Stock market networks: The dynamic conditional correlation approach

2012 ◽  
Vol 391 (16) ◽  
pp. 4147-4158 ◽  
Author(s):  
Štefan Lyócsa ◽  
Tomáš Výrost ◽  
Eduard Baumöhl
Keyword(s):  
Stock Market ◽  
Conditional Correlation ◽  
Dynamic Conditional Correlation ◽  
Market Networks

scholarly journals Contagion of the shareholder market: cases of Colombia, México, Perú, Chile and Argentina

2019 ◽  
Vol 18 ((1)) ◽  
Author(s):  
Marcos Vera Leyton
Keyword(s):  
Financial Crisis ◽  
Stock Market ◽  
Time Window ◽  
Sum Of Squares ◽  
Conditional Correlation ◽  
Cumulative Sum ◽  
Crisis Period ◽  
Dynamic Conditional Correlation ◽  
Highly Sensitive ◽  
Before And After

This document study the existence of financial crisis contagion, it defined like the transmission of the shocks between countries, which translates in increasing in the correlation anything beyond or fundamental link, taking as a source of contagion by EEUU, Brasil, and analyzing Mexico, Colombia, Peru, Chile and Argentina like “Infected” countries, for the period covered between July 3 of 2001, date of unification of the Colombia Stock Market, to July 3 of 2010. To identify crisis period, and to evoid volatility overestimation, it used the algorithm iterative cumulative sum of squares ICCS, developed by Inclan y Tiao (1994), additionally calculated the dynamic conditional correlation (DCC) Engle Model (2002). The document includes a review of several studies, concepts, and transmission (Contagion) methodologies, and it constitutes one of the few studies that includes Colombia like analysis source.  So this study verifies the existence of contagion in the countries studies, except Argentina, but warns that the measure of impact that a crisis in a given country has over other countries is highly sensitive to the way we choose the time window before and after the crisis.

scholarly journals Flight to quality or contagion during US subprime crisis: Evidence from Vietnam financial markets

2020 ◽  
Vol 128 (5B) ◽  
Author(s):  
Thanh Cong Bui ◽  
Khoa Cuong Phan ◽  
Thi Bich Ngoc Ngoc TRAN
Keyword(s):  
Stock Market ◽  
Financial Markets ◽  
Stock Index ◽  
Subprime Crisis ◽  
Conditional Correlation ◽  
Risky Assets ◽  
Dynamic Conditional Correlation ◽  
Flight To Quality ◽  
Correlation Models ◽  
The Relationship

<p>The purpose of this study is to investigate if contagion or flight-to-quality occurred in Vietnam financial markets during US subprime crisis in 2007. We apply asymmetric dynamic conditional correlation models (ADCC-GARCH (1,1)) to daily stock-index and bond index returns of Vietnam and US stock market. We test for contagion or flight-to-quality by using difference test for dynamic conditional correlation (DCC) means. The results obtained show a contagion between US and Vietnam stock market, confirming the widespread influence of US stock market to a young market like Vietnam. This result suggests a low benefit from diversification for investor holding portfolios containing assets in Vietnam stock market and US stock market during crisis. Moreover, the relationship between Vietnam stock and bond markets represents a flight-to-quality during US subprime crisis. This finding shows that the investors tend to hold less risky assets, i.e. bonds, instead of stocks during turbulent period in Vietnam.</p>

scholarly journals Commodity Price Correlation And Time Varying Hedge Ratios

2014 ◽  
Vol 30 (4) ◽  
pp. 1053
Author(s):  
Amine Lahiani ◽  
Khaled Guesmi
Keyword(s):  
Stock Market ◽  
Value At Risk ◽  
Price Volatility ◽  
Commodity Price ◽  
Conditional Value At Risk ◽  
Time Varying ◽  
Conditional Correlation ◽  
Dynamic Conditional Correlation ◽  
Hedging Strategies ◽  
Hedge Ratios

<p>This paper examines the price volatility and hedging behavior of commodity futures indices and stock market indices. We investigate the weekly hedging strategies generated by return-based and range-based asymmetric dynamic conditional correlation (DCC) processes. The hedging performances of short and long hedgers are estimated with a semi-variance, low partial moment and conditional value-at-risk. The empirical results show that range-based DCC model outperforms return-based DCC model for most cases.</p>

ARE STOCK MARKETS AND CRYPTOCURRENCIES CONNECTED?

