The stock market is viewed as a complex dynamic system, and investor sentiment has an important impact on index fluctuation. This study constructs investor sentiment from margin trading business ...perspective and investigates its impact on the Chinese stock market index fluctuation in multiple time scales. First, we utilize 12 indicators and two-stage PCA to construct a composite investor sentiment index of the margin trading business(ISMT). Second, based on TEI@I complex system theory, we use the VMD algorithm to decompose and reconstruct the ISMT, Shanghai Securities Composite Index(SSEC), and Shenzhen Securities Component Index(SZI), and obtain multiple time scale measurement sequences that reflect short-term, medium-term, and long-term fluctuation of each index, respectively. We provide evidence that the ISMT has an asymmetric impact on stock market index fluctuations. Specifically, for long-term trend, the ISMT has a significant positive impact on the SSEC, and a significant negative impact on the SZI. For medium and short-term trends, the ISMT has a significant positive impact on both the fluctuations of SSEC and SZI, and the impact degree on SSEC is greater than SZI. We also find that the impact degree of ISMT on SSEC and SZI decreases from short to long-term trend. In addition, we measure the fluctuation periodicity of ISMT in multiple time scales based on Fast Fourier Transformation, investigate the impact result during the COVID-19 pandemic, discuss the impact of ISMT on the other nine indexes commonly used in the Chinese stock market, and evaluate the predictive power of ISMT for 11 stock market index returns. This paper takes a new perspective and technology to investor sentiment research, and the results enrich relevant financial theories. The findings are crucial for investor decision-making and financial department regulation.
•Extend the research scenario about investor sentiment to the margin trading business, and construct corresponding sentiment index(ISMT).•Investigate the impact of ISMT on index fluctuation in multiple time scales.•Measure the fluctuation periodicity of ISMT in multiple time scales, discuss the results during the COVID-19 pandemic, and analyze the impact on more stock market indexes.•Evaluate the predictive power of ISMT for 11 stock market index returns.
In this paper, we study the power of moment‐based normality tests which include Jarque Bera (JB) test and D′Agostino and Pearson (DP) omnibus tests. Power comparison were obtained via Monte Carlo ...simulation of sample data generated from four alternative distributions like Uniform, Logistic, Student t and Gamma distribution. Our simulation results show that for Uniform distribution, DP test has better power compared to JB test. For Logistic, Student t and Gamma distributions, we find JB normality test to be powerful compared to DP test. We further apply the moment‐based normality tests empirically on the Indian stock market indices (NSE Nifty 50 and BSE Sensex) for different frequencies (daily, weekly, monthly and quarterly) during the period from 2010 to 2020. We find that daily returns of Indian stock indices are non‐normal whereas weekly, monthly and quarterly returns are normally distributed.
Kredi temerrüt takasları (CDS), kredi riskinin borç veren tarafından daha düşük bir maliyetle karşılanmasını sağlamaktadır. Yüksek CDS primleri beraberinde yüksek borçlanma maliyetlerini ...getirmektedir. Yükselen maliyetler ise risklerin artmasına neden olacaktır. Bu nedenle temerrüt riski hakkında bilgi sunan CDS primleri, yatırımcılara riskten korunmada yardımcı bir unsur olmaktadır. Bu çalışmanın amacı, BRICS (Brezilya, Rusya, Hindistan, Çin, Güney Afrika) ülkelerine ait CDS’lerle yine ilgili ülkelere ait belirlenmiş borsa endeks değerleri (Sao Paulo SE Bovespa, RTS, Nifty 500, Shanghai SE Composite, FTSE / JSE SA Top 40 Companies) arasında bir ilişki olup olmadığının tespit edilmesidir. BRICS, küresel ekonomik büyümeye etki eden yükselen ekonomilerin bir araya getirildiği önemli bir topluluktur. Bu kapsamda seçilen BRICS ülkelerine ait 5 yıllık CDS primleri ile borsa endeks değerleri arasındaki ilişki panel veri analizi yardımıyla incelenmiştir. Analiz sonucunda elde edilen bulgulara göre değişkenler arasında negatif yönlü, anlamlı bir ilişki olduğu sonucuna ulaşılmıştır. Bu da CDS primlerinde meydana gelen düşüşlerin borsa endeks değerlerini artırdığını göstermektedir.
In the developed world, capital markets are mentioned as one of the economic growth resources, and the fair distribution of wealth and also increasing per capita income. By attracting the micro ...capital of the society, while employ micro capitals in production, also generate income for real and legal shareholders. Another positive effects for this market is the absorption of market liquidity ,which is one of the main reasons for inflation in countries.One of the components that always causes the stock market to fluctuate is the price of oil. In countries such as Iran , which are heavily dependent on oil revenues.Fluctuation in oil prices and the stock market are more exposd to government interventions.Accordingly, in present study using the monthly data for the years from 2012 to 2019 with the method of Nonlinear Cointegrating Autoregressive Distributed Lag ,has been tried to test asymmetry in effectiveness.Research results show that fluctuation in oil prices ,exchange rate, money supply and consumer price index fluctuation in oil prices ,exchange rate, money supply and consumer price index can be effective among the channels in the stock market.Also, fluctuation in oil prices and asymmetric exchange rate and consumer price index and money supply are reported symmetrically.
