Sector Stock Returns Research Articles

The Impact of Determinants on the Volatility of Banking Sector Stock Returns in Europe

The Impact of Determinants on the Volatility of Banking Sector Stock Returns in Europe

Impact of changes in the level, slope and curvature of interest rates on U.S. sector returns: an asymmetric nonlinear cointegration approach

This article examines the sensitivity of U.S. sector equity indices to changes in nominal interest rates and in the corresponding principal components (level, slope and curvature of the U.S. yield curve) over the period 1990–2013 using factor models and a nonlinear autoregressive distributed lag (N.A.R.D.L.) approach. Furthermore, for robustness, this research analyses whether the sensitivity of sector stock returns is different depending on the stage of the economy, splitting the whole sample period into two sub-periods: pre-crisis and subprime crisis. In general, the empirical results confirm a substantial exposure to interest rate risk that depends on the model used and the period analysed. In addition, considering the three principal components of the U.S. yield curve, the sensitivity to changes in these components tends to be stronger during the subprime crisis sub-period. Finally, in the N.A.R.D.L. context, about 50% of sectors show long-run relations between sector stock returns and the explanatory factors, mainly during the whole sample and the pre-crisis sub-period. Nevertheless, short-run responses may be mostly shown in the subprime crisis sub-period. Therefore, our results evidence that nominal interest rates and its three components would have asymmetric effects on the U.S. stock returns at sector level, depending on the stage of the economy.

Does skewness help in better investment decision making?

PurposeThe purpose of this paper is to examine the significance of skewness in maximizing the investor utility using the daily data for eight sectors listed on the National Stock Exchange of India.Design/methodology/approachThe analysis is carried out in three different steps. In the first part, the author analyzes the monthly stock returns and the important financial ratios – price-to-book (PB) ratio, price-earnings (PE) ratio and dividend yield (DY). Second, the author tests the sector-wise return predictability using Westerlund and Narayan (2012) flexible generalized least squares estimator. Third, the author compares the mean–variance–skewness (MVS) utility function with the mean–variance (MV) utility function.FindingsThe author forecasts the sectoral stock returns using three financial ratios – PB ratio, PE ratio and DY – as predictors. The results indicate that sectoral stock returns are significantly predicted by these financial ratios. The author then formulates trading strategies by including skewness in the utility function and finds that the investor utility is high when the utility function includes skewness as opposed to when the skewness is excluded.Originality/valueThe author extends the MV utility function to the MVS utility function and shows that the Indian stock market is more profitable when the investor uses a MVS utility function which highlights the main contribution to the literature.

The impacts of global economic policy uncertainty on stock market returns in regime switching environment: Evidence from sectoral perspectives

AbstractThis study contributes in building emerging literature by investigating the impacts of global economic policy uncertainty on Malaysian sectoral stock performance. This study models sectoral stock returns as time‐varying transition probability Markovian processes and employs two‐stage Markov‐switching model for findings impacts of global economic policy uncertainty on sectoral stock returns in regime switching environment. The empirical results reveal that linear framework unable to detect the effects global economic policy uncertainty, and the Markov‐switching model exhibits significant effects of global economic policy uncertainty on all sectoral stock returns excluding technology sector in Malaysia stock market. The findings also expose that the effects of global economic policy uncertainty vary across regime states, sectors, and nature of effects, where the negative effects of global economic policy uncertainty dominate over positive effects. The global economic policy uncertainty exhibits greater impacts on stock returns in high‐volatility regime. Thus, the findings confirm the existence of asymmetric, nonlinear, nonmonotonic, and state‐dependent relationship between global economic policy uncertainty and sectoral stock returns in Malaysia. Therefore, the overall empirical findings can be applied in asset pricing and investment decision‐making purposes. The findings also suggest that global economic policy uncertainty can be a systemic risk factor and predictor of stock market returns.

