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Wahab, A., & Khan, S. (2018). Comments on “Fractional Extreme Value Adaptive Training Method: Fractional Steepest Descent Approach”. IEEE Transactions on Neural Networks and Learning Systems, 1-3.
https://doi.org/10.1109/TNNLS.2019.2899219

has been cited by the following article:

• TITLE: Strategies for Indexed Stock Option Hedgers with Loss-Risk-Minimizing Criterion Based on Monte-Carlo Method

  AUTHORS: Jianhua Guo, Lijuan Deng

  KEYWORDS: Indexed Stock Option Hedgers, Loss-Risk-Minimizing, Monte-Carlo Method

  JOURNAL NAME: Journal of Financial Risk Management, Vol.8 No.4, December 17, 2019

  ABSTRACT: Unlike traditional options, indexed stock options use market performance as a benchmark reference index, and the option exercise price is a variable that changes with market performance. This paper, by taking the expected loss at the end of the hedging period as a risk measure, conducts a study on the hedging strategies for indexed stock option hedgers. Empirical analysis shows that, firstly, it is more conducive for indexed stock options to play an incentive role by adjusting the exercise price according to changes in market conditions, secondly, when the frequency of hedging position adjustment is relatively high, it can better cope with the price fluctuations in the market, thereby reducing the risk of possible loss and achieving a better hedge effect, but the hedging costs will increase for because of the existence of transaction costs.