From 48b223a246bd861908cd26a4dae6144b3135aa9f Mon Sep 17 00:00:00 2001 From: Bin Yang Date: Fri, 19 Mar 2021 00:52:20 -0400 Subject: [PATCH] added readme parser --- README.md | 2 +- git_status.py | 45 +++++++++---- raw_data/url_list.csv | 147 ++++++++++++++++++++++++++++++++++++++++++ 3 files changed, 180 insertions(+), 14 deletions(-) create mode 100644 raw_data/url_list.csv diff --git a/README.md b/README.md index e8054c3..409e01b 100644 --- a/README.md +++ b/README.md @@ -195,5 +195,5 @@ If you want to contribute to this list (please do), send me a pull request or co - [NYU Courant](https://cims.nyu.edu/) - Courant Institute of Mathematical Sciences, New York University - [Oxford Man](https://www.oxford-man.ox.ac.uk/) - Oxford-Man Institute of Quantitative Finance - [Stanford Advanced Financial Technologies](https://fintech.stanford.edu/) - Stanford Advanced Financial Technologies Laboratory -- Berkley CIFT +- [Berkeley Lab CIFT](https://cs.lbl.gov/news-media/news/news-archive/2010/berkeley-lab-launches-new-center-for-innovative-financial-technology/) diff --git a/git_status.py b/git_status.py index dafc60e..4e43fbb 100644 --- a/git_status.py +++ b/git_status.py @@ -1,12 +1,22 @@ import os from conf import PROJECT_ROOT_DIR import re +import pandas as pd + @DeprecationWarning def parse_readme_md(): + """ + + :return: + usage: + >>> df = parse_readme_md() + >>> df.to_csv(os.path.join(PROJECT_ROOT_DIR, 'raw_data', 'url_list.csv')) + """ file_path = os.path.join(PROJECT_ROOT_DIR, 'README.md') with open(file_path) as f: - lines = f.readlines()[11:] # skip heading + lines = f.readlines()[11:] # skip heading + all_df_list = [] for line_num in range(len(lines)): line = lines[line_num] if line.strip().startswith('#'): @@ -17,21 +27,30 @@ def parse_readme_md(): line_num += 1 while line_num < len(lines) and not lines[line_num].strip().startswith('#'): link_line = lines[line_num].replace('\n', '').strip() - print(link_line) if len(link_line) > 0: # usually in the format of '- [NAME](link) - comment split_sections = link_line.split('- ') if len(split_sections) == 2: - title_and_link = split_sections[1].strip() - title = re.search(r'\[(.*?)\]', title_and_link).group(1) - m_link = re.search(r'\((.*?)\)', title_and_link) - link_str = '' - if m_link is not None: - link_str = m_link.group(1) + comment_str = None + elif len(split_sections) >= 3: + comment_str = '-'.join(split_sections[2:]).strip() + else: + raise Exception('link_line [{}] not supported'.format(link_line)) - pass - elif len(split_sections) == 3: - pass - - print(split_sections) + title_and_link = split_sections[1].strip() + title = re.search(r'\[(.*?)\]', title_and_link) + title_str = None + if title is not None: + title_str = title.group(1) + m_link = re.search(r'\((.*?)\)', title_and_link) + link_str = None + if m_link is not None: + link_str = m_link.group(1) + parsed_set = (title_str, link_str, comment_str) + parsed_list.append(parsed_set) line_num += 1 + parsed_df = pd.DataFrame(parsed_list, columns=['name', 'url', 'comment']) + parsed_df['category'] = heading + all_df_list.append(parsed_df) + final_df = pd.concat(all_df_list).reset_index(drop=True) + return final_df diff --git a/raw_data/url_list.csv b/raw_data/url_list.csv new file mode 100644 index 0000000..a56a963 --- /dev/null +++ b/raw_data/url_list.csv @@ -0,0 +1,147 @@ +,name,url,comment,category +0,Deep Learning,https://github.com/keon/deepstock,Technical experimentations to beat the stock market using deep learning.,Deep Learning +1,Deep Learning II,https://github.com/LiamConnell/deep-algotrading/tree/master/notebooks,Tensorflow