This study investigates the performance of Bitcoin as a diversifier under different
constraining portfolio optimization frameworks. The study employs different constraining …

This paper presents an efficient inverse global optimization approach for damage
identification of plate-like structures. In this approach, the damage identification process is …

Portfolio optimization is the process of allocating capital among a universe of assets to
achieve better risk–return trade-off. Due to the dynamic nature of financial markets, the …

In the modern era, one of the fundamental trading components of any country is its stock
market. Generally, it is the benchmark used to gauge the health of the country's economy …

The adoption of models based on key performance indicators to diagnose and evaluate the
competitiveness of companies has been presented as a trend in the operations' …

The term “price manipulation” is used to describe the actions of “rogue” traders who employ
carefully designed trading tactics to incur equity prices up or down to make profit. Such …

Geared toward the problems of predicting the unsteadily changing single oil well production
in water flooding reservoir, a machine learning model based on CNN (convolutional neural …

Dynamic environments are still a big challenge for optimization algorithms. In this paper, a
Genetic Algorithm using both Multiploid representation and the Bayesian Decision method is …

In this paper, an enhanced genetic algorithm (ERGA), based on memory updating and
environment reaction schemes, has been proposed to solve constrained knapsack problems …

This paper deals with the productivity index based on Hicks-Moorsteen (HM) productivity
index for analysis of Stock Exchange firms. In this paper, a decomposition of Hicks …