Browsing by Author "Bayram, Kamola"

This research sought to identify the optimal level of gold as a reserve asset to be held in official portfolios in order to enhance stability of nations in times of economic, financial and/or geopolitical turmoil by preserving the value of assets held in central bank reserves. After the collapse of the Bretton Woods fixed exchange rate system in 1971, countries moved towards floating exchange rates and the expectation was that requirement for foreign reserves would decrease. However, central banks currently hold more foreign exchange reserves, with the aim of enhancing the credibility of their exchange rate policy. The demand for gold, which was the main reserve asset prior the collapse of the Bretton Woods system, has increased as a reserve asset once again following the global financial crisis of 2008 (GFC), given gold’s characteristics as a safe haven asset and a store of value. The study analysed official reserves of four countries namely, Malaysia, Turkey, KSA and Pakistan. The countries were taken as a proxy for OIC member countries. The Black-Litterman model was used to build a new strategic portfolios with optimal allocation to gold. Another focus of the study was to identify and measure the determinants of the price of gold, which requires analysis of the gold market and other macroeconomic variables. By utilizing Multiple Regression Analysis the study tested the impact of the major economic factors: real interest rates (RIR), inflation rates (CPI), Dow Jones Industrial Average (DJIA), oil price (OP), silver price (SP), M2 money supply (M), USA Dollar Trade Weighted Index (USD Index) and official gold holdings (OGH) on gold prices (GP). To the extent of our knowledge the impact of OGH on GP have not been studied yet. The monthly data for the period from January 2005 to December 2014 was employed. The thesis also identified the opportunity cost of holding gold, in relation to the stock market, for the four countries under the analysis. The focus was to detect if gold acts as safe haven or hedge asset in times of distress. The Threshold GARCH (TARCH) model was utilized. The analysis used daily data for the period 2005-2014 for four OIC member countries: Malaysia, Turkey, KSA and Pakistan. The data for selling prices of gold was represented by selling prices derived from Saudi Gold Exchange (SGE), Pakistan Mercantile Exchange (PMEX), Precious Metals and Diamonds Markets (PMDM) for Turkey and Kijang Emas for Malaysia. The returns on Saudi Stock Exchange (Tadawul), Karachi Stock Exchange (KSE), Borsa Istanbul (BIS) and Kuala Lumpur Composite Index (KLCI) were employed to represent aggregate prices of stock market investment. The study showed that all countries under the analyses should increase their gold holdings to preserve the value of the portfolio during times of financial turmoil. It was also found that gold has safe haven asset features for all four countries under the analysis which shows that gold outperforms the average portfolio during times when stock market faces distress. The results of the Multiple Regression showed that that the variables that have significant impact on GP, for the studied period, are M2 money supply, SP, DJIA, RIR and CPI.

The binomial tree model is a natural bridge, overture to continuous models for which it is possible to derive the Black-Scholes option pricing formula. In turn a binomial branch model is the simplest possible non–trivial model which theory is based on the principle of no arbitrage works. The binomial tree model is defined by a pair of real numbers (u,d) such that the stock can move up from S0 to a new level, uS0 or down from S0 to a new level, dS0, where u > 1; 0 < d < 1. We shall call pair (u,d) the environment of the binomial tree model. The binomial tree model is called a random binomial tree model, if the corresponding environment is random. We introduce a simplest random binomial tree model, illustrating that risk – neutral valuation gives the same results as no-arbitrage arguments and describe some properties of the random binomial tree models. The random binomial tree model produces results which are a reflect of the real market better than the binomial tree model when fewer time steps are modelled. The model is solvable and there exist analytic pricing formulae for various options. In this thesis we produce these formulas for a European call and put options and also an American call and put options for a single period, a two periods and an arbitrary N-period time steps.