Modeling volatility of Indian exchange rates under the impact of regime shifts: A study with economic significance analysis

2018 ◽  
Vol 12 (1) ◽  
pp. 43-59
Author(s):  
Dilip Kumar
Keyword(s):  
Exchange Rates ◽  
Long Memory ◽  
Structural Breaks ◽  
Forecast Accuracy ◽  
Regime Shifts ◽  
Policy Implications ◽  
Economic Significance ◽  
Volatility Model ◽  
Modeling Volatility ◽  
The Impact

In this paper, we assess the impact of regime shifts on the long memory properties of the Indian exchange rates. We make use of Sanso, Arago and Carrion (2004) Iterated Cumulative Sum of Squares (hereafter referred as AIT-ICSS) algorithm to detect the points of structural breaks in volatility series. Our findings indicate that incorporating the impact of sudden changes in volatility in the model indeed reduces the magnitude of long memory parameter. In the case of INR/JPY, we observe a shift in characteristics from long memory to mean reversion when the impact of regime shifts is included in the volatility model. Our findings also highlight that incorporating the impact of regime shifts in the model also improves the volatility forecast accuracy. Moreover, we implement a trading strategy based on risk-averse investor and find that the volatility forecasts based on the model which incorporate the impact of structural breaks provide substantial gains in return in comparison to volatility models with no structural breaks. These findings have important policy implications for financial market participants, investors and policy makers.

scholarly journals The Impact of Russia’s Oil-Dominated Energy Economic Changes on the Exchange Rate of Russian Ruble – Chinese Renminbi

2017 ◽  
Vol 13 (22) ◽  
pp. 173
Author(s):  
Maoguo Wu ◽  
Yue Yu
Keyword(s):  
Economic Development ◽  
Exchange Rate ◽  
Exchange Rates ◽  
Explanatory Power ◽  
Close Relation ◽  
Policy Implications ◽  
The Exchange Rate ◽  
Exchange Rate Changes ◽  
Pillar Industry ◽  
The Impact

Russia’s economic development has a close relation with China, due to geographical and historical reasons. This paper investigates whether the ruble – renminbi exchange rate changes accordingly when the pillar industry of Russia is drastically changing, and how the exchange rate changes and how it affects Russia’s economic development. In this paper, data of 7 variables spanning 122 months are selected based on related literature and availability of data. Regression analysis and empirical tests are carried out consequently. The results show that the energy price index represented by oil prices is negatively correlated with the exchange rate, and the explanatory power is as high as 41.1%. Following basic arbitrage methods and strategies, this paper verifies the feasibility of using arbitrage by comparing actual exchange rates with forecasted exchange rates. According to empirical results, problems witnessed in the process of ruble internationalization provides policy implications for China. China’s economy is utilized as an example to discuss the shortcomings of Russia’s economy. Related solutions are proposed.

Structural breaks in unbiased volatility estimator: Modeling and forecasting

2017 ◽  
Vol 11 (1) ◽  
pp. 27-50 ◽  
Author(s):  
Dilip Kumar
Keyword(s):  
Long Memory ◽  
Structural Breaks ◽  
Realized Volatility ◽  
Extreme Value ◽  
Trading Strategy ◽  
Risk Averse ◽  
Memory Property ◽  
Economic Significance ◽  
Forecasting Performance ◽  
Modeling And Forecasting

The study provides a framework to model the unbiased extreme value volatility estimator (The AddRS estimator) in presence of structural breaks. We observe that the structural breaks in the volatility based on the AddRS estimator can partly explain its long memory property. We evaluate the forecasting performance of the proposed framework and compare the results with the corresponding results of the models from the GARCH family. The forecasts evaluation exercises consider the cases when future breaks are known as well as unknown. Our findings indicate that the proposed framework outperform the sophisticated GARCH class of models in forecasting realized volatility. Moreover, we devise a trading strategy based on the forecasts of the variance to highlight the economic significance of the proposed framework. We find that a risk averse investor can make substantial gain using the volatility forecasts based on the proposed frameworks in comparison to the GARCH family of models.

scholarly journals Structural Breaks and Volatility Spillover in South Asian Economies

