Global stock market index analysis based on complex networks and a multiple regression model

2015 ◽  
pp. 265-268
Author(s):  
Z Zhang ◽  
S Qiao
Keyword(s):  
Stock Market ◽  
Complex Networks ◽  
Regression Model ◽  
Multiple Regression ◽  
Multiple Regression Model ◽  
Stock Market Index ◽  
Market Index ◽  
Index Analysis ◽  
Global Stock

scholarly journals Capital Asset Pricing Model, Theory and Practice: Evidence from USA (2009-2016)

2017 ◽  
Vol 12 (8) ◽  
pp. 182 ◽  
Author(s):  
Mohammad AbdelMohsen Al-Afeef
Keyword(s):  
Stock Market ◽  
Multiple Regression Model ◽  
Theory And Practice ◽  
Pricing Model ◽  
Stock Market Index ◽  
Market Return ◽  
Market Index ◽  
Stock Market Return ◽  
The Us ◽  
The Impact

This study discussed the Capital Assets Pricing model (CAPM) and its ability to measure the required return, the researcher tested this model on Amazon Company listed in S&P 500 during the period (2009-2016), to measure the impact of beta stock and market index return on the required return. Multiple regression model was used to test the effect of independent variables (Beta stock, Market Index Return) on the dependent variable (Required return), it should be noted that there is a statistically significant impact of the US stock market Return (S&P500) and Amazon stock Beta factor on Amazon stock required return, and the study model explanatory was 20% , this means that 20% of the changes in the required return are due to beta and market return, and 80% of the changes due to other factors, also find that CAPM can be applied on efficiency markets and huge companies.The researcher recommends applying the variables of the study on a group of large companies in the S&P 500 index, and looking for other factors that may affect the required return.

scholarly journals Stock returns and liquidity risk in Chile

2019 ◽  
Vol 17 (2) ◽  
Author(s):  
Francisco Javier Vásquez-Tejos ◽  
Hernán Pape-Larre ◽  
Juan Martín Ireta-Sánchez
Keyword(s):  
Stock Market ◽  
Emerging Markets ◽  
Regression Model ◽  
Stock Returns ◽  
Multiple Regression ◽  
Risk Measures ◽  
Liquidity Risk ◽  
Multiple Regression Model ◽  
Developed Markets ◽  
The Impact

This study analyzes the impact of liquidity risk on the return of shares in the Chilean stock market, during the period from January 2000 to July 2018. A large number of studies have focused on measuring this effect in developed markets and few in emerging markets, especially the Chilean one. To do this, we used 6 risk measures in a multiple regression model; four widely used in previous studies and two new proposed measures. We found evidence of the significance of the liquidity risk over the stock return.RESUMENEste estudio analiza el impacto del riesgo de liquidez sobre el retorno de las acciones en el mercado bursátil chileno, durante el periodo de enero de 2000 hasta julio de 2018. Gran cantidad de estudios se han centrado en medir este efecto en los mercados desarrollados y pocos en mercados emergentes, especialmente el chileno. Para ello, se utilizó un modelo de regresión múltiple 6 medidas de riesgo; cuatro utilizadas ampliamente en estudios anteriores y dos medidas nuevas propuestas. Encontramos evidencia de significancia del riesgo de liquidez sobre el retorno accionario.RESUMOEste estudo analisa o impacto do risco de liquidez no retorno das ações no mercado de ações chileno, durante o período de janeiro de 2000 a julho de 2018. Muitos estudos têm se concentrado em medir este efeito em mercados desenvolvidos e poucos nos mercados emergentes, especialmente o chileno. Para isso, utilizamos 6 medidas de risco em um modelo de regressão múltipla; quatro amplamente utilizados em estudos anteriores e duas novas medidas propostas. Encontramos evidências da significância do risco de liquidez sobre o retorno das ações.  

Impact of Exchange Rate and Jakarta Composite Index on Stock Price: A Case of Pharmaceutical Company in Indonesia

2015 ◽  
Vol 21 (4) ◽  
pp. 823-825
Author(s):  
Nino Manggala Prabha ◽  
Togar Alam Napitulu
Keyword(s):  
Exchange Rate ◽  
Pharmaceutical Industry ◽  
Stock Market ◽  
Regression Model ◽  
Pharmaceutical Company ◽  
Multiple Regression ◽  
Stock Price ◽  
Investment Decision ◽  
Composite Index ◽  
Multiple Regression Model

Stock market is growing in Indonesia and has become an important source of financing for industry in the country. This is true for pharmaceutical industry and as such, predicting the stock price in this industry is deemed very important in making investment decision. It is therefore necessary to know variables that affect stock price in this industry, in particular those that can be easily acquired and have relationship with the stock price. The objective of the study then is to find such variables. It was conjectured that exchange rate and the Jakarta Composite Index were among such variables. A linear multiple regression model was utilized to test such hypothesis. The results indicated that exchange rate positively affects stock price with a magnitude of 0.105 points. Similarly, the Jakarta Composite Index also positively affects stock price with magnitude of 0.417 points. The reliability of this model in predicting the stock price was 63%. Therefore, it is recommended to consider these variables in predicting stock price of the pharmaceutical company, hence important indicators for investors to be considered in making decision whether to buy or not to buy.

