scholarly journals Option Portfolio Selection with Generalized Entropic Portfolio Optimization

Entropy ◽  
2020 ◽  
Vol 22 (8) ◽  
pp. 805
Author(s):  
Peter Joseph Mercurio ◽  
Yuehua Wu ◽  
Hong Xie
Keyword(s):  
Growth Rate ◽  
Portfolio Optimization ◽  
Portfolio Selection ◽  
Kelly Criterion ◽  
Optimization Framework ◽  
Wide Range ◽  
Option Strategies ◽  
Real Market ◽  
Efficient Option ◽  
Ideal Method

In this third and final paper of our series on the topic of portfolio optimization, we introduce a further generalized portfolio selection method called generalized entropic portfolio optimization (GEPO). GEPO extends discrete entropic portfolio optimization (DEPO) to include intervals of continuous returns, with direct application to a wide range of option strategies. This lays the groundwork for an adaptable optimization framework that can accommodate a wealth of option portfolios, including popular strategies such as covered calls, married puts, credit spreads, straddles, strangles, butterfly spreads, and even iron condors. These option strategies exhibit mixed returns: a combination of discrete and continuous returns with performance best measured by portfolio growth rate, making entropic portfolio optimization an ideal method for option portfolio selection. GEPO provides the mathematical tools to select efficient option portfolios based on their growth rate and relative entropy. We provide an example of GEPO applied to real market option portfolio selection and demonstrate how GEPO outperforms traditional Kelly criterion strategies.

scholarly journals Portfolio Optimization for Binary Options Based on Relative Entropy

Entropy ◽  
2020 ◽  
Vol 22 (7) ◽  
pp. 752 ◽  
Author(s):  
Peter Joseph Mercurio ◽  
Yuehua Wu ◽  
Hong Xie
Keyword(s):  
Portfolio Optimization ◽  
Portfolio Selection ◽  
Relative Entropy ◽  
Asset Allocation ◽  
Optimization Problem ◽  
General Setting ◽  
Short Term ◽  
Kelly Criterion ◽  
Portfolio Returns ◽  
Binary Options

The portfolio optimization problem generally refers to creating an investment portfolio or asset allocation that achieves an optimal balance of expected risk and return. These portfolio returns are traditionally assumed to be continuous random variables. In An Entropy-Based Approach to Portfolio Optimization, we introduced a novel non-parametric optimization method based on Shannon entropy, called return-entropy portfolio optimization (REPO), which offers a simple and fast optimization algorithm for assets with continuous returns. Here, in this paper, we would like to extend the REPO approach to the optimization problem for assets with discrete distributed returns, such as those from a Bernoulli distribution like binary options. Under a discrete probability distribution, portfolios of binary options can be viewed as repeated short-term investments with an optimal buy/sell strategy or general betting strategy. Upon the outcome of each contract, the portfolio incurs a profit (success) or loss (failure). This is similar to a series of gambling wagers. Portfolio selection under this setting can be formulated as a new optimization problem called discrete entropic portfolio optimization (DEPO). DEPO creates optimal portfolios for discrete return assets based on expected growth rate and relative entropy. We show how a portfolio of binary options provides an ideal general setting for this kind of portfolio selection. As an example we apply DEPO to a portfolio of short-term foreign exchange currency pair binary options from the NADEX exchange platform and show how it outperforms leading Kelly criterion strategies. We also provide an additional example of a gambling application using a portfolio of sports bets over the course of an NFL season and present the advantages of DEPO over competing Kelly criterion strategies.

Dependence of Microstructures and Mechanical Properties on the Growth Rate and Composition in Directionally Solidified Mg-Gd Alloys

2022 ◽  
Vol 327 ◽  
pp. 82-97
Author(s):  
He Qin ◽  
Guang Yu Yang ◽  
Shi Feng Luo ◽  
Tong Bai ◽  
Wan Qi Jie
Keyword(s):  
Mechanical Properties ◽  
Growth Rate ◽  
Tensile Strength ◽  
Ultimate Tensile Strength ◽  
Dendritic Structure ◽  
Directionally Solidified ◽  
Dendrite Morphology ◽  
Microstructural Parameters ◽  
Wide Range ◽  
Microstructures And Mechanical Properties

