INVESTOR SENTIMENT AND STOCK INDEX RETURNS: THE CASE OF SAUDI STOCK EXCHANGE (TADAWUL)

2019 ◽  
Vol 19 (2) ◽  
pp. 25-34
Author(s):  
Abdulrahman Alrabiah
Keyword(s):  
Stock Exchange ◽  
Investor Sentiment ◽  
Stock Index ◽  
Stock Index Returns

In Search of Stock Market Proxy to Calculate Systematic Risk (Beta) of Stocks in Indonesia Stock Exchange

2020 ◽  
Vol 29 (2) ◽  
pp. 80-88
Author(s):  
Mochammad Chabachib
Keyword(s):  
Stock Market ◽  
Real World ◽  
Stock Price ◽  
Price Index ◽  
Stock Exchange ◽  
The Other ◽  
Stock Index ◽  
Market Return ◽  
Stock Market Return ◽  
Stock Index Returns

The calculation of beta stock in Indonesia is still debatable to this day. Though many researchers who have used sophisticated methods mathematically, the assumptions applied in developing the methods are impossible to happen in the real world, such as the ability of stock market return the day after (lead) affects the market return today. This study was conducted to assess the stock price index in Indonesia Stock Exchange that can be used as a proxy of stock market in Indonesia. The results of this study showed that there was a gap between beta stocks counted with JCI return as a market proxy with beta stocks counted with index returns of LQ-45, SRI-KEHATI, PEFINDO-25, BISNIS-27, IDX-30 and KOMPAS-100. This study has also found that the beta counted by using KOMPAS-100 return produced the smallest standard error of the estimate (SEE) that it was more applicable compared to the other stock index returns.

scholarly journals Comparison of the Effect of Vix Fear Index on Stock Exchange Indices of Developed and Developing Countries: the G20 Case

2020 ◽  
Vol 15 (1) ◽  
pp. 105-121
Author(s):  
Ömer İskenderoglu ◽  
Saffet Akdag
Keyword(s):  
Developing Countries ◽  
Causal Relationship ◽  
Stock Exchange ◽  
Granger Causality Test ◽  
Developed Countries ◽  
Stock Index ◽  
Causality Test ◽  
Daily Data ◽  
Fear Index ◽  
Stock Index Returns

AbstractThis study aims to examine the potential causal relationship between the VIX and the indicator stock exchange index returns of G20 (9 developed and 10 developing) countries. Nineteen countries of the sample are G20 countries with available data. In this respect, the frequency domain Granger causality test of Breitung and Candelon (2006) is employed for the daily data between March 2011 and December 2017. The results obtained from the study indicate that there is no causal relationship between the VIX and the returns of the NASDAQ 100 index in developed countries. Similarly, no causal relationship is detected which runs from the VIX to the BIST100, BOVESPA, MERVAL, S&P/BMV IPC and TADAWUL stock index returns in developing countries. As a result, the causal relationship is more tend to be found in developed countries in comparison to developing countries.

Weather Effects on Industrial Stock Index Returns and Volatilities: Evidence from Korean Stock Market

2020 ◽  
Vol 18 (5-6) ◽  
pp. 602-618
Author(s):  
Beom Cheol Cin ◽  
Sung Woo Kim ◽  
Byoung Joon Kim
Keyword(s):  
Stock Returns ◽  
Financial Market ◽  
Stock Exchange ◽  
Weather Conditions ◽  
Stock Index ◽  
Foreign Investors ◽  
Weather Effects ◽  
Financial Deregulation ◽  
Sunshine Hours ◽  
Stock Index Returns

Abstract This study empirically investigates weather effects on Korean stock index returns and market volatility based on the GJR-GARCH-X model. We focus on the issue about whether the weather effect is associated with financial deregulation and foreign investors’ transactions, which should not be affected by the weather conditions in Seoul City. To explore the weather effects by controlling for foreign investors’ trading, we employ daily stock index data and weather indicators (cloud cover, precipitation, sunshine hours, snow, and humidity) during the period from 1981 to 2016. Our empirical results suggest that there is little evidence for weather effects on KOSPI and stock returns by industry listed in the Korea Stock Exchange even if Korean financial market deregulations in 1997 increases foreign investors’ trading, but there is some evidence for weather effects on market volatilities.

META-ANALYSIS ON AMERICAN PRESIDENTIAL ELECTION - 2016 AND AMERICAN STOCK MARKET

2020 ◽  
Vol 38 (1) ◽  
Author(s):  
Farhan Ahmed ◽  
Salman Bahoo ◽  
Sohail Aslam ◽  
Muhammad Asif Qureshi
Keyword(s):  
Content Analysis ◽  
Stock Market ◽  
Event Study ◽  
Presidential Election ◽  
Republican Party ◽  
Stock Exchange ◽  
Meta Analysis ◽  
Composite Index ◽  
Stock Index ◽  
Political Event

This paper aims to analyze the efficient stock market hypothesis as responsive to American Presidential Election, 2016. The meta-analysis has been done combining content analysis and event study methodology. The all major newspapers, news channels, public polls, literature and five important indices as Dow Jones Industrial Average (DJIA), NASDAQ Stock Market Composit Indexe (NASDAQ-COMP), Standard & Poor's 500 Index (SPX-500), New York Stock Exchange Composite Index (NYSE-COMP) and Other U.S Indexes-Russell 2000 (RUT-2000) are critically examined and empirically analyzed. The findings from content analysis reflect that stunned winning of Mr Trump from Republican Party worked as shock for American stock market. From event study, findings confirmed that all the major indices reflected a decline on winning of Trump and losing of Ms. Clinton from Democratic. The results are supported empirically and practically through the political event like BREXIT that resulted in shock to Global stock index and loss of $2 Trillion.

