有些国外的平台、社区、博客如果连接无法打开，那说明可能需要“科学”上网
量化交易平台
国内在线量化平台：
BigQuant - 你的人工智能量化平台 - 可以无门槛地使用机器学习、人工智能开发量化策略，基于python，提供策略自动生成器
镭矿 - 基于量化回测平台果仁网 - 回测量化平台
京东量化 - 算法交易和量化回测平台
聚宽 - 量化回测平台
优矿 - 通联量化实验室
Ricequant - 量化交易平台
况客 - 基于R语言量化回测平台
Factors - 数库多因子量化平台
国外量化平台：
Quantopian 研究、回测、算法众包平台
QuantConnect 研究，回测和投资交易
Quantstart 研究，回测和投资交易
ASC 研究、交易平台
zulutrade 自动交易平台
quantpedia 研究、策略平台
algotrading101 策略研究平台
investopedia 可以股票、外汇模拟交易的财经网站
Amibroker 提供系统交易工具的一家公司
AlgoTrades 股票、ETF、期货自动交易系统
Numerai 数据工程师众包的一家对冲基金
WealthFront 财富管理平台
Betterment 个人投资平台
TradeLink 量化交易平台
ActiveQuant 基于JavaScript开源交易开发框架
相关平台：
掘金量化 - 支持C/C++、C#、MATLAB、Python和R的量化交易平台
DigQuant - 提供基于matlab量化工具
SmartQuant - 策略交易平台
OpenQuant - 基于C#的开源量化回测平台
基于图表的量化交易平台
文华赢智 、TB、金字塔、MultiCharts 中国版 - 程序化交易软件、MT4、TradeStationAuto-Trader - 基于MATLAB的量化交易平台BotVS - 首家支持传统期货与股票证券与数字货币的量化平台
开源框架
Pandas - 数据分析包
Zipline - 一个Python的回测框架
vnpy - 基于python的开源交易平台开发框架
tushare - 财经数据接口包
easytrader - 进行自动的程序化股票交易
pyalgotrade - 一个Python的事件驱动回测框架
pyalgotrade-cn - Pyalgotrade-cn在原版pyalgotrade的基础上加入了A股历史行情回测，并整合了tushare提供实时行情。
zwPython - 基于winpython的集成式python开发平台
quantmod - 量化金融建模
rqalpha - 基于Python的回测引擎
quantdigger - 基于python的量化回测框架
pyktrader - 基于pyctp接口，并采用vnpy的eventEngine，使用tkinter作为GUI的python交易平台
QuantConnect/Lean - Lean Algorithmic Trading Engine by QuantConnect (C#, Python, F#, VB, Java)
QUANTAXIS - 量化金融策略框架
其他量化交易平台：
Progress Apama、龙软DTS、国泰安量化投资平台、飞创STP、易盛程序化交易、盛立SPT平台、天软量化回测平台 、量邦天语、EQB-Quant
数据源
TuShare - 中文财经数据接口包
Quandl - 国际金融和经济数据
Wind资讯-经济数据库 - 收费
东方财富 Choice金融数据研究终端 - 收费
iFinD 同花顺金融数据终端 - 收费
朝阳永续 Go-Goal数据终端 - 收费
天软数据 - 收费
国泰安数据服务中心 - 收费
锐思数据 - 收费
恒生API - 收费
Bloomberg API - 收费
数库金融数据和深度分析API服务 - 收费
Historical Data Sources - 一个数据源索引
预测者网 - 收费
巨潮资讯 - 收费
通联数据商城 - 收费
通达信 - 免费
历史数据 - 文档 | BigQuant - 免费
新浪、雅虎、东方财富网 - 免费
聚合数据、数粮 、数据宝 - 收费
数据库
manahl/arctic: High performance datastore for time series and tick data - 基于mongodb和python的高性能时间序列和tick数据存储
kdb | The Leader in High-Performance Tick Database Technology | Kx Systems - 收费的高性能金融序列数据库解决方案
MongoDB Blog - 用mongodb存储时间序列数据
InfluxDB – Time-Series Data Storage | InfluxData - Go写的分布式时间序列数据库
OpenTSDB/opentsdb: A scalable, distributed Time Series Database. - 基于HBase的时间序列数据库
kairosdb/kairosdb: Fast scalable time series database - 基于Cassandra的时间序列数据库
SQLite Home Page
网站、论坛、社区、博客
国外：
AQR - Alternative Investments
FOSS Trading
wilmott.com - Forum
Traders Magazine: The stock dealers and institutional traders complete interactive news and information service
http://practicalquant.blogspot.jp/?view=classic
http://www.thewholestreet.com/
Implementing QuantLib
http://tradingwithpython.blogspot.jp/
Coding the markets
Quantivity
Quant Mashup | Quantocracy
On a long enough timeline the survival rate for everyone drops to zero
Keplerian Finance - exploring the boundaries of quantitative finance
The Journal of Trading: Home
All things finance and technology…
Quant News
Quantitative Trading Strategies | Numerical Method Inc.