Microstructures and mechanical properties of directionally solidified Mg-xGd (5.21, 7.96 and 9.58 wt.%) alloys were investigated at a wide range of growth rates (V = 10-200 μm/s) under the constant temperature gradient (G = 30 K/mm). The results showed that when the growth rate was 10 μm/s, different interface morphologies were observed in three tested alloys: cellular morphology for Mg-5.21Gd alloy, a mixed morphology of cellular structure and dendritic structure for Mg-7.96Gd alloy and dendrite morphology for Mg-9.58Gd alloy, respectively. Upon further increasing the growth rate, only dendrite morphology was exhibited in all experimental alloys. The microstructural parameters (λ1, λ2) decreased with increasing the growth rate for all the experimental alloy, and the measured λ1 and λ2 values were in good agreement with Trivedi model and Kattamis-Flemings model, respectively. Vickers hardness and the ultimate tensile strength increased with the increase of the growth rate and Gd content, while the elongation decreased gradually. Furthermore, the relationships between the hardness, ultimate tensile strength, the growth rate and the microstructural parameters were discussed and compared with the previous experimental results.

Study of the low cycle fatigue of 12Cr18Ni10Ti steel based on fractal analysis and artificial intelligence approaches

2021 ◽  
Vol 87 (9) ◽  
pp. 59-67
Author(s):  
A. A. Khlybov ◽  
Yu. G. Kabaldin ◽  
M. S. Anosov ◽  
D. A. Ryabov ◽  
D. A. Shatagin
Keyword(s):  
Neural Network ◽  
Growth Rate ◽  
Fractal Dimension ◽  
Low Temperatures ◽  
Main Crack ◽  
Fatigue Loading ◽  
Wide Range ◽  
Lower Temperature ◽  
Number Of Cycles ◽  
Dimension Index

The evolution of the structure and assessment of the age limit of steel 12Cr18Ni10Ti upon fatigue loading is considered using neural network modeling and approaches of fractal analysis of the microstructure. An algorithm for processing images of the microstructures has been developed to improve their quality. An indicator of the fractal dimension of the image is used as a quantitative indicator for assessing the evolution of the microstructure of the surface metal layer. A quantitative assessment of the structures at different stress amplitudes is carried out in a wide range of low temperatures using the fractal dimension index. Correlation of the fractal dimension index with the run of the sample material is shown. The appearance of the main crack was observed in the range of 0.7 - 0.8 from the number of cycles to failure, after which the crack growth rate increased. At a lower temperature, the main crack is formed later, but further loading results in a higher crack growth rate. Formation of the secondary phases in austenitic steel at a lower temperature occurred at earlier stages than that at a temperature of t = +20°C, which led to hardening of the material. An artificial neural network (ANN) has been developed and trained for assessing structural changes in metal proceeding from the fractal dimensionality of the microstructure images at different stages of fatigue loading. The developed neural network made it possible to estimate with a sufficiently high accuracy the number of cycles before damage of the sample and the residual life of the material. Thus, the developed ANN can be used to assess the current state of the material in a wide range of low temperatures.

Portfolio optimization using the generalized reduced gradient nonlinear algorithm

2016 ◽  
Vol 9 (4) ◽  
pp. 570-582 ◽  
Author(s):  
Dima Waleed Hanna Alrabadi
Keyword(s):  
Portfolio Optimization ◽  
Stock Exchange ◽  
Arab World ◽  
Content Type ◽  
Optimization Framework ◽  
Monthly Return ◽  
Reduced Gradient ◽  
The Mean ◽  
Generalized Reduced Gradient ◽  
Mean Variance

Purpose This study aims to utilize the mean–variance optimization framework of Markowitz (1952) and the generalized reduced gradient (GRG) nonlinear algorithm to find the optimal portfolio that maximizes return while keeping risk at minimum. Design/methodology/approach This study applies the portfolio optimization concept of Markowitz (1952) and the GRG nonlinear algorithm to a portfolio consisting of the 30 leading stocks from the three different sectors in Amman Stock Exchange over the period from 2009 to 2013. Findings The selected portfolios achieve a monthly return of 5 per cent whilst keeping risk at minimum. However, if the short-selling constraint is relaxed, the monthly return will be 9 per cent. Moreover, the GRG nonlinear algorithm enables to construct a portfolio with a Sharpe ratio of 7.4. Practical implications The results of this study are vital to both academics and practitioners, specifically the Arab and Jordanian investors. Originality/value To the best of the author’s knowledge, this is the first study in Jordan and in the Arab world that constructs optimum portfolios based on the mean–variance optimization framework of Markowitz (1952) and the GRG nonlinear algorithm.

