Modeling the Exchange Rate Volatility Using the BRICS GARCH-type Models

The paper models the performance of GARCH-type models on BRICS exchange rates volatility. The levels of interdependence and dynamic connection among the BRICS financial markets using appropriate univariate time series models were evaluated for the period January 2008 to January 2018. The results revealed the presence of ARCH effects in the BRICS exchange rates. The univariate GARCH models for the BRICS exchange rates were fitted to the data using Student t-distribution. The GARCH (1,1) model found the unconditional volatility for each of the BRICS exchange rates series while EGARCH (1,1) and TGARCH (1,1) models presented the leverage effect. Moreover, the EGARCH (1,1) model illustrated that the asymmetric effects dominate the symmetric effects except for South Africa. The TGARCH (1,1) model on the other hand revealed contrary findings. The paper recommends a study be considered to draw comparison on the different types of GARCH models on the time varying integrated data other than the ones used in the paper.

THE RESPONSE OF ZIMBABWE TOBACCO EXPORTS TO REAL EXCHANGE RATES VOLATILITY

The focus of this study was on investigating the response of tobacco exports to real exchange rates and real exchange rate volatility and other factors in Zimbabwe using secondary data spanning from 1980 to 2019. Bilateral nominal exchange rates and time-variant weights of Zimbabwe’s 10 major trading partners were calculated and used to compute the real exchange rate index. The time-dependent weighting system was used to better represent the evolution of trade patterns in the index. The arithmetic method was employed for computing the index. Generalized autoregressive conditional heteroskedasticity (GARCH) and autoregressive conditional heteroscedasticity (ARCH) models were used to generate the real exchange rate volatility index. The export response function was adopted as the tobacco exports response model. The variables in the tobacco exports response model were the realworld Gross Domestic Product (GDP), real exchange rate, terms of trade, real exchange rate volatility and dollarization. A vector error correction model (VECM) was used to estimate the response of tobacco exports to real exchange rate, real exchange rate volatility and other factors. The VECM results indicated that real world GDP was insignificant in both the short and long run. In the long run, the real exchange rate appreciation had a negative impact on tobacco exports. Conversely, in the short run, the depreciation of real exchange rate had a positive impact on tobacco exports. Hence, the government has to adopt other mechanisms that reduce uncertain movements of exchange rates.

Interest Rate Policy and Exchange Rates Volatility Lessons from Indonesia

Whether or not inflation targeting adoption leads to increased volatility of exchange rates is controversial. The volatility increases with inflation targeting as a result of the flexible exchange rate regime. Others argue that inflation targeting delivers the best outcomes in terms of lower exchange rate volatility. The purpose of this paper is to investigate whether interest rate policy in inflation targeting frameworks – that is subjected to control inflation rate – may reduce the volatility of exchange rates. To test the hypothesis, we use monthly data in the case of Indonesia over the period 2005(7)-2016(7). Several control variables are introduced in the regressions. The result of the autoregressive distributed lag model proves the interest rate policy and foreign exchange intervention fail to reduce the exchange rates volatility. It seems inflation targeting in Indonesia puts too much emphasis on stabilizing the domestic currency thus leading to benign neglect of stabilizing its external value, ultimately resulting in increased exchange rate volatility. These findings suggest that central bank credibility plays an important role in conducting inflation targeting policy which operates primarily through a signalling effect.

Real Time Data

Interpretation of exchange rate volatility in the light of economic fundamentals comprises an issue of interest for policymakers when it comes to implementing the monetary policy. Understanding the impact of economic news on the Lek exchange rate against two main hard currencies, Euro and US dollar, would serve to better orient the monetary policy and forex market agents positioning in time. Exchange rates volatility on economic news in short-term is an often discussed phenomenon in the economic literature, but through this material we tend to measure these effects in the Albanian foreign currency market and contribute in the literature interpreting foreign currency markets volatility in developing economies. Very often, domestic foreign exchange movements are attributed to developments in large international markets. In the case of Albanian Lek volatility analysis, we tend to find answers regarding the importance of economic news coming from the two main economies in focus, Eurozone and the US. Furthermore, we investigate the importance of the economic information flow in Albania in determining the Lek exchange rate against Euro and US dollar. For a period in focus from January 2007 until July 2012, we try to understand if the exchange rate volatility has been a result of economic fundamentals or financial markets stress related economic news.

