Recent Developments in Quantitative Finance: An Overview

Abstract

Quantitative finance combines mathematical finance, financial statistics, financial econometrics and empirical finance to provide a solid quantitative foundation for the analysis of financial issues. The purpose of this special issue on "Recent developments in quantitative finance" is to highlight some areas of research in which novel methods in quantitative finance have contributed significantly to the analysis of financial issues, specifically fast methods for large-scale non-elliptical portfolio optimization, the impact of acquisitions on new technology stocks: the Google-Motorola case, the effects of firm characteristics and recognition policy on employee stock options prices after controlling for self-selection, searching for landmines in equity markets, whether CEO incentive pay improves bank performance, using a quantile regression analysis of U.S. commercial banks, testing price pressure, information, feedback trading, and smoothing effects for energy exchange traded funds, actuarial implications of structural changes in El Niño-Southern Oscillation Index dynamics, credit spreads and bankruptcy information from options data, QMLE of a standard exponential ACD model: asymptotic distribution and residual correlation, and using two-part quantile regression to analyze how earnings shocks affect stock repurchases.

Do Exchange Traded Funds in India Have Tracking and Pricing Efficiency?

“…Financial time series are characterized by time varying correlations and variances (So et al, 2018) and have stylized facts such as fat tailed return distributions, random walk, volatility clustering etc. (Chang et al, 2014;Selim et al, 2015). As examining the stationarity of time series is a pre-requisite before applying VECM, the study uses Augmented Dickey Fuller (Dickey & Fuller,1981) test to examine the stationarity of price and return series of NAVs and market prices of ETFs.…”