scholarly journals Stock price analysis based on the research of multiple linear regression macroeconomic variables

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Fei Wang ◽  
Wanling Chen ◽  
Bahjat Fakieh ◽  
Mohammed Alaa Alhamami
Keyword(s):  
Linear Regression ◽  
Interest Rates ◽  
Multiple Linear Regression ◽  
Stock Price ◽  
Arma Model ◽  
Value Added ◽  
Multiple Linear Regression Model ◽  
Price Analysis ◽  
High Degree ◽  
Statistical Analysis Software

Abstract The article uses SPSS statistical analysis software to establish a multiple linear regression model of short-term stock price changes of domestic agricultural listed companies. The article uses a stable time series based on the ARMA model for stable agricultural value-added, fiscal expenditure and market interest rates. The regression method is used to study its impact on the stock price index. Compared with the existing stock forecasting methods, this method has simple data collection and no specific requirements for data selection, and the prediction results have a high degree of fit. Therefore, this method is suitable for most stocks.

scholarly journals Pertumbuhan Arus Kas, Pertumbuhan Laba, Inflasi, Suku Bunga, Nilai Kurs dan Return Saham pada Badan Usaha Milik Negara di Bursa Efek Indonesia

2014 ◽  
Vol 1 (02) ◽  
pp. 171-186
Author(s):  
Moh. Abror ◽  
Dadang Sadeli
Keyword(s):  
Linear Regression ◽  
Exchange Rates ◽  
Interest Rates ◽  
Multiple Linear Regression ◽  
Stock Returns ◽  
Sampling Method ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Model ◽  
Earning Growth ◽  
Purposive Sampling

ABSTRACT The study aims to analyze the effect of cashflow growth, earning growth, inflation, interest rates and exchange rates to stock return BUMN. The sample selection is done by using purposive sampling method. Acquired a total sample of 15 companies of 19 state-owned companies listed in Indonesia Stock Exchange during the period 2009 - 2012. This study used multiple linear regression analysis techniques to examine the effect of the independent variable on the dependent variable. Based on the results of the study, there were no variables that deviated of the classical assumption, it indicates that the available data are qualified to use a multiple linear regression model. The results showed that the growth in cash flow, earnings growth, interest rates and exchange rates had no significant effect on stock returns. The study able to show that the interest rate significant positive effect on stock returns. ABSTRAK Penelitian bertujuan untuk menganalisis pengaruh pertumbuhan arus kas, pertumbuhan laba, inflasi, suku bunga dan nilai kurs terhadap return saham BUMN. Pemilihan sampel dilakukan dengan menggunakan purposive sampling method. Diperoleh jumlah sampel sebanyak 15 perusahaan dari 19 perusahaan BUMN yang terdaftar di Bursa Efek Indonesia selama periode 2009 – 2012. Penelitian ini menggunakan teknik analisa regresi linear berganda untuk menguji pengaruh variable independen terhadap variable dependen. Berdasarkan hasil penelitian, tidak ditemukan variabel yang menyimpang dari asumsi klasik, hal ini menunjukkan bahwa data yang tersedia telah memenuhi syarat untuk menggunakan model persamaan regresi linier berganda. Hasil penelitian menunjukkan bahwa pertumbuhan arus kas, pertumbuhan laba, suku bunga dan nilai kurs tidak berpengaruh signifikan terhadap return saham. Penelitian berhasil membuktikan bahwa suku bunga berpengaruh positif signifikan terhadap return saham BUMN. JEL Classification: G14, G30

scholarly journals Pertumbuhan Arus Kas, Pertumbuhan Laba, Inflasi, Suku Bunga, Nilai Kurs dan Return Saham pada Badan Usaha Milik Negara di Bursa Efek Indonesia

2014 ◽  
Vol 1 (02) ◽  
pp. 171-186
Author(s):  
Moh. Abror ◽  
Dadang Sadeli
Keyword(s):  
Linear Regression ◽  
Exchange Rates ◽  
Interest Rates ◽  
Multiple Linear Regression ◽  
Stock Returns ◽  
Sampling Method ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Model ◽  
Earning Growth ◽  
Purposive Sampling

