Jove
Visualize
Contact Us

Related Concept Videos

Stratified Sampling Method01:16

Stratified Sampling Method

13.9K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a stratified sample, divide the population into groups called strata and then take a...
13.9K
Actuarial Approach01:20

Actuarial Approach

179
The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
179
Randomized Experiments01:13

Randomized Experiments

8.5K
The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
8.5K
Multimachine Stability01:25

Multimachine Stability

273
Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
273
Cluster Sampling Method01:20

Cluster Sampling Method

13.5K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
13.5K
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

160
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
160

You might also read

Related Articles

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

Sort by
Same author

LSTM-GARCH Hybrid Model for the Prediction of Volatility in Cryptocurrency Portfolios.

Computational economics·2023
Same author

Dynamic factor structure of team performances in Liga MX.

Journal of applied statistics·2022
Same author

A multi-source global-local model for epidemic management.

PloS one·2022
Same author

What Drives Bitcoin? An Approach from Continuous Local Transfer Entropy and Deep Learning Classification Models.

Entropy (Basel, Switzerland)·2021
Same author

Measuring information flux between social media and stock prices with Transfer Entropy.

PloS one·2021
Same author

Transfer entropy as a variable selection methodology of cryptocurrencies in the framework of a high dimensional predictive model.

PloS one·2020
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 Experiment Video

Updated: Nov 9, 2025

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

14.8K

Multistage allocation problem for Mexican pension funds.

Andrés García-Medina1,2, Norberto A Hernández-Leandro2, Graciela González Farías3

  • 1Consejo Nacional de Ciencia y Tecnología, Ciudad de México, México.

Plos One
|April 13, 2021
PubMed
Summary
This summary is machine-generated.

Target Date Fund (TDF) strategies applied to Mexican pension systems show similar investment glide-paths across various forecasting models. The GARCH(1,1) model with a fixed covariance matrix offered the best risk-return trade-off.

More Related Videos

Semi-Targeted Ultra-High-Performance Chromatography Coupled to Mass Spectrometry Analysis of Phenolic Metabolites in Plasma of Elderly Adults
14:39

Semi-Targeted Ultra-High-Performance Chromatography Coupled to Mass Spectrometry Analysis of Phenolic Metabolites in Plasma of Elderly Adults

Published on: April 22, 2022

4.1K
Grafting Multiwalled Carbon Nanotubes with Polystyrene to Enable Self-Assembly and Anisotropic Patchiness
11:09

Grafting Multiwalled Carbon Nanotubes with Polystyrene to Enable Self-Assembly and Anisotropic Patchiness

Published on: April 1, 2018

8.3K

Related Experiment Videos

Last Updated: Nov 9, 2025

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

14.8K
Semi-Targeted Ultra-High-Performance Chromatography Coupled to Mass Spectrometry Analysis of Phenolic Metabolites in Plasma of Elderly Adults
14:39

Semi-Targeted Ultra-High-Performance Chromatography Coupled to Mass Spectrometry Analysis of Phenolic Metabolites in Plasma of Elderly Adults

Published on: April 22, 2022

4.1K
Grafting Multiwalled Carbon Nanotubes with Polystyrene to Enable Self-Assembly and Anisotropic Patchiness
11:09

Grafting Multiwalled Carbon Nanotubes with Polystyrene to Enable Self-Assembly and Anisotropic Patchiness

Published on: April 1, 2018

8.3K

Area of Science:

  • Financial Economics
  • Pension Fund Management
  • Quantitative Finance

Background:

  • The Mexican pension system operates under a specific regulatory framework influencing investment strategies.
  • Target Date Funds (TDFs) are increasingly utilized for retirement planning, requiring robust allocation models.
  • Multistage allocation problems necessitate sophisticated approaches to manage risk and return over time.

Purpose of the Study:

  • To solve the multistage allocation problem for the Mexican pension system using TDF strategies.
  • To analyze investment trajectories (glide-paths) across 14 heterogeneous assets over a 161-quarter horizon.
  • To evaluate the impact of different forecasting models and covariance matrix estimations on TDF performance.

Main Methods:

  • Employed Target Date Fund (TDF) strategy within regulatory constraints.
  • Estimated expected returns using GARCH(1,1), EGARCH(1,1), and GJR-GARCH(1,1) models.
  • Utilized a stationary block bootstrap as a benchmark and assessed fixed historical and DCC-GARCH(1,1) covariance matrices.
  • Quantified asymmetric dependencies using transfer entropy.

Main Results:

  • Observed highly similar glide-paths across various forecasting models, indicating robustness of the TDF structure.
  • Identified the GARCH(1,1) model with a fixed historical covariance matrix as yielding the highest Sharpe ratio.
  • Confirmed that glide-paths transition from risky assets to bonds over time, as expected.

Conclusions:

  • The proposed methodology is computationally efficient and suitable for realistic TDF implementation in pension systems.
  • Investment strategy structure remains consistent regardless of the specific forecasting model used.
  • Optimal risk-return trade-off achieved with GARCH(1,1) and a fixed covariance matrix highlights its effectiveness.