Search

It remains a challenge for existing financial models to accurately capture the shapes of implied volatility (IV) of options with all maturities simultaneously. Inspired by Chen et al.'s empirical finding, 'the shorter the option expiry, the higher the IV is', we propose a novel and simple approach to solve this challenge, by introducing a term-structure-based correction (i.e. an exponential increase function of the options expiry) to the volatility of volatility (vol–vol) term of the classical Heston stochastic volatility model. We derive an approximate formula for the IV under the corrected model with the perturbation method and further apply the formula to predict the IVs of options written on the Shanghai Stock Exchange 50 ETF. Numerical experiments and empirical results show that the introduction of a term-structure-based correction function surely overcomes the deficiency of the classical Heston model in capturing the short-term IVs, thus improving notably its performance of IV forecasting. [ABSTRACT FROM AUTHOR]

In order to cultivate children's computational thinking, researchers have developed many excellent programming systems. Among them, the tangible programming systems combined with graphic output have been widely accepted because of the intuitive input method and diversified visual feedback. However, few of them support collaborative learning or programming. Little is known about children's experiences, emotional states and behaviours on collaborative programming. Motivated by this gap, we present a novel tangible and collaborative enabled programming system named Lighters, which designed for children aged 7–10 and had two types of collaboration modes (block-based and role-based). We conducted an user experiment with 24 children, and collected physiological (EDA), questionnaire, video recording and interview data for analysis. Based on our experiment results, Lighters are effective in helping children learn to program collaboratively. In addition, Lighters can mobilize children's positive emotions and enthusiasm to learn programming. Compared with block-based collaboration, role-based collaboration is more likely to stimulate children's emotional states and has a better effect on learning programming. [ABSTRACT FROM AUTHOR]