Forecasting volatility using Box-Jenkins model case of Amman stock exchange

العناوين الأخرى

التنبؤ بالتذبذبات باستخدام نموذج بكس جنكيز : دراسة حالة بورصة عمان

مقدم أطروحة جامعية

al-Khazailah, Mansur Muhammad Hamad

مشرف أطروحة جامعية

al-Zayyud, Husayn Ali

أعضاء اللجنة

Maqabilah, Ali
Abbad, Jumah
Jaradat, Mahmud

الجامعة

جامعة آل البيت

الكلية

كلية إدارة المال و الأعمال

القسم الأكاديمي

قسم التمويل و المصارف

دولة الجامعة

الأردن

الدرجة العلمية

ماجستير

تاريخ الدرجة العلمية

2010

الملخص الإنجليزي

There are many forecasting techniques that can be used in the financial markets, the importance of forecasting is to able investment community to take their decisions about the future expectations, assets allocation, portfolio management, assets pricing and other benefits.

This thesis presents the Box-Jenkins model as one of the forecasting techniques, which we can use, in the financial time series.

The main aim of this study is to predict volatility of Amman Stock Exchange as one of the emerging markets for the indices of sectors banks, insurance, services, industry.

That is adopted to give an investment community a chance to plan about their buying or selling decisions for financial securities in the future.

That is achieved by finding the tentative Autoregressive Integrated Moving Average (ARIMA) models that describe the equation of the forecasting for each sector. The data are accumulated weekly from the web site of Amman Stock Exchange using the historical indices in the period froml / 1 / 2005-1 / 4 / 2010. We tested a number of the integrated equations by using co- integration test (Johansen test), the result of this test is that there were 4-co-integrating equations using trace test and maximum eigenvalue test, then we test the stationarity by using unit root test which indicates that there is a stationarity at level for banks, insurance and services, also the stationarity achieved at first difference for industry sector, and then use a minimum mean square error, t-statistics value and p-statistics value to choose the best ARIMA models at 95% confidence interval? The resulted models for this study for banks, insurance, services, industry respectively are : Z, = 0.0023745 + 0.6930Z, _2 -0.1042a, _2, Z, = 0.0064972 + 0.3657000Z _ Z, = 0.0008242 +0.9173ZM-0.7981ai_ Y, -7, _, = -0.1603(K, _, -Y, _2)-0.7569 at_ x From these proposed models we can get the forecasting equation for each sector.

التخصصات الرئيسية

العلوم المالية و المحاسبية

الموضوعات

• الأردن
• التنبؤات الاقتصادية
• النماذج الرياضية

عدد الصفحات

114

قائمة المحتويات

• APA
• MLA
• AMA

لغة النص

الإنجليزية

نوع البيانات

رسائل جامعية

رقم السجل

BIM-310883