Related Experiment Video

Updated: Jul 11, 2026

Reporter-based Growth Assay for Systematic Analysis of Protein Degradation
07:47

Reporter-based Growth Assay for Systematic Analysis of Protein Degradation

Published on: November 6, 2014

Need to Meet Investment Goals? Track Synthetic Indexes with the SDDP Method

Lorenzo Reus1, Rodolfo Prado2

  • 1Escuela de Negocios, Universidad Adolfo Ibañez, Diagonal Las Torres, 2640 Santiago, Chile.

Computational Economics
|July 7, 2021
PubMed

Keywords:
ALMDynamic asset allocationETFIndex trackingJuliaSDDP

More Related Videos

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

A Hydrogen-Deuterium Exchange Mass Spectrometry (HDX-MS) Platform for Investigating Peptide Biosynthetic Enzymes11:32

A Hydrogen-Deuterium Exchange Mass Spectrometry (HDX-MS) Platform for Investigating Peptide Biosynthetic Enzymes

Published on: May 4, 2020

Related Concept Videos

Standard Deviation01:10

Standard Deviation

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...
Calculating Standard Deviation01:08

Calculating Standard Deviation

The standard deviation is the most common measure of variation. It is a value that tells us how far a data value is from the mean value in a dataset. Further, the standard deviation is always a positive value or zero.
The standard deviation value is small when all the data is concentrated close to the mean. Here the data exhibits low variation. The standard deviation value is larger when the data values are more spread out from the mean. Here, the data displays high variation.       
Let us...
Standard Deviation of Calculated Results01:14

Standard Deviation of Calculated Results

Standard deviation measures the spread of data around the mean value. Many large data sets follow a Gaussian distribution, also known as a normal distribution. This distribution is bell-shaped curved, with the most frequently observed value (mean or central value) in the middle. The farther away from the central value, the greater the deviation from the central value, and the lower the frequency.
A broad Gaussian distribution curve has a wider standard deviation, representing a data set with...
Field Procedure for Staking Out Curves01:26

Field Procedure for Staking Out Curves

Staking out curves is an essential process in construction to ensure the accurate alignment of structures along a curved path. This task involves positioning stakes at calculated locations corresponding to the curve's design, effectively translating plans into physical markers in the field. The process begins by determining the geometric parameters of the curve, including the radius, central angle, and tangent distances. These parameters are critical for identifying key points such as the Point...
First Derivative Test: Problem Solving01:25

First Derivative Test: Problem Solving

Imagine an asset price that crashes to a low point, rebounds sharply as bargain-hunters step in, and then gradually declines. Such behavior can be modeled with a smooth function whose turning points represent locally overvalued and undervalued regions. A convenient example that captures rebound followed by decay is:The high and low points of this curve are identified using the first derivative test, which determines where the function changes from increasing to decreasing or vice versa. To...
Synthetic Disvision of Polynomials01:28

Synthetic Disvision of Polynomials

Synthetic division is an efficient algorithmic approach for dividing a polynomial by a linear binomial of the form x - c, where c is a real number. This method is helpful due to its streamlined process, which avoids the more cumbersome steps involved in the traditional long division of polynomials. It simplifies computation and serves as a practical tool for evaluating polynomials and identifying their factors.To perform synthetic division, one begins by listing the coefficients of the...