2020 ◽  
Vol 3 (1) ◽  
pp. 64-77
Author(s):  
Hafiz Rauf Iqbal ◽  
Syed Kashif Saeed ◽  
Syed Zulfiqar Ali Shah
Keyword(s):  
Financial Crisis ◽  
South Asian ◽  
Capital Markets ◽  
Financial Crises ◽  
Structural Breaks ◽  
Global Financial Crisis ◽  
Policy Implications ◽  
Specific Reference ◽  
Volatility Spillover ◽  
The Impact

Purpose - This study examines the volatility spillovers in the presence of structural breaks with specific reference to South Asian Capital markets. The global financial crisis of 2007-2009 has compelled policymakers to realize that financial instability has the potential to threaten economic stability and growth; therefore, managing the financial crisis is inevitable. To manage the impact of financial crises, understanding the dynamics of volatility spillover across various markets is imperative. This study has investigated the possible emergence of structural breaks in risk patterns after global financial crises in south Asian markets. Methodology - Using the data from July 2002 to June 2016, employing the Exponential GARCH methodology. Findings - This study finds a significant volatility spillover after the financial crisis of 2007-09. Therefore, the existence of a structural break in the risk pattern of south Asian capital markets cannot be fully rejected. Policy Implications - This conclusion is of prime importance to policymakers in devising policy guidelines concerning financial crises.

scholarly journals The COVID-19 Process and the Exchange Rate Relation: An Application on Turkey

2020 ◽  
Author(s):  
Eda Dineri ◽  
İbrahim Çütçü
Keyword(s):  
Exchange Rate ◽  
Exchange Rates ◽  
Structural Breaks ◽  
Health Problems ◽  
Cointegration Test ◽  
Causality Test ◽  
Economic Changes ◽  
The World ◽  
The Exchange Rate ◽  
The Impact

Abstract The recent shocks in supply and demand in the world are not due to unexpected economic reasons; in fact, they are related to Covid-19 that causes rapidly spreading global health problems and life threats around the world. While the global powers are dealing with the social problems created by Covid-19 pandemic, they should not neglect the economic changes created by this pandemic. The most important of these economic changes in developing countries with high fragility is exchange rates, because exchange rates can directly affect many macroeconomic variables, from inflation to foreign trade, from the balance of payments to interests. In countries with high fragility due to the effect of pandemic, economic uncertainty causes fluctuations in the exchange rate. Is the reason for the change in the exchange rate, the number of cases or economic risks that may occur due to possible health problems?In this study, the impact of the number of new cases and the number of new deaths for the process of Covid-19 pandemic on the exchange rate in Turkey is examined. The daily data consider the number of new cases, the number of new deaths and exchange rate for the period of 16.03.2020–06.05.2020. The first step of the analysis, the stationary of the series is tested by Lee and Strazicich (2003) unıt root test which allowed structural break. Hatemi-J (2008) Cointegration Test that allow two structural breaks and Hacker-Hatemi-J Bootstrap causality test are used in the analysis. In the results of the Hatemi- J (2008) cointegration test, there is a medium and long-term relationship, with under structural breaks between the number of new cases and the number of new deaths and the exchange rate. According to the results of the analysis, it can be concluded that the number of new cases and the number of new deaths have a significant effect on the exchange rate, causing uncertainty in the economy.JEL Classification: I19, F31, C22

scholarly journals The Links between Energy Consumption, Financial Development, and Economic Growth in Lebanon: Evidence from Cointegration with Unknown Structural Breaks

2015 ◽  
Vol 2015 ◽  
pp. 1-15 ◽  
Author(s):  
Salah Abosedra ◽  
Muhammad Shahbaz ◽  
Rashid Sbia
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Financial Development ◽  
Structural Breaks ◽  
Banking Sector ◽  
Oil And Gas ◽  
Vital Role ◽  
Policy Implications ◽  
Service Oriented ◽  
The Impact

We investigate the relation between financial development, energy consumption, and economic growth in the economy of Lebanon over the period 2000M2–2010M12. Our findings confirm the existence of cointegration among the variables. The results indicate that financial development and energy consumption contribute to economic growth in Lebanon. The impact of energy consumption on economic growth is positive showing the significance of energy as a main stimulant of economic growth. Financial development is also found to play a vital role in enhancing economic growth. Financial development and economic growth also result in further increase in energy consumption. We offer some policy implications specific to Lebanon considering the recent discovery of large oil and gas reserves in the country and the historical importance of its banking sector which remains a center of Lebanon’s service-oriented economy.

