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In this study, we examine the forecastability of a specific neural network architecture called General Regression Neural Network (GRNN) and compare its performance with a variety of forecasting techniques, including Multi-Layered Feedforward Network (MLFN), multivariate transfer function, and...
Persistent link: https://www.econbiz.de/10014150550
prices. We empirically assess efficiency gains in volatility estimation when using range-based estimators as opposed to …
Persistent link: https://www.econbiz.de/10010461231
A simple methodology is presented for modeling time variation in volatilities and other higher-order moments using a recursive updating scheme similar to the familiar RiskMetricsTM approach. We update parameters using the score of the forecasting distribution. This allows the parameter dynamics...
Persistent link: https://www.econbiz.de/10011332948
In this paper we aim to measure actual volatility within a model-based framework using high-frequency data. In the empirical finance literature it is known that tick-by-tick prices are subject to market micro-structure such as bid-ask bounces and trade information. Such market micro-structure...
Persistent link: https://www.econbiz.de/10011342558
We present a simple new methodology to allow for time-variation in volatilities using a recursive updating scheme similar to the familiar RiskMetrics approach. It exploits the link between exponentially weighted moving average and integrated dynamics of score driven time varying parameter...
Persistent link: https://www.econbiz.de/10010384110
We compare more than 1000 different volatility models in terms of their fit to the historical ISE-100 Index data and their forecasting performance of the conditional variance in an out-of-sample setting. Exponential GARCH model of Nelson (1991) with “constant mean, t-distribution, one lag...
Persistent link: https://www.econbiz.de/10013159436
Purpose: This paper examines the volatility of stock return in Dhaka stock exchange, BangladeshMethodology: Using Random Walk model (RW), Autoregressive model (AR), Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model, and extensive GARCH model with Normal, and Student...
Persistent link: https://www.econbiz.de/10012979338
The asymmetric moving average model (asMA) is extended to allow forasymmetric quadratic conditional heteroskedasticity (asQGARCH). Theasymmetric parametrization of the conditional variance encompassesthe quadratic GARCH model of Sentana (1995). We introduce a framework fortesting asymmetries in...
Persistent link: https://www.econbiz.de/10011303289
-parametric estimation is impractical given commonly available predictive sample sizes. Instead, this paper derives the approximate …
Persistent link: https://www.econbiz.de/10003962215
The study aimed at determining a set of superior generalized orthogonal-GARCH (GO-GARCH) models for forecasting time-varying conditional correlations and variances of five foreign exchange rates vis-à-vis the Nigerian Naira. Daily data covering the period 02/01/2009 to 19/03/2015 was used, and...
Persistent link: https://www.econbiz.de/10011534717