This study aims to investigate the effect of oil price and exchange rate on the two Vietnamese stock market indices: VN index and HXN index. This study uses the daily data from August 1st 2000 to ...October 25th 2019 of the two Vietnamese stock indices: VN index and HNX index, the two oil price indices: BRENT and WTI, and the two exchange rates: US dollar to Vietnamese dong and Euro to Vietnamese dong. Due to the presence of heteroskedasticity in our data, we use GARCH (1,1) regression model to perform our analysis. Our findings show that the oil price has a significant positive effect on the two Vietnamese stock market indices. In terms of the stock index volatility, both the VN index and HNX index volatilities are negatively impacted by the return of oil price. While the conclusion about the impact of oil price remained consistent through all three robustness tests, the effect of exchange rate on Vietnamese stock market indices is not consistent. We find thatchanges of the USD/VND exchange rate significantly impact the return and volatility of HNX index only in GARCH (1,1) setting. Our analysis also survives a number of robustness tests.
Stock price prediction is a prevalent research field in both industry and academia. There is a pressing demand to develop a prediction model that captures the pattern of the financial activities with ...high precision to make an informed decision. Stock price prediction is challenging due to the complex, incomplete, fuzzy, nonlinear, and volatile nature of financial data. However, developing a robust model is possible due to advancements in artificial intelligence, availability of large-scale data, and increased access to computational capability. This study performs a comparative analysis of three deep learning models—the Long Short-term Memory (LSTM), Gated Recurrent Unit (GRU), and Convolutional Neural Network (CNN)—in predicting the next day’s closing price of the Nepal Stock Exchange (NEPSE) index. A set of sixteen predictors is carefully chosen under the domain of the fundamental market data, macroeconomic data, technical indicators, and financial text data of the stock market of Nepal. The performances of employed models are compared using the standard assessment metrics—Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), and Correlation Coefficient (R). The experimental results show that the LSTM model architecture provides a superior fit with high prediction accuracy. Moreover, statistical evidences are presented to validate the models’ reliability and robustness.
This study empirically investigated the effect of adjustment of the China Securities Index 300 (CSI 300) on environmental information disclosure (EID) by index constituents, based on propensity score ...matching and difference-in-difference approaches. The results showed that the inclusion in the CSI 300 significantly improved the quality of EID by firms. Moreover, this positive impact was more pronounced among firms with lower agency costs and those located in regions with a stronger legal environment. Further testing of the mediating mechanism revealed that becoming an index constituent served to curb opportunistic behavior by managers arising from shortsightedness. Our results were valid after addressing the potential endogeneity between index adjustment and EID and remained unchanged in various other robustness tests. The findings provide support for the positive impact of stock market index adjustment on non-financial information disclosure and have practical implications for decision-making regarding EID in China and other emerging markets.
•CSI 300 inclusion improved the quality of corporate EID.•The above effect was moderated by agency costs and legal environment.•Reduction of managerial opportunistic behavior is the mediating mechanism.•Findings support index adjustment’ impact on non-financial information disclosure.•Findings have practical implications for decision-making regarding EID.
Purpose of the study: This work aims to find the type of relationship amongst the chosen variables, inflation (INF), short-term interest rate (SIR), money supply (M.S.) and crude oil price (COP) and ...oil price shocks represented by DUMMY respectively on the capital market of Saudi Arabia. It will also throw insight to policymaker to find factors which influence the capital market of Saudi Arabia and to take remedial measures to boost investment in the country.
Research Methodology: The relationships amongst the Saudi security market, the oil price shock, and the selected macroeconomic variables as mentioned above are determined using the Johansen test of co-integration, the vector error correction model, and the Wald test. The research employs the time series data for a period of 2009to 2016, for the study.
Findings: The results show a long-run equilibrium relationship between the Saudi stock market and the selected variables for the study. The study shows a positive association between the money supply and the stock market, but inflation, short-term interest rate, and crude oil price, the result indicates a negative relationship.
Implications: The present study can have implications for the policymaker to take corrective measures for better performance of the stock market by controlling inflation and regulating the short-term interest rate.As the findings indicate that they have a negative relationship with TASI. This paper will also help the policymaker in identifying the real cause for the decline in the value of the stock price. A good performing stock market means better economic growth and overall economic development. To diversify the economy to have an alternative to the oil-driven economy to a more balanced economy by promoting other sectors like manufacturing and tourism.
Novelty/Originality of this study: The literature review confirms that all work of oil price shock is related to its effect on the security market return. This work is different from the other study as it includes macroeconomic variables in the study, together with the oil price shocks. The study is unique from other studies as it is broader in approach, by including more variables than earlier studies which mostly included the oil price shocks and its impact on the stock market. There is no work done to investigate the joint effect of macroeconomic variables and oil price shocks on the Saudi stock market.
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