Nuclear Phynance
Elite Trader
Meb Faber Research - Stock Market and Investing Blog
Portfolio Workstation by Alpha Level
http://falkenblog.blogspot.jp/
Quantitative Finance Stack Exchange
The mathematics of investing and markets ? r/quantfinance
QuantNet Community
QUANTITATIVE RESEARCH AND TRADING - The latest theories, models and investment strategies in quantitative research and trading
QUSMA - Quantitative Systematic Market Analysis
CSSA
http://www.tradingtheodds.com/
Quantitative Trading, Statistical Arbitrage, Machine Learning and Binary Options
Collective2 - The platform that connects investors with top-traders
Alvarez Quant Trading
The Marketplace For Algorithmic Trading Systems | Quantiacs
Quantitative Finance
Quantopian Lectures
Kitces.com - Advancing Knowledge in Financial Planning
Forex Factory
The R Trader
How to be a Quant
关于交易策略的机器学习
scikit-learn: machine learning in PythonPaul WilmottThe Trend is your FriendPractical QuantJohn Mauldin’s Outside the BoxQuantum FinancierQuantified StrategiesBlackRock BlogQuant at Risk
国内：
BigQuant量化社区
算法组_新浪微博海洋部落
水木社区
（经管之家）人大经济论坛
清华大学学生经济金融论坛
matlab技术论坛
微量网
Code4Quant
量化交易 - 热门问答 - 知乎
集思录 - 低风险投资 - 集思录
雪球 - 聪明的投资者都在这里
myquant/strategy: 掘金策略集锦
botvs/strategies - 用Javascript or Python进行量化交易
芝诺量化交易,程序化交易
统计之都 (Capital of Statistics)
中国量化投资学会
宽客 (Quant) - 索引 - 知乎
faruto的博客
博文bicloud新浪博客
博文郑来轶新浪博客flitter_新浪博客
david自由之路
作者安道全_新浪博客
债券的大拿没钱又丑
期货用来复盘的blog
花荣_新浪博客
股海泛舟 - 股海范舟
带头大哥777的博客
交易API
上海期货信息技术有限公司CTP API - 期货交易所提供的API飞马快速交易平台 - 上海金融期货信息技术有限公司 - 飞马大连飞创信息技术有限公司 - 飞创vnpy - 基于python的开源交易平台开发框架QuantBox/XAPI2 - 统一行情交易接口第2版easytrader - 提供券商华泰/佣金宝/银河/广发/雪球的基金、股票自动程序化交易，量化交易组件IB API | Interactive Brokers - 盈透证券的交易API
编程
Python
安装
Anaconda - 推荐通过清华大学镜像 下载安装
Pycharm download
Python Extension Packages for Windows - Christoph Gohlke - Windows用户从这里可以下载许多python库的预编译包
教程
Python | Codecademy
用 Python 玩转数据 - 南京大学 | Coursera
Google 开源项目风格指南 (中文版)
廖雪峰python教程
Introduction to Data Science in Python - University of Michigan | Coursera
The Python Tutorial
Python for Finance
Algorithmic Thinking - Python 算法思维训练
Python Cookbook 3rd Edition Documentation
库
Python Extension Packages for Windows
awesome-python: A curated list of awesome Python frameworks, libraries, software and resources
pandas - Python做数据分析的基础
pyql: Cython QuantLib wrappers
ffn - 绩效评估
ta-lib: Python wrapper for TA-Lib (http://ta-lib.org/). - 技术指标
StatsModels: Statistics in Python — statsmodels documentation - 常用统计模型
arch: ARCH models in Python - 时间序列
pyfolio: Portfolio and risk analytics in Python - 组合风险评估
twosigma/flint: A Time Series Library for Apache Spark - Apache Spark上的时间序列库
R
安装
The Comprehensive R Archive Network - 从国内清华镜像下载安装RStudio - R的常用开发平台下载
教程
Free Introduction to R Programming Online Course - datacamp的在线学习R Programming - 约翰霍普金斯大学 | CourseraIntro to Computational Finance with R - 用R进行计算金融分析
库
CRAN Task View: Empirical Finance - CRAN官方的R金融相关包整理qinwf/awesome-R: A curated list of awesome R packages, frameworks and software. - R包的awesome
C++
教程
C++程序设计 - 北京大学 郭炜基于Linux的C++ - 清华大学 乔林面向对象程序设计（C++） - 清华大学 徐明星C++ Design Patterns and Derivatives Pricing - C++设计模式C++ reference - cppreference.com - 在线文档
库
fffaraz/awesome-cpp: A curated list of awesome C/C++ frameworks, libraries, resources, and shiny things. - C++库整理rigtorp/awesome-modern-cpp: A collection of resources on modern C++ - 现代C++库整理QuantLib: a free/open-source library for quantitative financelibtrading/libtrading: Libtrading, an ultra low-latency trading connectivity library for C and C++.
