Volatility of stock market and exchange rate returns in Peru: Long memory or short memory with level shifts?

This study investigated the impact of volatility shock persistence on the conditional variance in the Nigerian stock returns using symmetric and asymmetric higher order GARCH family models in the presence of random level shifts and non-Gaussian errors. The study utilised Bai and Perron methodology to detect structural breakpoints in the conditional variance of daily stock and volume of trade returns in the Nigerian stock market from 2nd January, 1998 to 22nd March, 2017. The study employed symmetric GARCH (3,2) and GARCH (2,1)-M models to estimate volatility of asset returns, symmetric GARCH (2,2) and GARCH (2,1)-M to model volatility of volume of trade returns and asymmetric EGARCH (2,2), TGARCH (3,2) and PGARCH (2,3) models to measure the volatility of asset returns as well as asymmetric EGARCH (2,1), TGARCH (1,3) and PGARCH (3,2) models to estimate volatility of volume of trade returns. These models were optimally selected using information criteria and log likelihood as the best fitting symmetric and asymmetric GARCH models to estimate the conditional volatility of asset and volume of trade returns in the Nigerian stock market with and without structural breaks. Results revealed that when random level shifts were ignored in volatility models, the shocks persistence were very high with long memory and variance explosion. But when the random level shifts were incorporated into the GARCH models, there was a significant reduction in the volatility shocks persistence and long memory. Moreover, volatility half-lives also declined drastically while accounting for these sudden level shifts in variance. The study found asymmetry without leverage effects as well as a positive risk-return tradeoff for both asset and volume of trade returns in the Nigerian stock market. The Nigeria banking reform of 2004, the Global Financial and Economic Crises, as well as other local events in Nigeria, were found to have negative and significant impacts on the Nigerian stock market. The study provided some policy recommendations.

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Long memory in the R$ / US$ exchange rate: A robust analysis

Brazilian Review of Econometrics ◽

10.12660/bre.v24n12004.2705 ◽

2004 ◽

Vol 24 (1) ◽

pp. 109 ◽

Cited By ~ 2

Author(s):

Márcio Poletti Laurini ◽

Marcelo Savino Portugal

Keyword(s):

Exchange Rate ◽

Long Memory ◽

Structural Breaks ◽

Monte Carlo Study ◽

Markov Switching Model ◽

Switching Model ◽

Short Memory ◽

Variance Parameters ◽

Short Memory Process ◽

Unconditional Variance

This article shows that the evidence of long memory for the daily R$ /US$ exchange rate series after the implementation of the Real Plan is not robust when we analyze the existence of structural breaks in this series. We demonstrate that the long memory observed is caused by changes in the structure of variance, captured by a Markov Switching model in all the parameters. A Monte Carlo study shows that the long memory structure can be induced by changes in the unconditional variance parameters, and that the data generating mechanism is a short memory process.

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MEMORY PARAMETER ESTIMATION IN THE PRESENCE OF LEVEL SHIFTS AND DETERMINISTIC TRENDS

Econometric Theory ◽

10.1017/s0266466613000042 ◽

2013 ◽

Vol 29 (6) ◽

pp. 1196-1237 ◽

Cited By ~ 28

Author(s):

Adam Mccloskey ◽

Pierre Perron

Keyword(s):

Time Series ◽

Long Memory ◽

Level Shift ◽

Finite Sample ◽

Memory Processes ◽

Trade Offs ◽

Level Shifts ◽

Long Memory Processes ◽

Short Memory ◽

Memory Parameter

We propose estimators of the memory parameter of a time series that are robust to a wide variety of random level shift processes, deterministic level shifts, and deterministic time trends. The estimators are simple trimmed versions of the popular log-periodogram regression estimator that employ certain sample-size-dependent and, in some cases, data-dependent trimmings that discard low-frequency components. We also show that a previously developed trimmed local Whittle estimator is robust to the same forms of data contamination. Regardless of whether the underlying long- or short-memory process is contaminated by level shifts or deterministic trends, the estimators are consistent and asymptotically normal with the same limiting variance as their standard untrimmed counterparts. Simulations show that the trimmed estimators perform their intended purpose quite well, substantially decreasing both finite-sample bias and root mean-squared error in the presence of these contaminating components. Furthermore, we assess the trade-offs involved with their use when such components are not present but the underlying process exhibits strong short-memory dynamics or is contaminated by noise. To balance the potential finite-sample biases involved in estimating the memory parameter, we recommend a particular adaptive version of the trimmed log-periodogram estimator that performs well in a wide variety of circumstances. We apply the estimators to stock market volatility data to find that various time series typically thought to be long-memory processes actually appear to be short- or very weak long-memory processes contaminated by level shifts or deterministic trends.

