This study, using more than 10 years of monthly time-series data and controlling for the non-crisis as well as crisis period, investigates the existence of Fama-French three factors and liquidity to the excess return of stock portfolio in Indonesia. The results show that market beta is consistently positive and significant in each portfolios, when sorted by size-illiquidity and book-to-market (BM)-illiquidity. SMB could explain ILLIQ and vice versa, and in general the hypothesis in this research are accepted, also there are consistency in SMB when sorted by size-illiquidity and also BM-illiquidity which are two out of six are not significant. Subprime mortgage crisis statistically has no effect in all portfolios. The results supported Fama and French (1992, 1993) and the results of Lam and Tam (2011).

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Penelitian ini bertujuan untuk menghasilkan LKPD Berbasis Discovery Learning Berbantuan Software Tracker untuk meningkatkan pemahaman konsep peserta didik kelas X di SMA Negeri 2 Babat Supat yang valid, praktis, dan memiliki efek potensial. Peneliti ini menggunakan metode Reseach and Development (R&D) model ADDIE. Pengumpulan data pada peneliti ini menggunakan validasi, kepraktisan, dan efek potensial. Subjek penelitian ini adalah peserta didik kelas X MIPA 1 di SMA Negeri 2 Babat Supat. Berdasarkan analisis data dinyatakan valid, praktis, dan memiliki efek terhadap peserta didik adapun hasil 1) expert review diperoleh nilai rata-rata dari ketiga ahli sebesar 96% yang dikategorikan sangat valid; 2) one to one memperoleh nilai rata-rata 92% yang dikategorikan sangat praktis; 3) small group memperoleh nilai rata-rata 96% dikategorikan sangat menarik; 4) field test memperoleh nila rata-rata pre test sebesar 24% dan post test 84% dengan nilai rata-rata N-Gain sebesar 0,74 dengan kategori sangat tinggi dan dapat disimpulkan bahwa produk yang dikembangakan peneliti dapat meningkatkan pemahaman konsep peserta didik.

PurposeThis research aims to determine the factors that affected Bitcoin price return in the period before and during the COVID-19 pandemic.Design/methodology/approachThe independent variables used in this study are hashrate, transaction volume, social media and some macroeconomics variables. The data are processed using the vector error correction model (VECM) to determine the short-term and long-term relationships between variables.FindingsThe research shows that (1) Twitter and Gold significantly affected Bitcoin in the short term before the COVID-19 pandemic; (2) hashrate, transaction volume, Twitter and the financial stress index had a significant effect on Bitcoin in the long term before the COVID-19 pandemic; (3) the volatility index had a significant effect on Bitcoin in the short term during the COVID-19 pandemic; and (4) hashrate, transaction volume, Twitter and CHF/USD had a significant effect on Bitcoin in the long term during the COVID-19 pandemic.Research limitations/implicationsThis research provides explanation about factors affecting Bitcoin so investors and regulators can pay more attention and prepare for the potential risks as well as to get a good understanding of market conditions for greater crypto adoption in the future.Originality/valueThe novelty in this study is the various factors driving the Bitcoin price were analyzed before and during the COVID-19 pandemic including the social media, as sentiment, interestingly, is being a predictive power for Bitcoin price return.