Sectoral exposure of financial markets to oil risk factors in BRICS countries

In this paper, we examine the exposure of sectoral equity returns to changes in oil risk factors among BRICS markets. The paper combines VAR model together with the Random Forest technique to provide a novel framework which overcome some weaknesses in VAR modelling and help in the selection of oil-risk factors considered. Our results in general show that the response of sectoral stocks to changes in oil-risk factors is not homogenous and their sensitivities are not uniform across BRICS markets. Stock returns of Basic Materials, Financials and Industrials sectors show consistently negative sensitivity to crude oil volatility (OVX) and oil price shocks for major oil importers, whereas sectoral stocks among major oil exporters seems to demonstrate systematic pattern. To explain sectoral stock variations, the results reveal OVX and oil to be the most significant risk transmitting factors in BRICS, irrespective of whether the market is a major oil importer or exporter. However, our results also confirm the presence of asymmetric effects in sectoral stocks for Brazil and Russia while no such evidence is found for India, China and South Africa. Overall, the findings suggest that the manner in which sectors respond to fluctuations in oil-risk factors varies between different sectors and it depends on the oil characteristics of the markets, nature of sectors and the type of oil-risk factors considered.

Asymmetric impacts of oil price uncertainty on Chinese stock returns under different market conditions: Evidence from oil volatility index

The crude oil volatility index (OVX) is a direct and more accurate measure of oil price uncertainty. This paper uses this kind of implied volatility index of oil prices to investigate the impacts of oil price uncertainty on the aggregate and sectoral stock returns in China. This issue is resolved by using a quantile regression, which can provide a more detailed examination under different market conditions. Meanwhile, the asymmetric effects of uncertainty shocks are also examined by using the positive and negative changes of the OVX. Furthermore, we assess whether the reform of March 27, 2013 affected the OVX-stock nexus since this reform was a major step to relax the control of domestic oil prices in China. Our results reveal that OVX changes mainly show significantly negative effects on the aggregate and sectoral stock returns in the bearish market. In particular, these effects depend largely on the positive shocks of the OVX rather than the negative shocks of the OVX. Moreover, the reform of March 27, 2013 decreased the impacts of the positive OVX shocks on Chinese stock returns.

The dynamic information spill-over effect of WTI crude oil prices on China’s traditional energy sectors

PurposeThe purpose of this paper is to explore the dynamic influence of WTI crude oil returns on the stock returns of China’s traditional energy sectors, including oil and gas exploitation, coal mining and processing, petroleum processing and coking, electricity, heat production and supply and mining services.Design/methodology/approachHong’s information spill-over test and the DP Granger causality test are applied to investigate the relationship between the two markets. Moreover, a rolling window is introduced into the above two tests to capture time-varying characteristics of the influence of WTI crude oil returns.FindingsThe empirical results indicate that, first, there exists significant bidirectional linear causality between WTI crude oil returns and China’s traditional energy sectoral stock returns, but the nonlinear causality appears weaker. Second, the influence of WTI crude oil returns on traditional energy sectoral stock returns has time-varying characteristics and industry heterogeneity both in the linear and nonlinear cases. Finally, the decline of WTI crude oil prices may strengthen its linear influence on the stock returns of traditional energy sectors, while the excessive rise of market values in traditional energy sectors may weaken the linear and nonlinear influence of WTI on them.Originality/valueThe general nexus between international crude oil market and China’s traditional energy stock market is explored both in the linear and nonlinear perspectives. In particular, the dynamic linear and nonlinear influence of WTI crude oil returns on China’s traditional energy sectoral stock returns and its industry heterogeneity are analysed in detail.

