sc-applied-quantitative-finance

HBAP course

General resources

Resources for finance with R

• https://www.optionstocksmachines.com/

• https://bookdown.org/roback/bookdown-BeyondMLR/

• https://otexts.com/fpp2/

• https://moderndive.com/7-sampling.html

Resources for finance with Python

• Some principles: https://medium.datadriveninvestor.com/how-to-find-undervalued-growth-stocks-e65f2620b589

• https://pythonforfinance.net/

• https://towardsdatascience.com/python-for-finance-the-complete-beginners-guide-764276d74cef

• https://home.tpq.io/media/yjh_py4fi_2nd_excerpt.pdf

Module 1's resources

Python

• Predicting stock price https://towardsdatascience.com/python-python-for-finance-stock-price-trend-analysis-9111afc29259

• Predicting stock prices with Stocker https://medium.datadriveninvestor.com/forecasting-stock-prices-using-stocker-66503c26307a

• Predicting stock prices with CNNs https://medium.com/hands-on-data-science/lstms-or-cnns-for-predicting-stock-prices-2974c0c8c4ef

• https://towardsdatascience.com/data-analysis-visualization-in-finance-technical-analysis-of-stocks-using-python-269d535598e4

• Motley Fool Stock Picks https://python.plainenglish.io/quickly-find-motley-fool-stock-picks-with-python-225729a76258

• superperformance stocks: https://medium.com/analytics-vidhya/super-performance-stocks-how-to-make-more-than-1-125-on-a-single-small-cap-stock-with-python-5ea3ae393791

R

• Changes in timeseries: https://predictivehacks.com/detect-the-changes-in-timeseries-data/

Module 2's resources

Classification models in Python

The following link https://predictivehacks.com/decision-boundary-in-python/ covers:

• logistic regression
• decision tree
• random forest
• SVM
• Naive Bayes
• Neural network

Classification and ensemble methods in Python

• https://educationalresearchtechniques.com/2019/01/21/combining-algorithms-for-classification-with-python/

Regression with stock market data in Python

• https://predictivehacks.com/stocks-market-beta-with-rolling-regression/

Time-series in Python

• https://jakevdp.github.io/PythonDataScienceHandbook/03.11-working-with-time-series.html

• https://medium.com/@soumyachess1496/cross-validation-in-time-series-566ae4981ce4

Automated Technical Analysis in Python

• buy/sell strategy: https://sarit-maitra.medium.com/machine-learning-algorithmic-trading-strategy-using-1ccc12ebfa14

• K-means clustering https://medium.datadriveninvestor.com/stock-market-clustering-with-k-means-clustering-in-python-4bf6bd5bd685

• https://medium.com/@farhadmalik/automating-stock-investing-technical-analysis-with-python-81c669e360b2?source=email-e1aecd04cbf7-1615707264629-digest.reader------1-83------------------93b98760_4ac6_445c_9dfc_ca1325f24a32-1-701d36d9_e0ff_495a_98c1_0a56af2253f4----&sectionName=top

• https://medium.com/fintechexplained/automating-stock-investing-fundamental-analysis-with-python-f854781ee0b4

Time-series in R

• https://blogs.rstudio.com/ai/posts/2021-03-10-forecasting-time-series-with-torch_1/?mkt_tok=NzA5LU5YTi03MDYAAAF7u4RAzMdnNIWHOoGLAELivntfOZDrUdjVT0oohfdRrVHy32zXyKj_5ltBDjKYiiiFGBWhXSmZdKvak6pRc51ucncVykzrHSSzNGkQuJuNLA

• https://robjhyndman.com/hyndsight/tscv/

• https://a-little-book-of-r-for-time-series.readthedocs.io/en/latest/src/timeseries.html

• https://bookdown.org/singh_pratap_tejendra/intro_time_series_r/

• Anomaly detection: https://towardsdatascience.com/tidy-anomaly-detection-using-r-82a0c776d523

Hedge funds and ETF in R

• Financial X-Rays: dissect any price series with a simple payoff diagram: https://blog.ephorie.de/financial-x-rays-dissect-any-price-series-with-a-simple-payoff-diagram

Module 3's resources

Python

• a pie chart of a portfolio (don't do pie charts ;-) ) https://medium.com/analytics-vidhya/visualize-your-portfolio-in-30-lines-of-code-d0200d15698c

• https://github.com/denisond/cryptocurrency_portfolio_sharpe_ratio_optimization/blob/master/cryptocurrency_portfolio_sharpe_ratio_optimization.ipynb

• https://medium.com/analytics-vidhya/python-will-make-you-rich-in-the-stock-market-b6dfaad711e7

Module 4's resources

Python

• https://github.com/erykml/Python-for-Finance-Cookbook

• https://github.com/scottandersen23/Medium_Blog/tree/main/Articles

R

• Portfolio diversification 1 https://blog.ephorie.de/parrondos-paradox-in-finance-combine-two-losing-investments-into-a-winner

• https://www.msperlin.com/blog/

• LIBOR interest rate swap https://kiandlee.blogspot.com/2021/07/delta-sensitivity-of-interest-rate-swap.html

• Automated stock trading with R https://towardsdatascience.com/automated-stock-trading-with-r-part-1-5a1020831096

• Automated stock trading using deep reinforcement learning https://medium.com/@mariko.sawada1/automated-stock-trading-with-deep-reinforcement-learning-and-financial-data-a63286ccbe2b

TL;DR

R

• Backtesting options strategies https://blog.ephorie.de/backtesting-options-strategies-with-r

• Stealth strategies: https://r-posts.com/nonlinear-market-forecasting-using-stealth-curves/