Regression.,Deep Learning +2,Deep Learning III,https://github.com/Rachnog/Deep-Trading,Algorithmic trading with deep learning experiments.,Deep Learning +3,Deep Learning IV,https://github.com/achillesrasquinha/bulbea,Bulbea: Deep Learning based Python Library.,Deep Learning +4,LTSM GRU,https://github.com/RajatHanda/Finance-Forecasting,Stock Market Forecasting using LSTM\GRU.,Deep Learning +5,LTSM Recurrent,https://github.com/VivekPa/AIAlpha,OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network.,Deep Learning +6,ARIMA-LTSM Hybrid,https://github.com/imhgchoi/Corr_Prediction_ARIMA_LSTM_Hybrid,Hybrid model to predict future price correlation coefficients of two assets.,Deep Learning +7,Neural Network,https://github.com/VivekPa/IntroNeuralNetworks,Neural networks to predict stock prices.,Deep Learning +8,AI Trading,https://github.com/borisbanushev/stockpredictionai/blob/master/readme2.md,AI to predict stock market movements.,Deep Learning +9,RL Trading,https://colab.research.google.com/drive/1FzLCI0AO3c7A4bp9Fi01UwXeoc7BN8sW,A collection of 25+ Reinforcement Learning Trading Strategies -Google Colab.,Reinforcement Learning +10,RL,https://github.com/kh-kim/stock_market_reinforcement_learning,OpenGym with Deep Q-learning and Policy Gradient.,Reinforcement Learning +11,RL II,https://github.com/deependersingla/deep_trader,reinforcement learning on stock market and agent tries to learn trading.,Reinforcement Learning +12,RL III,https://github.com/samre12/deep-trading-agent,Github -Deep Reinforcement Learning based Trading Agent for Bitcoin.,Reinforcement Learning +13,RL IV,https://github.com/jjakimoto/DQN,Reinforcement Learning for finance.,Reinforcement Learning +14,RL V,https://github.com/gstenger98/rl-finance,Building an Agent to Trade with Reinforcement Learning.,Reinforcement Learning +15,Pair Trading RL,https://github.com/shenyichen105/Deep-Reinforcement-Learning-in-Stock-Trading,Using deep actor-critic model to learn best strategies in pair trading.,Reinforcement Learning +16,Mixture Models I,https://github.com/BlackArbsCEO/Mixture_Models,Mixture models to predict market bottoms.,Other Models +17,Mixture Models II,https://github.com/BlackArbsCEO/mixture_model_trading_public,Mixture models and stock trading.,Other Models +18,Scikit-learn Stock Prediction,https://github.com/robertmartin8/MachineLearningStocks,Using python and scikit-learn to make stock predictions.,Other Models +19,Fundamental LT Forecasts,https://github.com/Hvass-Labs/FinanceOps,Research in investment finance for long term forecasts.,Other Models +20,Short-Term Movement Cues,https://github.com/anfederico/Clairvoyant,Identify social/historical cues for short term stock movement.,Other Models +21,Trend Following,http://inseaddataanalytics.github.io/INSEADAnalytics/ExerciseSet2.html,A futures trend following portfolio investment strategy.,Other Models +22,Advanced ML,https://github.com/BlackArbsCEO/Adv_Fin_ML_Exercises,Exercises too Financial Machine Learning (De Prado).,Data Processing Techniques and Transformations +23,Advanced ML II,https://github.com/hudson-and-thames/research,More implementations of Financial Machine Learning (De Prado).,Data Processing Techniques and Transformations +24,Distribution Characteristic Optimisation,https://github.com/VivekPa/OptimalPortfolio,Extends classical portfolio optimisation to take the skewness and kurtosis of the distribution of market invariants into account.,Portfolio Selection and Optimisation +25,Reinforcement Learning,https://github.com/filangel/qtrader,Reinforcement