Causality Test Inflation and Stock Return in Indonesia Stock Exchange

Investors can see the inflation rate as one of the basic investment decisions. The inflation rate has affected stock returns in overseas studies with diverse directions. Further research is important to provide an overview of the effect of Indonesia's inflation rate and stock returns that are useful for analyst to predict macroeconomic conditions as well as investment decisions. This study aims to identify the relationships between inflation and stock return in Indonesia’s Stock Exchange and identify the effect of inflationary shock to stock returns in Indonesia’s Stock Exchange. The research method used in this study are Vector Autoregression and Granger causality/Wald exogeneity block test. The result showed that Indonesia's inflation rate did not significantly affect stock returns, but when the analysis proceeded more specifically into sectoral stock returns, it was seen that Indonesia's inflation rate has significantly affected the stock returns of Basic Industry sector and Infrastructure sector. Inflation rate shocks was responded negatively by the sectors. Further findings were the causality relationship between the inflation rate of Indonesia and the stock return of Basic sector. The return of Jakarta Composite Index affected the inflation rate of Indonesia. Specific sectors that have influenced inflation rate were Agriculture sector, Basic Industry sector and Financial sector.

Financial crisis spillover from Wall Street to Main Street: further evidence

We examine the impact of significant news events during the 2007–2008 financial crisis on the abnormal stock returns for portfolios of financial and real sector firms. We estimate financial crisis event announcement abnormal returns in the context of an asset-pricing model similar to Fama and French (J Financ Econ 33:3–56, 1993) and Carhart (J Finance 52:57–82, 1997). Our results document significant negative abnormal returns for the portfolio of non-financial firms in response to both crisis and intervention news, quantifying the significant spillover of financial market news to real sector stock returns. In contrast, while small financial firms also exhibit negative abnormal returns, larger financial institutions do not. In fact, some larger financial institutions, such as depository institutions, yield positive abnormal returns in response to some financial crisis and intervention event announcements. The results provide further evidence of the incorporation of financial sector news events into non-financial asset prices during financial crises and new evidence on the short-term impact of crisis and policy intervention news on both financial and real sector firms.

Changing Risk-Return Profiles

We show that realized volatility, especially the realized volatility of financial sector stock returns, has strong predictive content for the future distribution of market returns. This is a robust feature of the last century of U.S. data and, most importantly, can be exploited in real time. Current realized volatility has the most information content on the uncertainty of future returns, whereas it has only limited content about the location of the future return distribution. When volatility is low, the predicted distribution of returns is less dispersed and probabilistic forecasts are sharper. Given this finding on the importance of financial sector volatility not just to financial equity return uncertainty but to the broader market, we test for changes in the realized volatility of banks over a $50 billion threshold associated with more stringent Dodd-Frank Wall Street Reform and Consumer Protection Act (Dodd-Frank) requirements. We find that the equity volatility of these large banks is differentially lower by 9 percentage points after Dodd-Frank compared to pre-crisis levels, controlling for changes over the same period for all banks and all large firms.

The interactions between OPEC oil price and sectoral stock returns: Evidence from China

This paper examines the volatility spillover between OPEC oil price and the Chinese sectoral stock returns from December 31, 2004 through October 17, 2014. In order to achieve this task, we used the VAR-GARCH model for the daily closing prices of six sectoral stock indices including: Construction, Machinery, Automobile, Military, Agriculture, and Financial indices. In addition, we analyzed the optimal weights and hedge ratios for oil–stock portfolio holdings. The findings show significant volatility spillover between OPEC oil prices and the Chinese sectoral stock returns. The volatility spillover is unidirectional from oil to stock returns. The spillover effects mainly come from past shocks. The past oil shocks have negative and significant impact on the conditional volatility of Construction, Machinery, Automobile, Military and Agriculture stock indices. On the contrary, with the exception of the Military stock index, there is no significant impact of the past stock return shocks on the volatility of oil returns. Moreover, our findings for optimal weights and hedge ratios suggest that oil can improve the risk-adjusted performance of a well-diversified portfolio of stocks.