The Effect of Underreaction and Overreaction of Firm Stocks to Firm Valuation: Data from the Indonesian Stock Exchange

2019 ◽  
Author(s):  
Yohanes Indrayono
Keyword(s):  
Behavioral Finance ◽  
Firm Value ◽  
Intangible Assets ◽  
Stock Exchange ◽  
Investor Sentiment ◽  
Firm Valuation ◽  
Good News ◽  
Industrial Sectors ◽  
Tangible Assets ◽  
Firm Profitability

<p>This study contributes to the on-going studies on behavioral finance by providing a case study on underreaction and overreaction of firm stocks to firm valuation. We use the Model of Investor Sentiment (Barberis et al., 2005) to evaluate underreaction and overreaction behavior and reflect on specific findings in the Indonesian market. The result of the study is most of the stocks in the Indonesian Stock Exchange are more overreaction to the news of firm financial statements. Firms on the industry with more intangible assets measure more overreaction than firms on industries with more tangible assets. For stocks with overreaction, the stock firm value is positively affected by a change in the total assets and profitability, but not by change of book value. The result concretized no evidence that firm stocks overreacted to the news more than underreacting. In stock industrial sectors, the financial institutions and wholesale industry stocks demonstrated remarkable overreactions. Nonetheless, automotive, building construction, food and beverage as well as cement evidenced more underreaction. For better return in financial markets, investors may buy stocks of the firm on industry with more tangible assets when there is no good news about the increasing firm profitability and sales; nonetheless, they should buy stocks of the firm on industry with more intangible assets when there is no lousy news about the increasing firm profitability and sales. </p>

scholarly journals A Neutrosophic Forecasting Model for Time Series Based on First-Order State and Information Entropy of High-Order Fluctuation

Entropy ◽  
2019 ◽  
Vol 21 (5) ◽  
pp. 455 ◽  
Author(s):  
Hongjun Guan ◽  
Zongli Dai ◽  
Shuang Guan ◽  
Aiwu Zhao
Keyword(s):  
Time Series ◽  
Information Entropy ◽  
Stock Exchange ◽  
Time Series Forecasting ◽  
High Order ◽  
Stock Index ◽  
Neutrosophic Set ◽  
Forecasting Model ◽  
Forecasting Models ◽  
Proposed Model

In time series forecasting, information presentation directly affects prediction efficiency. Most existing time series forecasting models follow logical rules according to the relationships between neighboring states, without considering the inconsistency of fluctuations for a related period. In this paper, we propose a new perspective to study the problem of prediction, in which inconsistency is quantified and regarded as a key characteristic of prediction rules. First, a time series is converted to a fluctuation time series by comparing each of the current data with corresponding previous data. Then, the upward trend of each of fluctuation data is mapped to the truth-membership of a neutrosophic set, while a falsity-membership is used for the downward trend. Information entropy of high-order fluctuation time series is introduced to describe the inconsistency of historical fluctuations and is mapped to the indeterminacy-membership of the neutrosophic set. Finally, an existing similarity measurement method for the neutrosophic set is introduced to find similar states during the forecasting stage. Then, a weighted arithmetic averaging (WAA) aggregation operator is introduced to obtain the forecasting result according to the corresponding similarity. Compared to existing forecasting models, the neutrosophic forecasting model based on information entropy (NFM-IE) can represent both fluctuation trend and fluctuation consistency information. In order to test its performance, we used the proposed model to forecast some realistic time series, such as the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX), the Shanghai Stock Exchange Composite Index (SHSECI), and the Hang Seng Index (HSI). The experimental results show that the proposed model can stably predict for different datasets. Simultaneously, comparing the prediction error to other approaches proves that the model has outstanding prediction accuracy and universality.

scholarly journals Universal Fluctuations of the S&100 Stock Index Returns

2009 ◽  
Author(s):  
Rui Gonçalves ◽  
Alberto Pinto ◽  
Theodore E. Simos ◽  
George Psihoyios ◽  
Ch. Tsitouras
Keyword(s):  
Stock Index ◽  
S 100 ◽  
Stock Index Returns

Cross-Market Linkages of Taiwan Index Futures Contracts Listed on the Taiwan Futures Exchange and the Singapore Exchange

2007 ◽  
Vol 10 (04) ◽  
pp. 561-583 ◽  
Author(s):  
Hung-Gay Fung ◽  
Qingfeng "Wilson" Liu ◽  
Gyoungsin "Daniel" Park
Keyword(s):  
Stock Exchange ◽  
Trading Strategies ◽  
Stock Index ◽  
Futures Contracts ◽  
Stock Index Futures ◽  
Index Futures ◽  
Taiwan Stock Exchange ◽  
Market Linkages ◽  
Cointegration Tests ◽  
Causality Tests

Cointegration tests and ex ante trading rules are applied to study cross-market linkages between the Taiwan Index futures contracts listed on the Singapore Exchange and the Taiwan Stock Exchange Capitalization-weighted Stock Index futures contracts listed on the Taiwan Futures Exchange. The exchange rate-adjusted returns of the two futures series do not differ significantly in mean but in variances, and show significant mean-reverting tendencies between them. Our trading strategies are able to generate statistically significant, if economically insignificant, profits, while our Granger causality tests demonstrate that information flows primarily from the Singapore market to the Taiwan market, a result confirming other research.

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