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Journal : Inferensi

Implementing Markov Switching Regression Using Best Subset Approach For BSI Stock Price Prediction Analysis Nurdiansyah, Denny; Ma'ady, Mochamad Nizar Palefi; Wijayanti, Lulud; Novitasari, Diah Ayu; Rohmawati, Siti
Inferensi Vol 8, No 2 (2025)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v8i2.21030

Abstract

Stocks are evidence of ownership of the capital or funds of a company or institution and are represented by a document that includes the par value, the company name, and the rights and obligations described for each owner. Since so many factors affect the rise and fall of stock prices, investors should pay attention to the factors that influence the rise and fall of stock prices to avoid incurring losses or profits when buying and selling stocks. The rise and fall of stock prices can be analyzed with Markov switching regression by trying all possible placements of factors to get the best subset. Public holdings will continue to increase due to nation-building and Sharia Bank Indonesia (BRIS) stock price appreciation. This study aims to determine the impact of increases and decreases in the closing price of BSI stock. The modeling used in this study is Markov switching regression using the best subset approach. The data used in this study are secondary in the form of daily data for the closing price of Bank Syariah Indonesia shares, Inflation, BI Rate, Selling Exchange Rate, Money Supply, and Gross Domestic Product (GDP). Data are obtained from the official BPS website. The results of this study show that Markov switching regression modeling can identify the feasibility of regimes as "bull" and "bear" periods. State 2 indicates an uptrend or "bullish," and state 1 indicates a downtrend or "bearish." The best subset approach obtains the best model with the lowest SSE value. The study concluded that the statistical modeling results of  BSI stock's closing prices during "bull" and "bear" periods provide significant predictors: BI Rate, Selling Exchange Rate, and Money Supply.
Co-Authors Achmad Muzakki Ahmad Andrean Syah Kusnuris Aisyah Putri Amni Ramdhanti Alfonsus Antero Arnayusrendito Alifiansyah Arrizqy Hidayat Allan Putra Pratama Andrew, Dennis Michael Anita Hakim Nasution Arip Ramadan Aris Kusumawati Aris Kusumawati Artwodini Muqtadiroh, Feby Azizah, Faradilla Nur Berlian Rahmy Lidiawaty Chandra, Salsabila Ramadhani Chuan-Kai Yang Cornelia Angela Caezaria Denny Nurdiansyah Deyastusesa, Junanda Dharmawan, Farhan Aditya Eka Sari Oktarina Elang Dewa Samudra Everald Anthony Arther Faisal Rizal Rahman Farrel Ardan Firiansyah Febryan, Rayhan Alief Feby Artwodini Muqtadiroh Ginza Maulana Putra Habib Husni Mubarok Mubarok Haryanti, Desyka Widya Hatma Suryotrisongko Ita Aristia Sa'ida Iwan Vanany Kartini, Alif Yuanita Liana, Serli April Maharani Citra Adi Ratna Meilanitasari, Prita Mohammad Hamim Zajuli Al Faroby Mohammad Yanuar Hariyawan Muhammad Ilham Alhari Mutiani, Tia Nafis Difaudin Nisa Isrofi Novitasari, Diah Ayu Pitoyo, Salsabilla Putri Pratama, Arya Yudha Purnama Anaking Purnama Anaking Puspita Rini, Hafida Rahim, Ainatul Fathiyah Abdul Rahmawati Hasan , Dyah Rahul Fahmi Satria Ramadhani, Cisa Valentino Cahya Renny Pradina Kusumawardani Rizal Firmansyah, Muhammad Rizal Rahman, Faisal Rizaldy, Denny Daffa Rizqy Athiyya Nafi’atus Sa’idah Rohmawati, Siti Rokhmatul Insani Rosidah, Nur Azizah Rosyid Abdillah Sanjaya, I Made Wisnu Adi Saputra, Ricky Adam Satria, Rahul Fahmi Serafina, Nauli Khalila Sonaya Devi Anja Amelia Sri Hidayati Sukmawaty, Yuana Surya Huditara , Kevin Tabina Shafa Nabila Syahda Tita Ayu Rospricilia Ully Asfari Utomo, Muchammad Chandra Cahyo Widyaiswari, Rahma Putri Wijayanti, Lulud Yohanes Setiawan Yuliana, Ummi Agustin Zakariya, Naufal