On the Problems of Short Term Forecasting of Russian Stock Market

2019 ◽  
Vol 6 (6) ◽  
pp. 84-88
Author(s):  
М. Галустян ◽  
M. Galustyan
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Developed Countries ◽  
Comparison Method ◽  
Graphical Analysis ◽  
Bric Countries ◽  
Daily Data ◽  
Main Indicator ◽  
Short Term Forecasting ◽  
Russian Stock Market

The features of the Russian stock market that affect the process and the result of forecasting its main indicator — MICEX — are considered, the mechanism that makes it difficult to predict the index for each of the features is described. A comparative analysis of the Russian stock market with the stock markets of other countries in accordance with the above features. Using the mathematical and statistical methods the increased influence of these features and problems on the Russian stock market in comparison with the stock markets of other BRIC countries, developed countries, the Eurozone countries is proved. The paper uses such methods as: correlation analysis, graphical analysis, analysis of variance, comparison method, method of retrospection. Monthly and daily data for 2010–2017 are used in calculations and graphs.

How to Assure Stable Development in Unstable Financial Environment?

2007 ◽  
pp. 4-26 ◽  
Author(s):  
M. Ershov
Keyword(s):  
Stock Market ◽  
Developed Countries ◽  
Market Liquidity ◽  
Market Mechanisms ◽  
Russian Economy ◽  
The Developed Countries ◽  
Russian Stock Market ◽  
Stable Development ◽  
Financial Environment

Growing involvement of Russian economy in international economic sphere increases the role of external risks. Financial problems which the developed countries are encountered with today result in volatility of Russian stock market, liquidity problems for banks, unstable prices. These factors in total may put longer-term prospects of economic growth in jeopardy. Monetary, foreign exchange and stock market mechanisms become the centerpiece of economic policy approaches which should provide for stable development in the shaky environment.

scholarly journals Which global stock indices trigger stronger contagion risk in the Vietnamese stock market? Evidence using a bivariate analysis

2013 ◽  
Vol 60 (4) ◽  
pp. 473-497 ◽  
Author(s):  
Kuan-Min Wang ◽  
Hung-Cheng Lai
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Correlation Coefficients ◽  
Bivariate Analysis ◽  
Contagion Effects ◽  
Daily Data ◽  
The Us ◽  
Egarch Model ◽  
Bivariate Egarch Model ◽  
Contagion Risk

This paper extends recent investigations into risk contagion effects on stock markets to the Vietnamese stock market. Daily data spanning October 9, 2006 to May 3, 2012 are sourced to empirically validate the contagion effects between stock markets in Vietnam, and China, Japan, Singapore, and the US. To facilitate the validation of contagion effects with market-related coefficients, this paper constructs a bivariate EGARCH model of dynamic conditional correlation coefficients. Using the correlation contagion test and Dungey et al.?s (2005) contagion test, we find contagion effects between the Vietnamese and four other stock markets, namely Japan, Singapore, China, and the US. Second, we show that the Japanese stock market causes stronger contagion risk in the Vietnamese stock market compared to the stock markets of China, Singapore, and the US. Finally, we show that the Chinese and US stock markets cause weaker contagion effects in the Vietnamese stock market because of stronger interdependence effects between the former two markets.

Do Global Financial, Oil and Gold Volatility Shocks Affect the GCC Stock Markets?

2019 ◽  
Vol 5 (2) ◽  
pp. 157-175 ◽  
Author(s):  
Abdullah Alqahtani
Keyword(s):  
Saudi Arabia ◽  
Stock Market ◽  
Stock Markets ◽  
Structural Var ◽  
Causality Test ◽  
Data Set ◽  
Financial Volatility ◽  
Daily Data ◽  
Positive Shock ◽  
The Impact

