CN: Investors' Confidence Index: Expectation on Stock Market: Rebound data was reported at 50.300 % in Apr 2018. This records an increase from the previous number of 49.100 % for Mar 2018. CN: Investors' Confidence Index: Expectation on Stock Market: Rebound data is updated monthly, averaging 49.100 % from Apr 2011 (Median) to Apr 2018, with 84 observations. The data reached an all-time high of 65.100 % in Apr 2015 and a record low of 34.500 % in Aug 2012. CN: Investors' Confidence Index: Expectation on Stock Market: Rebound data remains active status in CEIC and is reported by China Securities Investor Protection Fund Corporation Limited. The data is categorized under China Premium Database’s Business and Economic Survey – Table CN.OF: Investors’ Confidence Index.

Taiwan CCI: next 6 mth: Investment Prospect of Stock Market data was reported at 77.600 Point in Nov 2018. This records a decrease from the previous number of 85.300 Point for Oct 2018. Taiwan CCI: next 6 mth: Investment Prospect of Stock Market data is updated monthly, averaging 73.200 Point from Jan 2001 (Median) to Nov 2018, with 215 observations. The data reached an all-time high of 109.700 Point in Apr 2015 and a record low of 38.800 Point in Oct 2001. Taiwan CCI: next 6 mth: Investment Prospect of Stock Market data remains active status in CEIC and is reported by The Research Center for Taiwan Economic Development, National Central University. The data is categorized under Global Database’s Taiwan – Table TW.H018: Consumer Confidence Index (CCI).

China Investors' Confidence Index: Expectation on Stock Market: Optimistic data was reported at 47.900 % in Apr 2018. This records a decrease from the previous number of 49.700 % for Mar 2018. China Investors' Confidence Index: Expectation on Stock Market: Optimistic data is updated monthly, averaging 54.550 % from Apr 2011 (Median) to Apr 2018, with 84 observations. The data reached an all-time high of 77.600 % in Dec 2014 and a record low of 38.200 % in Aug 2015. China Investors' Confidence Index: Expectation on Stock Market: Optimistic data remains active status in CEIC and is reported by China Securities Investor Protection Fund Corporation Limited. The data is categorized under China Premium Database’s Business and Economic Survey – Table CN.OF: Investors’ Confidence Index.

View monthly updates and historical trends for US Index of Consumer Sentiment. from United States. Source: University of Michigan. Track economic data wit…

The Enhanced Investor Sentiment Index (STV) is an improved measure of investor sentiment, allowing contributions of each component of the index to vary over time instead of being fixed, as in the Baker and Wurgler (2006) investor sentiment index. STV has a better forecasting power and contains unique information about future market returns.

Source: Own creation.

Granger test results—causality relationship between the growth rates of the S&P 500 index and its respective confidence index.

United States CSI: Savings: Stock Market Increase Probability: Next Yr: 75-99% data was reported at 32.000 % in May 2018. This records an increase from the previous number of 31.000 % for Apr 2018. United States CSI: Savings: Stock Market Increase Probability: Next Yr: 75-99% data is updated monthly, averaging 26.000 % from Jun 2002 (Median) to May 2018, with 191 observations. The data reached an all-time high of 38.000 % in Sep 2017 and a record low of 9.000 % in Mar 2009. United States CSI: Savings: Stock Market Increase Probability: Next Yr: 75-99% data remains active status in CEIC and is reported by University of Michigan. The data is categorized under Global Database’s USA – Table US.H026: Consumer Sentiment Index: Savings & Retirement. The question was: What do you think the percent change that this one thousand dollar investment will increase in value in the year ahead, so that it is worth more than one thousand dollars one year from now?

United States CSI: Savings: Stock Market Increase Probability: Next Yr: Don’t Know data was reported at 2.000 % in May 2018. This records an increase from the previous number of 1.000 % for Apr 2018. United States CSI: Savings: Stock Market Increase Probability: Next Yr: Don’t Know data is updated monthly, averaging 2.000 % from Jun 2002 (Median) to May 2018, with 191 observations. The data reached an all-time high of 7.000 % in Jan 2005 and a record low of 0.000 % in Nov 2017. United States CSI: Savings: Stock Market Increase Probability: Next Yr: Don’t Know data remains active status in CEIC and is reported by University of Michigan. The data is categorized under Global Database’s USA – Table US.H026: Consumer Sentiment Index: Savings & Retirement. The question was: What do you think the percent change that this one thousand dollar investment will increase in value in the year ahead, so that it is worth more than one thousand dollars one year from now?

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.

