UIRP Hypothesis

Page 3: Introduction to the Financial System Page 7: Commercial Banks Page 12: The Share Market and the Corporation Page 15: Corporations Issuing Equity into the Share Market Page 19: Investors in the Share Market Page 24: Short-term Debt Page 28: Medium- to Long-term Debt Page 32: Interest Rate Determination and Forecasting Page 37: The Foreign Exchange Market Page 40: Factors that Influence the Exchange Rate Page 42: Futures Contracts and Forward Rate Agreements Page 47: Options

The exchange rates risk that is associated with economic, transaction, and translation exposure in Indian market. From the analysis, anticipate the fluctuations that seem to occur in the next 24 months

In order to determine the determinants of foreign exchange rate in Mauritius, a regression model is used using time series data. The Mauritius Exchange Rate Index 2 (MERI2) is used as the dependent variable while inflation rate, interest rate, government debt to GDP, terms of trade and GDP growth rate are used as independent variables in this study.

This paper aims to compare the Japanese Yen against the US Dollar over a five year period starting from 2005 till 2010. The exchange traded fund for Japanese Yen shall also be discussed in the paper and afterwards an analysis of both the currencies shall be presented. There are different factors that influence the exchange rate differences between any two chosen currencies. The effects produced by these different exchange rates can be of quite different intensity. The most common elements that have an impact on exchange rate difference include economic factors, socio political factors and other behavioral or technical factors also. The macroeconomic factors such as growth of a country, employment rate, gross domestic product etc. All

Prior to 1970, fixed, or say pegged exchange rate regime was adopted by almost all countries worldwide. Afterwards, some countries have gradually made the transition from fixed to flexible exchange rates, which allow currency to float

Interest rate is considered as one of the main parameters to control the economic conditions of any country. Interest rate is the key variable for time value of money, which causes a greater shift in money markets and capital markets. This study is basically carried out for the capital market or stock market.

The random walk model suggests that the current exchange rate is the best predictor of the future exchange rate. In other words, the current exchange rate reflects the future exchange rate. However, this model is questioned, past history of the exchange rate can’t predict the future of the exchange rate so we can say that the random walk model is inconsistent with the technical analysis because it tries to use today’s exchange rate to predict tomorrow’s exchange rate.

Various fundamental approaches exist in forecasting future exchange rates. The key approaches discussed below will include Purchasing Power Parity (PPP) and Asset Market Approach. The balance of payment approach will be utilised instantaneously with other methodologies in order to establish a forecasting methodology for EUR and USD against the AUD. Emphasis will be placed on PPP, International Fisher Effect and the Asset Market Approach.

We chose Japanese Yen as are benchmark exchange rate because Japan is part of the G-10 Countries with U.S. and one of the major economies in the world. Japan is also a Key U.S. Business Partner in importing and exporting goods and services. Through our findings we have developed our insight of the Japanese Yen being very volatile to the dollar. In the graph shown below, we can conclude that from 1995 till 1999 the Japanese yen was weaker against Dollar. The process has been repeated between the years 2001-03 and 2006-recent.

The historical data of foreign currencies exchange rate of New Zealand Dollars - NZD against United State Dollars - USD are collected from http://www.rbnz.govt.nz/statistics/key-graphs/key-graph-mortgage-rates.The factor that influenced the Forex rate are considered and their respective dataset are collected individually.

Use the table to answer following question. Yen: Spot and Forward (¥/$) Mid Rates Bid Ask Spot 129.87 129.82 129.92 Forward Rates 1 month 129.68 -20 -18 6 months 128.53 -136 -132 Swaps 2 year 117.65 1232 1212 3 year 115.50 1452 1422 Pound: Spot and Forward ($/£) Mid Rates Bid Ask 1.4484 1.4481 1.4487 1.4459 1.4327 1.4250 1.4225 -26 -160 -238 -265 -24 -154 -230 -253 16)

In comparing the exchange rates of the USD to foreign currencies, four additional countries were used to complete a two year comparison: Japanese Yen (YEN), European Euro (EURO), British Pound (GBP), and Mexican Peso (MXN). Exchange rates were obtained from March 2013 through March 2015. The monthly average direct exchange rates were compiled in graphs to show the strength of the USD against the foreign currencies of each country.

This study employs the adjusted price of GBP exchange rates for 12 different currencies where BNKR’s investments are dominated in, during the period of January 2010 till July 2015. The total number of daily logarithmic returns of each exchange rate is 1455. The daily logarithmic return is defined as:

Current spot rates………………………………….… Purchasing power parity forecasts…………….…… International Fisher forecasts………………………. Implied real interest rates…………………………… Forecasting with real interest rates………….…….. Forward rates………………………………….……… Real economic activity and misery………….……… Balance of payments approach……………….……. Current

This thesis explores the long run relationship between financial development and economic growth using time series modeling. For each of the four case-countries three types of Vector Autoregression (VAR) models will be developed except for the case of Serbia where only VAR related to credit institutions development will be developed since data related to stock market development indicators were unavailable to author. For the case of Croatia, Slovenia and China three separate VAR models will be applied. First, bivariate VAR model to explore the connection between credit institutions development and economic growth. Second, bivariate VAR model to explore the connection between stock markets development and economic growth. Third,