<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[QuantHero的博客]]></title><description><![CDATA[From quant to Hero]]></description><link>https://blog.youkuaiyun.com/guosuming</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; guosuming]]></copyright><item><title><![CDATA[美股历史行情数据之日频率数据]]></title><link>https://blog.youkuaiyun.com/guosuming/article/details/126516192</link><guid>https://blog.youkuaiyun.com/guosuming/article/details/126516192</guid><author>guosuming</author><pubDate>Thu, 25 Aug 2022 04:51:30 +0800</pubDate><description><![CDATA[美股数据仓库，美股全部日行情数据]]></description><category></category></item><item><title><![CDATA[arctic databas 实例]]></title><link>https://blog.youkuaiyun.com/guosuming/article/details/125612127</link><guid>https://blog.youkuaiyun.com/guosuming/article/details/125612127</guid><author>guosuming</author><pubDate>Tue, 05 Jul 2022 08:28:54 +0800</pubDate><description><![CDATA[数据库金融分析]]></description><category></category></item><item><title><![CDATA[dolphindb量化实例]]></title><link>https://blog.youkuaiyun.com/guosuming/article/details/125612033</link><guid>https://blog.youkuaiyun.com/guosuming/article/details/125612033</guid><author>guosuming</author><pubDate>Tue, 05 Jul 2022 07:53:09 +0800</pubDate><description><![CDATA[时序数据库量化实战]]></description><category></category></item><item><title><![CDATA[Python 量化交易系列教程2]]></title><link>https://blog.youkuaiyun.com/guosuming/article/details/125419860</link><guid>https://blog.youkuaiyun.com/guosuming/article/details/125419860</guid><author>guosuming</author><pubDate>Thu, 23 Jun 2022 08:15:01 +0800</pubDate><description><![CDATA[python基础练习]]></description><category></category></item><item><title><![CDATA[Python 量化交易系列教程]]></title><link>https://blog.youkuaiyun.com/guosuming/article/details/125419788</link><guid>https://blog.youkuaiyun.com/guosuming/article/details/125419788</guid><author>guosuming</author><pubDate>Thu, 23 Jun 2022 07:58:25 +0800</pubDate><description><![CDATA[python量化交易系列教程]]></description><category></category></item><item><title><![CDATA[Scikit Learn(sklearn) 入门]]></title><link>https://blog.youkuaiyun.com/guosuming/article/details/108302275</link><guid>https://blog.youkuaiyun.com/guosuming/article/details/108302275</guid><author>guosuming</author><pubDate>Sun, 30 Aug 2020 05:13:36 +0800</pubDate><description><![CDATA[按照如下步骤来按照scikit-learn 包到你的python IDE中

]]></description><category></category></item><item><title><![CDATA[量化回测框架-backtrader-强化学习-chainerrl]]></title><link>https://blog.youkuaiyun.com/guosuming/article/details/108302225</link><guid>https://blog.youkuaiyun.com/guosuming/article/details/108302225</guid><author>guosuming</author><pubDate>Sun, 30 Aug 2020 02:18:53 +0800</pubDate><description><![CDATA[安装框架-backtrader, chainerrl

pip install -U backtrader
pip install -U chainerrl


导入强化学习包和相关依赖
以下代码运行在jupter notebook, 在云端azure notebook运行

import chainer
import chainerrl
# Strategy

from datetime import datetime
import backtrader
import random

# Integra.]]></description><category></category></item><item><title><![CDATA[量化回测框架-backtrader-交易框架]]></title><link>https://blog.youkuaiyun.com/guosuming/article/details/108302193</link><guid>https://blog.youkuaiyun.com/guosuming/article/details/108302193</guid><author>guosuming</author><pubDate>Sun, 30 Aug 2020 01:55:08 +0800</pubDate><description><![CDATA[以下以SMA策略为例子来说明Backtrader-BT交易框架
from datetime import datetime
import backtrader
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import warnings
warnings.filterwarnings('ignore')

def Function_For_Build_SmaCross_Strategy_Object(short]]></description><category></category></item><item><title><![CDATA[量化回测框架-backtrader-KD策略]]></title><link>https://blog.youkuaiyun.com/guosuming/article/details/108302181</link><guid>https://blog.youkuaiyun.com/guosuming/article/details/108302181</guid><author>guosuming</author><pubDate>Sun, 30 Aug 2020 01:49:35 +0800</pubDate><description><![CDATA[from datetime import datetime
import backtrader
import pandas

