Impact of Margin Trading on the Liquidity of China’s Stock Market: Based on VAR Model

2021 ◽  
pp. 192-199
Author(s):  
Yiting Shen
Keyword(s):  
Stock Market ◽  
Var Model

scholarly journals The Regime-Switching Behaviour of Exchange Rates and Frontier Stock Market Prices in Sub-Saharan Africa

2021 ◽  
Vol 14 (3) ◽  
pp. 122
Author(s):  
Maud Korley ◽  
Evangelos Giouvris
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Regime Switching ◽  
Markov Switching ◽  
Sub Saharan Africa ◽  
Var Model ◽  
High Volatility ◽  
Sub Saharan ◽  
The Relationship ◽  
Fx Market

Frontier markets have become increasingly investible, providing diversification opportunities; however, there is very little research (with conflicting results) on the relationship between Foreign Exchange (FX) and frontier stock markets. Understanding this relationship is important for both international investor and policymakers. The Markov-switching Vector Auto Regressive (VAR) model is used to examine the relationship between FX and frontier stock markets. There are two distinct regimes in both the frontier stock market and the FX market: a low-volatility and a high-volatility regime. In contrast with emerging markets characterised by “high volatility/low return”, frontier stock markets provide high (positive) returns in the high-volatility regime. The high-volatility regime is less persistent than the low-volatility regime, contrary to conventional wisdom. The Markov Switching VAR model indicates that the relationship between the FX market and the stock market is regime-dependent. Changes in the stock market have a significant impact on the FX market during both normal (calm) and crisis (turbulent) periods. However, the reverse effect is weak or nonexistent. The stock-oriented model is the prevalent model for Sub-Saharan African (SSA) countries. Irrespective of the regime, there is no relationship between the stock market and the FX market in Cote d’Ivoire. Our results are robust in model selection and degree of comovement.

scholarly journals Monetary Policy and Liquidity of Vietnam’s Stock Market

2016 ◽  
Vol 23 (02) ◽  
pp. 02-21
Author(s):  
Ly Tran Thi Hai
Keyword(s):  
Time Series ◽  
Monetary Policy ◽  
Stock Market ◽  
Money Supply ◽  
Industrial Production ◽  
Market Liquidity ◽  
Var Model ◽  
Market Returns ◽  
Liquidity Measures ◽  
The Impact

This study investigates the impact of monetary policy on liquidity of Vietnam’s stock market from September 2007 to November 2014. Time series of liquidity are determined by monthly liquidity data for 643 enterprises in the surveyed period. Two variables of the monetary policy, including growth in money supply and interbank rate, are employed in VAR model along with four different measures of market liquidity. The results show that unexpected variance in the two monetary policy variables has no significant impact on the market liquidity, which, in turn, may be improved by the positive shocks of market returns, inflation, and growth in industrial production. Market variance does produce certain effects, but discrepancies occur in the signs of various liquidity measures.

The Relationship Between Stock Market Indices of the Biggest Six Economies of the European Union and BIST 100

2020 ◽  
pp. 257-275
Author(s):  
Serdar Ögel ◽  
Fatih Temizel
Keyword(s):  
European Union ◽  
Stock Market ◽  
Granger Causality ◽  
Granger Causality Test ◽  
Var Model ◽  
The European Union ◽  
Causality Test ◽  
Integration Test ◽  
Causality Relationship ◽  
The Relationship

This chapter examines the relationship between stock market indices of the biggest six economies of the European Union and BIST 100. In this context, this study used the daily time series regarding indices of DAX for Germany, CAC 40 for France, FTSE MIB for Italy, IBEX 35 for Spain, AEX for Holland, FTSE 100 for United Kingdom, and BIST 100 for Turkey from 2014 to 2018. To test whether there is a co-integration relationship among indices, Johansen co-integration test was used. Since a co-integration relationship was not found between series, causality relationship between the European stock market indices and Turkey was tested with Granger causality test by establishing standard VAR model. As a result, a unidirectional Granger causality relationship was found from DAX, FTSE 100, CAC 40, IBEX 35, and AEX to BIST 100 according to lag length 1 and 2. However, a unidirectional Granger causality relationship was only found from FTSE MIB to BIST 100 for lag length 1. For lag length 1 and 2, no causality relationship was found from BIST 100 to the selected European stock market indices.

scholarly journals Analysis on the Impact of Short-Term International Capital Flows on Chinese Stock Market on the Basis of VAR Model

