The role of stock market and banking sector development, and renewable energy consumption in carbon emissions: Insights from G-7 and N-11 countries
نقش توسعه بازار سهام و بخش بانکی و مصرف انرژی تجدید پذیر در انتشار کربن: بینش کشورهای G-7 و N-11-2019
This study probes the role of disaggregated financial development and renewable energy in carbon emissions by incorporating gross fixed capital formation and economic growth in the function of carbon emissions. The financial development is measured through the stock market and banking sector development. We also examine the validity of the EKC hypothesis, using the data of G-7 and N-11 countries spanning from 1990 to 2016. The integration properties of the considered variables are examined through second generation unit roots tests. The Lagrange Multiplier (LM) bootstrap panel cointegration method has confirmed the long-run equilibrium relationship among the variables for all the four models used. The long-run elasticity results suggest that renewable energy increases environmental quality by reducing carbon emission intensity for both groups of panel countries. Banking development index decreases carbon emissions in G-7 countries, while increases carbon emissions in N-11 countries. Similarly, stock market development index increases carbon emissions in G-7 countries, while decreases in N-11 countries. Overall, economic growth and fixed capital formation impede environmental quality by accelerating the intensity of carbon emissions. This study suggests policy implications based on the empirical results for both groups of countries.
Keywords: Carbon emissions | Stock market | Banking development | Renewable energy | Economic growth
Financial market Volatility, macroeconomic fundamentals and investor Sentiment
فراریت بازار مالی، اساس های اقتصاد کلان و احساسات سرمایه گذار-2018
In this paper, we investigate the dynamic relationship between financial market volatility, macroeconomic fundamentals and investor sentiment, employing a two-factor model to decompose volatility into a persistent long run component and a transitory short run component. Using a structural VAR model with Bayesian sign restrictions, we show that adverse shocks to aggregate demand and supply cause an increase in the persistent component of both stock and bond market volatility, and that adverse shocks to the persistent component of either stock or bond market volatility cause a deterioration in macroeconomic fundamentals. We find no evidence of a relationship between the transitory component of volatility and macroeconomic fundamentals. Instead, we find that the transitory component is more closely associated with changes in investor sentiment. Our results are robust to a wide range of alternative specifications. Out-of-sample forecasting shows that the components of volatility can improve forecasts of macroeconomic fundamentals, and vice versa.
keywords: Stock and bond market volatility |Two-factor volatility model |Macroeconomic fundamentals |Structural vector autoregression |Bayesian estimation
یک تعمیم از تاثیر جام جهانی فوتبال
سال انتشار: 2018 - تعداد صفحات فایل pdf انگلیسی: 3 - تعداد صفحات فایل doc فارسی: 6
هدف این مقاله بررسی تاثیر پیروزی تیم ملی فوتبال در جام جهانی روی موفقیت گردشگری آن کشور می باشد. برای بررسی تعمیم نتایج تجربی یافت شده تاکنون، چهار دوره با داده های موجود از دهه 90 تحلیل می شوند. نتیجه گیری نشان می دهد که به استثنای دوره 2010 هیچ تاثیر قابل توجه تعمیم یافته ای شناسایی نشده است.
کلمات کلیدی: جام جهانی فیفا | بازار سهام | دانش برند | تصویر
|مقاله ترجمه شده|
Web Media and Stock Markets : A Survey and Future Directions from a Big Data Perspective
رسانه های وب و بازار سهام: مرور و دستورالعمل های آینده از یک چشم انداز داده های بزرگ-2018
Stock market volatility is influenced by information release, dissemination, and public acceptance. With the increasing volume and speed of social media, the effects of Web information on stock markets are becoming increasingly salient. However, studies of the effects of Web media on stock markets lack both depth and breadth due to the challenges in automatically acquiring and analyzing massive amounts of relevant information. In this study, we systematically reviewed 229 research articles on quantifying the interplay between Web media and stock markets from the fields of Finance, Management Information Systems, and Computer Science. In particular, we first categorized the representative works in terms of media type and then summarized the core techniques for converting textual information into machine-friendly forms. Finally, we compared the analysis models used to capture the hidden relationships between Web media and stock movements. Our goal is to clarify current cutting-edge research and its possible future directions to fully understand the mechanisms of Web information percolation and its impact on stock markets from the perspectives of investors cognitive behaviors, corporate governance, and stock market regulation
Index Terms: Computing methodologies, text mining, financial market, stocks, big data, social media, news
Comparison between global financial crisis and local stock disaster on top of Chinese stock network
مقایسه بین بحران مالی جهانی و فاجعه سهام محلی در بالای شبکه سهام چینی-2018
The science of complex network theory can be usefully applied in many important fields, one of which is the finance. In these practical cases, a massive dataset can be represented as a very large network with certain attributes associated with its nodes and edges. As one of the most important components of financial market, stock market has been attracting more and more attention. In this paper, we propose a threshold model to build Chinese stock market networks and study the topological properties of these networks. To be specific, we compare the effects of different crises, namely the 2008 global crisis and the stock market disaster in 2015, on the threshold networks. Prices of the stocks belonging to the Shanghai and Shenzhen 300 index are considered for three periods: the global crisis, common period and the stock market disaster. We find the probability distribution of the cross-correlations of the stocks during the stock market disaster is fatter than that of others. Besides, the thresholds of cross-correlations are assigned to obtain the threshold networks and the power-law of degree distribution in these networks are observed in a certain range of threshold values. The networks during the stock market disaster also appear to have larger mean degree and modularity, which reveals the strong correlations among these stock prices. Our findings to some extent crosscheck the liquidity shortage reason which is believed to result in the outbreak of the stock market disaster. Moreover, we hope that this paper could give us a deeper understanding of the market’s behavior and also lead to interesting future research about the problems of modern finance theory.
