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Financial Data Science: Stock Market Recommender & Predictor
A homegrown recommender, backtested to a 10.1% annualized return.
BeautifulSoupRegexyFinanceMatplotlibBacktesterPickle
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Tickers scraped
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Data points
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Indicators
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Annualized return
Webscraper
BeautifulSoup and yFinance extract 500 ticker names with corresponding close prices and volumes across 5+ years.
Technical & Fundamental Indicator Calculation
Python builds technical indicators while BeautifulSoup scrapes company fundamentals, totaling 15+ indicators.
Visualizer
Matplotlib produces comprehensive price and volume visualizations per ticker, equipped with technical indicators.
Recommender & Backtester
A function recommends daily stock purchases based on programmed trading strategies. A custom backtester evaluates returns across strategies, landing at a 10.1% annualized return.
Next Targets
Push toward 30% annualized returns, and increase backtesting speed by 40%.