mirror of
https://github.com/firmai/financial-machine-learning.git
synced 2026-07-27 18:57:54 +00:00
added readme parser
This commit is contained in:
Bin Yang
@@ -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/)
|
||||
|
||||
|
||||
+32
-13
@@ -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
|
||||
|
||||
@@ -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"
|
||||
|
Reference in New Issue
Block a user