Publication: Türkiye’deki Yatırım Fonlarının Kaotik Davranışının İncelenmesi
No Thumbnail Available
Date
2021
Authors
Çağlar, H. Nazan
Journal Title
Journal ISSN
Volume Title
Publisher
7th International Mardin Artuklu Scientific Researches Conference
Abstract
Kaos Teorisi, doğrusal olmayan dinamik sistemlerin davranışlarını tanımlar ve ekonomi
alanında pek çok verinin modellenmesinde kullanılır. Kaos teori, sistemin doğrusal olmayan
ve deterministik bir süreç olduğu varsayımlarına dayanır. Doğrusal modeller, ekonometrik
sistemleri karmaşıklıklarını ortaya çıkarmakta yetersiz kalmaktadır. Bu çalışmanın amacı,
Yatırım Fonlarının getirilerinin zamana bağlı doğrusal olmayan dinamik bir sistem tarafından
üretilip üretilmediğini araştırmak ve sistemin uzun vadede geleceğe yönelik tahmin yeteneğini
araştırmaktır. Birçok ekonomik veri serisinin kaotik davranış gösterdiği bilinmektedir. Bu
çalışmada, doğrusal modellerle açıklanamayan ekonomik sistemlerin karmaşıklıklarını
tanımlamak için, zaman serilerine dayalı olarak, doğrusal olmayan dinamik bir sistemin yatırım
fonlarındaki etkileri incelenmektedir. Diğer bir ifadeyle amaç, yatırım fonlarının günlük endeks
getirilerinin kaotik bir davranış gösterip göstermediğini ortaya koymaktır. Çalışma sonunda,
gömme (embedding) boyutunun çok yüksek olduğu ve sistemin kaotik davranış gösterdiği
belirlenmiştir. Yatırım fonları için uzun vadeli tahminlerin öngörülemeyeceği gösterilmiştir.
Çalışma da, Temel teorik yapılar verildikten sonra, yatırım fonu verilerinin herhangi bir kaotik
davranış gösterip göstermediği araştırılmaktadır.
By and large, chaos theory describes the behavior of nonlinear dynamic systems and has been used in solving a wide range of problems in economics . Chaos is based on the assumptions that the underlying system is a nonlinear and deterministic process. However, there are some conclusions which prove that linear models failed in capturing the complexities of the economic system. The purpose of this article is to investigate whether the time series of Investment Funds Index returns are generated by a nonlinear dynamic system. If this has been proved, this means that the system’s ability for the future prediction is limited in the long run. It is well known that many economic data series show chaotic behavior. This article studies the effects of a nonlinear dynamic system in investment funds, based on time series in order to capture the complexities of the economic systems which linear models fail to do. In other words, the aim is to show whether investment funds daily index returns show chaotic behavior or not. Results indicated embedding dimension is very high and the mutual fund system has chaotic phenomena. Presently, the problem on chaotic phenomena and predictable time scale is very complex. Due to this reason, long-term forecasting is unpredictable for investment funds data. It is a major dilemma in the field of chaotic research. Results indicate that the embedding dimension is very high and the mutual fund system has chaotic phenomena. Here, the complex dynamical behavior of the investment funds is discussed. Aim is to find out if monthly index data show any chaotic behavior or not.
By and large, chaos theory describes the behavior of nonlinear dynamic systems and has been used in solving a wide range of problems in economics . Chaos is based on the assumptions that the underlying system is a nonlinear and deterministic process. However, there are some conclusions which prove that linear models failed in capturing the complexities of the economic system. The purpose of this article is to investigate whether the time series of Investment Funds Index returns are generated by a nonlinear dynamic system. If this has been proved, this means that the system’s ability for the future prediction is limited in the long run. It is well known that many economic data series show chaotic behavior. This article studies the effects of a nonlinear dynamic system in investment funds, based on time series in order to capture the complexities of the economic systems which linear models fail to do. In other words, the aim is to show whether investment funds daily index returns show chaotic behavior or not. Results indicated embedding dimension is very high and the mutual fund system has chaotic phenomena. Presently, the problem on chaotic phenomena and predictable time scale is very complex. Due to this reason, long-term forecasting is unpredictable for investment funds data. It is a major dilemma in the field of chaotic research. Results indicate that the embedding dimension is very high and the mutual fund system has chaotic phenomena. Here, the complex dynamical behavior of the investment funds is discussed. Aim is to find out if monthly index data show any chaotic behavior or not.
Description
Keywords
Kaos teorisi, Faz uzayı, Zaman serisi, Gömme (embedding) boyutu, Doğrusal olmayan kaotik sistem, Yatırım fonu, Chaos theory, Phase space, Time series, Embedding dimension, Nonlinear chaotic system, Mutual funds