 系数内震荡行情

            data_json['config']['double_throw_ratio'] = **5** + self.get_step() / 4
            data_json['config']['profit_ratio'] = **5** + self.get_step() / 4
        self._modify_json_data(data_json)

钉钉预警

如果您想使用钉钉通知,那么你需要创建一个钉钉群,然后加入自定义机器人。最后将机器人的token粘贴到authorization文件中的dingding_token 关键词输入:报警

钉钉通知交易截图

钉钉交易信息

25日实战收益

收益图

私人微信:欢迎志同道合的朋友一同探讨,一起进步。

交流群 wechat-QRcode 币圈快讯爬取群 wx号:findpanpan 麻烦备注来自github

钉钉设置教程

钉钉设置教程

免责申明

本项目不构成投资建议,投资者应独立决策并自行承担风险 币圈有风险,入圈须谨慎。

?? 风险提示:防范以“虚拟货币”“区块链”名义进行非法集资的风险。

Owner
幸福村的码农
努力中...
幸福村的码农
Price forecasting of SGB and IRFC Bonds and comparing there returns

Project_Bonds Project Title : Price forecasting of SGB and IRFC Bonds and comparing there returns. Introduction of the Project The 2008-09 global fina

Tishya S 1 Oct 28, 2021
Python package for concise, transparent, and accurate predictive modeling

Python package for concise, transparent, and accurate predictive modeling. All sklearn-compatible and easy to use. 📚 docs • 📖 demo notebooks Modern

Chandan Singh 983 Jan 01, 2023
Implementation of K-Nearest Neighbors Algorithm Using PySpark

KNN With Spark Implementation of KNN using PySpark. The KNN was used on two separate datasets (https://archive.ics.uci.edu/ml/datasets/iris and https:

Zachary Petroff 4 Dec 30, 2022
Data Efficient Decision Making

Data Efficient Decision Making

Microsoft 197 Jan 06, 2023
Lightweight Machine Learning Experiment Logging 📖

Simple logging of statistics, model checkpoints, plots and other objects for your Machine Learning Experiments (MLE). Furthermore, the MLELogger comes with smooth multi-seed result aggregation and co

Robert Lange 65 Dec 08, 2022
Pandas Machine Learning and Quant Finance Library Collection

Pandas Machine Learning and Quant Finance Library Collection

148 Dec 07, 2022
Model search (MS) is a framework that implements AutoML algorithms for model architecture search at scale.

Model Search Model search (MS) is a framework that implements AutoML algorithms for model architecture search at scale. It aims to help researchers sp

AriesTriputranto 1 Dec 13, 2021
Bayesian optimization in JAX

Bayesian optimization in JAX

Predictive Intelligence Lab 26 May 11, 2022
A pure-python implementation of the UpSet suite of visualisation methods by Lex, Gehlenborg et al.

pyUpSet A pure-python implementation of the UpSet suite of visualisation methods by Lex, Gehlenborg et al. Contents Purpose How to install How it work

288 Jan 04, 2023
Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.

Horovod Horovod is a distributed deep learning training framework for TensorFlow, Keras, PyTorch, and Apache MXNet. The goal of Horovod is to make dis

Horovod 12.9k Jan 07, 2023
Retrieve annotated intron sequences and classify them as minor (U12-type) or major (U2-type)

(intron I nterrogator and C lassifier) intronIC is a program that can be used to classify intron sequences as minor (U12-type) or major (U2-type), usi

Graham Larue 4 Jul 26, 2022
Bayesian Additive Regression Trees For Python

BartPy Introduction BartPy is a pure python implementation of the Bayesian additive regressions trees model of Chipman et al [1]. Reasons to use BART

187 Dec 16, 2022
A quick reference guide to the most commonly used patterns and functions in PySpark SQL

Using PySpark we can process data from Hadoop HDFS, AWS S3, and many file systems. PySpark also is used to process real-time data using Streaming and

Sundar Ramamurthy 53 Dec 21, 2022
🌊 River is a Python library for online machine learning.

River is a Python library for online machine learning. It is the result of a merger between creme and scikit-multiflow. River's ambition is to be the go-to library for doing machine learning on strea

OnlineML 4k Jan 03, 2023
This project used bitcoin, S&P500, and gold to construct an investment portfolio that aimed to minimize risk by minimizing variance.

minvar_invest_portfolio This project used bitcoin, S&P500, and gold to construct an investment portfolio that aimed to minimize risk by minimizing var

1 Jan 06, 2022
A comprehensive repository containing 30+ notebooks on learning machine learning!

A comprehensive repository containing 30+ notebooks on learning machine learning!

Jean de Dieu Nyandwi 3.8k Jan 09, 2023
inding a method to objectively quantify skill versus chance in games, using reinforcement learning

Skill-vs-chance-games-analysis - Finding a method to objectively quantify skill versus chance in games, using reinforcement learning

Marcus Chiam 4 Nov 19, 2022
A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.

pmdarima Pmdarima (originally pyramid-arima, for the anagram of 'py' + 'arima') is a statistical library designed to fill the void in Python's time se

alkaline-ml 1.3k Jan 06, 2023
Auto updating website that tracks closed & open issues/PRs on scikit-learn/scikit-learn.

Repository Status for Scikit-learn Live webpage Auto updating website that tracks closed & open issues/PRs on scikit-learn/scikit-learn. Running local

Thomas J. Fan 6 Dec 27, 2022
mlpack: a scalable C++ machine learning library --

a fast, flexible machine learning library Home | Documentation | Doxygen | Community | Help | IRC Chat Download: current stable version (3.4.2) mlpack

mlpack 4.2k Jan 01, 2023