Prediction of Cryptocurrency Prices through a Path Dependent Monte Carlo Simulation

Fuente: arXiv
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Hauptverfasser: Singh, Ayush, Jha, Anshu K., Kumar, Amit N.
Format: Preprint
Veröffentlicht: 2024
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author Singh, Ayush
Jha, Anshu K.
Kumar, Amit N.
author_facet Singh, Ayush
Jha, Anshu K.
Kumar, Amit N.
contents In this paper, our focus lies on the Merton's jump diffusion model, employing jump processes characterized by the compound Poisson process. Our primary objective is to forecast the drift and volatility of the model using a variety of methodologies. We adopt an approach that involves implementing different drift, volatility, and jump terms within the model through various machine learning techniques, traditional methods, and statistical methods on price-volume data. Additionally, we introduce a path-dependent Monte Carlo simulation to model cryptocurrency prices, taking into account the volatility and unexpected jumps in prices.
format Preprint
id arxiv_https___arxiv_org_abs_2405_12988
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Prediction of Cryptocurrency Prices through a Path Dependent Monte Carlo Simulation
Singh, Ayush
Jha, Anshu K.
Kumar, Amit N.
Statistical Finance
Probability
In this paper, our focus lies on the Merton's jump diffusion model, employing jump processes characterized by the compound Poisson process. Our primary objective is to forecast the drift and volatility of the model using a variety of methodologies. We adopt an approach that involves implementing different drift, volatility, and jump terms within the model through various machine learning techniques, traditional methods, and statistical methods on price-volume data. Additionally, we introduce a path-dependent Monte Carlo simulation to model cryptocurrency prices, taking into account the volatility and unexpected jumps in prices.
title Prediction of Cryptocurrency Prices through a Path Dependent Monte Carlo Simulation
topic Statistical Finance
Probability
url https://arxiv.org/abs/2405.12988