This study employed the non-structural VAR econometrics approach to examine the impact of Global Oil (OVX), Financial (VIX), and Gold (GVZ) volatility indices on GCC stock markets using a daily data set spanning from January 5, 2009 to August 16, 2018. From the VAR result obtained, disequilibrium in the global financial volatility (VIX) was able to significantly transmit negative shock to Bahrain and Kuwait stock markets and positive shock on GVZ. While the global Gold volatility was capable of transmitting fairly positive shock to the UAE and VIX market. The OLS also revealed more to the result obtained from VAR as it shows that OVX and VIX can have impact on the GCC stock markets. The causality test revealed that there is a unidirectional causality running from Qatar and UAE to OVX; none of the variables was able to granger cause VIX, while unidirectional causality exist from VIX and UAE to GVZ and VIX and Qatar to Bahrain. VIX and Qatar can granger cause Kuwait stock market, and only Saudi Arabia and Oman have bidirectional causality. Unidirectional causality exists from Saudi Arabia to Qatar, and Qatar is the only stock market capable of causing UAE unidirectionally. Hence, the study concludes that VIX and GVZ are capable of transmitting shocks to three of the six GCC stock markets—(Bahrain, Kuwait and The UAE) negatively (Bahrain and Kuwait) and positively (The UAE). And on this note, the study recommends that appropriate financial and gold transaction policies should be institutionalized so as to mitigate the transmission of shocks into the markets. Also, financial and gold experts who regulate the stock and gold markets especially in Bahrain and Kuwait should watch for any abnormality changes in the volatility movement of the financial and gold markets.

scholarly journals The effects of volatility and changes in conditional correlations in the stock markets of Russia and developed countries

2020 ◽  
Vol 65 (227) ◽  
pp. 67-94
Author(s):  
Oleg Salmanov ◽  
Natalia Babina ◽  
Marina Samoshkina ◽  
Irina Drachena ◽  
Irina Salmanova
Keyword(s):  
Stock Markets ◽  
Statistical Significance ◽  
Developed Countries ◽  
Investment Strategies ◽  
Russian Market ◽  
The Us ◽  
The Usa ◽  
International Portfolios ◽  
Russian Stock Market ◽  
The Uk

The aim of this article is to identify patterns of profitability volatility and to establish the degree of dynamic conditional correlation between the stock markets of developed countries and those of Russia. This issue is important for investment strategies and the international diversification of investments. We use the BEKK-GARCH, CCC-GARCH, and DCCGARCH models and show that the correlation between the Russian stock market and the markets of the USA, UK, Germany, and France has decreased significantly in recent years. We find that while the correlation between the Russian market and the mature European markets is bidirectional, the relationship between the US market and the Russian market is unidirectional. An assessment of the transfer of volatility from all of the mature markets to the Russian market establishes its statistical significance and shows that feedback from the Russian market to the UK and German markets is insignificant. Diversification of international portfolios in the Russian market is recommended.

scholarly journals The Role of Sri Lankan Stock Market in the Asian Region

2016 ◽  
Vol 2 (1) ◽  
Author(s):  
D. Kuruppuarachchi
Keyword(s):  
Hong Kong ◽  
Stock Market ◽  
Impulse Response ◽  
Stock Markets ◽  
Response Analysis ◽  
Sri Lankan ◽  
Chinese Stock Market ◽  
It Use ◽  
Market Interactions ◽  
Daily Data

This paper investigates the interaction of the Sri Lankan stock market with other Asian stock markets in terms of cointegration, contemporaneous correlations, information spillovers, and impulse responses. The study consider India, China, Pakistan, Singapore, Malaysia, Hong Kong, Korea, and Japan as neighboring stock markets to the Sri Lankan market. And it use daily data of leading stock indices for each country from 01st January 2000 to 31st December 2012. Findings reveal that the Sri Lankan stock market is cointegrated with the Korean stock market but not with others. Contemporaneous correlations are significant between Sri Lanka and other Asian countries such as India, Singapore, Malaysia, Hong Kong, Korea, and Japan. Pakistan, Malaysian, and Korean stock markets Granger cause in mean to the Sri Lankan stock market while India and Korea Granger cause in variance. Extreme downside risks in Chinese stock market also Granger causes the Sri Lankan stock market. Impulse response analysis provides evidence for the following day’s impact on the Sri Lankan stock market due a current shock on other Asian stock markets. Findings of this paper provide insightful information to both policy makers and investors in order to understand the behavior of Sri Lankan stock market.KeywordsAsian Stock Markets, Granger Causality, Impulse Response, InformationSpillover, Sri Lankan Stock Market, Stock Market Interactions

scholarly journals Volatility spillover from the united states and Japanese stock markets to the Vietnamese stock market: A frequency domain approach

2020 ◽  
pp. 3-3
Author(s):  
Le Nghi ◽  
Nguyen Kieu
Keyword(s):  
United States ◽  
Stock Market ◽  
Frequency Domain ◽  
Stock Markets ◽  
The United States ◽  
Frequency Domain Analysis ◽  
Volatility Spillover ◽  
Causality Test ◽  
Daily Data ◽  
Frequency Domain Approach