Learning for Portfolio Management.,Portfolio Selection and Optimisation +26,Efficient Frontier,https://github.com/tthustla/efficient_frontier/blob/master/Efficient%20_Frontier_implementation.ipynb,Modern Portfolio Theory.,Portfolio Selection and Optimisation +27,PyPortfolioOpt,https://github.com/robertmartin8/PyPortfolioOpt,"Financial portfolio optimisation, including classical efficient frontier and advanced methods.",Portfolio Selection and Optimisation +28,Policy Gradient Portfolio,https://github.com/ZhengyaoJiang/PGPortfolio,A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem.,Portfolio Selection and Optimisation +29,Deep Portfolio Theory,https://github.com/tcloaa/Deep-Portfolio-Theory,Autoencoder framework for portfolio selection.,Portfolio Selection and Optimisation +30,401K Portfolio Optimisation,https://github.com/otosman/Python-for-Finance/blob/master/Portfolio%20Optimization%20401k.ipynb,Portfolio analyses and optimisation for 401K.,Portfolio Selection and Optimisation +31,Online Portfolio Selection,https://nbviewer.jupyter.org/github/paulperry/quant/blob/master/OLPS_Comparison.ipynb,****Comparing OLPS algorithms on a diversified set of ETFs.,Portfolio Selection and Optimisation +32,OLMAR Algorithm,https://github.com/charlessutton/OLMAR/blob/master/Part3.ipynb,Relative importance of each component of the OLMAR algorithm.,Portfolio Selection and Optimisation +33,Modern Portfolio Theory,https://nbviewer.jupyter.org/github/Marigold/universal-portfolios/blob/master/modern-portfolio-theory.ipynb,Universal portfolios; modern portfolio theory.,Portfolio Selection and Optimisation +34,DeepDow,https://github.com/jankrepl/deepdow,Portfolio optimization with deep learning.,Portfolio Selection and Optimisation +35,Various Risk Measures,https://github.com/Jorgencr/Alternative-and-Responsible-Investments/blob/master/Final_masterfile.ipynb,Risk measures and factors for alternative and responsible investments.,Factor and Risk Analysis: +36,Pyfolio,https://github.com/quantopian/pyfolio,Portfolio and risk analytics in Python.,Factor and Risk Analysis: +37,Risk Basic,https://github.com/RJT1990/Active-Portfolio-Management-Notes/blob/master/Chapter%203%2C%20Risk.ipynb,Active portfolio risk management .,Factor and Risk Analysis: +38,CAPM,https://github.com/RJT1990/Active-Portfolio-Management-Notes/blob/master/Chapter%202%2C%20CAPM.ipynb,Expected returns using CAPM.,Factor and Risk Analysis: +39,Factor Analysis,https://github.com/garvit-kudesia91/factor_analysis/blob/master/Factor%20Analysis%20of%20Mutual%20Funds.ipynb,Factor analysis for mutual funds.,Factor and Risk Analysis: +40,VaR GaN,https://github.com/hamaadshah/market_risk_gan_keras,Estimate Value-at-Risk for market risk management using Keras and TensorFlow.,Factor and Risk Analysis: +41,VaR,https://github.com/willb/var-notebook/blob/master/var-notebook/var-pdfs.ipynb,Value-at-risk calculations.,Factor and Risk Analysis: +42,Python for Finance,https://github.com/yhilpisch/py4fi/tree/master/jupyter36,Various financial notebooks.,Factor and Risk Analysis: +43,Performance Analysis,https://github.com/quantopian/alphalens,Performance analysis of predictive (alpha) stock factors.,Factor and Risk Analysis: +44,Quant Finance,https://github.com/mrefermat/quant_finance,General quant repository.,Factor and Risk Analysis: +45,Risk and Return,https://github.com/PyDataBlog/Python-for-Data-Science/tree/master/Tutorials,Riskiness of portfolios and assets.,Factor and Risk Analysis: +46,Convex Optimisation,https://github.com/ssanderson/convex-optimization-for-finance/blob/master/notebooks/Main.ipynb,Convex