An In-depth Analysis of the S&P 500 Index: Performance, Composition, and Implications

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

View weekly updates and historical trends for US Investor Sentiment, % Bullish. from United States. Source: The American Association of Individual Investo…

Consumer Confidence in the United States decreased to 55.10 points in September from 58.20 points in August of 2025. This dataset provides the latest reported value for - United States Consumer Sentiment - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The Consumer Sentiment Index in the United States stood at 64.7 in January 2025, an increase from the previous month. The index is normalized to a value of 100 in December 1964 and based on a monthly survey of consumers, conducted in the continental United States. It consists of about 50 core questions which cover consumers' assessments of their personal financial situation, their buying attitudes and overall economic conditions.

Consumer Confidence in India increased to 96.50 points in July from 95.40 points in May of 2025. This dataset provides - India Consumer Confidence - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Graph and download economic data for Equity Market Volatility Tracker: Macroeconomic News and Outlook: Business Investment And Sentiment (EMVMACROBUS) from Jan 1985 to Aug 2025 about volatility, uncertainty, equity, investment, business, and USA.

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.

Madison Square Garden Entertainment (MSGE) : A Rollercoaster Ride Ahead?

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

This data set contains the data used in the research project "Cognitive Biases in Consumer Sentiment: the Peak-End Rule and Herding". The following files and items are includedICSdata.xlsx: Index of Consumer Sentiment and its constituents (sheet 1), and PAGO per region (sheet 2); original source University of Michigan, Survey of Consumers, https://data.sca.isr.umich.edu/ALFRED_data: macro economic series related to economic growth, inflation, (un)employment and consumption, including publication date; original source ArchivaL Federal Reserve Economic Data (ALFRED), https://alfred.stlouisfed.org/; for each series a README sheet is included with metadataFREDdata: financial and economic series related to stock, bond, housing markets, interest rates,gasoline prices and regional unemployment rates; each sheet contains the mnemonic of the donwloaded series.MicroData_20220113: demographic information of each respondent in the Survey of Consumers conducted by the University of Michigan; downloaded from University of Michigan, Survey of Consumers, https://data.sca.isr.umich.edu/Prelim_PA.xlsx: the Index of Consumer Sentiment and its constituent series, as reported in the preliminary annoucement by the University of Michigan (prelim), and the series constructed based on the surveys after the preliminary announcements. The prelim series are publicly available via https://data.sca.isr.umich.edu/ . The pa series have been constructed based on interview datas obtains from the University of Michigan. These data are proprietory and cannot be shared freely.DemographicDifferences.xlsx: average differences between the prelim and pa monthly subsample in the demographic statistics available in MicroData_20220113.xlsx. The difference have been constructed based on interview datas obtains from the University of Michigan. These data are proprietory and cannot be shared freely.Methodology: Linear regressions and time-series methods.Findings: We show that two heuristics, the peak-end rule and herding, generate biases in indexes of consumer sentiment. Both affect respondents' assessment of changes in their financial position over the past year. Conform the peak-end rule, their answers relate more to extreme detrimental monthly than to yearly changes in key financial and macro variables. These effects are stronger for more salient variables. As for herding, we document that respondents interviewed in the second round about past financial changes rely too strongly on future expectations from first-round respondents. These effects persist when we account for structural differences in sample composition or for the effect of other predictive variables. Our research shows the presence of both biases outside controlled environments and sheds new light on the relevance of sentiment indexes.

United States CSI: Savings: Stock Market Increase Probability: Next Yr: 100% data was reported at 11.000 % in Oct 2018. This records an increase from the previous number of 10.000 % for Sep 2018. United States CSI: Savings: Stock Market Increase Probability: Next Yr: 100% data is updated monthly, averaging 6.000 % from Jun 2002 (Median) to Oct 2018, with 196 observations. The data reached an all-time high of 13.000 % in Jan 2018 and a record low of 1.000 % in Nov 2011. United States CSI: Savings: Stock Market Increase Probability: Next Yr: 100% data remains active status in CEIC and is reported by University of Michigan. The data is categorized under Global Database’s United States – Table US.H029: Consumer Sentiment Index: Savings & Retirement. The question was: What do you think the percent change that this one thousand dollar investment will increase in value in the year ahead, so that it is worth more than one thousand dollars one year from now?

United States CSI: Savings: Stock Market Increase Probability: Next Yr: 51-74% data was reported at 13.000 % in May 2018. This records a decrease from the previous number of 16.000 % for Apr 2018. United States CSI: Savings: Stock Market Increase Probability: Next Yr: 51-74% data is updated monthly, averaging 15.000 % from Jun 2002 (Median) to May 2018, with 191 observations. The data reached an all-time high of 24.000 % in Apr 2015 and a record low of 6.000 % in Mar 2009. United States CSI: Savings: Stock Market Increase Probability: Next Yr: 51-74% data remains active status in CEIC and is reported by University of Michigan. The data is categorized under Global Database’s USA – Table US.H026: Consumer Sentiment Index: Savings & Retirement. The question was: What do you think the percent change that this one thousand dollar investment will increase in value in the year ahead, so that it is worth more than one thousand dollars one year from now?

Johansen test for confidence x S&P 500.