As the real estate market develops rapidly and is increasingly securitized, it has become an important investment asset in the portfolio design. Thus the measurement of its market risk exposure has attracted attentions from academics and industries due to its peculiar behavior and unique characteristics such as heteroscedasticity and multi scale heterogeneity in its risk and noise evolution etc...

Abstract: The evolution of financial markets is a complicated real-world phenomenon that ranks at the top in terms of difficulty of modeling and/or prediction. One reason for this difficulty is the well-documented nonlinearity that is inherently at work. The state-of-the-art on the nonlinear modeling of financial returns is given by the popular ARCH (Auto-Regressive Conditional Heteroscedastici...

To assess the time-varying dynamics in value-at-risk (VaR) estimation, this study has employed an integrated approach of dynamic conditional correlation (DCC) and generalized autoregressive heteroscedasticity (GARCH) models on daily stock return emerging markets. A log-returns three leading indices such as KSE100, KSE30, KSE-ALL from Pakistan Stock Exchange SSE180, SSE50 SSE-Composite Shanghai ...

This paper aimed at modelling the volatility of monthly average official exchange rate (Naira/USD) using Autoregressive Integrated Moving Average (ARIMA) and Generalized Conditional Heteroscedasticity (GARCH) for period January, 1981 to December, 2021. The data study was obtained from Central Bank Nigeria 2021 Statistical Bulletin. time plot, Augmented Dickey Fuller (ADF) Phillip’s Perron (PP) ...

We use Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models to examine volatility of stock prices for firms listed in the Dar es Salaam Stock Exchange (DSE). In doing so, both symmetric and asymmetric GARCH are used this study. The descriptive analysis data shows that standard deviation series returns is high, indicating a high level daily fluctuations, log value mean close ...

The emergence of the recent financial crisis, during which markets frequently underwent changes in their statistical structure over a short period of time, illustrates the importance of non-stationary modelling in financial time series. Motivated by this observation, we propose a fast, well performing and theoretically tractable method for detecting multiple change points in the structure of an...

Infrastructure investment is essential for economic development both developed and developing economies. We analyze the short-term return behavior portfolio characteristics of global, regional, selected Asian countries’ infrastructure indexes during pandemic over sample period 3 July 2018 to 1 2021. According multivariate Glosten, Jagannathan, Runkle (GJR) Generalized Autoregressive Conditional...

In this paper new semiparametric generalized autoregressive conditional heteroscedasticity (GARCH) models with long memory are introduced. A multiplicative decomposition of the volatility into a component and an unconditional is assumed. The estimation latter carried out by means data-driven local polynomial smoother. According to revised recommendations Basel Committee on Banking Supervision m...