Julia
教程
Learning Julia - 官方整理QUANTITATIVE ECONOMICS with Julia - 经济学诺奖获得者Thomas Sargent教你Julia在量化经济的应用。
库
Quantitative Finance in Julia - 多数为正在实现中，感兴趣的可以参与
编程论坛
Stack OverflowSegmentFaultQuora
Github知乎 - 与世界分享你的知识、经验和见解
编程能力在线训练
Solve Programming Questions | HackerRank - 包含常用语言(C++, Java, Python, Ruby, SQL)和相关计算机应用技术(算法、数据结构、数学、AI、Linux Shell、分布式系统、正则表达式、安全)的教程和挑战。LeetCode Online Judge - C, C++, Java, Python, C#, JavaScript, Ruby, Bash, MySQL在线编程训练
Quant Books
《投资学》第6版[美]兹维·博迪.文字版 (link)
《打开量化投资的黑箱》 里什·纳兰《宽客》[美] 斯科特·帕特森（Scott Patterson） 著；译科，卢开济 译《解读量化投资：西蒙斯用公式打败市场的故事》 忻海
《Trends in Quantitative Finance》 Frank J. Fabozzi, Sergio M. Focardi, Petter N. Kolm
《漫步华尔街》麦基尔
《海龟交易法则》柯蒂斯·费思
《交易策略评估与最佳化》罗伯特·帕多
《统计套利》 安德鲁·波尔《信号与噪声》纳特?西尔弗
《期货截拳道》朱淋靖
《量化投资—策略与技术》 丁鹏
《量化投资—以matlab为工具》 李洋faruto《量化投资策略:如何实现超额收益Alpha》 吴冲锋
《中低频量化交易策略研发（上）》 杨博理
《走出幻觉走向成熟》 金融帝国
《失控》凯文·凯利 《通往财务自由之路》范K撒普
《以交易为生》 埃尔德
《超越技术分析》图莎尔·钱德
《高级技术分析》布鲁斯·巴布科克
《积极型投资组合管理》格里纳德，卡恩
《金融计量学:从初级到高级建模技术》 斯维特洛扎《投资革命》Bernstein
《富可敌国》Sebastian Mallaby
《量化交易——如何建立自己的算法交易事业》欧内斯特·陈
《聪明的投资者》 巴菲特《黑天鹅·如何应对不可知的未来》 纳西姆·塔勒布
《期权、期货和其他衍生品》 约翰·赫尔《Building Reliable Trading Systems: Tradable Strategies That Perform As They Backtest and Meet Your Risk-Reward Goals》 Keith Fitschen
《Quantitative Equity Investing》by Frank J. Fabozzi, Sergio M. Focardi, Petter N. Kolm
Barra USE3 handbook
《Quantitative Equity Portfolio Management》 Ludwig Chincarini
《Quantitative Equity Portfolio Management》 Qian & Hua & Sorensen
Quant Papers
Machine Learning Related
Cavalcante, Rodolfo C., et al. “Computational Intelligence and Financial Markets: A Survey and Future Directions.” Expert Systems with Applications 55 (2016): 194-211.(link)
Low Frequency Prediction
Atsalakis G S, Valavanis K P. Surveying stock market forecasting techniques Part II: Soft computing methods. Expert Systems with Applications, 2009, 36(3):5932–5941. (link)
Cai X, Lin X. Feature Extraction Using Restricted Boltzmann Machine for Stock Price Predic- tion. 2012 IEEE International Conference on Computer Science and Automation Engineering (CSAE), 2012. 80–83.(link)
Nair B B, Dharini N M, Mohandas V P. A stock market trend prediction system using a hybrid decision tree-neuro-fuzzy system. Proceedings - 2nd International Conference on Advances in Recent Technologies in Communication and Computing, ARTCom 2010, 2010. 381–385. (link)
Lu C J, Lee T S, Chiu C C. Financial time series forecasting using independent component analysis and support vector regression. Decision Support Systems, 2009, 47(2):115–125. (link)
Creamer G, Freund Y. Automated trading with boosting and expert weighting. Quantitative Finance, 2010, 10(4):401–420. (link)
Batres-Estrada, Bilberto. “Deep learning for multivariate financial time series.” (2015). (link)
Xiong, Ruoxuan, Eric P. Nicholas, and Yuan Shen. “Deep Learning Stock Volatilities with Google Domestic Trends.” arXiv preprint arXiv:1512.04916 (2015).(link)
Sharang, Abhijit, and Chetan Rao. “Using machine learning for medium frequency derivative portfolio trading.” arXiv preprint arXiv:1512.06228 (2015).(link)
Reinforcement Learning
Dempster, Michael AH, and Vasco Leemans. “An automated FX trading system using adaptive reinforcement learning.” Expert Systems with Applications 30.3 (2006): 543-552. (link)
Tan, Zhiyong, Chai Quek, and Philip YK Cheng. “Stock trading with cycles: A financial application of ANFIS and reinforcement learning.” Expert Systems with Applications 38.5 (2011): 4741-4755. (link)