Latitude and Relative Growth in the Razor Clam, Siliqua Patula

1931 ◽  
Vol 8 (3) ◽  
pp. 228-249
Author(s):  
F. W. WEYMOUTH ◽  
H. C. McMILLIN ◽  
WILLIS H. RICH
Keyword(s):  
Growth Rate ◽  
Life Span ◽  
Relative Growth Rate ◽  
Growth Data ◽  
Natural Conditions ◽  
Relative Growth ◽  
Absolute Growth Rate ◽  
Mathematical Expressions ◽  
Wide Range ◽  
Absolute Growth

1. The present paper is a study of the growth of a clam (Siliqua patula) under natural conditions and over a wide range of latitude. 2. Various constants derived from the growth data are compared for the different localities. For this species, over the range considered, growth in the southern localities as compared with the northern is initially more rapid but less sustained, leads to a smaller total length and is associated with a shorter life span. 3. Reasons are presented for considering the relative growth-rate as a particularly significant constant leading to more sound biological conclusions than the use of the absolute growth-rate. 4. On the basis of the relative growth-rate, current mathematical expressions for the course of growth are discussed and a formula used which emphasises Minot's conception of a growth-rate constantly declining with age. This expression L = Be-ce-ce-kt, in which L = length at time t, e = base of natural logarithms, and B, c and k are constants, is found to graduate the extensive data in clam growth with significant accuracy.

Microbial community composition is linked to Sphagnum acclimation to warming

2021 ◽  
Author(s):  
Tatjana Živković ◽  
Alyssa A Carell ◽  
Gustaf Granath ◽  
Mats B Nilsson ◽  
Manuel Helbig ◽  
...  
Keyword(s):  
Growth Rate ◽  
Host Plant ◽  
Climate Warming ◽  
Elevated Temperatures ◽  
Critical Role ◽  
Temperature Acclimation ◽  
Microbial Interactions ◽  
Germ Free ◽  
Wide Range ◽  
Thermal Origin

<p>Peatlands store about third of the terrestrial carbon (C) and exert long-term climate cooling. Dominant plant genera in acidic peatlands, <em>Sphagnum</em> mosses, are main contributors to net primary productivity. Through associative relationships with diverse microbial organisms (microbiome), <em>Sphagnum</em> mosses control major biogeochemical processes, namely uptake, storage and potential release of carbon and nitrogen. Climate warming is expected to negatively impact C accumulation in peatlands and alter nutrient cycling, however <em>Sphagnum</em>-dominated peatland resilience to climate warming may depend on <em>Sphagnum</em>-microbiome associations. The ability of the microbiome to rapidly acclimatize to warming may aid <em>Sphagnum</em> exposed to elevated temperatures through host-microbiome acquired thermotolerance. We investigated the role of the microbiome on <em>Sphagnum</em>’s ability to acclimate to elevated temperatures using a microbiome-transfer approach to test: a) whether the thermal origin of the microbiome influences acclimation of <em>Sphagnum</em> growth and b) if microbial benefits to <em>Sphagnum</em> growth depend on donor <em>Sphagnum</em> species.</p><p>            Using a full-factorial design, microbiomes were separated from <em>Sphagnum</em> “donor” species from four different peatlands across a wide range of thermal environments (11.4-27°C). The microbiomes were transferred onto germ-free “recipient” <em>Sphagnum</em> species in the laboratory and exposed to a range of experimental temperatures (8.5 – 26.5°C) for growth analysis over 4 weeks.</p><p>            Normalized growth rates were maximized for plants that received a microbiome from a matched “donor” and with a similar origin temperature (ΔT<sub>treatment-origin</sub>: 0.3±0.9°C [±standard error], p = 0.73). For non-matched “donor-recipient” <em>Sphagnum</em> pairs, ΔT<sub>treatment-origin</sub> was slightly negative with -4.1±2.1°C (p = 0.06). The largest growth rate of the “recipient” was measured when grown with a microbiome from a matching “donor” <em>Sphagnum</em> species and was 252% and 48% larger than the maximum growth rate of the germ-free <em>Sphagnum</em> and the non-matched “donor-recipient” <em>Sphagnum</em> pairs, respectively.</p><p>            Our results suggest that the composition of the <em>Sphagnum</em> microbiome plays a critical role in host plant temperature acclimation. We found that microbially-provided benefits to the host plant were most pronounced when: 1) the thermal origin of the microbiome is similar to experimental temperatures, and 2) when donor and recipient <em>Sphagnum</em> species are the same. Together, these results suggest that <em>Sphagnum</em> temperature acclimation can be modulated, in part, by microbial interactions and may potentially play a role in peatland resilience to climate warming.</p>

