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Capital Asset Pricing Model (CAPM) Analysis: Technology Sector Stock Conditions Before and During the Pandemic Rizky Ramadhoni, Refindi; Matoati, Rindang; Rahmawati, Siti; Kaewlaead, Chuta; Juwita Ermawati, Wita
Jurnal Manajemen dan Organisasi Vol. 15 No. 2 (2024): Jurnal Manajemen dan Organisasi
Publisher : IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jmo.v15i2.56449

Abstract

The COVID-19 pandemic made people more active in saving, such as investing in the capital market. Stocks in the technology sector were excellent stocks because the trading volume increased by up to 7.3 times during the pandemic. The Capital Asset Pricing Model (CAPM) was a model to see the expected rate of return and aimed to assist investors in making investment decisions. CAPM used beta (β) to measure the sensitivity a stock or portfolio is to market movements. Beta indicates the tendency of an asset's return to react to fluctuations in the overall market. This study aimed to look at differences in technology sector stocks in the period before and during the pandemic using the CAPM method and paired t-test. The research using a purposive sampling method. A quantitative descriptive method was used in this study and used secondary data in the form of financial statements of technology sector companies listed on the Indonesia Stock Exchange. Based on the results of the study, seven stocks had an average negative return before the pandemic and positive returns during the pandemic. There was one efficient stock in the pre-pandemic period and six inefficient shares, and seven shares were classified as efficient shares during the pandemic. The results of the paired t-test showed that there was a significant difference between individual returns before and during the pandemic.
The Influence of Macroeconomic Variables on Non-Performing Loan (NPL) at PT Bank Mandiri (Persero) Tbk Radhianas, Binky Mohammad; Matoati, Rindang; Viana, Eka Dasra; Dewi, Farida Ratna; Kaewlaead, Chuta
GREENOMIKA Vol. 6 No. 1 (2024): GREENOMIKA
Publisher : Universitas Nahdlatul Ulama Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55732/unu.gnk.2024.06.1.6

Abstract

In recent years, Bank Mandiri's non-performing loan (NPL) ratio has been on a relatively stable decline until the COVID-19 pandemic in 2020 quarter I put pressure on the Indonesian economy. Since then, Bank Mandiri's NPL ratio has increased significantly due to the global economic recession that also occurred in Indonesia in 2020 quarter III. This study aims to analyse the effect of macroeconomic variables such as gross domestic product, inflation, interest rates, and exchange rates on non-performing loans (NPL) specifically at Bank Mandiri. This study uses secondary data in the form of historical data of related variables and Vector Error Correction Model (VECM) to estimate the dynamics of long-term and short-term relationships between variables. The results of this study indicate that macroeconomic variables such as BIRATE, INF, and LNPDB significantly affect Bank Mandiri's NPLs in the long-run dynamics, while LNKURS is statistically significant in the short-run dynamics. Keywords: Macroeconomic, Non-Peforming Loan, VECM
Optimal Portfolio Formation of SRIKEHATI Index Stocks on the Indonesia Stock Exchange (2019-2023 Period) Az-Zahra, Layalia Briliani; Viana, Eka Dasra; Kaewlaead, Chuta
GREENOMIKA Vol. 6 No. 2 (2024): GREENOMIKA
Publisher : Universitas Nahdlatul Ulama Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55732/unu.gnk.2024.06.2.9

Abstract

The stable economic conditions in Indonesia have had a positive impact, leading to an increase in the number of investors in the Indonesian capital market. One of the key instruments in this market is stocks. The aim of this research is to create an optimal portfolio that can be recommended to investors. The study utilizes the CAPM and Markowitz models and involves the use of secondary data. The research sample selection process makes use of non-probability sampling techniques, specifically purposive sampling. This research focuses on the SRI KEHATI Index for the period from January 2019 to December 2023. Using the CAPM method, 7 efficient stocks have been identified, namely BBCA, BBNI, BBRI, BMRI, JSMR, KLBF, and UNTR. The combination of 7 stocks using the Markowitz model forms two preferences. The first preference generates an allocation proportion with a formula that results in an annual portfolio expected return of 40.55% and an annual portfolio risk of 30.33%. The second preference generates an allocation proportion with a solver that results in an annual portfolio expected return of 46.79% and an annual portfolio risk of 32.91%.
Optimal Portfolio Formation of SRIKEHATI Index Stocks on the Indonesia Stock Exchange (2019-2023 Period) Az-Zahra, Layalia Briliani; Viana, Eka Dasra; Kaewlaead, Chuta
GREENOMIKA Vol. 6 No. 2 (2024): GREENOMIKA
Publisher : Universitas Nahdlatul Ulama Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55732/unu.gnk.2024.06.2.9

Abstract

The stable economic conditions in Indonesia have had a positive impact, leading to an increase in the number of investors in the Indonesian capital market. One of the key instruments in this market is stocks. The aim of this research is to create an optimal portfolio that can be recommended to investors. The study utilizes the CAPM and Markowitz models and involves the use of secondary data. The research sample selection process makes use of non-probability sampling techniques, specifically purposive sampling. This research focuses on the SRI KEHATI Index for the period from January 2019 to December 2023. Using the CAPM method, 7 efficient stocks have been identified, namely BBCA, BBNI, BBRI, BMRI, JSMR, KLBF, and UNTR. The combination of 7 stocks using the Markowitz model forms two preferences. The first preference generates an allocation proportion with a formula that results in an annual portfolio expected return of 40.55% and an annual portfolio risk of 30.33%. The second preference generates an allocation proportion with a solver that results in an annual portfolio expected return of 46.79% and an annual portfolio risk of 32.91%.
The Influence of Macroeconomic Variables on Non-Performing Loan (NPL) at PT Bank Mandiri (Persero) Tbk Radhianas, Binky Mohammad; Matoati, Rindang; Viana, Eka Dasra; Dewi, Farida Ratna; Kaewlaead, Chuta
GREENOMIKA Vol. 6 No. 1 (2024): GREENOMIKA
Publisher : Universitas Nahdlatul Ulama Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55732/unu.gnk.2024.06.1.6

Abstract

In recent years, Bank Mandiri's non-performing loan (NPL) ratio has been on a relatively stable decline until the COVID-19 pandemic in 2020 quarter I put pressure on the Indonesian economy. Since then, Bank Mandiri's NPL ratio has increased significantly due to the global economic recession that also occurred in Indonesia in 2020 quarter III. This study aims to analyse the effect of macroeconomic variables such as gross domestic product, inflation, interest rates, and exchange rates on non-performing loans (NPL) specifically at Bank Mandiri. This study uses secondary data in the form of historical data of related variables and Vector Error Correction Model (VECM) to estimate the dynamics of long-term and short-term relationships between variables. The results of this study indicate that macroeconomic variables such as BIRATE, INF, and LNPDB significantly affect Bank Mandiri's NPLs in the long-run dynamics, while LNKURS is statistically significant in the short-run dynamics. Keywords: Macroeconomic, Non-Peforming Loan, VECM