Natural Language Processing on Stocks' Earnings Call Transcripts: An Investment Strategy Backtest Based on S&P Global Papers.
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Updated
Aug 30, 2023 - Python
Natural Language Processing on Stocks' Earnings Call Transcripts: An Investment Strategy Backtest Based on S&P Global Papers.
Constituent history of the S&P 500 from various data sources
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IME-published article on Long-term Real Dynamic Investment Planning. While we enhance predictability of the real returns of S&P500 Index, we derive optimal non-myopic investment strategy, and we compare its performance with near-optimal Dynamic and Constant Merton investment strategies.
This application compares the performance of Unsupervised machine learning models and Supervised models. It downloads 3 yrs of market daily close data from all SP500 companies and divides them into Sectors to be used as features for learning and training the data, in order to predict wether the index will be a Buy or Sell the next day. The resul…
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A project featuring exploratory data analysis (EDA) and machine learning applications for S&P 500 stock data, utilizing Python and relevant libraries.
This system is designed to provide valuable insights into future market movements, enabling users to make informed decisions regarding their investments without directly executing trades. It leverages the VIX (CBOE Volatility Index) as a key indicator for predicting trends, in the SPY (S&P 500 ETF) market.
In this project, dive into an interactive app that brings stock data to life! Explore dynamic candlestick charts, track returns, and analyze rolling alpha and beta with ease. Compare your chosen stock to the S&P 500 Index and uncover trends with eye-catching visualizations. Perfect for data enthusiasts and investors alike!
Algorithmic Trading means using computers to make investment decisions. We will be using World's most popular S&P 500 Stock market index in order to do Data Analysis and generate predictions. Let us make investments on Stocks, easy for everyone!
My version of SP 500 data analyzer
Web Application to sort, analyze, & render data for all SP500 companies.
About A project featuring exploratory data analysis (EDA) and machine learning applications for S&P 500 stock data, utilizing Python and relevant libraries.
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