2018 ◽  
Vol 10 (8) ◽  
pp. 77
Author(s):  
Ning Wu
Keyword(s):  
Stock Market ◽  
Capital Flows ◽  
Composite Index ◽  
International Capital Flows ◽  
Capital Inflows ◽  
Var Model ◽  
Chinese Stock Market ◽  
International Capital ◽  
Short Term ◽  
The Impact

With the continuous development of global economic integration and financial markets, international capital flows more and more frequently, the frequent flow of international capital will inevitably affect the yield of Chinese stock market. This article uses short-term international capital inflows SS and Shanghai composite index R as research objects. Based on monthly data from January 2002 to October 2017, VAR model was constructed using Eviews8.0 to study the impact of short-term international capital flows on Chinese stock market. Empirical studies have found that short-term international capital flow is the granger cause of changes in the Shanghai composite index yield, while the yield of Chinese stock market will not affect short-term international capital flows. At the end of this paper, relevant suggestions are put forward according to the conclusions.

scholarly journals The effect of ambiguity on the UK stock market: evidence from a new empirical approach

2017 ◽  
Vol 14 (4) ◽  
pp. 133-147
Author(s):  
Run Qing Tan ◽  
Viktor Manahov ◽  
Jacco Thijssen
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Prices ◽  
Linear Models ◽  
The Other ◽  
Var Model ◽  
Market Returns ◽  
Stock Market Returns ◽  
Bid Ask Spread ◽  
The Uk

This study developed a new ambiguity measure using the bid-ask spread. The results suggest that the degree of ambiguity has an impact on the daily UK stock market returns, but ambiguity does not cause changes in the returns. This implies that UK stock prices or returns cannot be predicted using variation in the degree of ambiguity through linear models, such as the VAR model, which was used in the study. The two sets of results in the study show that the degree of ambiguity from the previous two days might affect stock market returns. The authors observe that an increase in the degree of ambiguity two days ago is associated with a positive premium required by the investors. On the other hand, the degree of ambiguity tends to be affected by its past five-day values. Thus, the degree of ambiguity seems to persist for five days until investors update their priors. The intuition behind the result is that the degree of ambiguity can affect the returns of the UK stock market and UK stock market returns can in turn have an impact on the degree of ambiguity. The authors also observe that the degree of ambiguity does not seem to predict stock market returns in the UK when one applies linear models. However, this does not mean that there is no non-linear relationship between the degree of ambiguity and stock market returns or stock returns.

scholarly journals Detection of structural regimes and analyzing the impact of crude oil market on Canadian stock market: Markov regime-switching approach

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohammadreza Mahmoudi ◽  
Hana Ghaneei
Keyword(s):  
Stock Market ◽  
Crude Oil ◽  
Stock Return ◽  
Stock Exchange ◽  
Markov Switching ◽  
Stock Index ◽  
Var Model ◽  
Content Type ◽  
Oil Market ◽  
The Impact

Purpose This study aims to analyze the impact of the crude oil market on the Toronto Stock Exchange Index (TSX). Design/methodology/approach The focus is on detecting nonlinear relationship based on monthly data from 1970 to 2021 using Markov-switching vector auto regression (VAR) model. Findings The results indicate that TSX return contains two regimes: positive return (Regime 1), when growth rate of stock index is positive; and negative return (Regime 2), when growth rate of stock index is negative. Moreover, Regime 1 is more volatile than Regime 2. The findings also show the crude oil market has a negative effect on the stock market in Regime 1, while it has a positive effect on the stock market in Regime 2. In addition, the authors can see this effect in Regime 1 more significantly in comparison to Regime 2. Furthermore, two-period lag of oil price decreases stock return in Regime 1, while it increases stock return in Regime 2. Originality/value This study aims to address the effect of oil market fluctuation on TSX index using Markov-switching approach and capture the nonlinearities between them. To the best of the author’s knowledge, this is the first study to assess the effect of the oil market on TSX in different regimes using Markov-switching VAR model. Because Canada is the sixth-largest producer and exporter of oil in the world as well as the TSX as the Canada’s main stock exchange is the tenth-largest stock exchange in the world by market capitalization, this paper’s framework to analyze a nonlinear relationship between oil market and the stock market of Canada helps stock market players like policymakers, institutional investors and private investors to get a better understanding of the real world.

Sign in / Sign up

Export Citation Format

Share Document