Optimization for Finance.,Factor and Risk Analysis: +47,Factor Analysis,https://github.com/alpha-miner/alpha-mind/tree/master/notebooks,Factor strategy notebooks.,Factor and Risk Analysis: +48,Statistical Finance,https://github.com/mrefermat/FinancePhD/tree/master/FinancialExperiments,Various financial experiments.,Factor and Risk Analysis: +49,PCA Pairs Trading,https://github.com/joelQF/quant-finance/tree/master/Artificial_IntelIigence_for_Trading,"PCA, Factor Returns, and trading strategies.",Unsupervised: +50,Fund Clusters,https://github.com/frechfrechfrech/Mutual-Fund-Market-Clusters/blob/master/Initial%20Data%20Exploration.ipynb,Data exploration of fund clusters.,Unsupervised: +51,VRA Stock Embedding,https://github.com/ml-hongkong/stock2vec,Variational Reccurrent Autoencoder for Embedding stocks to vectors based on the price history.,Unsupervised: +52,Industry Clustering,https://github.com/SeanMcOwen/FinanceAndPython.com-ClusteringIndustries,Clustering of industries.,Unsupervised: +53,Pairs Trading,https://github.com/marketneutral/pairs-trading-with-ML/blob/master/Pairs%2BTrading%2Bwith%2BMachine%2BLearning.ipynb,Finding pairs with cluster analysis.,Unsupervised: +54,Industry Clustering,https://github.com/SeanMcOwen/FinanceAndPython.com-ClusteringIndustries,Project to cluster industries according to financial attributes.,Unsupervised: +55,NLP,https://github.com/toamitesh/NLPinFinance,This project assembles a lot of NLP operations needed for finance domain.,Textual: +56,Earning call transcripts,https://github.com/lin882/WebAnalyticsProject,Correlation between mutual fund investment decision and earning call transcripts.,Textual: +57,Buzzwords,https://github.com/swap9047/Cutting-Edge-Technologies-Effect-on-S-P500-Companies-Performance-and-Mutual-Funds,Return performance and mutual fund selection.,Textual: +58,Fund classification,https://github.com/frechfrechfrech/Mutual-Fund-Market-Clusters/blob/master/Initial%20Data%20Exploration.ipynb,Fund classification using text mining and NLP.,Textual: +59,NLP Event,https://github.com/yuriak/DLQuant,Applying Deep Learning and NLP in Quantitative Trading.,Textual: +60,Financial Sentiment Analysis,https://github.com/EricHe98/Financial-Statements-Text-Analysis,"Sentiment, distance and proportion analysis for trading signals.",Textual: +61,Financial Statement Sentiment,https://github.com/MAydogdu/TextualAnalysis,Extracting sentiment from financial statements using neural networks.,Textual: +62,Extensive NLP,https://github.com/TiesdeKok/Python_NLP_Tutorial/blob/master/NLP_Notebook.ipynb,Comprehensive NLP techniques for accounting research.,Textual: +63,Accounting Anomalies,https://github.com/GitiHubi/deepAI/blob/master/GTC_2018_Lab-solutions.ipynb,Using deep-learning frameworks to identify accounting anomalies.,Textual: +64,Options,https://github.com/QuantConnect/Tutorials/tree/master/06%20Introduction%20to%20Options%5B%5D,Introduction to options.,Derivatives and Hedging: +65,Derivative Markets,https://github.com/broughtj/Fin6470/tree/master/Notebooks,"The economics of futures, futures, options, and swaps.",Derivatives and Hedging: +66,Black Scholes,https://github.com/irajwani/numerical_methods_python/blob/master/black_scholes.ipynb,Options pricing.,Derivatives and Hedging: +67,Computational Derivatives,https://github.com/chenbowen184/Computational_Finance,Projects focusing on investigating simulations and computational techniques applied in finance.,Derivatives and Hedging: +68,Reinforcement Learning,https://github.com/FinTechies/HedgingRL,Hedging