Assessment of crypto market heterogeneity using clustering methods

الموضوعات

علوم تطبيقية وتكنولوجية

الملخص

Since the introduction of Bitcoin, the cryptocurrency market has witnessed significant growth in both market value and the number of available cryptocurrencies. However, this market is characterized by heterogeneity, with a wide variety of cryptocurrencies exhibiting diverse technologies, user bases, and use cases. This heterogeneity makes it challenging for investors to make informed decisions. To address this issue, this thesis aims to assess the heterogeneity of the crypto market using clustering methods, enhanced by back-testing. By incorporating back-testing into clustering techniques, the thesis examines the historical performance of clusters, thus providing a measure of their validity. The study utilizes a five-year dataset, considering different time periods to evaluate the clusters’ consistency. The clustering process involves three methods: K-means clustering, dynamic clustering using histograms, and TADPole clustering based on time-series volatility. The data is transformed into distinct distributions of returns, enabling the application of each clustering method. The optimal number of clusters for K-means clustering is determined using cluster validity indices. Furthermore, association tests are conducted between the clusters and various variables, including market capitalization, trading volume, financial ratios such as Beta and Sharpe Ratio, and heavy-tail behavior. Fisher’s test is employed to assess the significance of these associations, providing additional insights into the cluster characteristics. In cases where time-series clustering fails, the Hierarchical Risk Parity (HRP) algorithm is utilized to cluster highly correlated coins.

روابط وملفات

التعريف والنوع

رقم الوثيقة

ef66bd2c-ce60-4593-b8ae-88b587102d13

رقم العقد

0

نوع الوسائط

Crawler

نوع المحتوى

الرسائل العلمية

صيغة المصدر

رسائل ماجيستير

نوع الملف

pdf text

أسماء الملفات

2282514_1.pdf

بيانات النشر

ألقاب المؤلفين

[{"name_ar":"Ernesto Damiani","title_ar":"اشراف","title_en":"Supervision"},{"name_ar":"Hamdan Al Ahbabi","title_ar":"اعداد","title_en":"Preparation"},{"name_ar":"Ibrahim (Abe) M. Elfadel","title_ar":"اشراف","title_en":"Supervision"}]

اللغة

English

المصدر والدورية

اسم المصدر

Assessment of crypto market heterogeneity using clustering methods

المحتوى والصفحات

عدد الصفحات

0

كلمات الباحثين

Cryptocurrencies, Market heterogeneity, Clustering methods, Back-testing, K-means clustering, Dynamic clustering, Time-series clustering, Association tests, Financial ratios, Hierarchical Risk Parity (HRP), Random Forest.

إشراف وإعداد

الإشراف

Ernesto Damiani, Ibrahim (Abe) M. Elfadel

الإعداد

Hamdan Al Ahbabi

الاقتباسات الببليوغرافية