scholarly journals Hedging the Brazilian stock index in the era of low interest rates: What has changed?

2020 ◽  
Vol 18 (3) ◽  
pp. 5
Author(s):  
Fernando Antonio Lucena Aiube ◽  
Winicius Botelho Faquieri
Keyword(s):  
Interest Rates ◽  
Multivariate Garch ◽  
Stock Index ◽  
Fixed Income ◽  
Conditional Correlation ◽  
Macroeconomic Policies ◽  
High Interest Rate ◽  
Low Interest Rates ◽  
Asset Classes ◽  
Multivariate Garch Models

<p>In this paper we analyze the ability of different asset classes to hedge the Brazilian stock index in periods of high and low interest rates in the Brazilian economy, using two multivariate GARCH models. Our analysis includes two categories of assets: those traded in domestic currency and those traded in U.S. dollars. From the perspective of a local investor, we find that the exchange rate (R$/US$) and gold are the assets least correlated with equities. From the standpoint of a foreign investor, commodity index and fixed-income assets are the most useful. These results prevail in the low- and high-interest-rate periods. Moreover, in the period of low interest rates, the standard deviation of the estimated conditional correlation time series decreases, suggesting that in this period investors are more confident about macroeconomic policies.</p>

scholarly journals An application of multivariate GARCH models in research for the interaction of world financial markets

Equilibrium ◽  
2009 ◽  
Vol 2 (1) ◽  
pp. 61-68
Author(s):  
Tomasz Chruściński
Keyword(s):  
Financial Markets ◽  
Stock Markets ◽  
Multivariate Garch ◽  
Garch Models ◽  
Data Sets ◽  
Conditional Correlation ◽  
Main Emphasis ◽  
Multivariate Garch Models ◽  
Diagonal Vech

This article presents information about taxonometric methods in classification stock-markets and selected Multivariate GARCH models. The main emphasis is placed on which market (country) influences others. Research has been geared towards three kinds of measurement: diagonal VECH models, diagonal BEKK models and Constant Conditional Correlation. The results obtained for the DBEKK model is optimal for most data-sets.

scholarly journals Risk Spillover during the COVID-19 Global Pandemic and Portfolio Management

2021 ◽  
Vol 14 (5) ◽  
pp. 222
Author(s):  
Mohamed Yousfi ◽  
Abderrazak Dhaoui ◽  
Houssam Bouzgarrou
Keyword(s):  
Portfolio Management ◽  
Stock Markets ◽  
Multivariate Garch ◽  
Conditional Correlation ◽  
Financial Variables ◽  
Global Pandemic ◽  
Daily Data ◽  
Hedge Ratios ◽  
Portfolio Managers ◽  
Multivariate Garch Models

This paper aims to examine the volatility spillover, diversification benefits, and hedge ratios between U.S. stock markets and different financial variables and commodities during the pre-COVID-19 and COVID-19 crisis, using daily data and multivariate GARCH models. Our results indicate that the risk spillover has reached the highest level during the COVID-19 period, compared to the pre-COVID period, which means that the COVID-19 pandemic enforced the risk spillover between U.S. stock markets and the remains assets. We confirm the economic benefit of diversification in both tranquil and crisis periods (e.g., a negative dynamic conditional correlation between the VIX and SP500). Moreover, the hedging analysis exhibits that the Dow Jones Islamic has the highest hedging effectiveness either before or during the recent COVID19 crisis, offering better resistance to uncertainty caused by unpredictable turmoil such as the COVID19 outbreak. Our finding may have some implications for portfolio managers and investors to reduce their exposure to the risk in their portfolio construction.

scholarly journals The Normalization of the European Central Bank’s Monetary Policy from an Austrian Perspective

2018 ◽  
pp. 359-371
Author(s):  
Leef H. Dierks
Keyword(s):  
Monetary Policy ◽  
Interest Rates ◽  
Euro Area ◽  
Quantitative Easing ◽  
Fixed Income ◽  
Fixed Income Securities ◽  
Market Prices ◽  
European Central ◽  
The Us ◽  
Low Interest Rates

After several years of historically low interest rates and quantitative easing, the European Central Bank (ECB) has finally started wind-ing down its ultra-accommodative monetary policy in late 2018. Among the first steps tapering its asset purchase programme (APP), which foresees monthly purchases of up to €30bn per month until September 2018 — «or beyond, if necessary, and in any case until the Governing Council sees a sustained adjustment in the path of infla-tion consistent with its inflation aim» (ECB, 2018a). By then, pur-chases of euro area fixed income securities on behalf of the ECB will have mounted to as much as €2,550bn or almost 90% of euro area GDP (€2,834bn in market prices in Q4 2017, the latest date for which data were available (ECB, 2018b)). Further, according to market esti-mates, the first hike of the main refinancing rate, which was slashed to 0% in March 2016, could emerge in Q1 2019, thereby following a tightening of the monetary policy the US Federal Reserve (FED) had already started in December 2015 (FED, 2015).