Portfolio Optimization and Asset Allocation With Metaheuristics

2021 ◽  
pp. 78-96
Author(s):  
Jhuma Ray ◽  
Siddhartha Bhattacharyya ◽  
N. Bhupendro Singh
Keyword(s):  
Portfolio Optimization ◽  
Portfolio Selection ◽  
Asset Allocation ◽  
Value At Risk ◽  
Optimal Allocation ◽  
Short Note ◽  
Objective Functions ◽  
Cardinality Constraints ◽  
Distribution Of Wealth ◽  
Risk Optimization

Portfolio optimization stands to be an issue of finding an optimal allocation of wealth to place within the obtainable assets. Markowitz stated the problem to be structured as dual-objective mean-risk optimization, pointing the best trade-off solutions within a portfolio between risks which is measured by variance and mean. Thus the major intention was nothing else than hunting for optimum distribution of wealth over a specific amount of assets by diminishing risk and maximizing returns of a portfolio. Value-at-risk, expected shortfall, and semi-variance measures prove to be complex for measuring risk, for maximization of skewness, liquidity, dividends by added objective functions, cardinality constraints, quantity constraints, minimum transaction lots, class constraints in real-world constraints all of which are incorporated in modern portfolio selection models, furnish numerous optimization challenges. The emerging portfolio optimization issue turns out to be extremely tough to be handled with exact approaches because it exhibits nonlinearities, discontinuities and high-dimensional, efficient boundaries. Because of these attributes, a number of researchers got motivated in researching the usage of metaheuristics, which stand to be effective measures for finding near optimal solutions for tough optimization issues in an adequate computational time frame. This review report serves as a short note on portfolio optimization field with the usage of Metaheuristics and finally states that how multi-objective metaheuristics prove to be efficient in dealing with portfolio selection problems with complex measures of risk defining non-convex, non-differential objective functions.

scholarly journals Magnetic Rayleigh–Taylor instability at a contact discontinuity with an oblique magnetic field

2020 ◽  
Vol 634 ◽  
pp. A96
Author(s):  
E. Vickers ◽  
I. Ballai ◽  
R. Erdélyi
Keyword(s):  
Magnetic Field ◽  
Growth Rate ◽  
Dispersion Relation ◽  
Contact Discontinuity ◽  
Homogeneous Magnetic Field ◽  
Taylor Instability ◽  
Wide Range ◽  
Rayleigh Taylor Instability ◽  
The Magnetic Field ◽  
Theoretical Results

Aims. We investigate the nature of the magnetic Rayleigh–Taylor instability at a density interface that is permeated by an oblique homogeneous magnetic field in an incompressible limit. Methods. Using the system of linearised ideal incompressible magnetohydrodynamics equations, we derive the dispersion relation for perturbations of the contact discontinuity by imposing the necessary continuity conditions at the interface. The imaginary part of the frequency describes the growth rate of waves due to instability. The growth rate of waves is studied by numerically solving the dispersion relation. Results. The critical wavenumber at which waves become unstable, which is present for a parallel magnetic field, disappears because the magnetic field is inclined. Instead, waves are shown to be unstable for all wavenumbers. Theoretical results are applied to diagnose the structure of the magnetic field in prominence threads. When we apply our theoretical results to observed waves in prominence plumes, we obtain a wide range of field inclination angles, from 0.5° up to 30°. These results highlight the diagnostic possibilities that our study offers.

