Financial Data Science Notebooks

UNDER CONSTRUCTION

30+ Projects in Financial Data Science, presented as Jupyter Notebooks, using the FinDS Python package

Topics

notebook	Financial	Data	Science
stock_prices	Stock distributions, delistings	CRSP stocks	Sample selection
jegadeesh_titman	Overlapping portfolios; Momentum	CRSP stocks	Hypothesis testing; Newey-West correction
fama_french	Bivariate sorts; Value, Size; CAPM	CRSP stocks; Compustat	Linear regression; Quadratic programming
fama_macbeth	Cross-sectional Regressions; Beta	Ken French data library	Feature transformations; Kernel regression, LOOCV
weekly_reversals	Mean reversion; Implementation shortfall	CRSP stocks	Structural break tests
quant_factors	Factor zoo; Performance evaluation	CRSP stocks; Compustat; IBES	Clustering for unsupervised learning
event_study	Event studies	S&P key developments	Multiple testing; FFT
economic_releases	Macroeconomic analysis; Unemployment	ALFRED	Economic data revisions
regression_diagnostics	Regression analysis; Inflation	FRED	Linear regression diagnostics; Residual Analysis
econometric_forecast	Time series analysis; National Output	FRED	Stationarity, Autocorrelation
approximate_factors	Approximate factor models	FRED-MD	Unit Root; PCA; EM Algorithm
economic_states	State space models	FRED-MD	Gaussian Mixture; HMM; Kalman Filter
conditional_volatility	Value at risk; Conditional volatility	FRED cryptos and currencies	ARCH, GARCH; VaR, TVaR
covariance_matrix	Covariance matrix estimation; Portfolio risk	Ken French data library	Shrinkage
term_structure	Interest rates, yield curve	FRED	Splines, PCA
bond_returns	Bond portfolio returns	FRED	SVD
option_pricing	Binomial trees; the Greeks	OptionMetrics; FRED	Simulations
market_microstructure	Liquidity costs; Bid-ask spreads	TAQ tick data	Realized volatility; Variance ratio
event_risk	Earnings surprises	IBES; FRED-QD	Poisson regression; GLM's
customer_ego	Principal customers	Compustat customer segments	Graph Networks
bea_centrality	Input-output use tables	Bureau of Economic Analysis	Graph centrality
industry_community	Industry sectors	Hoberg&Phillips data library	Community detection
link_prediction	Product markets	Hoberg&Phillips data library	Links prediction
spatial_regression	Earnings surprises	IBES; Hoberg&Phillips data library	Spatial regression
fomc_topics	Fedspeak	FOMC meeting minutes	Topic modelling
mda_sentiment	Company filings	SEC Edgar	Sentiment analysis
business_description	Growth and value stocks	SEC Edgar	Part-of-speech tagging
classification_models	News classification	S&P key developments	Classification for supervised learning
regression_models	Macroeconomic forecasting	FRED-MD	Regression for supervised learning
deep_classifier	News classification	S&P key developments	Feedforward neural networks; Word embeddings; Deep averaging
convolutional_net	Macroeconomic forecasting	FRED-MD	Temporal convolutional networks; Vector autoregression
recurrent_net	Macroeconomic forecasting	FRED-MD	Elman recurrent networks; Kalman filter
fomc_language	Fedspeak	FOMC meeting minutes	Language modelling; Transformers
reinforcement_learning	Spending policy	Stocks, bonds, bills, and inflation	Reinforcement learning

Resources

1. Online Jupyter-book, or download pdf

2. FinDS API reference

3. FinDS repo

4. Jupyter notebooks repo

Contact

Github: https://terence-lim.github.io