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Standard Deviation01:10

Standard Deviation

23.5K
The most commonly used measure of variation is the standard deviation. It is a numerical value measuring how far data values are from their mean. The standard deviation value is small when the data are concentrated close to the mean, exhibiting slight variation or spread. The standard deviation value is never negative, it is either positive or zero. The standard deviation is larger when the data values are more spread out from the mean, which means the data values are exhibiting more variation.
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Variance01:15

Variance

11.1K
 The deviations show how spread out the data are about the mean. A positive deviation occurs when the data value exceeds the mean, whereas a negative deviation occurs when the data value is less than the mean. If the deviations are added, the sum is always zero. So one cannot simply add the deviations to get the data spread. By squaring the deviations, the numbers are made positive; thus, their sum will also be positive.
The standard deviation measures the spread in the same units as the...
11.1K
Coefficient of Variation01:10

Coefficient of Variation

6.8K
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...
6.8K
Stability of Substituted Cyclohexanes02:30

Stability of Substituted Cyclohexanes

13.8K
This lesson discusses the stability of substituted cyclohexanes with a focus on energies of various conformers and the effect of 1,3-diaxial interactions.
The two chair conformations of cyclohexanes undergo rapid interconversion at room temperature. Both forms have identical energies and stabilities, each comprising equal amounts of the equilibrium mixture. Replacing a hydrogen atom with a functional group makes the two conformations energetically non-equivalent.
For example, in...
13.8K
Hazan and Shaver's Attachment Styles01:28

Hazan and Shaver's Attachment Styles

65
Attachment theory, developed initially to explain infant–caregiver bonds, has been extended to illuminate patterns of intimacy in adult romantic relationships. Psychologists Cindy Hazan and Phillip Shaver proposed that the attachment styles observed in infancy form a framework for how individuals approach emotional closeness and conflict in adulthood. These attachment styles—secure, avoidant, and anxious—are linked to enduring patterns of behavior and emotional regulation in...
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Volatilization01:10

Volatilization

1.3K
Volatilization gravimetry is an analytical technique that measures the mass lost due to the volatilization of the substance. This technique is used to estimate the amount of volatile material in a sample. To perform this method, heat a known amount of the sample to a high temperature in a crucible or other suitable vessel. The volatile substance in the sample evaporates, and the vapor is completely expelled from the crucible either by heating the sample or bubbling a stream of inert gas through...
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Related Experiment Video

Updated: Oct 25, 2025

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
13:04

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

Published on: September 19, 2012

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Cryptocurrency volatility markets.

Fabian Woebbeking1

  • 1Goethe University Frankfurt, Frankfurt, Germany.

Digital Finance
|August 9, 2021
PubMed
Summary
This summary is machine-generated.

We developed a cryptocurrency volatility index (CVX) to measure market expectations of future volatility, even in illiquid conditions. This new index reveals cryptocurrency volatility is often independent of traditional markets but can share common shocks.

Keywords:
BitcoinBlockchainCryptocurrencyDerivativesLiquidityOptionsVolatility

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Area of Science:

  • Quantitative Finance
  • Financial Econometrics
  • Digital Asset Markets

Background:

  • The cryptocurrency market, a nascent asset class, exhibits unique volatility characteristics.
  • Assessing future volatility expectations in this market is challenging due to liquidity constraints.
  • Understanding cryptocurrency volatility is crucial for risk management and investment strategies.

Purpose of the Study:

  • To compute a stable and reliable volatility index (CVX) for the cryptocurrency market.
  • To analyze cryptocurrency market's expectation of future volatility using option prices.
  • To investigate the relationship between cryptocurrency volatility and traditional asset market volatility.

Main Methods:

  • Developed two alternative methods to compute volatility from granular intra-day cryptocurrency options data.
  • Calculated a cryptocurrency volatility index (CVX) addressing liquidity challenges.
  • Utilized an error correction model on cointegrated index series to indicate market-implied tail-risk.

Main Results:

  • Successfully extracted stable market-implied volatilities for cryptocurrencies, even during the COVID-19 pandemic.
  • The computed CVX data captured normal market dynamics, as well as periods of distress and recovery.
  • Found that cryptocurrency volatility dynamics are often disconnected from traditional markets (e.g., equity VIX, gold GVX).
  • Identified that cryptocurrency markets can experience common shocks with traditional asset classes.

Conclusions:

  • The novel CVX provides a robust measure of cryptocurrency market's expectation of future volatility.
  • The CVX and its associated error correction model serve as valuable indicators for tail-risk in digital asset markets.
  • Cryptocurrency volatility exhibits distinct dynamics from traditional assets but is not entirely isolated from global financial shocks.