portfolios with reinforcement learning.,Derivatives and Hedging: +69,Delta Hedging,https://github.com/RobinsonGarcia/delta-hedging,Advanced derivatives.,Derivatives and Hedging: +70,Options Risk Measures,https://github.com/wanglouis49/risk_estimation,Efficient financial risk estimation via computer experiment design (regression + variance-reduced sampling).,Derivatives and Hedging: +71,Derivatives Python,https://github.com/yhilpisch/dawp/tree/master/python36,Derivative analytics with Python.,Derivatives and Hedging: +72,Volatility and Variance Derivatives,https://github.com/yhilpisch/lvvd/tree/master/lvvd,Volatility derivatives analytics.,Derivatives and Hedging: +73,Options,https://github.com/PHBS/2018.M1.ASP/tree/master/py,Black Scholes and Copula.,Derivatives and Hedging: +74,Option Strategies,https://github.com/rstreppa/valuation-OptionStrategies,"Valuation of Vanilla and Exotic option strategies (Butterfly, Risk Reversal etc.) with widget animations.",Derivatives and Hedging: +75,Derman,https://github.com/rstreppa/valuation-convertibles-Goldman1994/blob/master/ConvertibleBond_Goldman1994_Derman.ipynb,Binomial tree for American call.,Derivatives and Hedging: +76,Hull White,https://github.com/rstreppa/valuation-callables-HullWhite/blob/master/CallableBond_HullWhite.ipynb,"Callable Bond, Hull White.",Derivatives and Hedging: +77,Vasicek,https://github.com/RobinsonGarcia/fixed-income/blob/master/2.0%20Vasicek%20-%20example.ipynb,Bootstrapping and interpolation.,Fixed Income +78,Binomial Tree,https://github.com/hy-lei/math-finance-exercise,Utility functions in fixed income securities.,Fixed Income +79,Corporate Bonds,https://github.com/ishank011/gs-quantify-bond-prediction,Predicting the buying and selling volume of the corporate bonds.,Fixed Income +80,Kiva Crowdfunding,https://github.com/CJL89/Kiva-Crowdfunding/blob/master/Kiva%20Crowdfunding.ipynb,Exploratory data analysis.,Alternative Finance +81,Venture Capital,https://github.com/julian-chan/etothex,Insight into a new founder to make data-driven investment decisions.,Alternative Finance +82,Venture Capital NN,https://github.com/tr7200/National-Culture-and-Venture-Capital-Monitoring,Cox-PH neural network predictions for VC/innovations finance research.,Alternative Finance +83,Private Equity,https://github.com/TheVinhLuong102/ChicagoBooth-EntrepreneurialFinancePrivateEquity/blob/master/RightNow%20Technologies/RightNow%20Technologies.ipynb,Valuation models.,Alternative Finance +84,VC OLS,https://github.com/fionawhitefield/venture-capital-ols/blob/master/sec_project.ipynb,VC regression.,Alternative Finance +85,Watch Valuation,https://github.com/alporter08/Luxury-Watch-Valuation/blob/master/Luxury-Watch-Valuation.ipynb,Analysis of luxury watch data to classify whether a certain model is likely to be over-or undervalued.,Alternative Finance +86,Art Valuation,https://github.com/ahmedhosny/theGreenCanvas/blob/gh-pages/ImageProcessing1210.ipynb,Art evaluation analytics.,Alternative Finance +87,Blockchain,https://github.com/nud3l/dInvest,Repository for distributed autonomous investment banking.,Alternative Finance +88,HFT,https://github.com/rorysroes/SGX-Full-OrderBook-Tick-Data-Trading-Strategy,High frequency trading.,Extended Research: +89,Deep Portfolio,https://github.com/DLColumbia/DL_forFinance,Deep learning for finance Predict volume of bonds.,Extended Research: +90,Mathematical Finance,https://github.com/Auquan/Tutorials,Notebooks for math and financial tutorials.,Extended Research: +91,NLP Finance