|
[1]
|
Predicting Volatility Index According to Technical Index and Economic Indicators on the Basis of Deep Learning Algorithm
Sustainability,
2021
DOI:10.3390/su132414011
|
|
|
|
|
[2]
|
An Intelligent Learning and Ensembling Framework for Predicting Option Prices
Emerging Markets Finance and Trade,
2021
DOI:10.1080/1540496X.2019.1695598
|
|
|
|
|
[3]
|
Real‐time waiting‐price trading interval in a heterogeneous options market: a Bernoulli distribution
International Transactions in Operational Research,
2020
DOI:10.1111/itor.12778
|
|
|
|
|
[4]
|
Real‐time waiting‐price trading interval in a heterogeneous options market: a Bernoulli distribution
International Transactions in Operational Research,
2020
DOI:10.1111/itor.12778
|
|
|
|
|
[5]
|
Advances in Cross-Section Data Methods in Applied Economic Research
Springer Proceedings in Business and Economics,
2020
DOI:10.1007/978-3-030-38253-7_38
|
|
|
|
|
[6]
|
Comparative empirical study of binomial call-option pricing methods using S&P 500 index data
The North American Journal of Economics and Finance,
2019
DOI:10.1016/j.najef.2019.101071
|
|
|
|
|
[7]
|
An empirical exploration of the performance of alternative option pricing models
Journal of Indian Business Research,
2018
DOI:10.1108/JIBR-04-2018-0114
|
|
|
|
|
[8]
|
The economic determinants of the implied volatility function for currency options: Evidence from India
International Journal of Emerging Markets,
2018
DOI:10.1108/IJoEM-08-2017-0308
|
|
|
|
|
[9]
|
Ad-Hoc Black–Scholes vis-à-vis TSRV-based Black–Scholes: Evidence from Indian Options Market
Journal of Quantitative Economics,
2017
DOI:10.1007/s40953-017-0078-3
|
|
|
|