2020 ◽  
pp. 1-16
Author(s):  
MUHAMMAD UMAR ◽  
NGO THAI HUNG ◽  
SHIHUA CHEN ◽  
AMJAD IQBAL ◽  
KHALIL JEBRAN
Keyword(s):  
Operating System ◽  
Stock Market ◽  
Stock Markets ◽  
Stock Exchange ◽  
Composite Index ◽  
Wavelet Coherence ◽  
Time Varying ◽  
Conditional Correlation ◽  
Dynamic Conditional Correlation ◽  
Nasdaq Composite Index

This study explores the connectedness between cryptocurrencies (Bitcoin, Ethereum, Ripple, Bitcoin cash and Ethereum Operating System) and major stock markets (NYSE composite index, NASDAQ composite index, Shanghai Stock Exchange, Nikkei 225 and Euronext NV). Using the asymmetric dynamic conditional correlation (ADCC) and wavelet coherence approaches, we document a significant time-varying conditional correlation between the majority of the cryptocurrencies and stock market indices and that the negative shocks play a more prominent role than the positive shocks of the same magnitude. Overall, our findings explore potential avenues for diversification for investors across cryptocurrencies and major stock markets.

Time-varying synchronization and dynamic conditional correlation among the stock market returns of leading South American economies

2018 ◽  
Vol 14 (2) ◽  
pp. 245-262 ◽  
Author(s):  
Ajaya Kumar Panda ◽  
Swagatika Nanda
Keyword(s):  
Time Series ◽  
Stock Market ◽  
Stock Markets ◽  
South American ◽  
Conditional Correlation ◽  
Market Returns ◽  
Stock Market Returns ◽  
Content Type ◽  
Dynamic Conditional Correlation ◽  
Auto Regressive

Purpose The purpose of this paper is to capture the pattern of return volatility and information spillover and the extent of conditional correlation among the stock markets of leading South American economies. It also examines the connectedness of market returns within the region. Design/methodology/approach The time series properties of weekly stock market returns of benchmark indices spanning from the second week of 1995 to the fourth week of December 2015 are analyzed. Using univariate auto-regressive conditional heteroscedastic, generalized auto-regressive conditional heteroscedastic, and dynamic conditional correlation multivariate GARCH model approaches, the study finds evidence of returns and volatility linkages along with the degree of connectedness among the markets. Findings The findings of this study are consistent with increasing market connectedness among a group of leading South American economies. Stocks exhibit relatively fewer asymmetries in conditional correlations in addition to conditional volatility; yet, the asymmetry is relatively less apparent in integrated markets. The results demonstrate that co-movements are higher toward the end of the sample period than in the early phase. The stock markets of Argentina, Brazil, Chile, and Peru are closely and strongly connected within the region followed by Colombia, whereas Venezuela is least connected with the group. Practical implications The implication is that foreign investors may benefit from the reduction of the risk by adding the stocks to their investment portfolio. Originality/value The unique features of the paper include a large sample of national stock returns with updated time series data set that reveals the time series properties and empirical evidence on volatility testing. Unlike other studies, this paper uncovers the relation between the stock markets within the same region facing the same market condition.

scholarly journals Penerapan Model Dynamic Conditional Correlation GARCH Pada Data Saham

2021 ◽  
pp. 80-87
Author(s):  
Ika Fitriana ◽  
Erna Tri Herdiani ◽  
Georgina Maria Tinungki
Keyword(s):  
Stock Market ◽  
Financial Market ◽  
Stock Prices ◽  
Model Equation ◽  
Garch Model ◽  
Time Dependent ◽  
Conditional Correlation ◽  
Stock Volatility ◽  
Dynamic Conditional Correlation ◽  
A Company

Stock is one of the popular financial market instruments. Issuing shares are one of the company's choices when deciding to fund a company. The uncertainty of stock prices in the stock market is an important event to be taken into consideration in making a decision by investors so that a model is needed to describe a stock event. GARCH Dynamic Conditional Correlation (DCC) is a model with a conditional and variance time-dependent that describes the dynamics of stock volatility. This study discusses the DCC GARCH model equation which is applied to the LQ 45 data. The model obtained for BCA shares 𝑸t = +  +  so it can be concluded that DCC GARCH is more appropriate for BCA shares.

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