DYNAMICS OF NOMINAL EXCHANGE RATE WITH PRICE LEVELS: WHAT HAPPENS IN INTERNATIONAL MARKETS?

Since inception exchange rate determination in Pakistan has been studied extensively but under various approaches. Current study explores empirically the relationship of the domestic price level & foreign price level with nominal exchange rate in Pakistan, using a daily data set for 13 years (July 2000- June 2013) as provided by State Bank of Pakistan. Variables are analyzed for stochastic properties and existence of unit root, for this purpose ADF is used. Along with regression analysis the co-integration is tested to detect long term co-movement between variables. It has been found that domestic price level has positive relationship with nominal exchange rate, whereas, foreign price level has a negative relationship with nominal exchange rate in the long run

Gold, Oil, and Stocks

We employ a wavelet approach and conduct a time-frequency analysis of dynamic correlations between pairs of key traded assets (gold, oil, and stocks) covering the period from 1987 to 2012. The analysis is performed on both intra-day and daily data. We show that heterogeneity in correlations across a number of investment horizons between pairs of assets is a dominant feature during times of economic downturn and financial turbulence for all three pairs of the assets under research. Heterogeneity prevails in correlations between gold and stocks. After the 2008 crisis, correlations among all three assets increase and become homogenous: the timing differs for the three pairs but coincides with the structural breaks that are identified in specific correlation dynamics. A strong implication emerges: during the period under research, and from a different-investment-horizons perspective, all three assets could be used in a well-diversified portfolio only during relatively short periods

Dynamic interactions between commodity prices and Australian macroeconomic variables

Price swings of commodities affect the economies of commodity exporting nations worldwide and these fluctuations are a major concern for Australian policy makers. Australia is one of the major commodity exporting countries in the global market; therefore, the main focus of this thesis was to shed light on the influence of various fundamental macroeconomic variables on Australian commodity prices. First, emphasis was placed on what magnitude changes in real interest rates and fluctuations of the real exchange rate account for volatility in commodity prices and whether commodity prices tend to show overshooting phenomena (J. Frankel, 1986; J. Frankel, 2006) in reaction to interest rate changes. The possible contribution of global real economic activity to Australian commodities prices was then assessed, which can lead to both higher interest rates and volatile commodity prices (Akram, 2009; Svensson, 2008) within Australia. Similarly, the current slowdown in world economic growth after several years of high growth might clarify the sharp drop in real interest rates and commodity prices. In addition, the present study explored whether Australian resources stock prices had significant predictive ability for the future global commodity price index as suggested by Rossi (2012). Johansen’s (1988, 1991) cointegration technique was utilised to attain the above research objectives and to examine the long-run relationship of the considered variables. This thesis utilised seasonally adjusted monthly time series for real interest rate, real exchange rate, industrial production and resources stock price from January 2000 to December 2015 after considering an appropriate structural break. The study found significant long-run relationships among the variables; therefore, the vector error correction model was applied to judge the short-run dynamic relationship among variables. Then, the forecast ability of all variables was assessed by employing vector error correction Granger causality or block exogeneity tests. Single equation models do not allow the examination of dynamic relations between commodity prices and other macroeconomic variables over different time horizons (Akram, 2009); therefore, the study applied the impulse response technique as well as forecast error variance decomposition to assess the comparative influences of diverse shocks to the variations in key variables of the proposed commodity price model. The research found significant negative relationships between real interest rates and commodity prices. However, the impulse response results did not show any immediate responses of commodity prices because of an impulse in the real interest rate. This showed a significant negative response of commodity prices after six months of the initial shock and the importance of interest rate information to predict the commodity prices in the long run. In two years’ time, approximately one third of the commodity price changes will be explained by the shocks in real interest rate. The shocks from opposite directions showed a significant negative response for real interest rate after having shocks from Australian commodity prices in the medium term. The results of the present study also suggested an immediate fall in Australian commodity prices and thereafter increases at a higher rate significantly in response to the real exchange rate shock, consistent with Frankel’s (1986) overshooting model of commodity prices. This finding raised the question as to whether real exchange rate shocks are a significant factor of Australian macroeconomic instability as commodity export plays an important role in its economy. Results of the present study revealed the response to this query as being in the negative, especially in the long run. The interaction of these two variables from opposite directions showed interesting results. Separate commodity-related drivers of exchange rates results showed that Australian real exchange rate movements were not purely random. Vector error correction-based Granger causality tests indicated a strong support of causality from commodity prices to real exchange rate in the short run. The impulse response results showed the most noteworthy results. The shocks from Australian commodity prices showed immediate significant depreciation in real exchange rates and the index remained depreciated significantly in all horizons, which shows the complete opposite results to many studies (Connolly & Orsmond, 2011; Minifie, Cherastidtham, Mullerworth, & Savage, 2013; Plumb, Kent, & Bishop, 2013; Sheehan & Gregory, 2013). However, this finding is consistent with the theoretical explanation provided by Dumrongrittikul (2012) to explain the puzzle of the Chinese real exchange rate, which is supported by the theoretical explanation of S. Edwards’ (1989) real exchange rate model. The results of the present study also showed that the shock to industrial production had a negative effect on Australian commodity prices and the effect remained significant during all time horizons. It also showed that the commodity price fluctuation had predictive ability of the Australian resources stock prices. After considering these above findings, several policy recommendations for relevant Australian authorities are suggested and limitations are discussed including the pathway for future research