ABSTRACT The study aims to analyze the effect of cashflow growth, earning growth, inflation, interest rates and exchange rates to stock return BUMN. The sample selection is done by using purposive sampling method. Acquired a total sample of 15 companies of 19 state-owned companies listed in Indonesia Stock Exchange during the period 2009 - 2012. This study used multiple linear regression analysis techniques to examine the effect of the independent variable on the dependent variable. Based on the results of the study, there were no variables that deviated of the classical assumption, it indicates that the available data are qualified to use a multiple linear regression model. The results showed that the growth in cash flow, earnings growth, interest rates and exchange rates had no significant effect on stock returns. The study able to show that the interest rate significant positive effect on stock returns. ABSTRAK Penelitian bertujuan untuk menganalisis pengaruh pertumbuhan arus kas, pertumbuhan laba, inflasi, suku bunga dan nilai kurs terhadap return saham BUMN. Pemilihan sampel dilakukan dengan menggunakan purposive sampling method. Diperoleh jumlah sampel sebanyak 15 perusahaan dari 19 perusahaan BUMN yang terdaftar di Bursa Efek Indonesia selama periode 2009 – 2012. Penelitian ini menggunakan teknik analisa regresi linear berganda untuk menguji pengaruh variable independen terhadap variable dependen. Berdasarkan hasil penelitian, tidak ditemukan variabel yang menyimpang dari asumsi klasik, hal ini menunjukkan bahwa data yang tersedia telah memenuhi syarat untuk menggunakan model persamaan regresi linier berganda. Hasil penelitian menunjukkan bahwa pertumbuhan arus kas, pertumbuhan laba, suku bunga dan nilai kurs tidak berpengaruh signifikan terhadap return saham. Penelitian berhasil membuktikan bahwa suku bunga berpengaruh positif signifikan terhadap return saham BUMN. JEL Classification: G14, G30

ANALISIS PENGARUH INFLASI, KURS DAN IHSG TERHADAP RETURN REKSA DANA SAHAM PT NIKKO SECURITIES INDONESIA PERIODE 2014-2017

2019 ◽  
Vol 2 (2) ◽  
pp. 103
Author(s):  
Muhammad Rois Rois ◽  
Manarotul Fatati Fatati ◽  
Winda Ihda Magfiroh
Keyword(s):  
Regression Analysis ◽  
Exchange Rate ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Stock Price ◽  
Price Index ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Equity Fund ◽  
Stock Price Index

This study aims to determine the effect of Inflation, Exchange Rate and Composite Stock Price Index (IHSG) to Return of PT Nikko Securities Indonesia Stock Fund period 2014-2017. The study used secondary data obtained through documentation in the form of PT Nikko Securities Indonesia Monthly Net Asset (NAB) report. Data analysis is used with quantitative analysis, multiple linear regression analysis using eviews 9. Population and sample in this research are PT Nikko Securities Indonesia. The result of multiple linear regression analysis was the coefficient of determination (R2) showed the result of 0.123819 or 12%. This means that the Inflation, Exchange Rate and Composite Stock Price Index (IHSG) variables can influence the return of PT Nikko Securities Indonesia's equity fund of 12% and 88% is influenced by other variables. Based on the result of the research, the variables of inflation and exchange rate have a negative and significant effect toward the return of PT Nikko Securities Indonesia's equity fund. While the variable of Composite Stock Price Index (IHSG) has a negative but not significant effect toward Return of Equity Fund of PT Nikko Securities Indonesia

An Enhanced Multiple Linear Regression Model for Seasonal Rainfall Prediction

2020 ◽  
Vol 10 (4) ◽  
pp. 473-483
Author(s):  
Pundra Chandra Shaker Reddy ◽  
Alladi Sureshbabu
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Multiple Linear Regression ◽  
Linear Regression Model ◽  
Weather Prediction ◽  
Big Data Analytics ◽  
Multiple Linear Regression Model ◽  
Seasonal Rainfall ◽  
Climate Data ◽  
Rainfall Forecasting

Aims & Background: India is a country which has exemplary climate circumstances comprising of different seasons and topographical conditions like high temperatures, cold atmosphere, and drought, heavy rainfall seasonal wise. These utmost varieties in climate make us exact weather prediction is a challenging task. Majority people of the country depend on agriculture. Farmers require climate information to decide the planting. Weather prediction turns into an orientation in farming sector to deciding the start of the planting season and furthermore quality and amount of their harvesting. One of the variables are influencing agriculture is rainfall. Objectives & Methods: The main goal of this project is early and proper rainfall forecasting, that helpful to people who live in regions which are inclined natural calamities such as floods and it helps agriculturists for decision making in their crop and water management using big data analytics which produces high in terms of profit and production for farmers. In this project, we proposed an advanced automated framework called Enhanced Multiple Linear Regression Model (EMLRM) with MapReduce algorithm and Hadoop file system. We used climate data from IMD (Indian Metrological Department, Hyderabad) in 1901 to 2002 period. Results: Our experimental outcomes demonstrate that the proposed model forecasting the rainfall with better accuracy compared with other existing models. Conclusion: The results of the analysis will help the farmers to adopt effective modeling approach by anticipating long-term seasonal rainfall.