Papers,https://github.com/chenbowen184/Research_Documents_Curation_with_NLP,Curating quantitative finance papers using machine learning.,Extended Research: +92,Simulation,https://github.com/chenbowen184/Computational_Finance,Investigating simulations as part of computational finance.,Extended Research: +93,Market Crash Prediction,https://github.com/sarachmax/MarketCrashes_Prediction/blob/master/LPPL_Comparasion.ipynb,Predicting market crashes using an LPPL model.,Extended Research: +94,Commodity,https://github.com/felipessalvatore/fin2vec/blob/master/src/Commodity2BR.ipynb,Commodity influence over Brazilian stocks.,Extended Research: +95,Finance Graph Theory,https://github.com/AvijitGhosh82/Finance_Graph_Theory,Modelling Contentedness of Firms in Financial Markets with Heterogeneous Agents.,Extended Research: +96,Real Estate Property Fraud,https://github.com/aviroop1/Real_Estate_Property_Fraud,Unsupervised fraud detection model that can identify likely candidates of fraud.,Extended Research: +97,Behavioural Economics,https://github.com/pcmichaud/notebooks,Behavioural Economics and Finance Python Notebooks.,Extended Research: +98,Bayesian Finance,https://github.com/marketneutral/alphatools/blob/master/notebooks/pymc3-minimal.ipynb,Notebook PyMC3 implementation.,Extended Research: +99,Bayesian Finance I,https://github.com/AlexIoannides/pymc-stochastic-process/blob/master/bayes_stoch_proc_calib.ipynb,Stochastic Process Calibration using Bayesian Inference & Probabilistic Programs.,Extended Research: +100,Currency PCA,https://github.com/shanemulqueen/python-finance-pca/blob/master/FX_spots_w_PCA.ipynb,Forex spots PCA.,Extended Research: +101,Backtests,https://github.com/AlgoTraders/stock-analysis-engine,Trading data and algorithms.,Extended Research: +102,High Frequency,https://github.com/cswaney/prickle,A Python toolkit for high-frequency trade research.,Extended Research: +103,Financial Economics,https://github.com/rsvp/fecon235/tree/master/nb,Financial Economics Models.,Extended Research: +104,Critical Transitions,https://github.com/ryanholbrook/critical-transitions,Detecting critical transitions in financial networks with topological data analysis.,Extended Research: +105,Economic Foundations,https://github.com/SeanMcOwen/FinanceAndPython.com-EconomicFoundations,Basic economic models.,Extended Research: +106,Corporate Finance,https://github.com/SeanMcOwen/FinanceAndPython.com-CorporateFinance,Basic corporate finance.,Extended Research: +107,Applied Corporate Finance,https://github.com/chenbowen184/Data_Science_in_Applied_Corporate_Finance,Studies the empirical behaviours in stock market.,Extended Research: +108,M&A,https://github.com/atulram/Finance-and-Stocks,Mergers and Acquisitions.,Extended Research: +109,Life-cycle,https://github.com/atulram/Finance-and-Stocks/blob/master/CompanyLifeCycle.ipynb,Company life cycle.,Extended Research: +110,Computational Finance,https://github.com/lnsongxf/Applied_Computational_Economics_and_Finance,Applied Computational Economics and Finance.,Extended Research: +111,Liquidity and Momentum,https://github.com/mrefermat/quant_finance,Various factors and portfolio constructions.,Extended Research: +112,Mathematical Finance,https://github.com/yadongli/nyumath2048,NYU Math-GA 2048: Scientific Computing in Finance.,Courses +113,Algo Trading,https://github.com/JCreeks/Machine-Learning-in-Finance/tree/master/0_Intro_to_Algo_Trading,Intro to algo trading.,Courses +114,Python for Finance,https://github.com/siaen/python_finance_course,CEU python for finance course material.,Courses +115,Handson Python for