def Function_For_Build_KD_Object(KD_Period):
    
    
    class Strategy_KD_Object(backtrader.Strategy):
        
        def __init__(self):
    
            self.data_open = self.datas[0].op]]></description><category></category></item><item><title><![CDATA[经典策略回测系列之Elder Impulse System]]></title><link>https://blog.youkuaiyun.com/guosuming/article/details/107455438</link><guid>https://blog.youkuaiyun.com/guosuming/article/details/107455438</guid><author>guosuming</author><pubDate>Mon, 20 Jul 2020 06:44:18 +0800</pubDate><description><![CDATA[Alexander Elder- come into my trading room
The Impulse System is based on two indicators, a 13-day exponential moving average and the MACD-Histogram. The moving average identifies the trend, while the MACD-Histogram measures momentum. As a result, the Impu]]></description><category></category></item><item><title><![CDATA[技术分析-趋势的基本原理]]></title><link>https://blog.youkuaiyun.com/guosuming/article/details/107455340</link><guid>https://blog.youkuaiyun.com/guosuming/article/details/107455340</guid><author>guosuming</author><pubDate>Mon, 20 Jul 2020 03:11:08 +0800</pubDate><description><![CDATA[技术分析-趋势的基本原理学习目标说明定义什么是趋势解释趋势确认在技术分析的重要性识别主要，次要，短期和日内趋势隐藏在技术分析的艺术背后的那些事技术分析是基于一个基本假设：市场价格通常在趋势运行中自由交易技术分析如何获利什么是趋势趋势如何识别出来趋势如何在供需关系中演变趋势包括哪些内容技术分析还包括什么假设结论
学习目标说明
定义什么是趋势
解释趋势确认在技术分析的重要性
识别主要，次要，短期和日内趋势
隐藏在技术分析的艺术背后的那些事
技术分析的艺术，对于艺术来说，是指如何在早期确认趋势变化并且一直持有头寸]]></description><category></category></item><item><title><![CDATA[Linux 系统目录解说]]></title><link>https://blog.youkuaiyun.com/guosuming/article/details/107455277</link><guid>https://blog.youkuaiyun.com/guosuming/article/details/107455277</guid><author>guosuming</author><pubDate>Mon, 20 Jul 2020 01:57:03 +0800</pubDate><description><![CDATA[登录系统后，在当前命令窗口下输入命令：



以下是对这些目录的解释：


	/bin：
	bin是Binary的缩写, 这个目录存放着最经常使用的命令。
	
	
	/boot：
	这里存放的是启动Linux时使用的一些核心文件，包括一些连接文件以及镜像文件。
	
	
	/dev ：
	dev是Device(设备)的缩写, 该目录下存放的是Linux的外部设备，在Linux中访问设备的方式和访问文件的方式是相同的。
	
	
	/etc：
	这个目录用来存放所有的系统管理所需要的配置文件和子目录。
	
	
.]]></description><category></category></item><item><title><![CDATA[获取金融历史数据-IQfeed]]></title><link>https://blog.youkuaiyun.com/guosuming/article/details/107308943</link><guid>https://blog.youkuaiyun.com/guosuming/article/details/107308943</guid><author>guosuming</author><pubDate>Mon, 13 Jul 2020 01:36:42 +0800</pubDate><description><![CDATA[自1984以来，DTN IQ Feed提供流数据集标准 精确覆盖农业、能源和金融市场的服务和贸易解决方案。DTN IQ Feed在高端分析软件、流式报价服务和定制的Web内容，在交付数据源方面是一个被证实的行业领导者。DTN IQ Feed 对股票、期权、期货、大宗商品和固定收益证券、实时新闻线、历史数据和更多的时间敏感报价.
下面的代码实现了如何获取IQ feed支持品种的历史数据，不过前期是已经订阅IQ feed数据服务并且启动终端。
from iqfeed import historicData
im]]></description><category></category></item><item><title><![CDATA[如何成立海外量化对冲基金]]></title><link>https://blog.youkuaiyun.com/guosuming/article/details/107298592</link><guid>https://blog.youkuaiyun.com/guosuming/article/details/107298592</guid><author>guosuming</author><pubDate>Sun, 12 Jul 2020 13:50:34 +0800</pubDate><description><![CDATA[Generally in order to start a new quantitative hedge fund it will be expected that the manager will have had significant industry experience in other funds or asset managers in order to develop the necessary skills and network required.
The primary issue w]]></description><category></category></item><item><title><![CDATA[用matlab的交易员]]></title><link>https://blog.youkuaiyun.com/guosuming/article/details/106955738</link><guid>https://blog.youkuaiyun.com/guosuming/article/details/106955738</guid><author>guosuming</author><pubDate>Thu, 25 Jun 2020 10:49:47 +0800</pubDate><description><![CDATA[Matlab - 数据准备
1. 用tushare数据源
先上代码：
% 演示如何利用tushare 下载中国金融数据
% 获取股票列表的示例
token = 'pro token, 需要的话私信我';
api = pro_api(token);
%df_basic = api.query('stock_basic');
%disp(df_basic(1:10,:));

