Neural network stochastic differential equation models with applications to financial data forecasting

Yang, Luxuan; Gao, Ting; Lu, Yubin; Duan, Jinqiao; Liu, Tao

doi:10.1016/j.apm.2022.11.001

Cited by 24 publications

(3 citation statements)

References 32 publications

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“…In the figure above, we see that the clustering was carried out according to the characteristics of films, namely: by genre, film rating, age limit, film duration, film format, and country code of the producer. It can also be noted that from the entire set of features in each cluster, one main feature was selected, namely: for the first cluster, the main feature is all films in 3D format, for the second cluster, the absence of films with an age limit of 18+, for the third cluster, films with the longest duration and the fourth cluster is characterized by films for the older generation [14].…”

Section: Research and Resultsmentioning

confidence: 99%

Methods of data analysis in the problem of optimizing the rental schedule

et al. 2023

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In this paper, the main problems of scheduling screenings for a cinema were considered. The activity of one cinema “X” is described and the restrictions that must be observed and taken into account when planning the schedule of sessions are analyzed. The solution to this problem is due to the complexity and time-consuming planning of the cinema schedule. To achieve this goal, the article analyzes the statistical data obtained in the cinema “X”. An analysis was carried out using the methods of statistical data analysis and predictive factors of movie attendance were identified, regression models of attendance were developed. Based on the developed regression models, statistical estimates of attendance predictive factors were obtained. Taking into account the results obtained, an optimization mathematical model for the formation of a rental schedule has been developed, which makes it possible to increase the box office of a cinema.

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Section: Research and Resultsmentioning

confidence: 99%

Methods of data analysis in the problem of optimizing the rental schedule

et al. 2023

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“…The three operational parameters that are commonly used in trading and measured in pips (a pip is the minimum variation that can occur in the price of a currency) with a numeric integer value in [5,300] are the following: • A stop-loss order is designed to limit an investor's loss on a position. • A take-profit order specifies the number of pips from the current price point to close out their current position for a profit.…”

Section: Chromosome Related To the Operation Of The Marketmentioning

confidence: 99%

“…The way of conducting this study can be classified as fundamental or technical analysis. Fundamental analysis (FA) studies the price of an asset from the point of view of the future evolution of its performance [5]. Technical analysis (TA) [6] is based mainly on a market action study through graphics.…”

Section: Introductionmentioning

confidence: 99%

Collaborative Multiobjective Evolutionary Algorithms in the Search of Better Pareto Fronts: An Application to Trading Systems

Soltero,

Fernández-Blanco,

Hidalgo

2023

Applied Sciences

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Technical indicators use graphic representations of datasets by applying various mathematical formulas to financial time series of prices. These formulas comprise a set of rules and parameters whose values are not necessarily known and depend on many factors, such as the market in which they operate, the size of the time window, and so on. This paper focuses on the real-time optimization of the parameters applied for analyzing time series of data. In particular, we optimize the parameters of some technical financial indicators. We propose the combination of several Multiobjective Evolutionary Algorithms. Unlike other approaches, this paper applies a set of different Multiobjective Evolutionary Algorithms, collaborating to construct a global Pareto Set of solutions. Solutions for financial problems seek high returns with minimal risk. The optimization process is continuous and occurs at the same frequency as the investment time interval. This technique permits the application of the non-dominated solutions obtained with different MOEAs at the same time. Experimental results show that Collaborative Multiobjective Evolutionary Algorithms obtain up to 22% of profit and increase the returns of the commonly used Buy and Hold strategy and other multi-objective strategies, even for daily operations.

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Averaging principle for Hilfer–Katugampola fractional stochastic differential equations

Huo,

Yang

2024

Math Methods in App Sciences

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In this paper, we mainly study the averaging principle for a class of Hifer–Katugampola fractional stochastic differential equations driven by standard Brownian motion. Firstly, we establish the existence and uniqueness of mild solution for the considered system using Banach contraction principle. Then, under suitable assumptions, we demonstrate that the solution to the original differential equations converges to that of the averaged differential equations in the sense of mean square and probability as the time scale goes to zero. Finally, an illustrative example is provided to verify our theoretical results.

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Neural network stochastic differential equation models with applications to financial data forecasting

Cited by 24 publications

References 32 publications

Methods of data analysis in the problem of optimizing the rental schedule

Methods of data analysis in the problem of optimizing the rental schedule

Collaborative Multiobjective Evolutionary Algorithms in the Search of Better Pareto Fronts: An Application to Trading Systems

Averaging principle for Hilfer–Katugampola fractional stochastic differential equations

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