scholarly journals General election effect on the network topology of Pakistan’s stock market: network-based study of a political event

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Bilal Ahmed Memon ◽  
Hongxing Yao ◽  
Rabia Tahir
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Spanning Tree ◽  
Oil And Gas ◽  
Minimum Spanning Tree ◽  
Centrality Measures ◽  
Political Event ◽  
Industrial Sectors ◽  
General Elections ◽  
Key Nodes

AbstractTo examine the interdependency and evolution of Pakistan’s stock market, we consider the cross-correlation coefficients of daily stock returns belonging to the blue chip Karachi stock exchange (KSE-100) index. Using the minimum spanning tree network-based method, we extend the financial network literature by examining the topological properties of the network and generating six minimum spanning tree networks around three general elections in Pakistan. Our results reveal a star-like structure after the general elections of 2018 and before those in 2008, and a tree-like structure otherwise. We also highlight key nodes, the presence of different clusters, and compare the differences between the three elections. Additionally, the sectorial centrality measures reveal economic expansion in three industrial sectors—cement, oil and gas, and fertilizers. Moreover, a strong overall intermediary role of the fertilizer sector is observed. The results indicate a structural change in the stock market network due to general elections. Consequently, through this analysis, policy makers can focus on monitoring key nodes around general elections to estimate stock market stability, while local and international investors can form optimal diversification strategies.

scholarly journals A MAP OF THE BRAZILIAN STOCK MARKET

2012 ◽  
Vol 15 (05) ◽  
pp. 1250042 ◽  
Author(s):  
LEONIDAS SANDOVAL
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Network Theory ◽  
Correlation Matrix ◽  
Spanning Tree ◽  
Minimum Spanning Tree ◽  
Stock Exchange ◽  
Sao Paulo ◽  
Threshold Values ◽  
Using Data

The correlation matrix of stocks returns is used in order to create maps of the São Paulo Stock Exchange (BM&F-Bovespa), Brazil's main stock exchange. The data refer to the year 2010, and the correlations between stock returns lead to the construction of a minimum spanning tree and of asset graphs with a variety of threshold values. The results are analyzed using techniques of network theory. Also, using data from 2007 to 2010, a study is made on the dynamics of the network formed by stocks from that same stock exchange.

scholarly journals The Effect of Political Elections on Stock Market Volatility in Malaysia

2018 ◽  
Vol 7 (3.21) ◽  
pp. 114
Author(s):  
Ricky Chia Chee Jiun
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
General Election ◽  
Stock Index ◽  
Stock Market Volatility ◽  
Political Uncertainty ◽  
Stock Volatility ◽  
Volatility Risk ◽  
Company Stock ◽  
General Elections

During the past general elections held in Malaysia, empirical evidence showed a significant election effect in stock volatility. In this study, we investigate the influence of election on Malaysian stock market during the 12th and 13th general election where political tensions persisted due to the close fight between the two major parties. The findings indicate that the political uncertainty surrounding elections significantly affected investors respond. Results from statistical analysis uncover significant higher stock volatility in the pre-general election periods. Nevertheless, lower stock volatility is only found in two stock indices in the post-general election periods. By using the EGARCH model, a significant election effect is found in stock volatility but not in stock returns. Notably, political uncertainty showed up its significant role in influencing the stock volatility prior to the general elections in the year 2008 and 2013. Furthermore, lower stock volatility is found in the Shariah-compliant indices and stock index with greater market capitalization. Our findings have important implications for investors who are exposed to volatility risk. Investors may shift to large company stock and Shariah-compliant stock during the general election period. Investors should also be cautious because the high volatility is not compensated with a significant abnormal return. 

Impact of Oil Price on Australian Stock Market Returns

2018 ◽  
Vol 21 (03) ◽  
pp. 1850018 ◽  
Author(s):  
Hui Li ◽  
Raul Paraco
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Oil Price ◽  
Lower Sensitivity ◽  
Positive Trend ◽  
Oil Shocks ◽  
Market Returns ◽  
Stock Market Returns ◽  
Industrial Sectors ◽  
Asymmetrical Effect

We observe a positive correlation between an oil price factor and the All Ordinaries Index of the Australian stock market. Furthermore, an asymmetrical effect is observed when the sample is divided into sub-periods. A more pervasive stock market response is observed when the price of oil displays a positive trend. We also study the influence of oil shocks on the stock returns of specific Australian industries. As expected, the energy and material sectors exhibit a positive response to oil disturbances, whereas the financial and industrial sectors show a negative relation to oil shocks. The utility and consumer discretionary sectors exhibit a lower sensitivity to oil shocks.

scholarly journals A Network Analysis of Shariah-Compliant Stocks across Global Financial Crisis: A Case of Malaysia

2019 ◽  
Vol 13 (7) ◽  
pp. 80 ◽  
Author(s):  
Fatin Nur Amirah Mahamood ◽  
Hafizah Bahaludin ◽  
Mimi Hafizah Abdullah
Keyword(s):  
Topological Structure ◽  
Spanning Tree ◽  
Minimum Spanning Tree ◽  
Global Financial Crisis ◽  
Closeness Centrality ◽  
Centrality Measures ◽  
Financial Networks ◽  
Eigenvector Centrality ◽  
Land Holdings ◽  
Year 2000