scholarly journals Reaksi Pasar Modal di Asia Tenggara Terhadap Pandemi Covid-19

2021 ◽  
Vol 23 (1) ◽  
pp. 162-172
Author(s):  
Sari Octavera ◽  
Febri Rahadi
Keyword(s):  
Stock Market ◽  
Regression Model ◽  
Composite Index ◽  
Least Square ◽  
Stock Market Index ◽  
Market Reactions ◽  
Ordinary Least Square ◽  
Market Index ◽  
Panel Data Regression ◽  
Result Show

Covid 19 is global case in almost around the world. Early April 2020, Covid 19 cases reached 1 million in a number of countries and increased significantly. This pandemic caused a major impact on economic activity, and more than 100 countries carried out a full or partial lockdown which resulted in economic disruption in many sectors including the stock market. This study investigation impact that occurs on the stock market, especially in Southeast Asia (Malaysia, Indonesia, Thailand and Singapore). Change in the composite index from the capital market are used as a proxy to measure market reactions using the OLS panel data regression model. The natural log of GDP is used as a control variabel for differences between the four capital markets. In addition, to control for the effect of different transaction days, a dummy variable is included in the regression model. The result show that changes in the number of covid 19 infections have been shown to significantly affect index changes. The market response in this regard has moved in a negative direction. Meanwhile, the measurement of the effect to the death  to covid 19 is not proven to significantly affect change in the composite stock market index. ABSTRAK Covid 19 menjadi kasus global dengan penyebaran yang sangat cepat hampir diseluruh belahan dunia. Awal April 2020 kasus Covid 19 menyentuh angka 1 juta penderita yang tersebar di sejumlah negara dan terus meningkat secara signifikan. Pandemi ini berpengaruh besar terhadap aktifitas perekonomian hampir di seluruh dunia. Puncaknya, akhir Maret 2020 lebih dari 100 negara melakukan Lockdown baik secara penuh maupun sebagian yang memberikan dampak terbatasnya aktifitas ekonomi di berbagai sektor seperti transportasi, pariwisata, perbankan, asuransi termasuk pasar modal. Penelitian ini berupaya melihat dampak yang terjadi di pasar modal khususnya di empat negara di Asia Tenggara (Malaysia, Indonesia, Thailand dan Singapura). Perubahan Indeks gabungan dari pasar modal dipergunakan sebagai proksi untuk mengukur reaksi pasar dengan menggunakan pendekatan model regresi data panel Ordinary Least Square (OLS). Untuk mengendalikan dampak yang mungkin muncul dari perbedaan yang mendasar dari keempat pasar modal tersebut, dipergunakan log natural PDB sebagai variabel kontrol. Selain itu, untuk mengontrol efek perbedaaan hari transaksi dimasukkan pula variabel dummy didalam model regresi. Hasil menunjukkan perubahan angka terinfeksi COVID-19 terbukti secara signifikan mempengaruhi perubahan indeks. Respon pasar terkait hal tersebut bergerak kearah negatif. Sementara pengukuran terhadap pengaruh angka maninggal dunia akibat COVID-19 tidak terbukti secara signifikan mempengaruhi perubahan indeks pasar saham gabungan

On the sensibility of the Pairs Trading strategy: the case of the FTS stock market index

2020 ◽  
Vol 38 (3) ◽  
Author(s):  
Ainhoa Fernández-Pérez ◽  
María de las Nieves López-García ◽  
José Pedro Ramos Requena
Keyword(s):  
Standard Deviation ◽  
Stock Market ◽  
Trading Strategy ◽  
Stock Market Index ◽  
Pairs Trading ◽  
Empirical Application ◽  
Statistical Arbitrage ◽  
Market Index ◽  
Standard Deviations ◽  
Using Data

In this paper we present a non-conventional statistical arbitrage technique based in varying the number of standard deviations used to carry the trading strategy. We will show how values of 1 and 1,2 in the standard deviation provide better results that the classic strategy of Gatev et al (2006). An empirical application is performance using data of the FST100 index during the period 2010 to June 2019.

scholarly journals Investors’ Reactions to CSR News in Family Versus Nonfamily Firms: A Study on Signal (In)credibility

2021 ◽  
pp. 104225872110104
Author(s):  
Naciye Sekerci ◽  
Jamil Jaballah ◽  
Marc van Essen ◽  
Nadine Kammerlander
Keyword(s):  
Stock Market ◽  
Event Study ◽  
Family Firms ◽  
Signaling Theory ◽  
Family Firm ◽  
Stock Market Index ◽  
Important Condition ◽  
Post Hoc Analysis ◽  
Market Index ◽  
Post Hoc

We study family firm status as an important condition in signaling theory; specifically, we propose that the market reacts more positively to positive, and more negatively to negative, CSR news (i.e., signals) from family firms than to similar news from nonfamily firms. Moreover, we propose that during recessions, the direction of these relationships reverses. Based on an event study of 1247 positive and negative changes in the CSR ratings for all firms listed on the French SFB120 stock market index (2003-2013), we find support for our hypotheses. Moreover, a post hoc analysis reveals that the relationships are contingent on whether a family CEO leads the firm.

Sign in / Sign up

Export Citation Format

Share Document