scholarly journals Um Estudo Empírico da Dinâmica da Correlação do Retorno das Ações do Brasil

2019 ◽  
Vol 16 (4) ◽  
pp. 635 ◽  
Author(s):  
Hudson Chaves Costa ◽  
Sabino Da Silva Porto Junior ◽  
Gabrielito Menezes
Keyword(s):  
Structural Breaks ◽  
Statistical Tests ◽  
Multivariate Garch ◽  
Garch Models ◽  
Conditional Correlation ◽  
Temporal Series ◽  
Largest Eigenvalues ◽  
Multivariate Garch Models ◽  
Long Term Trend

This article examines empirically the behavior of the correlation between the return of shares listed on the BMF& BOVESPA over the period from 2000 to 2015. To this end, we use multivariate GARCH models introduced by Bollerslev (1990) to remove the temporal series of arrays of conditional correlation of returns of stocks. With the temporal series of the largest eigenvalues of matrices of correlation estimated conditional, we apply statistical tests (unit root, structural breaks and trend) to verify the existence of stochastic trend or deterministic to the intensity of the correlation between the returns of the shares represented by eigenvalues. Our results confirm that both in times of crises at national and international turbulence, there is greater correlation between the actions. However, we did not find any long-term trend in time series of the largest eigenvalues of matrices of correlation conditional.

scholarly journals Variance Persistence in the Greater China Region: A Multivariate GARCH Approach

2018 ◽  
Vol 23 (2) ◽  
pp. 49-68
Author(s):  
John Francis Diaz ◽  
Peh Ying Qian ◽  
Genevieve Liao Tan
Keyword(s):  
Stock Returns ◽  
Stock Exchange ◽  
Composite Index ◽  
Cross Product ◽  
Multivariate Garch ◽  
Stock Index ◽  
Conditional Correlation ◽  
Greater China ◽  
Long Run ◽  
China Region

This paper utilizes three Multivariate General Autoregressive Conditional Heteroscedasticity (MGARCH) models to determine variance persistence in the Greater China region from 2009 to 2014. The first approach applies the Baba, Engle, Kraft and Kroner (BEKK) model and shows that the Shanghai Stock Exchange Composite Index (SSEI), Taiwan Capitalization Weighted Stock Index (TAEIX) and the Hang Seng Stock Index (HSEI) stock returns are all functions of their lagged covariances and lagged cross-product innovations. The second MGARCH approach applies two methodologies, namely, dynamic conditional correlation (DCC), and constant conditional correlation (CCC) estimations. The DCC model concludes both short- and long-run persistencies between Taiwan’s TAIEX and Hong Kong’s HSEI. Alternatively, the CCC model confirms the initial findings of the BEKK model, and adds that the relationships among these three strong economies are stable in the long-run. The log-likelihood values determine that the DCC model is better in judging volatility dynamics in the Greater China region, because of economic clauses brought by the Closer Economic Partnership Arrangement (CEPA), the Economic Co-operation Framework Agreement (ECFA) and the Hong Kong - Taiwan Business Cooperation Committee (BCC).

scholarly journals Can Bitcoin Replace Gold in an Investment Portfolio?

2018 ◽  
Vol 11 (3) ◽  
pp. 48 ◽  
Author(s):  
Irene Henriques ◽  
Perry Sadorsky
Keyword(s):  
High Performance ◽  
Economic Value ◽  
Minimum Variance ◽  
Multivariate Garch ◽  
Risk Averse ◽  
Investment Portfolio ◽  
Conditional Correlation ◽  
Multivariate Garch Models ◽  
Investment Portfolios ◽  
Generalized Orthogonal

Bitcoin is an exciting new financial product that may be useful for inclusion in investment portfolios. This paper investigates the implications of replacing gold in an investment portfolio with bitcoin (“digital gold”). Our approach is to use several different multivariate GARCH models (dynamic conditional correlation (DCC), asymmetric DCC (ADCC), generalized orthogonal GARCH (GO-GARCH)) to estimate minimum variance equity portfolios. Both long and short portfolios are considered. An analysis of the economic value shows that risk-averse investors will be willing to pay a high performance fee to switch from a portfolio with gold to a portfolio with bitcoin. These results are robust to the inclusion of trading costs.

Sign in / Sign up

Export Citation Format

Share Document