Forecasting Gold Price with Auto Regressive Integrated Moving Average Model

The present study forecasts the gold price of India by using ARIMA (Auto Regressive Integrated Moving Average) model over a period of 25 years from July 1990 to February 2015. The study also uses Mean Absolute Error(MAE), Root Mean Square Error(RMSE), Maximum Absolute Percentage Error(Max APE), Maximum Absolute Error(Max AE), and Mean Absolute Percentage Error(MAPE) to evaluate the accuracy of the model.  The result of the study suggests that ARIMA (0, 1, 1) is the most suitable model used for forecasting the Indian gold prices since it contains least MAPE, Max AE and MAE .The study suggests that the past one-month gold price has a significant impact on current gold price. The result of the study are particularly important to investors, economists, market regulators and policy makers for understanding the effectiveness of gold price to take better investment decision and devise better risk management tools. Keywords: ARIMA, Gold Price, Forecasting techniques, Multiple Regression JEL Classifications: G1, G17, C

Drivers of agricultural future commodity prices : a co-integration analysis

Mestrado em FinançasEstes contratos de futuros são negociados na ICE (Intercontinental Exchange, Inc.) e apresentam uma liquidez notável. Para este estudo foram recolhidos dados semanais, desde março de 2013 até março de 2015, num total de 105 observações. Os preços foram coligidos a partir da base de dados Quandl, e uniformizados através do método Back-Adjusted. Começámos por estudar a correlação entre o Índice Dólar Americano e o preço do Petróleo. Confirmando a conclusão de anteriores estudos, encontrámos uma correlação negativa entre o preço dessas duas variáveis. O teste de causalidade de Granger forneceu-nos evidência estatística suficiente para concluir que uma variação no preço do Petróleo tem impacto no valor do Índice Dólar Americano. Por aplicação do teste de cointegração de Johansen, encontrámos vetores de cointegração entre as variáveis Petróleo, Índice Dólar Americano e cada um dos bens agrícolas estudados. Em seguida, obtivemos modelos de vetores de correção de erro (VECM). Embora alguns destes modelos se tenham revelado menos sólidos, conseguimos, ainda assim, estabelecer uma relação entre as variáveis, nomeadamente no caso da soja, que pode ser considerada um referência para quem negoceia em contratos de futuros.This dissertation aims to study the effects of changes in the prices of future contracts on Brent Crude Oil and US Dollar Index in the price of several agricultural future contract prices (Cocoa, Cotton, Coffee, Sugar, Soybean, Wheat and Corn). These futures outrights are traded on ICE (Intercontinental Exchange, Inc.) and have a remarkable liquidity. Weekly data was used from March 2013 to March 2015 with a total of 105 observations. The prices were collected from the Quandl futures database and are settlement prices from the front outrights. The Back-Adjusted method was chosen to perform the roll over. We started by studying the correlation between US Dollar Index and Brent Crude Oil prices. Confirming the conclusions of other studies, we found a negative correlation between the prices of Brent Crude Oil and the US Dollar Index. The Granger Causality test gave us enough statistical evidence to conclude that a variation in Brent Crude Oil prices indeed cause an impact on the US Dollar Index. By applying Johansen`s cointegration test we found cointegrating vectors between Brent Crude Oil, the US Dollar Index and each one of the studied agricultural commodities. The next step was to build vector error correction models. Although some of them proved not to be rock solid, we manage to establish a link among the variables, namely in the case of Soybean, which produce remarkable results and may, in fact, be treated as a benchmark for traders of future contracts

Structural Modelling And Analysis Of The Behavioural Dynamics Of Foreign Exchange Rate [HG3851. Y51 2006 f rb].

