Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.774321
Title: Developing a new stock scoring model for Shariah-compliant investment
Author: Simon, Shahril
ISNI:       0000 0004 7961 5250
Awarding Body: University of Bolton
Current Institution: University of Bolton
Date of Award: 2019
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Abstract:
This study aims to develop a new stock scoring model, M-Score model, that based on the musharakah parameters by using a momentum technique that separate the out-performing Shariahcompliant stocks from the under-performing. Motivation for this study is centred towards the performance dragged from Shariah-compliant stocks in relative to the conventional stocks during the stock market recovery and the out-performance of Shariah-compliant portfolio attributed by a few stocks only. Hence, separating the out-performing from the under-performing Shariahcompliant stocks will enhance the portfolio returns. In doing so, a quantitative research in time series analysis is designed to measure the momentum, periodical changes, of the musharakah parameters. The essential musharakah parameters identified are industry performance, management style, profitability ratios and capital growth. These musharakah parameters are then represented by the financial indicators such as sector return, book value, cash flow, equity return, asset return, total assets and enterprise value to determine the momentum of stock price returns. There are several main findings based on the quantitative analysis of the research results. First, this study has evidenced that musharakah parameters explain stock price returns since they have monotonic positive relationship with the newly developed M-Score model. Second, the model improves its statistical significance when the financial indicators are progressively added into the equation. Importantly, the M_Score model requires all musharakah parameters to be included in generating robust results. Third, there has been no concern on the temporal issue in the M-Score model since it responds well to every stock market cycle and to diverse investment horizons. Fourth, the M-Score model also has monotonic positive relationship with company size, stock orientations, trading volume, stock price or leverage position. Fifth, the predictive power has improved substantially when the M-Score model employs active investment strategies i.e. long-only and long-short and has further improved when the restriction is relaxed by allowing short selling. On another note, this study has contributed in several ways. On theoretical side; in contrast to efficient market hypothesis theory, the M-Score model shows that stock market is inefficient and therefore, stock price returns are predictable. Although past performance is no guarantee of future returns, historical data remains the ideal tool to forecast the stock prices. As on the empirical side; the M-Score model captures most of the financial information and helps process recent information better. When applied to various portfolio strategies, the M-Score model has shown that active investing produces higher excess returns than passive investing. Moreover, the M-Score model does not discriminate stock specific characteristics like the company size, value or growth orientation, liquidity, stock price and leverage position. On methodological side; unlike many other models, using momentum of multiple financial indicators on M-Score model has addressed the concern of single variable biasness. Furthermore, the M-Score model does not require long historical data to produce robust results. In addition, the model is flexible to handle missing values and can withstand the outliers. Accordingly, this study discovers that the M-Score model can assist those investing in Shariah-compliant stocks to make informed investment decisions by using the model as an alternative investment analysis tool to forecast stock price returns, to determine market timing and to construct profitable stock portfolio returns.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.774321  DOI: Not available
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