Search

The purpose of this paper is to assess unbiased options pricing predictions via ad hoc Black–Scholes model approaches. This paper investigates a number of technical issues when fitted values of implied volatility from linear regression are plugged into the Black–Scholes model, which leads to biased estimation. First, the study observes that the implied volatility linear regression can yield a negative outcome, which is meaningless. Therefore, a logarithmic transformation is applied to the linear function to ensure that the forecast is positive. Second, the retransformation from log to original metric to fitted values of implied volatility and the nonlinearity of Black–Scholes to implied volatility yields biased forecasts. A smearing technique has been applied in this study to correct this bias. Finally, the smearing estimation method also provides biased results if there is heteroscedasticity in the OLS estimation residuals. This study applies the weighted least square regression technique in order to avoid heteroscedasticity. According to the performance measures such as mean bias (MB), mean absolute error (MAE) and mean absolute relative error, the study concludes that the smearing method is the most effective to correct the bias in ad hoc Black–Scholes approaches as well as that an absolute smile approach is better than a relative smile approach without the smearing technique, but with smearing methods, relative smile performs superior to absolute. [ABSTRACT FROM AUTHOR]

Single-crystal SnSe holds the world record for high thermoelectric performance. However, the efficiency of polycrystalline SnSe is limited due to high thermal conductivity (κ) and low electronic conductivity (σ) compared to single-crystal SnSe. Here, we report the low κ and high σ on SnSe with Si doping using semi-classical Boltzmann transport theory and first-principles calculations. Our calculated phonon dispersion curves and elastic constants of the SixSn1−xSe alloys (x varied from 0 to 0.25) show the thermodynamic and mechanical stability. Our density functional theory (DFT)-calculated elastic moduli of the α-SnSe match well with theoretical and experiment reports. The electronic properties are calculated using diversity of exchange-correlation functionals. The band gap for pristine α-SnSe is estimated to be 0.88 eV using the hybrid functional (HSE06), which is in excellent agreement with the experimental value 0.86 eV. The G0W0+Bethe–Salpeter Equation, which incorporates combined electron–electron (e–e) and electron–hole (e–h) interactions, is used to calculate the optical characteristics of pure and Si-alloyed α-SnSe. Our DFT-calculated Seebeck coefficient for SixSn1−xSe alloys for all Si doping concentrations revealed p-type behavior. At 770 K, for x = 0.25, SixSn1−xSe is found to have the lowest thermal conductivity of ~ 0.16 Wm - 1 K - 1 attributed to the high lattice anharmonicity. Our results propose a novel strategy to enhance the optical and thermoelectric properties in the SnSe-based thermoelectric materials. [ABSTRACT FROM AUTHOR]

Indices are a crucial part of the global investment business. The main objective of the study is to determine the impact of COVID-19 on stock indices to analyse financial markets' response. The study applied a log-log simple regression model to analyse the effects of COVID-19 on stock indices by using EVIEWS. The result shows that COVID-19 has a substantial negative impression on market indices. In addition, critical analysis findings are benchmark index like the S&P 500, and Dow Jones Industrial Average has plummeted. On the other hand, indices like FTSE 100, NIKKEI 225, NASDAQ 100, SSE 50, DAX, HENG SENG, MOEX.ME and SENSEX have shown a negative percentage change. Moreover, Global stock markets have posted the biggest fall since the 2008 financial crises. It was recommended that future researchers should conduct different stock indices and sample period, the impact of COVID-19 on economic factors like GDP, inflation, interest rate, and effects of COVID-19 on credit markets. [ABSTRACT FROM AUTHOR]