scholarly journals Persistence in real exchange rate convergence

2014 ◽  
Vol 18 (1) ◽  
Author(s):  
Thanasis Stengos ◽  
M. Ege Yazgan
Keyword(s):  
Exchange Rates ◽  
Purchasing Power Parity ◽  
Long Memory ◽  
Structural Breaks ◽  
Real Exchange Rates ◽  
Purchasing Power ◽  
Memory Process ◽  
Power Parity ◽  
Long Memory Process ◽  
Memory Parameter

AbstractIn this paper we use a long memory framework to examine the validity of the Purchasing Power Parity (PPP) hypothesis using both monthly and quarterly data for a panel of 47 countries over a 50 year period (1957–2009). The analysis focuses on the long memory parameter d that allows us to obtain different convergence classifications depending on its value. Our analysis allows for the presence of smooth structural breaks and it does not rely on the use of a benchmark. Overall the evidence strongly points to the presence of a long memory process, where 0.5<d<1. The implication of our results is that we find long memory mean reverting convergence, something that is also consistent with Pesaran, M. H., R. P. Smith, T. Yamagata, and L. Hvozdyk. 2009. “Pairwise Tests of Purchasing Power Parity.” Econometric Reviews 28: 495–521. In explaining the speed of convergence as captured by the estimated long memory parameter d we find impediments to trade such as distance between neighboring countries and sticky prices to be mainly responsible for the slow adjustment of real exchange rates to PPP rather than nominal rates for all country groups but Asia, where the opposite is true.

scholarly journals Are multifractal processes suited to forecasting electricity price volatility? Evidence from Australian intraday data

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Mawuli Segnon ◽  
Chi Keung Lau ◽  
Bernd Wilfling ◽  
Rangan Gupta
Keyword(s):  
Long Memory ◽  
Structural Breaks ◽  
Moving Average ◽  
Markov Switching ◽  
Price Volatility ◽  
Predictive Ability ◽  
Electricity Price ◽  
Smooth Transition ◽  
Volatility Model ◽  
Intraday Data

AbstractWe analyze Australian electricity price returns and find that they exhibit volatility clustering, long memory, structural breaks, and multifractality. Consequently, we let the return mean equation follow two alternative specifications, namely (i) a smooth transition autoregressive fractionally integrated moving average (STARFIMA) process, and (ii) a Markov-switching autoregressive fractionally integrated moving average (MSARFIMA) process. We specify volatility dynamics via a set of (i) short- and long-memory GARCH-type processes, (ii) Markov-switching (MS) GARCH-type processes, and (iii) a Markov-switching multifractal (MSM) process. Based on equal and superior predictive ability tests (using MSE and MAE loss functions), we compare the out-of-sample relative forecasting performance of the models. We find that the (multifractal) MSM volatility model keeps up with the conventional GARCH- and MSGARCH-type specifications. In particular, the MSM model outperforms the alternative specifications, when using the daily squared return as a proxy for latent volatility.

scholarly journals Inflation Dynamics: Expectations, Structural Breaks and Global Factors

2020 ◽  
Vol 12 (2) ◽  
pp. 203-233
Author(s):  
Pierre L. Siklos
Keyword(s):  
Structural Breaks ◽  
Policy Implications ◽  
Inflation Expectations ◽  
Inflation Dynamics ◽  
Standard Practice ◽  
The Impact ◽  
Domestic Inflation

There is no consensus over the importance of “global forces” on inflation. This study explores the role of structural breaks in the inflation process, and their timing, whether it is common across countries, and the extent to which ‘global forces’ are relevant. Three conclusions stand out. Global inflation impacts inflation in both AE and EME, but the impact is more heterogeneous than existing narratives have argued. One’s interpretation of global influences on domestic inflation differs, according to whether poorly performing economies in inflation terms are considered as opposed to the standard practice of examining mean inflation performance. A focus on observed inflation alone ignores that inflation expectations, including a global version of this variable, also plays a critical in inflation dynamics. Finally, there are significant spillovers in inflation between AE and EME, but these too are sensitive according to relative inflation performance. Some policy implications are also drawn.

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