The Impact of Oil Price Shocks on Sector Indices: Evidence from Borsa İstanbul

We analyze the dynamic relationship between daily Brent oil prices and selected sector index returns of Borsa Istanbul. To perform an elaborate analysis, because oil price fluctuations affect sectors differently, the sectoral index returns are classified as oil-user, oil-related, oil-substitute, and financial. Employing Johansen and Juselius (1990) cointegrating technique, the long-run relationship is examined between the oil price changes and sectoral stock returns. After the investigation of the causal relationship between these two variables, Impulse Response Functions and Variance Decomposition Analysis are used to evaluate how shocks to variables rebound through a system. Given that significant changes have occurred across capital markets throughout the period, it would appear to be worthwhile to investigate whether changes in interactions among oil prices and sectoral stock returns have occurred as a result. The findings indicate that; there is cointegration between returns of half of the sectoral indices analyzed and oil prices Granger causes sectoral index returns.

THE INFLUENCE OF MACROECONOMICS VARIABLES: RUPIAH / USD, BI RATE

2008 global economic crisis has led to poor growth across all sectors in Indonesia. The crisis also had an impact on stock market conditions that exist in Indonesia, including the shares of the manufacturing sector. The stock price itself more easily influenced by external factors or changes in macroeconomic conditions. Macroeconomic factors will continue to experience growth and development as always turmoil fluctuation, well after the global crisis well so far. Therefore, this study aims to determine how large the macro-economic factors that influence the stock return of the manufacturing sector. Macroeconomic factors that will be examined is the exchange rate USD / USD, BI rate, inflation and oil prices. The analytical method used in this research is multiple regression analysis were performed with SPSS 23. One of the requirements to perform multiple test analysis necessary to test classic assumptions. This is necessary so that the resulting regression equation is BLUE (Best, Linear, Unbiased, Estimator). In addition to assessing the goodness of fit of a model made for the t-test, F, and test the coefficient of determination. This study uses monthly data from 2006-2015. The results of this study indicate that the variable Exchange Rate / USD, oil prices negatively affect Sunia Stock Return manufacturing sector 2006-2008 period and a variable BI Rate, Oil Price Inflation influence positively and negatively affect the manufacturing sector Stock Return period 2010-2015.Keywords: global crisis in 2008, Manufacturing Sector, Exchange Rate, BI Rate, Inflation, Oil Price, Stock Return.

The Economic Cost of Terrorism and Natural Disasters: A Deeper Analysis of the Financial Markets of Pakistan

Do natural disasters and terrorism affect the financial markets of Pakistan? We aimed to answer this question by studying a large data-set of stock returns of Pakistani financial markets with respect to natural disasters and terrorist activities. Two methods are used for that purpose i.e. event study and nonlinear GARCH (Generalized Autoregressive Conditional Heteroskedasticity) estimation. The event study methodology used to analyze daily, weekly, and monthly stock returns of KSE-100 (Karachi Stock Exchange-100 index), Banking, and Insurance sectors. We calculated the abnormal returns with the help of market adjusted return model. Findings reveal that terrorist events have a statistically significant negative impact on banking and insurance sector returns, while insignificant impact on KSE-100 index. Natural disasters have an insignificant impact on stock market returns, with the exception of floods which showed a significant impact on bank returns but remained insignificant for insurance and stock market returns. Earthquakes showed a negative effect on the stock market returns whilst no significant impact has shown for insurance and banks’ returns. Whereas, nonlinear estimation such as GARCH model is applied to model the volatility and the influence of terrorist events on conditional variance for three mentioned stock market indices. Moreover, GARCH model indicates the higher volatility during 2000-2010, which is decreasing towards the end of sample period. The higher volatility periods in financial markets correspond to higher number of terrorist attacks in the country and instability in the political environment.

A New Approach to Modeling Sector Stock Returns in China

This article analyzes the relationship between excess stock returns and the macroeconomy of China. A factor-augmented regression is applied to a panel of 123 monthly Chinese macroeconomic time series. Eight fundamental macroeconomic factors are identified and used to examine the excess returns in industrial, commercial, real estate, and utilities sectors of the market. It is found that interest rate, output level, as well as property supply factors possess explanatory power for sector stock returns in China.

Has the uniformity of banking regulation within the European Union restricted rather than encouraged sectoral development?