Exchange rate volatility in West African countries: is there a shred of Spillover?

Purpose The purpose of this paper is to evaluate selected West African currencies/US dollar exchange rates for the evidence of volatility spillover. Specifically, the paper examines West African CFA franc, Gambian dalasi and Nigerian naira exchange rates in relation to the USD, for any evidence of shock and volatility spillover. Design/methodology/approach The author employs multivariate GARCH (1,1)–BEKK model which enables the evaluation of the interaction within the volatility of two or more series because of its capability to detect volatility spillover among time series observations, as well as the persistence of volatility within each series. Findings The major findings of this study are as follows: there is evidence of volatility clustering in West African CFA franc, Gambian dalasi and Nigerian naira exchange rates in relation to the USD. There is evidence of bi-directional shock and volatility spillover between the Nigerian naira and West African CFA franc/USD exchange rates, and uni-directional shock spillover from the Gambian dalasi to the West African CFA franc/USD exchange rates. There is, however, no evidence of exchange rate shock and volatility spillover between Nigerian naira and Gambian dalasi. Originality/value Although considerable literature exists on the volatility of exchange rate in West Africa and comparative analysis of exchange rates volatility in few countries of West Africa, there is absence of empirical studies on exchange rate volatility spillover among countries in the region. Since containing exchange rate volatility is one of the major objectives of monetary policy, understanding the nature and direction of exchange rate volatility spillover would propel formulation exchange rate policies that would minimise exchange rate uncertainty and entrench sustainable development. In addition, the nature of exchange rate volatility spillover between West African countries would provide basis for international traders and foreign portfolio investors to develop effective strategies for hedging against exchange rate shocks that are propagated across countries by designing appropriate risk management techniques.

Application of Artificial Neural Network (Ann) in Modeling Foreign Currency Exchange Rates

Investors, Policy makers, Governments etc. are all consumers of exchange rates data and thus exchange rate volatility is of great interest to them. Modeling foreign exchange (FOREX) rates is one of the most challenging research areas in modern time series prediction. Neural Network (NNs) are an alternative powerful data modeling tool that has ability to capture and represent complex input/output relationships. This study describes application of neural networks in modeling of the Kenyan currency (KES) exchange rates volatility against four foreign currencies namely; USA dollar (USD), European currency (EUR), Great Britain Pound (GBP) and Japanese Yen (JPY) foreign currencies. The general objective of the proposed study is to model the Kenyan exchange rate volatility and confirm applicability of neural network model in the forecasting of foreign exchange rates volatility. In our case the Multilayer Perceptron (MLP) neural networks with back-propagation learning algorithm will be employed. The specific objectives of the study is to build the neural network for the Kenyan exchange rate volatility and examine the properties of the network, finally to forecast the volatility against four other major currencies. The proposed study will use secondary data of the mean daily exchange rates between the major currencies quoted against the Kenyan shilling. The data will be acquired from the central bank of Kenya's (CBK) website collected for ten years of trading period between the years 2005 to 2017. The data will be analyzed using both descriptive and inferential statistics, with the aid of R's neuralnet package. A number of performance metrics will be employed to evaluate the model. Conclusion and recommendations will be made at the end of the study.

Global Derivatives Hedge Fund Strategies

Hedge funds represent discretionary pools of capital that have very flexible investment strategies. Some funds allocate capital to derivative-based strategies on a global basis, loosely referred to as global macro funds. These investments are typically high-level, directional views on exchange rates, volatility, interest rates and other macro-related factors. In short, this “go anywhere” strategy often uses futures, forwards, and options on equities as well as interest rates and currencies. The investment manager employs top-down investments by placing high-level bets at the country level as well as taking positions in stock, currency, and derivatives on particular countries based on economic views. Many global macro funds increasingly use systematic managed futures, although fewer funds follow a discretionary managed futures strategy.