%获取日线行情数据的示例
df_daily = api.query('daily', 'ts_code', '000001.SZ', ']]></description><category></category></item><item><title><![CDATA[Ninjatrader (NT) 软件介绍]]></title><link>https://blog.youkuaiyun.com/guosuming/article/details/106954307</link><guid>https://blog.youkuaiyun.com/guosuming/article/details/106954307</guid><author>guosuming</author><pubDate>Thu, 25 Jun 2020 07:40:04 +0800</pubDate><description><![CDATA[Ninjatrader是一款国外很受欢迎的量化自动交易软件,能够交易外盘期货/股票/外汇，并内置了功能强大的回测，优化引擎。下图是交易外汇fx的界面
我用的实时数据源是IQfeed。据我所知，目前NT8中国版只支持回测版本，但是接口没有解决，所以不能交易内盘期货和股票。

以下将开系列说明这个软件功能和使用

...]]></description><category></category></item><item><title><![CDATA[Backtrader 量化平台研究]]></title><link>https://blog.youkuaiyun.com/guosuming/article/details/106954125</link><guid>https://blog.youkuaiyun.com/guosuming/article/details/106954125</guid><author>guosuming</author><pubDate>Thu, 25 Jun 2020 03:44:25 +0800</pubDate><description><![CDATA[Backtrader 中国期货回测
Backtrader 简介
先说几句题外话，Backtrader 到底谁在用？一下内容转自backtrader官方网站中References部分：https://www.backtrader.com/home/references/who-is-using-it/
Who is using it
我简单说几点：

2家 Eurostoxx50 银行
6家量化私募
不过这些都是很早以前的数据，还有一些做能源交易的对冲基金。
reddit里面有个algo trading 板块]]></description><category></category></item><item><title><![CDATA[vnpy实盘自动交易]]></title><link>https://blog.youkuaiyun.com/guosuming/article/details/106953978</link><guid>https://blog.youkuaiyun.com/guosuming/article/details/106953978</guid><author>guosuming</author><pubDate>Thu, 25 Jun 2020 01:23:20 +0800</pubDate><description><![CDATA[VNPY 实盘系列教程1教程1分享用vnpy交易Binance BTCUSDT future环境搭建
教程1分享用vnpy交易Binance BTCUSDT future
环境搭建
初始环境(下载vnstation)搭建我就分享了，网络上有很多教程，vnpy社区也有很多大家遇到的坑，可以直接搜索找答案
本人用的是直接下载GitHub包，没有安装傻瓜版的程序。所以之后分享图片和文件路径不一样。这里说明一下
本机已经有Ancona3，在GitHub下载最新版，记住要下最新版(2.1.4)
https://git]]></description><category></category></item><item><title><![CDATA[Algorithm trading]]></title><link>https://blog.youkuaiyun.com/guosuming/article/details/106755324</link><guid>https://blog.youkuaiyun.com/guosuming/article/details/106755324</guid><author>guosuming</author><pubDate>Mon, 15 Jun 2020 05:22:40 +0800</pubDate><description><![CDATA[Backtrader: Multiple Data Feeds &amp; Indicators
Backtrader: Multiple Data Feeds &amp; Indicators&nbsp;
Multi Example
import backtrader as bt
from datetime import datetime
class BOLLStrat(bt.Strategy):
‘’’
&nbsp;&nbsp;&nbsp; This is a simple mean reversion]]></description><category></category></item></channel></rss>