---
res:
  bibo_abstract:
  - "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. @eng"
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Dominik Christian
      foaf_name: Hanke, Dominik Christian
      foaf_surname: Hanke
      foaf_workInfoHomepage: http://www.librecat.org/personId=63677
  - foaf_Person:
      foaf_givenName: Yuanhua
      foaf_name: Feng, Yuanhua
      foaf_surname: Feng
      foaf_workInfoHomepage: http://www.librecat.org/personId=20760
  - foaf_Person:
      foaf_givenName: André
      foaf_name: Uhde, André
      foaf_surname: Uhde
      foaf_workInfoHomepage: http://www.librecat.org/personId=36049
  dct_date: 2026^xs_gYear
  dct_language: eng
  dct_subject:
  - Modulus Log-GARCH
  - Modified (FI)EGARCH
  - Modulus asymmetric (FI)Log-GARCH
  - (FI)EGARCH
  - long memory
  - modulus-log transformation
  - QMLE
  - model selection
  - implementation in  R
  dct_title: Comparing the behaviors of some original short  and long memory exponential
    volatility models@
...