相关实验视频

Updated: Jun 28, 2025

Polar Histogram Visualization of Acute Stress Disorder Scale Scores for Comprehensive Clinical Assessment
08:25

Polar Histogram Visualization of Acute Stress Disorder Scale Scores for Comprehensive Clinical Assessment

Published on: December 6, 2024

351

中国的波动性指数能否反映出投资者的情绪?

Wen Long1,2,3, Manyi Zhao1,2,3, Yeran Tang4

  • 1School of Economics & Management, University of Chinese Academy of Sciences, Beijing 100190, PR China.

International review of financial analysis
|April 15, 2024
PubMed
概括

中国的波动性指数 (iVX) 有效地反映了不同时间尺度的投资者情绪. 它的组成部分与宏观,中级和微观层面的情绪相关,确认 iVX 是一个全面的情绪指标.

关键词:
相对应关系 相对应关系在 EEMD 中,我们可以使用 EEMD.投资者的情绪投资者的情绪.混合频率的动态因子分析.iVX iVX iVX 在线观看

更多相关视频

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods13:04

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods

Published on: September 19, 2012

12.1K
Functional Near-Infrared Spectroscopy Hyperscanning Study in Psychological Counseling06:04

Functional Near-Infrared Spectroscopy Hyperscanning Study in Psychological Counseling

Published on: January 17, 2025

490

相关概念视频

Coefficient of Variation01:10

Coefficient of Variation

The coefficient of variation measures the dispersion of the data points or distribution around the mean. Using the coefficient of variation, we can compare two data series with drastically different means or different units of measurement. The coefficient of variation for a sample and a population is expressed as a percentage of the ratio of standard deviation to the mean.
The coefficient of variation is a practical statistical tool in finance. It allows investors to assess the volatility or...
3.8K
Central Tendency: Analysis01:10

Central Tendency: Analysis

Measures of central tendency are tools used in biostatistics to identify the average or center of a dataset. They offer a single representative value for understanding and summarizing data distribution.
The mean is one such measure, calculated by totaling all values in a dataset and dividing by the number of values. For instance, the mean blood pressure reading (120, 130, 140, 150) would be 135. However, the mean can be affected by extreme values or outliers.
The median, another measure,...
150
Interpretation of Confidence Intervals01:19

Interpretation of Confidence Intervals

A confidence interval is a better estimate of the population than a point estimate, as it uses a range of values from a sample instead of a single value.
Confidence intervals have confidence coefficients that are crucial for their interpretation. The most common confidence coefficients are 0.90, 0.95, and 0.99, which can be written as percentages–90%, 95%, and 99%, respectively.
Suppose a person calculates a confidence interval with a confidence coefficient of 0.95. In that case, they can...
5.7K
Empirical Method to Interpret Standard Deviation01:09

Empirical Method to Interpret Standard Deviation

The empirical rule, also known as the three-sigma rule, allows a statistician to interpret the standard deviation in a normally distributed dataset. The rule states that 68% of the data lies within one standard deviation from the mean, 95% lies within two standard deviations from the mean, and 99.7% lies within three standard deviations from the mean. Additionally, this rule is also called the 68-95-99.7 rule.
This rule is used widely in statistics to calculate the proportion of data values...
5.2K
Expected Value01:15

Expected Value

The expected value is known as the "long-term" average or mean. This means that over the long term of experimenting over and over, you would expect this average. The expected average is represented by the symbol μ. It is calculated as follows:
3.9K
Interpreting X̄ Charts01:13

Interpreting X̄ Charts

Interpreting x̄ charts, a type of control chart used in statistical process control helps monitor the variation in processes over time. The x̄ chart is based on the sample mean and allows for monitoring variations in the process mean over time. These charts are pivotal for quality assurance in manufacturing and other sectors.
An x̄ chart plots the values of individual measurements over time against control limits calculated from historical data. The central line...
65