Predictive Factors for Hamstring Autograft Diameter in Anterior Cruciate Ligament Reconstruction

2019 ◽  
Author(s):  
Willem M.P. Heijboer ◽  
Mathijs A.M. Suijkerbuijk ◽  
Belle L. van Meer ◽  
Eric W.P. Bakker ◽  
Duncan E. Meuffels
Keyword(s):  
Anterior Cruciate Ligament ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Acl Reconstruction ◽  
Cruciate Ligament ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Model ◽  
Gracilis Tendon ◽  
Thigh Circumference ◽  
Anterior Cruciate

AbstractMultiple studies found hamstring tendon (HT) autograft diameter to be a risk factor for anterior cruciate ligament (ACL) reconstruction failure. This study aimed to determine which preoperative measurements are associated with HT autograft diameter in ACL reconstruction by directly comparing patient characteristics and cross-sectional area (CSA) measurement of the semitendinosus and gracilis tendon on magnetic resonance imaging (MRI). Fifty-three patients with a primary ACL reconstruction with a four-stranded HT autograft were included in this study. Preoperatively we recorded length, weight, thigh circumference, gender, age, preinjury Tegner activity score, and CSA of the semitendinosus and gracilis tendon on MRI. Total CSA on MRI, weight, height, gender, and thigh circumference were all significantly correlated with HT autograft diameter (p < 0.05). A multiple linear regression model with CSA measurement of the HTs on MRI, weight, and height showed the most explained variance of HT autograft diameter (adjusted R 2 = 44%). A regression equation was derived for an estimation of the expected intraoperative HT autograft diameter: 1.2508 + 0.0400 × total CSA (mm2) + 0.0100 × weight (kg) + 0.0296 × length (cm). The Bland and Altman analysis indicated a 95% limit of agreement of ± 1.14 mm and an error correlation of r = 0.47. Smaller CSA of the semitendinosus and gracilis tendon on MRI, shorter stature, lower weight, smaller thigh circumference, and female gender are associated with a smaller four-stranded HT autograft diameter in ACL reconstruction. Multiple linear regression analysis indicated that the combination of MRI CSA measurement, weight, and height is the strongest predictor.

scholarly journals Magnetization Transfer Ratio of Peripheral Nerve and Skeletal Muscle

2021 ◽  
Author(s):  
Olivia Fösleitner ◽  
Véronique Schwehr ◽  
Tim Godel ◽  
Fabian Preisner ◽  
Philipp Bäumer ◽  
...  
Keyword(s):  
Skeletal Muscle ◽  
Body Weight ◽  
Sciatic Nerve ◽  
Linear Regression ◽  
Peripheral Nerve ◽  
Regression Model ◽  
Multiple Linear Regression ◽  
Linear Regression Model ◽  
Magnetization Transfer ◽  
Multiple Linear Regression Model

Abstract Purpose To assess the correlation of peripheral nerve and skeletal muscle magnetization transfer ratio (MTR) with demographic variables. Methods In this study 59 healthy adults evenly distributed across 6 decades (mean age 50.5 years ±17.1, 29 women) underwent magnetization transfer imaging and high-resolution T2-weighted imaging of the sciatic nerve at 3 T. Mean sciatic nerve MTR as well as MTR of biceps femoris and vastus lateralis muscles were calculated based on manual segmentation on six representative slices. Correlations of MTR with age, body height, body weight, and body mass index (BMI) were expressed by Pearson coefficients. Best predictors for nerve and muscle MTR were determined using a multiple linear regression model with forward variable selection and fivefold cross-validation. Results Sciatic nerve MTR showed significant negative correlations with age (r = −0.47, p < 0.001), BMI (r = −0.44, p < 0.001), and body weight (r = −0.36, p = 0.006) but not with body height (p = 0.55). The multiple linear regression model determined age and BMI as best predictors for nerve MTR (R2 = 0.40). The MTR values were different between nerve and muscle tissue (p < 0.0001), but similar between muscles. Muscle MTR was associated with BMI (r = −0.46, p < 0.001 and r = −0.40, p = 0.002) and body weight (r = −0.36, p = 0.005 and r = −0.28, p = 0.035). The BMI was selected as best predictor for mean muscle MTR in the multiple linear regression model (R2 = 0.26). Conclusion Peripheral nerve MTR decreases with higher age and BMI. Studies that assess peripheral nerve MTR should consider age and BMI effects. Skeletal muscle MTR is primarily associated with BMI but overall less dependent on demographic variables.

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