Finance,https://github.com/PacktPublishing/Hands-on-Python-for-Finance,Hands-on Python for Finance published by Packt.,Courses +116,Machine Learning for Trading,https://github.com/stefan-jansen/machine-learning-for-trading,"Notebooks, resources and references accompanying the book Machine Learning for Algorithmic Trading.",Courses +117,ML Specialisation,https://github.com/Ahmed0028/Machine-Learning-and-Reinforcement-Learning-in-Finance-Specialization,Machine Learning in Finance.,Courses +118,Risk Management,https://github.com/andrey-lukyanov/Risk-Management,Finance risk engagement course resources.,Courses +119,Basic Investments,https://github.com/SeanMcOwen/FinanceAndPython.com-Investments,Basic investment tools in python.,Courses +120,Basic Derivatives,https://github.com/SeanMcOwen/FinanceAndPython.com-Derivatives,Basic forward contracts and hedging.,Courses +121,Basic Finance,https://github.com/SeanMcOwen/FinanceAndPython.com-BasicFinance,Source code notebooks basic finance applications.,Courses +122,Capital Markets Data,https://www.capitalmarketsdata.com/,,Data +123,Employee Count SEC Filings,https://github.com/healthgradient/sec_employee_information_extraction,,Data +124,SEC Parsing,https://github.com/healthgradient/sec-doc-info-extraction/blob/master/classify_sections_containing_relevant_information.ipynb,,Data +125,Open Edgar,https://github.com/LexPredict/openedgar,,Data +126,EDGAR,https://github.com/TiesdeKok/UW_Python_Camp/blob/master/Materials/Session_5/EDGAR_walkthrough.ipynb,,Data +127,IRS,http://social-metrics.org/sox/,,Data +128,Rating Industries,http://www.ratingshistory.info/,,Data +129,Web Scraping (FirmAI),FirmAI,,Data +130,Financial Corporate,http://raw.rutgers.edu/Corporate%20Financial%20Data.html,,Data +131,Non-financial Corporate,http://raw.rutgers.edu/Non-Financial%20Corporate%20Data.html,,Data +132,http://finance.yahoo.com/,http://finance.yahoo.com/,,Data +133,https://fred.stlouisfed.org/,https://fred.stlouisfed.org/,,Data +134,https://stooq.com,https://stooq.com,,Data +135,https://github.com/timestocome/StockMarketData,https://github.com/timestocome/StockMarketData,,Data +136,Financial Event Prediction using Machine Learning,https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3481555,,Personal Papers +137,Machine Learning in Asset Management—Part 1: Portfolio Construction—Trading Strategies,https://jfds.pm-research.com/content/2/1/10,,Personal Papers +138,Machine Learning in Asset Management—Part 2: Portfolio Construction—Weight Optimization,https://jfds.pm-research.com/content/2/2/17,,Personal Papers +139,Machine Learning in Asset Management,https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3420952,,Personal Papers +140,NYU FRE,https://engineering.nyu.edu/academics/departments/finance-and-risk-engineering,Finance and Risk Engineering (NYU Tandon),"Colleges, Centers and Departments" +141,Cornell University,https://www.cornell.edu/,,"Colleges, Centers and Departments" +142,NYU Courant,https://cims.nyu.edu/,"Courant Institute of Mathematical Sciences, New York University","Colleges, Centers and Departments" +143,Oxford Man,https://www.oxford-man.ox.ac.uk/,Oxford-Man Institute of Quantitative Finance,"Colleges, Centers and Departments" +144,Stanford Advanced Financial Technologies,https://fintech.stanford.edu/,Stanford Advanced Financial Technologies Laboratory,"Colleges, Centers and Departments" +145,Berkeley Lab CIFT,https://cs.lbl.gov/news-media/news/news-archive/2010/berkeley-lab-launches-new-center-for-innovative-financial-technology/,,"Colleges, Centers and Departments"