Analysis of Part Electric Gas Turbine: A Novel Hybrid Propulsion Concept

2019 ◽  
Author(s):  
M. S. N. Murthy ◽  
Subhash Kumar ◽  
Sheshadri Sreedhara
Keyword(s):  
Gas Turbine ◽  
Electric Motor ◽  
Gas Turbines ◽  
Operating Conditions ◽  
Variable Speed ◽  
Hybrid Propulsion ◽  
Design Point ◽  
Part Load ◽  
Wide Range ◽  
Efficient Option

Abstract A gas turbine engine (GT) is very complex to design and manufacture considering the power density it offers. Development of a GT is also iterative, expensive and involves a long lead time. The components of a GT, viz compressor, combustor and turbine are strongly dependent on each other for the overall performance characteristics of the GT. The range of compressor operation is dependent on the functional and safe limits of surging and choking. The turbine operating speeds are required to be matched with that of compressor for wide range of operating conditions. Due to this constrain, design for optimum possible performance is often sacrificed. Further, once catered for a design point, gas turbines offer low part load efficiencies at conditions away from design point. As a more efficient option, a GT is practically achievable in a split configuration, where the compressor and turbine rotate on different shafts independently. The compressor is driven by a variable speed electric motor. The power developed in the combustor using the compressed air from the compressor and fuel, drives the turbine. The turbine provides mechanical shaft power through a gear box if required. A drive taken from the shaft rotates an electricity generator, which provides power for the compressor’s variable speed electric motor through a power bank. Despite introducing, two additional power conversions compared to a conventional GT, this split configuration named as ‘Part Electric Gas Turbine’, has a potential for new applications and to achieve overall better efficiencies from a GT considering the poor part load characteristics of a conventional GT.

Combustion Instabilities Damping System Development for Dry Low NOx Emissions Operability Enhancement of a Heavy-Duty Gas Turbine

2019 ◽  
Author(s):  
Matteo Cerutti ◽  
Nicola Giannini ◽  
Bruno Schuermans ◽  
Riccardo Brenci ◽  
Alessandro Marini ◽  
...  
Keyword(s):  
Growth Rate ◽  
Gas Turbine ◽  
Growth Rates ◽  
Fine Tuning ◽  
Optimized Design ◽  
Nox Emissions ◽  
Preliminary Design ◽  
Heavy Duty ◽  
Wide Range ◽  
Heavy Duty Gas Turbine

Abstract This paper describes the development phases of a damping system for combustion instability reduction in an annular type combustor for heavy-duty gas turbine applications. As reported by the authors in a previous paper, the full scale annular test rig allowed for an extensive characterization of the combustor with realistic acoustic boundaries at engine-relevant conditions. Emissions and operability assessment over a wide range of load conditions was performed, allowing the evaluation of the response of the system near the thermo-acoustic instability onset. The instability is quantified by its acoustic growth rate. This quantity is a crucial input in the design process of dampers. A methodology has been used to extract these growth rates form measured pulsation data. Experimentally determined growth rates have been evaluated for different fuel flow rate split between the main and the pilot injections, providing input to dampers preliminary design. Given current combustor architecture constraints, a first attempt configuration has been proposed and performances evaluated in the full annular rig. Dampers have been equipped with dynamic sensors and thermocouples with the purpose of measuring the growth rate abatement and the consequent NOx emissions reduction. A dedicated numerical toolbox, in-house developed by GE Power, has been used for both dampers preliminary design and growth rate reduction evaluation. Fine tuning of dampers elements as well as design assumptions adjustments required additional experimental evaluations and design iterations. Encouraged by the successful test in the concept phase, an optimized design for engine implementation was defined, that featured a significant increased damper volume, involving combustor parts re-design. The optimized configuration was finally tested in full annular rig and results demonstrated an important enhancement of operability while maintaining NOx emissions below the target levels.

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