Sentence examples for variance optimization from inspiring English sources

We solve the dual [ 44] of the variance optimization problem mentioned above.

Open-loop simulations of a two-phase synthetic reservoir demonstrate that TE methods may significantly improve short-term risk measures such as expected return, standard deviation and conditional value-at-risk compared to nominal, robust and mean-variance optimization.

Roger Ibbotson's data goes back to 1925 and these are the actual numbers we used when we first started doing our mean-variance optimization in our simulations, trying to come to conclusions about what the appropriate allocations would be for Yale's portfolio.

In fact, Markowitz's mean-variance optimization, also known as the "efficient frontier," is embedded in most software that financial advisors use to create portfolios today.

Portfolio construction methodologies based on mean-variance optimization are ultimately inspired by the Nobel Prize-winning research of Harry Markowitz and others.

It had a good run, gaining popularity in the 1970s and 80s as a shorthand for the mean-variance optimization model that came out of Nobel prize-winning modern portfolio theory (MPT) in the 1950s.

The solution to the two-period mean-variance optimization problem of maximizing U as given by Eq. (9) subject to the constraints (10) and (11) is given by two mean-variance efficient portfolios in the two periods satisfying Eqs.

This paper presents a novel iterative procedure augmented by electromagnetic transient type simulations and the state of the art mean variance mapping optimization algorithm.

The variance weighed optimization procedure developed by van der Heijden et al. (1994) was used to test elemental recovery and subsequently to reconcile the measured primary fermentation data, based on elemental balancing; it was also used to calculate the biomass-specific uptake and production rates.

This chapter presents a mean-variance portfolio optimization analysis that develops and evaluates optimal EU electricity generating mixes for 2020.

In order to account for the effect of uncertainty in the model parameters, mean-variance robust optimization is performed, allowing a trade-off between performance and robustness.