There is a growing awareness among financial researchers that the traditional models of asset returns cannot capture essential time series properties of the current stock return data. We examine commonly used models, such as the autoregressive integrated moving average (ARIMA) and the autoregressive conditional heteroskedasticity (ARCH) family, and show that these models cannot account for the essential characteristics of the real Istanbul Stock Exchange and Moscow Stock Exchange returns. These models often fail, and when they succeed, they do at the cost of an increasing number of parameters and structural equations. The measures of risk obtained from these models do not reflect the true risk to traders, since they cannot capture all key features of the data. In this paper, we offer an alternative framework of analysis based on multifractal models. Compared to the traditional models, the multifractal models we use are very parsimonious and replicate all key features of the data with only three universal parameters. The multifractal models have superior risk evaluation performance. They also produce better forecasts at all scales. The paper also offers a justification of the multifractal models for financial modeling. -
Keywords: Key words: fractal Brownian motion, Hö, lder exponent, multifractal market hypothesis, multifractal spectrum, scaling phenomena, statistical self-similarity, Wavelet transform
Yayın Adı (dc.title) | Multifractality of the Istanbul and Moscow Stock Market Returns |
Yazar/lar (dc.contributor.yazarlar) | Mehmet Balcilar |
Yayın Türü (dc.type) | Konferans Bildirisi |
Dil (dc.language) | İngilizce |
Yayımlanma Yılı (dc.date.issued) | 2003 |
Ulusal/Uluslararası (dc.identifier.ulusaluluslararasi) | Uluslararası |
Kaynak (dc.relation.journal) | Emerging Markets Finance and Trade |
Kaynak Adı Ek Bilgi / Konferans Bilgisi (dc.identifier.kaynakadiekbilgi) | 5th International Conference on Economics Location: Ankara (Turkey) September 10-13, 2001 |
Süreli Sayı (dc.identifier.issue) | 2 |
Cilt/Sayı (dc.identifier.volume) | 39 |
Sayfa (dc.identifier.startpage) | 5-46 |
ISSN/ISBN (dc.identifier.issn) | ISSN: 1540-496X; Online ISSN: 1558-0938 |
Yayıncı (dc.publisher) | Taylor & Francis |
Veri Tabanları (dc.contributor.veritaban) | Web of Science Core Collection |
Veri Tabanları (dc.contributor.veritaban) | Taylor & Francis |
Veri Tabanları (dc.contributor.veritaban) | Scopus |
İndex Türü (dc.identifier.index) | CPCI-SSH |
İndex Türü (dc.identifier.index) | Scopus |
Etki Faktörü (dc.identifier.etkifaktoru) | 0,828 / 2017-WOS / 5 Year: 0,75 |
Özet (dc.description.abstract) | There is a growing awareness among financial researchers that the traditional models of asset returns cannot capture essential time series properties of the current stock return data. We examine commonly used models, such as the autoregressive integrated moving average (ARIMA) and the autoregressive conditional heteroskedasticity (ARCH) family, and show that these models cannot account for the essential characteristics of the real Istanbul Stock Exchange and Moscow Stock Exchange returns. These models often fail, and when they succeed, they do at the cost of an increasing number of parameters and structural equations. The measures of risk obtained from these models do not reflect the true risk to traders, since they cannot capture all key features of the data. In this paper, we offer an alternative framework of analysis based on multifractal models. Compared to the traditional models, the multifractal models we use are very parsimonious and replicate all key features of the data with only three universal parameters. The multifractal models have superior risk evaluation performance. They also produce better forecasts at all scales. The paper also offers a justification of the multifractal models for financial modeling. - |
Özet (dc.description.abstract) | Keywords: Key words: fractal Brownian motion, Hö, lder exponent, multifractal market hypothesis, multifractal spectrum, scaling phenomena, statistical self-similarity, Wavelet transform |
URL (dc.rights) | http://www.tandfonline.com/doi/abs/10.1080/1540496X.2003.11052538 |
DOI (dc.identifier.doi) | 10.1080/1540496X.2003.11052538 |
Fakültesi / Enstitütü (dc.identifier.fakulte) | İktisadi ve İdari Bilimler Fakültesi |
Bölümü (dc.identifier.bolum) | İktisat Bölümü |
Kurumdaki Yazar/lar (dc.contributor.author) | Mehmet BALCILAR |
Kayıt No (dc.identifier.kayitno) | BLED0E2DB2 |
Kayıt Giriş Tarihi (dc.date.available) | 2016-03-18 |
Not (Yayımlanma Yılı) (dc.identifier.notyayinyili) | 2003 |
Wos No (dc.identifier.wos) | WOS:000182706800002 |
Konu Başlıkları (dc.subject) | fractal brownian motion |
Konu Başlıkları (dc.subject) | hölder exponent |
Konu Başlıkları (dc.subject) | multifractal market hypothesis |
Konu Başlıkları (dc.subject) | multifractal spectrum |
Konu Başlıkları (dc.subject) | scaling phenomena |
Konu Başlıkları (dc.subject) | statistical self-similarity |
Konu Başlıkları (dc.subject) | wavelet transform |