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"Penelitian ini menguji secara empiris perubahan dynamic linkages variabel yield SBN-Domestik, IHSG terhadap shocks yield US Treasury bond, SP500 dan IDR/USD. Analisis menggunakan VECM. Uji IRF, VD dan Granger causality membuktikan bahwa dalam jangka panjang, periode pandemic-covid19 variabel yield SBN-domestik mengalami perubahan hubungan dinamis yang signifikan terhadap semua shock, namun perubahan terbesar terdapat pada yield SBN3Y dan SBN5Y. Hal ini disebabkan karena pada periode pendemic-covid19, SBN3Y dan SBN5Y sebagai SBN tenor pendek dan menengah dianggap lebih berisiko. Perubahan IHSG signifikan terhadap shockSP500 periode pandmeic-covid19. Uji variance decomposition periode pandemic-covid19 membuktikan dalam jangka panjang SP500 mempunyai kontribusi varians tertinggi.

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This study empirically examines the dynamic linkages among yield SBN-Domestic and IDX-Composite to the shocks of US Treasury bonds, SP500 and IDR/USD. Analysis applying VECM. IRF, VD and Granger causality tests prove that in the long-run, during the pandemic-covid19 period, the SBN-Domestic experienced a significant change to all shocks, but the biggest changes were on SBN3Y and SBN5Y. This was due to the fact that during the Covid-19 pandemic, SBN3Y and SBN5Y were considered high risk. IDX-Composite was significantly changes for SP500 during pandemic-covid19 period. Variance decomposition test proved that in the long run, SP500 has the highest variance contribution."

"Investor membentuk ekspektasi mereka dengan bereaksi terhadap informasi baru. Seiring berkembangnya teknologi, media sosial memainkan peran yang semakin penting dalam pengambilan keputusan investor dengan menyediakan informasi bervolume yang besar dan cepat. Studi sebelumnya mencatat hubungan antara sentiment di media sosial dan volatilitas pasar saham. Oleh karena itu, dalam banyak penelitian, Twitter banyak digunakan sebagai sumber sentimen publik untuk memprediksi pasar saham. Selanjutnya, karena variabel makroekonomi secara definitif mempengaruhi ekspektasi investor dan harga saham, penelitian ini bertujuan untuk memprediksi pergerakan harian IHSG dengan menggunakan sentimen Twitter pada ekonomi Indonesia dan variable makroekonomi. Hasil penelitian kami menunjukkan bahwa sentimen Twitter terhadap perekonomian Indonesia berkorelasi positif terhadap pergerakan IHSG walau lemah. Lalu, kami menggunakan algoritma Multilayer Perceptron untuk memprediksi pergerakan IHSG yang mampu mencapai akurasi 63,11%. Angka tersebut 8,19% lebih tinggi daripada model yang hanya menggunakan variabel makroekonomi.

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Investors form their expectations by reacting to new information. As technology advances, social media plays an increasingly important role in investor decision-making by providing large volumes of information quickly. Previous studies have noted a relationship between sentiment on social media and stock market volatility. Therefore, in many studies, Twitter is widely used as a source of public sentiment to predict the stock market. Furthermore, since macroeconomic variables definitively affect investor expectations and stock prices, this study aims to predict the daily movement of the JCI using Twitter sentiment on the Indonesian economy and macroeconomic variables. Our results show that Twitter sentiment on the Indonesian economy is positively correlated with the movement of the JCI, although weak. Then, we use the Multilayer Perceptron algorithm to predict the movement of the JCI which is able to achieve an accuracy of 63.11%. This figure is 8.19% higher than the model that only uses macroeconomic variables."