Using frequency domain analysis, this paper examines the volatility spillover from the United States and Japanese stock markets to the Vietnamese stock market. Daily data of S&P 500, Nikkei 225 and VN-Index from January 01, 2012 to May 31, 2016 is used. In terms of estimation, the GARCH model is used to estimate volatilities in these stock markets; the Granger Causality Test is used to examine volatility spillover; and the test for causality in the frequency domain by Jorg Breitung and Bertrand Candelon (2006) is used to examine the volatility spillover at different frequencies. The empirical results provide two main contributions: (i) there is a significant volatility spillover from the United States to the Vietnamese stock markets, but the evidence of volatility spillover from the Japanese to the Vietnamese stock market is not found; and (ii) the volatility spillover may vary across frequency spectrum bands. To our best understanding, volatility spillover analysis using frequency domain approach was not previously reported in literature.

scholarly journals Stock prices, uncertainty and risks: Evidence from developing and advanced economies

2020 ◽  
Vol 9 (3) ◽  
pp. 265-279
Author(s):  
Mary Elena Sánchez Gabarre
Keyword(s):  
Economic Policy ◽  
Stock Market ◽  
Stock Prices ◽  
Stock Markets ◽  
Developed Countries ◽  
Market Volatility ◽  
Policy Uncertainty ◽  
Stock Market Volatility ◽  
Share Prices ◽  
Geopolitical Risks

This paper studies the relationship between stock prices and three types of uncertainty: economic policy uncertainty, stock market volatility, and geopolitical risks. In particular, our aim is to determine whether these forms of uncertainty play the same role in developed and developing countries. With this purpose, we take Spain and Brazil as representative cases. In order to provide new insights into the abovementioned relationship, a cointegration approach is applied, specifically an ARDL model, using monthly data from the period January 2006-December 2019 for a series of financial and macroeconomic variables. The results obtained reveal that there is no uniform effect of uncertainty in stock markets of developing and developed countries. First, in Spain, there is a high perception of uncertainty in economic policy and stock market volatility, which impact negatively in share prices, both in the short and long term. Regarding Brazil, the global uncertainty in the stock markets has effects on share prices, in both time horizons. By contrast, geopolitical risks do not show any significant impact on Brazilian and Spanish share returns.

Forecasting developed and BRICS stock markets with cryptocurrencies and gold: generalized orthogonal generalized autoregressive conditional heteroskedasticity and generalized autoregressive score analysis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ahmed Jeribi ◽  
Achraf Ghorbel
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Value At Risk ◽  
Developed Countries ◽  
The Other ◽  
Conditional Heteroskedasticity ◽  
Content Type ◽  
Autoregressive Conditional Heteroskedasticity ◽  
Developed Stock Markets ◽  
Generalized Orthogonal

PurposeThe purpose of this paper is threefold. First, it models and forecasts the risk of the five leading cryptocurrencies, stock market indices (developed and BRICS) and gold returns. Second, it conducts different backtesting procedures forecasts. Third, it focuses on the hedging potential of cryptocurrencies and gold.Design/methodology/approachThe authors used the generalized autoregressive score (GAS) models to model and forecast the risk of cryptocurrencies, stock market indices and gold returns. They conduct different backtesting procedures of the 1% and 5%-value-at-risk (VaR) forecasts. They also use the generalized orthogonal generalized autoregressive conditional heteroskedasticity (GO-GARCH) model to explore the hedging potential of cryptocurrencies by estimating the dynamic conditional correlation between cryptocurrencies and gold, on the one hand, and stock markets on the other hand.FindingsWhen conducting different backtesting procedures of VaR, our finding suggests that Bitcoin has the highest VaR among cryptocurrencies and Gold and the BRICS indices returns have lower VaR compared to the developed countries. Finally, we provide evidence that the risks among developed stock markets can be hedged by Bitcoin and Gold. Bitcoin can be considered as the new Gold for these economies. Unlike Bitcoin, Gold can be considered as a hedge for Chinese and Indian investors. However, Gold and Bitcoin can be considered as diversifier assets for the other BRICS economies while Dash and Monero are diversifier assets for developed stock markets.Originality/valueThe first paper's empirical contribution lies in analyzing optimal forecast models for cryptocurrencies (other than Bitcoin) returns and risk. The second contribution consists of studying the hedging potential of five leading cryptocurrencies. To the best of our knowledge, no previous studies have investigated the role of cryptocurrencies for BRICS investors.

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