Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Cause and Effect01:53

Cause and Effect

11.4K
While variables are sometimes correlated because one does cause the other, it could also be that some other factor, a confounding variable, is actually causing the systematic movement in our variables of interest. For instance, as sales in ice cream increase, so does the overall rate of crime. Is it possible that indulging in your favorite flavor of ice cream could send you on a crime spree? Or, after committing crime do you think you might decide to treat yourself to a cone?
11.4K
Properties of Fourier series II01:21

Properties of Fourier series II

292
Time scaling of signals is a crucial concept in signal processing that affects the Fourier series representation without altering its coefficients. The process modifies the fundamental frequency, thereby changing how the series represents the signal over time. This principle is essential in various applications, including audio and image processing, where signal manipulation is frequent. Understanding function symmetries is fundamental to simplifying the Fourier series.
A function f(t) is...
292
Relative Frequency Histogram01:14

Relative Frequency Histogram

5.8K
The relative frequency depicts the proportion of data points that have each value. The frequency tells the number of data points that have each value. Like the histogram, a relative frequency histogram also has the same shape with a horizontal scale (the x-axis), but the vertical scale (the y-axis) is marked with relative frequencies (percentages of the whole) instead of actual frequencies. A relative frequency histogram is a graphical representation of a frequency distribution where the...
5.8K
Noncompartmental Analysis: Statistical Moment Theory00:56

Noncompartmental Analysis: Statistical Moment Theory

198
Noncompartmental analyses leverage statistical moment theory to examine time-related changes in macroscopic events, encapsulating the collective outcomes stemming from the constituent elements in play. Statistical moment theory is a mathematical approach used to describe the time course of drug concentration in the body without assuming a specific compartmental model. SMT provides insights into drug absorption, distribution, metabolism, and elimination by treating drug concentration versus time...
198
Aliasing01:18

Aliasing

263
Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original...
263
Biological Clocks and Seasonal Responses02:45

Biological Clocks and Seasonal Responses

39.4K
The circadian—or biological—clock is an intrinsic, timekeeping, molecular mechanism that allows plants to coordinate physiological activities over 24-hour cycles called circadian rhythms. Photoperiodism is a collective term for the biological responses of plants to variations in the relative lengths of dark and light periods. The period of light-exposure is called the photoperiod.
39.4K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Coordination of network heterogeneity and individual preferences promotes collective fairness.

Patterns (New York, N.Y.)·2025
Same author

Application of Zeolite-Based Materials for Chemical Sensing of VOCs.

Sensors (Basel, Switzerland)·2025
Same author

Study of the diffusion properties of zeolite mixtures by combined gravimetric analysis, IR spectroscopy and inversion methods (IRIS).

Physical chemistry chemical physics : PCCP·2023
Same author

A general urban spreading pattern of COVID-19 and its underlying mechanism.

npj urban sustainability·2023
Same author

Giant and Tunable Excitonic Optical Anisotropy in Single-Crystal Halide Perovskites.

Nano letters·2023
Same author

Hydrological changes caused by the construction of dams and reservoirs: The CECP analysis.

Chaos (Woodbury, N.Y.)·2023
Same journal

Research on a Regional Availability Evaluation Model for Road-Area High-Entropy Energy Based on Synergy Factors.

Entropy (Basel, Switzerland)·2026
Same journal

Atmospheric Turbulence Channel Modeling and Performance Analysis of a CO-ZP-OFDM Coherent Optical Communication System for UAV Air-to-Ground Scenarios.

Entropy (Basel, Switzerland)·2026
Same journal

Information Geometry and Asymptotic Theory for SMML Estimators.

Entropy (Basel, Switzerland)·2026
Same journal

Correlation Entropy and Power-Law Kinetics.

Entropy (Basel, Switzerland)·2026
Same journal

Research on the Contagion of Systemic Financial Risk Under the Impact of Climate Risks-From the Perspective of Complex Networks and Machine Learning.

Entropy (Basel, Switzerland)·2026
Same journal

The Statistical-Mechanical Meaning of the Wave Function of Quantum Mechanics.

Entropy (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: Sep 26, 2025

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

10.8K

A New Look at Calendar Anomalies: Multifractality and Day-of-the-Week Effect.

Darko Stosic1, Dusan Stosic1, Irena Vodenska2

  • 1Centro de Informática, Universidade Federal de Pernambuco, Av. Luiz Freire s/n, Recife 50670-901, PE, Brazil.

Entropy (Basel, Switzerland)
|April 23, 2022
PubMed
Summary
This summary is machine-generated.

Stock market analysis reveals day-of-the-week effects using multifractal analysis. Monday returns show unique persistent behavior and complex structures, impacting market efficiency.

Keywords:
calendar anomaliesday-of-the-week effectmarket indicesmultifractal detrended fluctuation analysis

More Related Videos

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons
07:59

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons

Published on: June 9, 2023

1.5K
Recording and Analysis of Circadian Rhythms in Running-wheel Activity in Rodents
05:46

Recording and Analysis of Circadian Rhythms in Running-wheel Activity in Rodents

Published on: January 24, 2013

21.5K

Related Experiment Videos

Last Updated: Sep 26, 2025

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

10.8K
Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons
07:59

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons

Published on: June 9, 2023

1.5K
Recording and Analysis of Circadian Rhythms in Running-wheel Activity in Rodents
05:46

Recording and Analysis of Circadian Rhythms in Running-wheel Activity in Rodents

Published on: January 24, 2013

21.5K

Area of Science:

  • Econophysics
  • Financial Markets Analysis

Background:

  • Calendar anomalies, like the day-of-the-week effect, are known to cause stock market inefficiencies.
  • These phenomena require further exploration within the field of econophysics.

Purpose of the Study:

  • To investigate the presence of day-of-the-week effects in the temporal dynamics of market returns.
  • To apply multifractal analysis to evaluate calendar anomalies in global stock market indices.

Main Methods:

  • Multifractal detrended fluctuation analysis (MF-DFA) was applied to daily returns of worldwide market indices.
  • Analysis was conducted separately for each day of the week to identify distinct patterns.

Main Results:

  • Distinct multifractal properties were observed for individual days of the week.
  • Monday returns exhibited greater persistence and richer multifractal structures compared to other days.
  • Multifractality was linked to broad probability density functions and long-term correlations, particularly evident in Monday returns during financial crises.

Conclusions:

  • Day-of-the-week effects are present in the multifractal dynamics of market returns.
  • Findings suggest further research into calendar anomalies across different market regimes is warranted.