Predicting Option Prices and Volatility with High Frequency
Data Using Neural Network
H. Wang. BOHR International Journal of Finance and Market Research, 2 (1):
65–67(July 2022)
DOI: 10.54646/BIJFMR.011
Abstract
Neural network utilizes the huge amount of data for analysis and prediction. This paper predicts option prices and volatility using neutral network based on high frequency intraday data.We focus on short term prediction because option prices and volatility in fact are very volatile and almost impossible to predict. We find that neural network is able to predict option prices and volatility by using predictors constructed from the prices of option and its underlining index, especially in short term which is what practitioners care about more in practice.
%0 Journal Article
%1 wangpredicting
%A Wang, Hua
%D 2022
%J BOHR International Journal of Finance and Market Research
%K HighFrequencyData NeuralNetwork Option PricePrediction Volatility
%N 1
%P 65–67
%R 10.54646/BIJFMR.011
%T Predicting Option Prices and Volatility with High Frequency
Data Using Neural Network
%U https://journals.bohrpub.com/index.php/bijfmr/article/view/110
%V 2
%X Neural network utilizes the huge amount of data for analysis and prediction. This paper predicts option prices and volatility using neutral network based on high frequency intraday data.We focus on short term prediction because option prices and volatility in fact are very volatile and almost impossible to predict. We find that neural network is able to predict option prices and volatility by using predictors constructed from the prices of option and its underlining index, especially in short term which is what practitioners care about more in practice.
@article{wangpredicting,
abstract = {Neural network utilizes the huge amount of data for analysis and prediction. This paper predicts option prices and volatility using neutral network based on high frequency intraday data.We focus on short term prediction because option prices and volatility in fact are very volatile and almost impossible to predict. We find that neural network is able to predict option prices and volatility by using predictors constructed from the prices of option and its underlining index, especially in short term which is what practitioners care about more in practice.},
added-at = {2022-07-16T12:29:43.000+0200},
author = {Wang, Hua},
biburl = {https://www.bibsonomy.org/bibtex/2eea62761a6ae3fc8634f1613838aa7c7/ijfmrjournal},
doi = {10.54646/BIJFMR.011},
interhash = {1895ad869aa7457103a82b7fe2fe3572},
intrahash = {eea62761a6ae3fc8634f1613838aa7c7},
journal = {BOHR International Journal of Finance and Market Research},
keywords = {HighFrequencyData NeuralNetwork Option PricePrediction Volatility},
language = {English},
month = {July},
number = 1,
pages = {65–67},
timestamp = {2023-01-03T13:27:46.000+0100},
title = {Predicting Option Prices and Volatility with High Frequency
Data Using Neural Network},
url = {https://journals.bohrpub.com/index.php/bijfmr/article/view/110},
volume = 2,
year = 2022
}