Lobachevskii Journal of Mathematics最新文献_第10页

Corrected Triple Correction Method, CNN and Transfer Learning for Prediction the Realized Volatility of Bitcoin and E-Mini S&P500 预测比特币和 E-Mini S&P500 实际波动率的修正三重校正法、CNN 和迁移学习法

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Lobachevskii Journal of Mathematics Pub Date : 2024-07-19 DOI: 10.1134/s1995080224600705

V. A. Manevich

{"title":"Corrected Triple Correction Method, CNN and Transfer Learning for Prediction the Realized Volatility of Bitcoin and E-Mini S&P500","authors":"V. A. Manevich","doi":"10.1134/s1995080224600705","DOIUrl":"https://doi.org/10.1134/s1995080224600705","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>Compares ARMA models, boosting, neural network models, HAR_RV models and proposes a new method for predicting one day ahead realized volatility of financial series. HAR_RV models are taken as compared classical volatility prediction models. In addition, the phenomenon of transfer learning for boosting and neural network models is investigated. Bitcoin and E-mini S&P500 are chosen as examples. The realized volatility is calculated based on intraday (intraday—24 hours) data. The calculation is based on the closing values of the internal five-minute intervals. Comparisons are made both within and between the two intervals. The intervals considered are January 1, 2018–January 1, 2022 and January 1, 2018–April 2, 2023. Since there were structural changes in the markets during these intervals, the models are estimated in sliding windows of 399 days length. For each time series, we compare three-parameter enumeration boosting, about 10 different neural network architectures, ARMA models, the newly proposed CTCM method, and various training transfer and training sample expansion options. It is shown that ARMA and HAR_RV models are generally inferior to other listed methods and models. The CTCM model and neural networks of CNN architecture are the most suitable for financial time series forecasting and show the best results. Although transfer learning shows no improvement in terms of forecast precision and yields little decline. It requires more extensive and detailed study. The smallest MAPEs for Bitcoin and E-mini S&P500 realized volatility forecasts are achieved by the newly proposed CTCM model and are 21.075%, 25.311% on the first interval and 21.996%, 26.549% on the second interval, respectively.</p>","PeriodicalId":46135,"journal":{"name":"Lobachevskii Journal of Mathematics","volume":"25 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141743918","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Concentration of Measure and Global Optimization of Bayesian Multilayer Perceptron. Part I 贝叶斯多层感知器的集中测量和全局优化。第一部分

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Lobachevskii Journal of Mathematics Pub Date : 2024-07-19 DOI: 10.1134/s1995080224600651

B. K. Temyanov, R. R. Nigmatullin

引用次数: 0

Normal Extensions of Differential Operators for Degenerate First-order 畸变一阶微分算子的正态扩展

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Lobachevskii Journal of Mathematics Pub Date : 2024-07-19 DOI: 10.1134/s1995080224600882

M. Sertbaş, F. Yılmaz

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Delay in Solving Autonomous Singularly Perturbed Equations Near an Unstable Equilibrium Position 在不稳定平衡位置附近求解自主奇异扰动方程的延迟

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Lobachevskii Journal of Mathematics Pub Date : 2024-07-19 DOI: 10.1134/s1995080224600791

K. S. Alybaev, A. M. Juraev, M. N. Nurmatova

引用次数: 0

Determining a Source Function in the Mixed Parabolic–Hyperbolic Equation with Characteristic Type Change Line 确定具有特征类型变化线的抛物线-双曲混合方程中的源函数

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Lobachevskii Journal of Mathematics Pub Date : 2024-07-19 DOI: 10.1134/s1995080224600584

D. K. Durdiev, D. A. Toshev, H. H. Turdiev

引用次数: 0

A Large-update Primal-dual Interior-point Algorithm for Convex Quadratic Optimization Based on a New Bi-parameterized Bi-hyperbolic Kernel Function 基于新的双参数化双双曲核函数的凸二次方优化大更新原点-双内部点算法

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Lobachevskii Journal of Mathematics Pub Date : 2024-07-19 DOI: 10.1134/s1995080224600560