Keywords: Threshold network ، Stock market disaster ، Complex network ، Modularity ، Stock price cross-correlation
Can economic news predict Taiwan stock market returns?
آیا می توان اخبار اقتصادی را پیش بینی کرد تا بازار سهام تایوان را پیش بینی کند؟-2018
News reports have become an imperative conduit of public information. Several recent studies have used news data from public media to investigate the impact of news on stock market returns. This study analyses the usefulness of news for predicting stock returns in the Taiwan stock market. We employ text mining of economic news, transform documents using a keyword matrix, and then convert the results into news variables. Subsequently, together with other quantitative variables, we construct a fixed effect model to investigate the behaviours of stock market returns in 20 subsectors from January 2008 to December 2014. Empirical analysis reveals that the news variables provide useful information for pre dicting Taiwan stock market returns, although the out-sample performance is only marginally improved. We also discover an asymmetric effect of economic news for predicting stock market returns. The pre diction accuracy is higher when the stock market is booming than when it is glooming.
Keywords: News ، Text mining ، Stock market sentiment ، Macroeconomic factors
Commodity market based hedging against stock market risk in times of financial crisis: The case of crude oil and gold
مبادله بازار کالا در برابر بحران بازار سهام در زمان بحران مالی: مورد نفت خام و طلا-2018
Based on daily data from 1989 to 2016 we find that the correlations between gold and oil market futures and equity returns in the aggregate US market, and specifically in the energy sector stocks have changed strongly during the stock market crisis periods. The cor relation between crude oil futures and aggregate US equities increases in crisis periods, whereas in case of gold futures the correlation becomes negative, which supports the safe haven hypothesis of gold. Also for the US energy sector equities our results support using gold futures for cross-hedging especially during the stock market crises.
Keywords: Crisis ، Hedging ، Commodity markets ، Stock markets
Risk contribution of the Chinese stock market to developed markets in the post-crisis period
سهم ریسک از بازار سهام چینی به بازارهای توسعه یافته در دوره پس از بحران-2018
China sped up its progress toward the opening of its stock market in the post-crisis period after 2010. This study aims to investigate the risk contribution of the Chinese stock mar ket to four representative developed markets. The significance and dominance of the risk contribution are tested with the extended Kolmogorov-Smirnov statistic by a bootstrap strategy. The results show a significant risk contribution of China to all the four developed countries. The dominance testing result shows clear regional effect in the risk contribution. The determinants of the risk contribution by macroeconomic variables are also identified in a forward-looking way.
Keywords: Chinese stock market ، Risk contribution ، CoVaR ، Tail risk
How does the stock market absorb shocks?
چگونه بازار سهام سرمایه ها را جذب می کند؟-2018
Using a comprehensive set of news stories, we find a stark difference in market responses to positive and negative price shocks accompanied by new information. When there is a news story about a firm, positive price shocks are followed by reversal, while negative ones result in drift. This is interpreted as the stock market overreaction to good news and underreaction to bad news. These seemingly contradictory results can be explained in a single framework, considering the interaction of retail investors with attention bias, and arbitrageurs with short-run capital constraints. Consistent with this hypothesis, we find that both patterns are stronger when the attention bias is stronger, and when the arbitrage capital is scarce.
keywords: Stock return predictability |News|Limits to arbitrage |Limited attention |Overreaction |Underreaction |Text analysis
Causality and Contagion in Emerging Stock Markets
عوارض و آلودگی در بازار سهام در حال ظهور-2018
Given the evidence of occasional discrete shifts in the conditional variance process, it is essential to test the volatility transmission between financial markets when a reasonable suspicion exists for structural change. This paper aims to study the interdependencies in terms of stock market volatility and to assess the impact of Global Financial Crisis (GFC) on these interdependencies. We found evidence of structural breaks in the volatility of time series for the majority of markets. The results show also that, in view of the crisis, new significant causal linkages appeared together with the intensification of the causal relationship in 40% of the cases in which we find causality during both the tranquil and crisis period. These additional linkages during crisis periods in excess of those that arise during non-crisis periods contributes significantly in amplifying the international transmission of volatility and the risk of contagion.
Key words: Causality; Contagion; Structural breaks; Global Financial Crisis; Emerging stock markets; Granger Causality test