Rutkauskas, Aleksandras Vytautas, and Tomas Ramanauskas. “Building an artificial stock market populated by reinforcement‐learning agents.” Journal of Business Economics and Management 10.4 (2009): 329-341.(link)
Deng, Yue, et al. “Deep Direct Reinforcement Learning for Financial Signal Representation and Trading.” (2016).(link)
Natual Language Processing Related
Bollen J, Mao H, Zeng X. Twitter mood predicts the stock market. Journal of Computational Science, 2011, 2(1):1–8. (link)
Preis T, Moat H S, Stanley H E, et al. Quantifying trading behavior in financial markets using Google Trends. Scientific reports, 2013, 3:1684. (link)
Moat H S, Curme C, Avakian A, et al. Quantifying Wikipedia Usage Patterns Before Stock Market Moves. Scientific Reports, 2013, 3:1–5. (link)
Ding, Xiao, et al. “Deep learning for event-driven stock prediction.” Proceedings of the 24th International Joint Conference on Artificial Intelligence (ICJAI’15). 2015. (link)
Fehrer, R., & Feuerriegel, S. (2015). Improving Decision Analytics with Deep Learning: The Case of Financial Disclosures. arXiv preprint arXiv:1508.01993. (link)
High Frequency Trading
Nevmyvaka Y, Feng Y, Kearns M. Reinforcement learning for optimized trade execution. Proceedings of the 23rd international conference on Machine learning ICML 06, 2006, 17(1):673–680. (link)
Ganchev K, Nevmyvaka Y, Kearns M, et al. Censored exploration and the dark pool problem. Communications of the ACM, 2010, 53(5):99. (link)
Kearns M, Nevmyvaka Y. Machine learning for market microstructure and high frequency trading. High frequency trading - New realities for traders, markets and regulators, 2013. 1–21. (link)
Sirignano, Justin A. “Deep Learning for Limit Order Books.” arXiv preprint arXiv:1601.01987 (2016). (link)
Deng, Yue, et al. “Sparse coding-inspired optimal trading system for HFT industry.” IEEE Transactions on Industrial Informatics 11.2 (2015): 467-475.(link)
Ahuja, Saran, et al. “Limit order trading with a mean reverting reference price.” arXiv preprint arXiv:1607.00454 (2016). (link)
A?t-Sahalia, Yacine, and Jean Jacod. “Analyzing the spectrum of asset returns: Jump and volatility components in high frequency data.” Journal of Economic Literature 50.4 (2012): 1007-1050. (link)
Portfolio Management
B. Li and S. C. H. Hoi, “Online portfolio selection,” ACM Comput. Surv., vol. 46, no. 3, pp. 1–36, 2014. (link)
Heaton, J. B., Polson, N. G., & Witte, J. H. (2016). Deep Portfolio Theory. (link)
Eugene F. Fama, Kenneth R. French. The cross-section of expected stock returns. Journal of Finance, 47 (1992), pp. 427–465.
学术期刊
一堆学术期刊可以常常去浏览一下，也会有许多思路，作者常常看的有：
Journal of FinanceJournal of Financial Economics
Review of Financial Studies
Journal of Accounting and Economics
Review of Accounting Studies
Journal of Accounting Research
Accounting Review
Journal of Financial and Quantitative Analysis
Financial Analysts Journal
Financial Management
Journal of Empirical Finance
Quantitative Finance
Journal of Alternative Investments
Journal of Fixed Income
Journal of Investing
Journal of Portfolio Management
Journal of Trading
Review of Asset Pricing Studies
经济研究
经济学（季刊）
金融研究
管理世界
会计研究
投资研究
再分享一下我老师大神的人工智能教程吧。零基础！通俗易懂！风趣幽默！还带黄段子！希望你也加入到我们人工智能的队伍中来！https://blog.csdn.net/jiangjunshow
原文地址：https://www.cnblogs.com/wicnwicnwh/p/10308779.html