Forecasting emerging markets interest rates using optimal time-varying financial conditions index

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dc.contributor.authorDlamini, Lefu Jonase
dc.date.accessioned2019-01-11T08:52:15Z
dc.date.available2019-01-11T08:52:15Z
dc.date.issued2018
dc.descriptionA research report submitted to the Faculty of Commerce, Law and Management, in partial fulfilment of the requirements for the degree of Master of Management in Finance and Investment, University of the Witwatersrand, Johannesburg, 2018
dc.description.abstractThis paper aims to optimise the financial conditions index (FCI) indicator that best describes the monetary policy interest rate setting behaviour of twelve emerging market central banks. This is achieved by analysing and looking at the background of modelling interest rates and forecasting interest rate setting behaviour from various regions globally. Following the credit crisis of 2008, the conventional wisdom and foundations that prevailed before were profoundly shaken. Particularly the conduct and behaviour of central banks in response to financial conditions assumed centre stage. Consequently, there has been a consensus among economists and policymakers on the importance of financial conditions, and the influence thereof, on the interest rate setting. However, in order for central banks to achieve their financial stability objectives, they need to construct an optimal indicator that best describes financial conditions. To construct such an optimal indicator, this paper firstly investigates whether the central banks of emerging markets follow the Taylor rule in setting their interest rates. Secondly, it investigates whether the FCI with optimal time-varying weights better describes interest rate movements in emerging markets, when incorporated in the Taylor rule. Lastly, it evaluates interest rate predictability by comparing various models that include non-optimized FCIs. The paper finds that the majority of emerging countries follow the Taylor rule. It also finds that most emerging markets take into account the information contained in FCIs and the majority of these countries, optimize the variables that enter the FCIs. When evaluating the forecasting accuracy of these models, the paper finds that the optimized model ranks superior in most countries in terms of forecasting accuracy. The optimization and allocation of the variables that enter the optimized FCI happen in a similar manner that was proposed by Markowitz in portfolio allocation theory.en_ZA
dc.description.librarianGR2019en_ZA
dc.format.extentOnline resource (iv, 52 leaves)
dc.identifier.citationDlamini, Lefu Jonase (2018) Forecasting emerging markets interest rates using optimal time-varying financial conditions index, , University of the Witwatersrand, Johannesburg, <http://hdl.handle.net/10539/26250>
dc.identifier.urihttps://hdl.handle.net/10539/26250
dc.language.isoenen_ZA
dc.subject.lcshGlobal Financial Crisis, 2008-2009
dc.subject.lcshCapital market
dc.subject.lcshMonetary policy
dc.titleForecasting emerging markets interest rates using optimal time-varying financial conditions indexen_ZA
dc.typeThesisen_ZA
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