Tesis ini berkaitan dengan Kadar Wang Pertukaran Asing (KWPA) yang dihasilkan oleh satu regime urusniaga bebas. Pada amnya, kita mengkaji Pemodelan Struktur dan Analisis Tingkahlaku Dinamik Kadar Pertukaran Wang Asing. This thesis deals specifically with the foreign exchange rates that resulted from free float regimes. In general, we study the structural modelling and analysis of the behavioural dynamics of foreign exchange rates

Technical analysis on foreign exchange markets: MACD and RSI

For many years, technical analysis has been a topic of discussion regarding its contribution to rational investment decisions in financial markets. In an era where computational power is greater than ever and so many market analysis tools have been developed, one may question if the least sophisticated indicators, widely used in the past, remain relevant to current traders or if, on the other hand, their ability to predict investment opportunities lost their value. In this empirical study, we assess the individual performance of Moving Average Convergence/Divergence (MACD) and Relative Strength Index (RSI) in the Forex Market, specifically on the top five currency pairs currently traded, namely, USD/EUR, USD/JPY, USD/GBP, USD/AUD and USD/CAD, using daily closing prices from January 1st, 2009 to December 31st, 2018. Based on the signals collected from the tested indicators, we simulate long and short orders using a predetermined capital amount in order to assess the overall performance and accumulated profitability of each indicator. We conclude that, for both indicators, the results are ambiguous as they differ depending on the currency pair or the period for which they are applied to. Therefore, it is not possible to confirm that these tools can systematically outperform the market indicating profitable decisions in the covered context.Há muito tempo que a análise técnica tem sido um tópico de discussão relativamente à sua contribuição para decisões racionais de investimento nos mercados financeiros. Numa era em que o poder computacional é maior do que nunca e tantas ferramentas de análise de mercado foram desenvolvidas, pode-se questionar se os indicadores menos sofisticados, amplamente utilizados no passado, permanecem relevantes para os investidores atuais ou se, por outro lado, a sua capacidade de prever oportunidades de investimento perderam o seu valor. Neste estudo empírico, avaliamos o desempenho individual dos indicadores Convergência/Divergência das Médias Móveis (MACD) e Índice de Força Relativa (RSI) no mercado cambial, especificamente nos cinco principais pares de divisas atualmente negociados, nomeadamente, USD/EUR, USD/JPY, USD/GBP, USD/AUD e USD/CAD, usando preços de fecho diários de 1 de janeiro de 2009 a 31 de dezembro de 2018. De acordo com os sinais obtidos dos indicadores testados, simulamos ordens de compra e venda usando um capital predeterminado de forma a avaliar o desempenho global e a rentabilidade acumulada de cada indicador. Concluímos que, para ambos os indicadores, os resultados são ambíguos, uma vez que diferem consoante o par de divisas ou o período para o qual são aplicados. Desta forma, não é possível confirmar que aqueles indicadores superam o mercado sistematicamente indicando decisões rentáveis no contexto abordado

Three essays on exchange-rate misalignment

Theories of exchange-rate determination have generated a vast theoretical and empirical literature. This thesis adds to that body of literature by asking three questions. (i) How do policymakers respond to exchange-rate misalignment? (ii) How does misalignment affect the decisions of financial-market participants? (iii) What do exchange-rate dynamics reveal about the choices of investors in the face of currency risk? These three questions are tackled with studies that offer broad and tractable conclusions and contribute to furthering the current field of research

Forex Trading System Development

The focus of this report is to demonstrate the process of building a trading system to be used in the foreign exchange market. The report will introduce an overview of the currency market and different trading techniques and concepts used in the construction of a trading system. The process of building a forex trading strategy, from initial formation to optimization, is laid out based on existing research. The results and analysis of the group’s own experience building and testing a forex strategy is included to exhibit the method presented in the report

Analysis of dependence structure between the Rand/U.S Dollar exchange rate and the gold/platinum prices

Copulas functions are a flexible tool for modelling the dependence structure between variables. The joint and marginal distributions of Copulas are not constrained by the assumptions of normality. This study examines the dependence structure between the gold, platinum prices and the ZAR/U.S.D exchange rate using Copulas. The study found that marginal distributions of Copulas follows the ARMA (1, 1)-EGARCH (1, 1) and ARMA(1, 1)-APARCH (1, 1) models under different error terms including the normal, the student-t and the skew student-t error terms. It used the Normal, the Student-t, the Gumbel, the rotated Gumbel, the Clayton, the rotated Clayton, the Plackett, the Joe Clayton and the Normal time varying Copulas to analyse the dependence structure between returns prices of gold, platinum and ZAR/U.S.D exchange rate. The results showed evidence of a positive strong dependence between the returns prices of gold, platinum and returns on the Rand/U.S.D exchange rate for constant and time varying Copulas. The result also showed a co-movement of exchange rates and gold and platinum prices during a rise or declining prices of gold and platinum. The results imply that fluctuations in gold and platinum prices generate Rand/U.S.D exchange rate volatility.StatisticsM. Sc. (Statistics