Financial network is a complex system in which transaction of securities take place. Due to its complexity, a minimum spanning tree (MST) technique is used to visualize the structure. This paper investigates the topological structure of 125 shariah-compliant stocks traded in Bursa Malaysia from the year 2000 until 2017. Financial networks of the shariah-compliant stocks are constructed using MST for three duration periods namely the pre-crisis, during crisis and post-crisis. To determine the important stocks in the networks, centrality measures are applied such as degree centrality, betweenness centrality, closeness centrality and eigenvector centrality. Lastly, overall centrality measures are computed to identify the overall characteristic of each node. The findings showed that, KUB Malaysia Berhad was the most influential stock in the pre-crisis and crisis periods. While, MK Land Holdings was the main stock in the post-crisis network.

scholarly journals Are CDS Spreads Sensitive to the Term Structure of the Yield Curve? A Sector-Wise Analysis under Various Market Conditions

2019 ◽  
Vol 12 (4) ◽  
pp. 158 ◽  
Author(s):  
Aman
Keyword(s):  
Stock Returns ◽  
Term Structure ◽  
Oil And Gas ◽  
Yield Curve ◽  
Credit Default Swap ◽  
Yield Rate ◽  
Industrial Sectors ◽  
Volatility Index ◽  
Market State ◽  
The Impact

This study examines the impact of changes in the yield curve factors on the Credit Default Swap (CDS) spreads of the U.S. industrial sectors. Stock returns and the crude oil-based volatility index are used in a quantile regression framework to test the validity of Merton’s model. The results suggest that the long-term factor of the yield curve is a negatively significant determinant of the CDS premia regardless of the sector and market state. The CDS spread of the financial sector exhibits sensitivity to the short-term factor of the yield rate in extreme market states. Basic materials, oil and gas and the utilities sector are responsive to variations in the medium-term factor of the yield rate in upmarket conditions. The empirical findings also suggest a significant inverse relationship between CDS spreads and stock returns.

scholarly journals Short-term Economic Indicators, Stock Market Indexes and Indian Oil and Gas Stocks Returns

2020 ◽  
Vol 4 (1) ◽  
pp. 1-13
Author(s):  
Rama Krishna Yelamanchili
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Causal Relationship ◽  
Oil And Gas ◽  
Jel Classification ◽  
Economic Indicators ◽  
Short Term ◽  
Explanatory Variables ◽  
Short Run ◽  
Market Indexes

In this paper we examine the causal relationship between short term economic indicators, stock market indexes and oil and gas stocks returns. We postulate that economic indicators positively and significantly cause and predict stock market indexes and oil and gas stock returns in short run. In addition, we posit that stock market indexes cause and predict oil and gas stock returns in short run. To test our hypotheses we chose four short-term economic indicators, two stock market indexes, and 10 oil and gas companies. Our results indicate that there is no causal relationship between both short-term economic indicators and stock market indexes, and between short-term economic indicators and oil and gas stock returns. However, we receive support to one of our hypotheses that stock market indexes cause oil and gas stock returns. This causation is contemporaneous only and we observe that stock market indexes lack short-term predictive power of oil and gas stock returns. We conclude that investors need to be vigilant in considering coincident indicators as explanatory variables to predict stock returns. We suggest that stock market indexes are helpful to predict contemporaneous returns but not future returns of oil and gas stocks. JEL Classification: B1, C32, D4, G2.

scholarly journals Empirical Analysis of AH-Shares

2016 ◽  
Vol 4 (4) ◽  
pp. 343-353
Author(s):  
Hongxing Yao ◽  
Kejuan Zhou
Keyword(s):  
Stock Market ◽  
Correlation Coefficient ◽  
Minimum Spanning Tree ◽  
Stock Exchange ◽  
Financial Time Series ◽  
Dynamic Evolution ◽  
Chinese Stock Market ◽  
Coefficient Distribution ◽  
Industrial Sectors ◽  
The Difference

Abstract Recent studies of correlations in Chinese stock market have mainly focused on the static correlations in financial time series, and then we pay great attention to investigate their dynamic evolution of correlations. Our paper reports on topology of 41 AH-shares companies traded on Shanghai and Hong Kong Stock Exchange in Chinese stock market. We apply the concept of minimum spanning tree (MST) and hierarchical tree (HT) to analyze and reveal the dynamic evolution of correlations between different market sectors for the period 2008–2014. From these trees, we can detect that significantly industry clustering effects are in the stock network. We measure the linkage of different companies geared to different industrial sectors. We observe the evolution of AH-shares companies in the stock network based on the moving window technique and investigate the correlations by calculating the correlation coefficient distribution, mean correlation coefficient and mean distance of these companies with time. Therefore, through our analysis, we find that companies working in the same branch of production tend to make up cluster. The results present the difference and similarity between different industry sectors in different time periods.

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