Prices for United States Stock Market Index (US2000) including live quotes, historical charts and news. United States Stock Market Index (US2000) was last updated by Trading Economics this March 27 of 2025.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

iShares Russell 2000 BuyWrite: A Smart Bet for Income?

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

A daily data ranging from January 2014 until December 2018 is employed. The period between January, 1, 2014 until November 7, 2016 refers to the pre-election period. The period ranging from November 8, 2016, until December, 31 2018 defines the post-election period. Four U.S stock price indices are retrieved from DataStream: The standard and Poor’s 500 index (S&P 500) covers the performance of 500 largest capitalization stocks. The Dow Jones Industrial Average (DJIA) index tracks the prices of the top 30 US companies. The NASDAQ 100 measures the performance of the 100 largest non-financial stocks traded on NASDAQ. The Russell 2000 index covers the performance of 2.000 lowest capitalization stocks. A daily political risk index is calculated for each period using Google trends and the principal component analysis.