The recent international financial crisis exposed many of the frailties that exist within the European banking sector. One major decision taken by the European Commission was to transition the powers of the Committee of European Banking Supervisors to that of the European Banking Authority (EBA). Our analysis focuses primarily on the differing behaviour by each European country's banking sector to major shocks, namely that in the form of bank closures. It is then necessary to investigate and further understand the role that the European Banking Authority now possesses with regards to releasing sensitive announcements based on the underlying currents of the European Banking system as measured by domestic banking sector stock returns. Finally, we investigate the cultural characteristics that can be uncovered by analysing the responses of domestic banking sectors to uniform regulation. We present three key findings. First, European countries with more local banking networks in the form of credit unions, public banks or savings banks, generate greater levels of volatility when compared to that of their commercial counterparts, particularly in countries with more monopolistic sectors. Secondly, the announcements of the European Banking Authority generate significant volatility effects for the European banking sector at large, with particular emphasis on stress testing results, but also announcements based on recapitalisation, regulation and transparency. Finally, cultural distance effects are identified, indicating that peripheral states are experiencing more substantial volatility effects to European Banking Authority decisions. These results indicate that uniformity of regulation may in fact be hindering and restricting the growth of some domestic and more peripheral and locally designed banking sectors in the form of rules designed for commercial banking operations.

RETURN AND VOLATILITY SPILLOVER BETWEEN SECTORAL STOCK AND OIL PRICE: EVIDENCE FROM PAKISTAN STOCK EXCHANGE

This paper aims to investigate the return and volatility spillover between world oil prices and the sectoral stock of Pakistan. We estimate a bivariate VAR(1)-AGARCH (1,1) model using weekly data sampled from January 1, 2001 to December 31, 2015. The model results are used to estimate the optimal portfolio weights and hedge ratios. The empirical findings suggest no short-run price transmission between world oil prices and stock sectors of Pakistan Stock Exchange. Only the past unexpected shocks in world oil prices has significant effect on the volatility of sectoral stock returns of Pakistan Stock Exchange, and no volatility spillover exist between world oil price and stock sectors. The optimal portfolio weights and hedge ratios for oil/stock holdings are sensitive to sectors considered. These findings are of great interest for policy makers, hedge fund managers, [Formula: see text] investors and market participants.

Empirical Analysis on Exchange Rate Fluctuation and Sectoral Stock Returns in Malaysia

Empirical Analysis on Exchange Rate Fluctuation and Sectoral Stock Returns in Malaysia

Oil prices and stock returns: nonlinear links across sectors

We present evidence of an asymmetric relationship between oil prices and stock returns. The two regime multivariate Markov switching vector autoregressive (MSVAR) model allow us to capture the state shifts in the relationship between regional stock markets and sectors. Results suggest that oil price risk is significantly priced in the sample used. The impact is asymmetric with respect to market phases, and regimes have been associated with world economic, social and political events. Our study also suggests asymmetric responses of sector stock returns to oil price changes and different transmission impacts depending on the sector analyzed. There is a high causality from oil to sectors like Industrials and Oil & Gas. Companies inside the Utilities sector were more able to hedge against oil price increases between 2007 and 2012. Historical crisis events between 1992–1998 and 2003–2007 do not seem to have affected the relationship between oil and sector stock returns, given the higher probability of remaining smoother. For all sectors there seems to be a turn back to stability from 2012 onwards. Finally, investors gain more through portfolio diversification benefits built across, rather than within sectors.

Stock returns and economic forces—An empirical investigation of Chinese markets

This study finds evidence that a better macroeconomic climate and an improvement in liquidity help to explain Chinese stock returns. There is no evidence to support the hypothesis that growth in dividend yields can predict stock returns. The sectoral stock returns in China's markets are correlated with stock returns in the US markets as evidenced by: (i) a positive correlation with US stock returns; (ii) a significant negative error correcting term; (iii) a negative response of Chinese stocks to financial stress in the US market; and (iv) a positive correlation with a depreciation in the China/US exchange rate.