Assessment of Exchange Rate Volatility Using Garch Models: A Case Study from Indian Markets| Chapter 1 | Contemporary Research in Business, Management and Economics Vol. 7

 

The present study focuses on the time series behaviour of select currencies using GARCH Models. Exchange rate volatility is a useful measure of uncertainty about the economic environment of a country. Various forms of statistical models have been evolved to capture the volatility effect. These models are often applied to estimate the degree of exchange rate instability. Monthly returns of currency prices exhibit aggressiveness and a high degree of interdependence. In particular, generalized autoregressive conditional heteroscedastic GARCH (1, 1) processes fit to data very satisfactorily. A number of statistically compared out-of-sample estimates of monthly return variances are produced. It is discovered that GARCH model-based forecasts are preferable. This model is predicated on the basic assumptions of linearity and dependency.  This paper aims to model the volatility of INR exchange rates against USD for the period from January 2000 to 5 January 2023 using the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models. Both symmetric and asymmetric models have been applied to measure factors that are related to the exchange rate returns such as leverage effect and volatility clustering. Based on the results, the static forecast of GJR-GARCH (1, 1) is the best model for predicting the future pattern for both INR and USD. The sustainability and relative value of a currency fluctuate due to several factors such as changes in demand & supply of goods & services, changes in the cost of the economy, rise & cut of interest rates, fiscal policy, govt.’s anti-inflationary measures, and inflation.

 

Author(s)details:-

 

Jagannayaki K.
MBA Department, Institute of Aeronautical Engineering, Dundigal, Hyderabad, Telangana, 500043, India.

 

Sreekanth Yerramilli
Department of Management Sciences, Sun Stone-MRU University, India.

 

Vara Lakshmi Thavva
MBA Department, Institute of Aeronautical Engineering, Dundigal, Hyderabad, Telangana, 500043, India.

Nunna Suresh
MBA Department, Institute of Aeronautical Engineering, Dundigal, Hyderabad, Telangana, 500043, India.

 

Please See the book here :- https://doi.org/10.9734/bpi/crbme/v7/129

Study on the Effect of Economic Factors on the Malaysian Exchange Rate | Chapter 3 | Current Aspects in Business, Economics and Finance Vol. 1

The impact of economic variables on the volatility of the Malaysian exchange rate must be investigated since the value of the Malaysian currency is declining. The World Development Indicators (WDI) gathered yearly time series data on GDP, unemployment rates, and currency exchange rates. The information on inflation rates was given by Malaysia's Ministry of Statistics. 120 observations were examined using the Eviews programme between 1989 and 2018. Descriptive statistics initially establish the mean, minimum, maximum kurtosis, skewness, and standard deviation of the data. Using the Phillips-Perron (P.P.) and Augmented Dickey-Fuller (ADF) approaches, data stationarity is examined. You can determine whether there is a relationship between the two variables using a correlation test. Multiple regression analysis is used to analyse the influence and significance of the connection between the variables. The information reveals a strong relationship between GDP and the exchange rate. GDP, inflation, and the exchange rate are closely correlated. In times of high unemployment, the exchange rate declines. However, this study found that neither unemployment nor inflation had an impact on the volatility of the exchange rate. To maintain the stability of the Ringgit, Malaysia must review its monetary policies.

Author(s) Details:

Suhana Mohamed,
Faculty of Business and Management, Universiti Teknologi MARA, Johor Branch, Pasir Gudang Campus, Johor, Malaysia.

Meezatulakma Abdullah,
Faculty of Business and Management, Universiti Teknologi MARA, Johor Branch, Pasir Gudang Campus, Johor, Malaysia.

Siti Salwa Hassan,
Faculty of Business and Management, Universiti Teknologi MARA, Sarawak Branch, Samarahan Campus, Sarawak, Malaysia.

Wan Muhd Faez Wan Ibrahim,
Faculty of Business and Management, Universiti Teknologi MARA, Sarawak Branch, Samarahan Campus, Sarawak, Malaysia.

Mohamad Azwan Md Isa,
Faculty of Business and Management, Universiti Teknologi MARA, Johor Branch, Segamat Campus, Johor, Malaysia.

Ferri Nasrul,
Faculty of Business and Management, Universiti Teknologi MARA, Johor Branch, Segamat Campus, Johor, Malaysia.

Mohd Khairul Ariff Noh,
Faculty of Business and Management, Universiti Teknologi MARA, Johor Branch, Segamat Campus, Johor, Malaysia.

Please see the link here: https://stm.bookpi.org/CABEF-V1/article/view/7298