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Article
From regression models to machine learning approaches for long term Bitcoin price forecast
We carry on a long term analysis for Bitcoin price, which is currently among the most renowned crypto assets available on markets other than Forex. In the last decade Bitcoin has been under spotlights among tr...
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Chapter and Conference Paper
On the Use of the SYMMBK Algorithm for Computing Negative Curvature Directions Within Newton–Krylov Methods
In this paper, we consider the issue of computing negative curvature directions, for nonconvex functions, within Newton–Krylov methods for large scale unconstrained optimization. This issue has been widely inv...
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Chapter and Conference Paper
Bitcoin Price Prediction: Mixed Integer Quadratic Programming Versus Machine Learning Approaches
Reliable Bitcoin price forecasts currently represent a challenging issue, due to the high volatility of this digital asset with respect to currencies in the Forex market. Since 2009 several models for Bitcoin ...
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Chapter and Conference Paper
An Improvement of the Pivoting Strategy in the Bunch and Kaufman Decomposition, Within Truncated Newton Methods
In this work we consider the solution of large scale (possibly nonconvex) unconstrained optimization problems. We focus on Truncated Newton methods which represent one of the commonest methods to tackle such p...
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Chapter
Krylov-Subspace Methods for Quadratic Hypersurfaces: A Grossone–based Perspective
We study the role of the recently introduced infinite number grossone, to deal with two renowned Krylov-subspace methods for symmetric (possibly indefinite) linear systems. We preliminarily explore the relationsh...
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Article
Open AccessA novel hybrid PSO-based metaheuristic for costly portfolio selection problems
In this paper we propose a hybrid metaheuristic based on Particle Swarm Optimization, which we tailor on a portfolio selection problem. To motivate and apply our hybrid metaheuristic, we reformulate the portfo...
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Article
Open AccessMURAME parameter setting for creditworthiness evaluation: data-driven optimization
In this paper, we amend a multi-criteria methodology known as MURAME, to evaluate the creditworthiness of a large sample of Italian Small and Medium-sized Enterprises, using as input their balance sheet data. ...
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Chapter and Conference Paper
Comparing RL Approaches for Applications to Financial Trading Systems
In this paper we present and implement different Reinforcement Learning (RL) algorithms in financial trading systems. RL-based approaches aim to find an optimal policy, that is an optimal map** between the v...
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Article
Open AccessIssues on the use of a modified Bunch and Kaufman decomposition for large scale Newton’s equation
In this work, we deal with Truncated Newton methods for solving large scale (possibly nonconvex) unconstrained optimization problems. In particular, we consider the use of a modified Bunch and Kaufman factoriz...
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Article
Open AccessIterative Grossone-Based Computation of Negative Curvature Directions in Large-Scale Optimization
We consider an iterative computation of negative curvature directions, in large-scale unconstrained optimization frameworks, needed for ensuring the convergence toward stationary points which satisfy second-or...
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Chapter and Conference Paper
How Grossone Can Be Helpful to Iteratively Compute Negative Curvature Directions
We consider an iterative computation of negative curvature directions, in large scale optimization frameworks. We show that to the latter purpose, borrowing the ideas in [1, 3] and [4], we can fruitfully pair the...
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Chapter
A PSO-Based Framework for Nonsmooth Portfolio Selection Problems
We propose a Particle Swarm Optimization (PSO) based scheme for the solution of a mixed-integer nonsmooth portfolio selection problem. To this end, we first reformulate the portfolio selection problem as an un...
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Article
Planar methods and grossone for the Conjugate Gradient breakdown in nonlinear programming
This paper deals with an analysis of the Conjugate Gradient (CG) method (Hestenes and Stiefel in J Res Nat Bur Stand 49:409–436, 1952), in the presence of degenerates on indefinite linear systems. Several approac...
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Chapter and Conference Paper
Quasi-Newton Based Preconditioning and Damped Quasi-Newton Schemes for Nonlinear Conjugate Gradient Methods
In this paper, we deal with matrix-free preconditioners for nonlinear conjugate gradient (NCG) methods. In particular, we review proposals based on quasi-Newton updates, and either satisfying the secant equati...
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Article
Conjugate Direction Methods and Polarity for Quadratic Hypersurfaces
We use some results from polarity theory to recast several geometric properties of Conjugate Gradient-based methods, for the solution of nonsingular symmetric linear systems. This approach allows us to pursue ...
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Article
Exploiting damped techniques for nonlinear conjugate gradient methods
In this paper we propose the use of damped techniques within Nonlinear Conjugate Gradient (NCG) methods. Damped techniques were introduced by Powell and recently reproposed by Al-Baali and till now, only appli...
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Article
Ram-pressure feeding of supermassive black holes
The majority of ‘jellyfish’ galaxies, characterized by long ‘tentacles’ of gas, also have active nuclei, indicating that gas is being fed to the central supermassive black hole by ram pressure.
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Article
A novel class of approximate inverse preconditioners for large positive definite linear systems in optimization
We propose a class of preconditioners for large positive definite linear systems, arising in nonlinear optimization frameworks. These preconditioners can be computed as by-product of Krylov-subspace solvers. Prec...
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Chapter and Conference Paper
Dense Orthogonal Initialization for Deterministic PSO: ORTHOinit+
This paper describes a novel initialization for Deterministic Particle Swarm Optimization (DPSO), based on choosing specific dense initial positions and velocities for particles. This choice tends to induce or...
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Article
A Framework of Conjugate Direction Methods for Symmetric Linear Systems in Optimization
In this paper, we introduce a parameter-dependent class of Krylov-based methods, namely Conjugate Directions \((CD)\) ...