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Macroeconomic Determinants of Stock Market Prices in Nepal

Quest Journal of Management and Social Sciences ◽

10.3126/qjmss.v2i1.29022 ◽

2020 ◽

Vol 2 (1) ◽

pp. 56-65

Author(s):

Bhim Prasad Panta

Keyword(s):

Exchange Rate ◽

Interest Rate ◽

Stock Market ◽

Money Supply ◽

Developing Economies ◽

Annual Data ◽

Economic Variables ◽

Market Prices ◽

Ardl Model ◽

Long Run

Background: Stock market plays a crucial role in the financial system of a country. It can be viewed as a channel through which resources are properly channelized. It enables the governments and industry to raise long-term capital for financing new projects. The stock markets of developing economies are likely to be sensitive to various macro-economic factors such as GDP, imports, exports, exchange rates etc., when there is high demand on financial products, as a constituent of financial market, ultimately stock market needs to develop. Many factors can be a signal to stock market participants to expect a higher or lower return when investing in stock and one of these factors are macroeconomic variables and thus, macro-economic variables tend to effect on stock market development. Objective: This study examines the linkage between stock market prices (NEPSE index) and five macro-economic variables, namely; real GDP, broad money supply, interest rate, inflation, and exchange rate using ARDL model and to explain the behavior of the Nepal Stock Exchange Index. Methods: The ECM which is delivered from ARDL model through simple linear transformation to integrate short run adjustments with long run equilibrium without losing long run information. The analysis has been done by using 25 years' annual data from 1994 to 2019. Findings: The result suggests that the fluctuation of Nepse Index in long run is strongly associated with broad money supply, interest rate, inflation, and exchange rate. Conclusion: Though Nepalese stock market is in primitive stage, broad money supply, interest rate, inflation and exchange rate are major factors affecting stock market price of Nepal. So, policies and strategies should be made and directed taking these in to consideration. Implication: The findings of research can be helpful to understand the behavior of Nepalese stock market and develop policies for market stabilization.

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(A Study on the Impact of the China's Exchange Rate Regime Policy Changes on the Price Spill-Over Process of the Chinese Stock Market Index)

SSRN Electronic Journal ◽

10.2139/ssrn.3016997 ◽

2013 ◽

Author(s):

Kyung Won Kim

Keyword(s):

Exchange Rate ◽

Stock Market ◽

Exchange Rate Regime ◽

Chinese Stock Market ◽

Policy Changes ◽

Stock Market Index ◽

Market Index ◽

The Impact

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Interest Rate, Foreign Exchange Rate, and Stock Market Development in Nigeria

Binus Business Review ◽

10.21512/bbr.v9i3.4941 ◽

2018 ◽

Vol 9 (3) ◽

pp. 247-253 ◽

Cited By ~ 1

Author(s):

Edward Adedoyin Adebowale ◽

Akindele Iyiola Akosile

Keyword(s):

Exchange Rate ◽

Interest Rate ◽

Stock Market ◽

Foreign Exchange ◽

The United States ◽

Ordinary Least Squares ◽

Foreign Exchange Rate ◽

Market Development ◽

National Bureau ◽

Stock Market Development

This research investigated the effect of interest rate and foreign exchange rate on stock market development in Nigeria. This research was centered on two research problems. First, it was whether interest rate had a significant effect on stock market development in Nigeria. Second, it was whether foreign exchange rate had a significant impact on stock market development in Nigeria. The scope of the research covered the period from 1981 to 2017. Data for this period were chosen because it covered pre and post-liberalization periods of Nigerian financial system. This research made use of ex post facto research design. Secondary data were sourced from Nigerian Stock Exchange reports, Central Bank of Nigeria statistical bulletins, and National Bureau of Statistics publications. Data were collected on Stock Market Capitalization (SMC), Prime Lending Rate (PLR) and Real Exchange Rate (RER) (Nigerian Naira in relation to American Dollars of the United States). Data analysis was carried out with Ordinary Least Squares (OLS) and Cochrane-Orcutt Iterative techniques. The findings reveal that interest rate has a significant negative effect, and foreign exchange rate has a significant positive effect on Nigerian stock market development during the period covered. It is suggested that monetary authorities should strive to formulate policies that will make interest and foreign exchange rates stable, competitive, and at a level that will stimulate the investment of funds in the stock market.

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