Youssra Bouhenache, Wided Chikouche, Imene Touil

{"title":"A Large-update Primal-dual Interior-point Algorithm for Convex Quadratic Optimization Based on a New Bi-parameterized Bi-hyperbolic Kernel Function","authors":"Youssra Bouhenache, Wided Chikouche, Imene Touil","doi":"10.1134/s1995080224600560","DOIUrl":"https://doi.org/10.1134/s1995080224600560","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>We present a polynomial-time primal-dual interior-point algorithm (IPA) for solving convex quadratic optimization (CQO) problems, based on a bi-parameterized bi-hyperbolic kernel function (KF). The growth term is a combination of the classical quadratic term and a hyperbolic one depending on a parameter <span>(pin[0,1],)</span> while the barrier term is hyperbolic and depends on a parameter <span>(qgeqfrac{1}{2}sinh 2.)</span> Using some simple analysis tools, we prove with a special choice of the parameter <span>(q,)</span> that the worst-case iteration bound for the new corresponding algorithm is <span>(textbf{O}big{(}sqrt{n}log nlogfrac{n}{epsilon}big{)})</span> iterations for large-update methods. This improves the result obtained in (Optimization <b>70</b> (8), 1703–1724 (2021)) for CQO problems and matches the currently best-known iteration bound for large-update primal-dual interior-point methods (IPMs). Numerical tests show that the parameter <span>(p)</span> influences also the computational behavior of the algorithm although the theoretical iteration bound does not depends on this parameter. To our knowledge, this is the first bi-parameterized bi-hyperbolic KF-based IPM introduced for CQO problems, and the first KF that incorporates a hyperbolic function in its growth term while all KFs existing in the literature have a polynomial growth term exepct the KFs proposed in (Optimization <b>67</b> (10), 1605–1630 (2018)) and (J. Optim. Theory Appl. <b>178</b>, 935–949 (2018)) which have a trigonometric growth term.</p>","PeriodicalId":46135,"journal":{"name":"Lobachevskii Journal of Mathematics","volume":"24 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141746169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Note on Class of Weibull–Pareto Distribution 关于 Weibull-Pareto 分布类别的说明

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Lobachevskii Journal of Mathematics Pub Date : 2024-05-14 DOI: 10.1134/s1995080224600213

Adil Rashid, Zahoor Ahmad, Aafaq A. Rather, Irfan Ali

引用次数: 0

Heterogeneity Measure in Meta-analysis without Study-specific Variance Information 没有特定研究方差信息的 Meta 分析中的异质性测量方法

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Lobachevskii Journal of Mathematics Pub Date : 2024-05-14 DOI: 10.1134/s1995080224600262

P. Sangnawakij, R. Sittimongkol

{"title":"Heterogeneity Measure in Meta-analysis without Study-specific Variance Information","authors":"P. Sangnawakij, R. Sittimongkol","doi":"10.1134/s1995080224600262","DOIUrl":"https://doi.org/10.1134/s1995080224600262","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>Assessing heterogeneity between the independent studies in a meta-analysis plays a critical role in quantifying the amount of dispersion. The well-known Higgins’ I2 statistic has been used most often for measuring heterogeneity. However, the problem of the within-study variances involved in this measure is discussed, which leads to misinterpretation. Alternatively, the between-study coefficient of variation, the ratio of the standard deviation of the random effects to the effect, is of interest. This current work is motivated by meta-analytic data on continuous outcomes reported only the sample means and sample sizes. No sampling variance estimate is available in the studies. In such a case, we introduce the mean difference estimator based on the profile likelihood and bootstrap methods and propose the coefficient of variation estimator for measuring the heterogeneity of the mean differences. The statistical power of the coefficient of variation is determined based on simulations. The results indicate that the estimated between-study coefficient of variation derived from maximum profile likelihood estimation has a lower bias than that obtained from bootstrap estimation. The Wald-type confidence interval using variance estimation derived from the delta method provides a suitable coverage probability and has a short length interval.</p>","PeriodicalId":46135,"journal":{"name":"Lobachevskii Journal of Mathematics","volume":"218 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140941829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mathematical Model for Dynamic Adsorption with Immiscible Multiphase Flows in Three-dimensional Porous Media 三维多孔介质中不相溶多相流的动态吸附数学模型

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Lobachevskii Journal of Mathematics Pub Date : 2024-05-14 DOI: 10.1134/s1995080224600134

T. R. Zakirov, O. S. Zhuchkova, M. G. Khramchenkov

{"title":"Mathematical Model for Dynamic Adsorption with Immiscible Multiphase Flows in Three-dimensional Porous Media","authors":"T. R. Zakirov, O. S. Zhuchkova, M. G. Khramchenkov","doi":"10.1134/s1995080224600134","DOIUrl":"https://doi.org/10.1134/s1995080224600134","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>In this paper, we present the mathematical model describing the dynamic adsorption processes in three-dimensional porous media. The novelty of this model lies in the ability to study the mass transfer processes with immiscible multiphase flows in porous media. The governing equations describing fluid flow and convective-diffusion of the active component are based on the lattice Boltzmann equations. The phenomena on the interface between two fluids and between fluids and solid phase, including interfacial tension and wetting effects, are described using the most modern version of the color-gradient method. The kinetic of the mass transfer between active component and adsorbent particles is described using the Langmuir adsorption equation. The numerical algorithm has been validated on two benchmarks including the immiscibility of the active component and the displaced fluid, as well as the problem of mass conservation of the active component during its adsorption and transport in porous media. The mathematical model has been adapted for porous media presented by X-ray computed tomography images of natural porous media.</p>","PeriodicalId":46135,"journal":{"name":"Lobachevskii Journal of Mathematics","volume":"17 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140936082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Two Phase Adaptive Cluster Sampling Under Transformed Population Approach 变换种群法下的两阶段自适应聚类抽样

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Lobachevskii Journal of Mathematics Pub Date : 2024-05-14 DOI: 10.1134/s1995080224600237

Yashpal Singh Raghav, Rajesh Singh, Rohan Mishra, Abdullah Ali H. Ahmadini, Nitesh Kumar Adichwal, Irfan Ali

引用次数: 0