---
_id: '66447'
abstract:
- lang: eng
  text: "Volatility modeling is utilized across numerous fields including finance,
    environmental studies, and \r\nsocial sciences. It is particularly relevant in
    scenarios where understanding and predicting conditional \r\nvariability is crucial,
    such as when dealing with incremental or time-dependent data. In this paper, novel
    \r\nshort and long memory volatility models of the EGARCH family are introduced
    and analyzed, which \r\nare closely related to the well-established EGARCH model
    proposed by Nelson (1991) but share \r\ndesirable theoretical properties in several
    dimensions. Recently developed members of the so-called \r\nEGARCH family, which
    introduces a modulus-log transformation proposed by John and Draper (1980) \r\nand
    a power transformation for the size and magnitude effect to tackle the problem
    with near-zero \r\ninnovations and the asymmetric impact of positive and negative
    shocks on the volatility, are discussed. \r\nAfter a theoretical discussion of
    the proposed and related volatility models, the practical performance \r\nof the
    elaborated volatility models is compared to well-established and traditional GARCH
    approaches. \r\nA general QMLE algorithm is proposed to estimate the model parameters.
    The practical relevance of the \r\nadvanced models is illustrated through a comparative
    study. By applying these volatility models to a \r\nvariety of international stock
    index returns, this paper identifies market-specific characteristics as well \r\nas
    unique strengths and weaknesses of discussed volatility models. Although the practical
    performance \r\nof the recently introduced models is comparable to those obtained
    by the traditional EGARCH model, \r\nthey generally outperform traditional non-exponential
    volatility models used as benchmarks and thus \r\nprovide a useful alternative
    to existing short and long memory volatility models. "
author:
- first_name: Dominik Christian
  full_name: Hanke, Dominik Christian
  id: '63677'
  last_name: Hanke
- first_name: Yuanhua
  full_name: Feng, Yuanhua
  id: '20760'
  last_name: Feng
- first_name: André
  full_name: Uhde, André
  id: '36049'
  last_name: Uhde
citation:
  ama: Hanke DC, Feng Y, Uhde A. <i>Comparing the Behaviors of Some Original Short 
    and Long Memory Exponential Volatility Models</i>.; 2026.
  apa: Hanke, D. C., Feng, Y., &#38; Uhde, A. (2026). <i>Comparing the behaviors of
    some original short  and long memory exponential volatility models</i>.
  bibtex: '@book{Hanke_Feng_Uhde_2026, title={Comparing the behaviors of some original
    short  and long memory exponential volatility models}, author={Hanke, Dominik
    Christian and Feng, Yuanhua and Uhde, André}, year={2026} }'
  chicago: Hanke, Dominik Christian, Yuanhua Feng, and André Uhde. <i>Comparing the
    Behaviors of Some Original Short  and Long Memory Exponential Volatility Models</i>,
    2026.
  ieee: D. C. Hanke, Y. Feng, and A. Uhde, <i>Comparing the behaviors of some original
    short  and long memory exponential volatility models</i>. 2026.
  mla: Hanke, Dominik Christian, et al. <i>Comparing the Behaviors of Some Original
    Short  and Long Memory Exponential Volatility Models</i>. 2026.
  short: D.C. Hanke, Y. Feng, A. Uhde, Comparing the Behaviors of Some Original Short 
    and Long Memory Exponential Volatility Models, 2026.
date_created: 2026-07-13T09:15:09Z
date_updated: 2026-07-16T09:07:24Z
ddc:
- '330'
department:
- _id: '186'
file:
- access_level: open_access
  content_type: application/pdf
  creator: dhanke
  date_created: 2026-07-13T09:14:58Z
  date_updated: 2026-07-13T09:14:58Z
  file_id: '66448'
  file_name: TAF_WP_104_HankeFengUhde2026.pdf
  file_size: 1169286
  relation: main_file
file_date_updated: 2026-07-13T09:14:58Z
has_accepted_license: '1'
jel:
- C4
- C5
- B23
- B26
- C32
keyword:
- Modulus Log-GARCH
- Modified (FI)EGARCH
- Modulus asymmetric (FI)Log-GARCH
- (FI)EGARCH
- long memory
- modulus-log transformation
- QMLE
- model selection
- implementation in  R
language:
- iso: eng
oa: '1'
status: public
title: Comparing the behaviors of some original short  and long memory exponential
  volatility models
type: working_paper
user_id: '63677'
year: '2026'
...