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Abstrak :
Para pelaku pasar modal di Indonesia saat ini hanya memiliki satu rujukan utama dalam bertransaksi saham-saham syariah, yaitu dengan menggunakan saham-saham Jakarta Islamic Index (JII) yang diluncurkan pertama kali pada tahun 2000. Berdasarkan data historis yang ada, dapat ditarik suatu kesimpulan bahwa portofolio saham, termasuk saham-saham yang berada dalam Jakarta Islamic Index (JII) cenderung berfluktuasi atau volatile. Volatilitas inilah yang kemudian dipahami sebagai salah satu risiko yang harus dihadapi oleh para pelaku pasar modal. Volatilitas portofolio saham syariah dapat memiliki karakteristik homoskedastik atau hetero skedastik. Volatilitas homoskedastik dapat dihitung dengan menggunakan deviasi standar sedangkan volatilitas heteroskedastik dapat diukur dengan menggunakan pendekatan Risk Metric. Pada tesis ini digunakan metode volatilitas Generalized Amoregressive Conditional Heteroscedasticity (GARCH) dan Exponential Weighted Moving Average (EWMA). Risiko ketidakpastian tentang hasil yang akan diperoleh pada masa yang akan datang, sebagai akibat dari kondisi pasar merupakan permasalahan yang sering dipertanyakan oleh para pengambil keputusan. Oleh karena itulah, perlu dilakukan penelitian empiris terhadap karakteristik penyebaran risiko tersebut. Pada penelitian ini dilakukan studi banding antara kedua model volatilitas tersebut. Studi banding ini perlu dilakukan untuk mendapatkan metode analisis volatilitas yang retail, lebih akurat untuk karakteristik portofolio saham syariah. Hasil penelitian menunjukkan bahwa karakteristik volatilitas portofolio saham syariah memiliki pergerakkan volatilitas heteroskedastik secara signifikan. Bentuk pola penyebaran volatilitas antara ARCH-GARCH dan EWMA adalah sama, akan tctapi EWMA berada di bawah grafik ARCH-GARCH. Perbandingan tingkat failure rate dari kedua model yang dipakai dalam penelitian ini menunjukkan bahwa metode ARCH-GARCH lehih akurat dibandingkan EWMA. Sedangkan perbandingan Value at Risk untuk menentukan harga portofolio saham syariah pada T+I membuktikan bahwa EWMA lebih akurat jika dibandingkan dengan metode ARCH-GARCH.

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At this moment, almost every capital market players in Indonesia has only one prime benchmark, in making transaction for Sharia' Equities; by using Jakarta Islamic Index (JII) equities launched at 2000. Based on current historical data, it is clear that equities portfolio, included Jakarta Islamic Index (JII) equity, tends to fluctuate or volatile. This volatility is known as one of risks that every capital market players must deal with. Sharia equity volatility portfolio has homoscedastic or heteroscedastic characteristics. Homoscedastic Volatility can be measured with the use of standard deviation, whereas heteroscedastic volatility can be measured with the use of Risk Metric Method. This thesis will use Generalized Autoregressive Conditional Heteroscedasticity (GARCH) and Exponential Weighted Moving Average (EWMA) volatility models. Possible uncertain risks resulted from capital market have been frequently questioned by decision makers. That is where the need of empiric research on the spread of risk characteristic arises. This research will generate a comparable study between the two of volatility models. This comparable study is inevitable in order to get accurate volatility analysis model for the characteristics of sharia' equities portfolio. Results from the research show that volatility characteristics of Sharia' equities portfolio have significant heteroscedastic fluctuation. There are identical patterns of dissemination between ARCH-GARCH (1,1) and EWMA, but EWMA is drawn below ARCH-GARCH graphic. Failure rate of equation from both models used in this research shows that ARCH-GARCH models are more accurate than EWMA. And Value at Risk comparison for determine sharia' equities portfolio price at T+ I proves that EWMA is more accurate than ARCH-GARCH.

Abstrak :
This paper explores the relationship between global wealth and happiness. We employ a bivariate generalized autoregressive conditional heteroskedasti city framework for global wealth and happiness represented, respectively, by FTSE All-World and Twitter's Daily Happiness Sentiment indexes from October 14, 2013 to December 31, 2019. We find that daily changes in happiness significantly mitigate wealth volatility, and daily wealth returns positively affect the changes in happiness sentiment. These findings reveal a spiral transmission in daily changes in happiness sentiment and global wealth volatility and returns. Metaphysically, our findings imply that the relationship between the mind and matter of finance is either materialist or monistically neutral. From alternative perspective, we construct a pseudo portfolio of global wealth and happiness indexes in which the factor of happiness plays a more important role. Thus, a concentration on happiness is preferable for the pursuit of multiple objectives, which essentially include mind and matter.

Abstrak :
Investasi merupakan kegiatan yang sudah umum dilakukan bagi banyak orang yang ingin menyimpan kekayaannya dengan harapan mendapatkan keuntungan suatu hari. Salah satu instrumen investasi yang sering digunakan adalah saham. Karena saham dikenal sebagai data keuangan yang bersifat sangat fluktuatif maka pergerakan antar waktu menyebabkan variansi error bersifat tidak konstan atau heteroskedastisitas. Sehingga dalam memodelkan return saham, dikembangkan model Multivariate Generalized Autoregressive Heteroscedatic (GARCH) yang dapat memodelkan lebih dari satu variabel secara bersamaan dan dapat digunakan pada data yang bersifat heteroskedastisitas. Model Dynamic Conditional Correlation-Multivariate Generalized Autoregressive Heteroscedatic (DCC-MGARCH) digunakan untuk mengetahui hubungan volatilitas antar saham dan pergerakannya. Adapun emiten saham yang dimodelkan adalah PT Bank Central Asia (BBCA) dan PT Bank Rakyat Indonesia (BBRI) karena terdaftar sebagai saham dengan peringkat teratas yang memiliki kapitalisasi pasar yang besar dan tercatat dalam indeks LQ45. Selanjutnya, DCC MGARCH(1,1) digunakan untuk memodelkan return dari kedua saham tersebut secara bersamaan. Selain itu signifikansi parameter Dynamic Conditional Correlation menunjukkan bahwa hanya terdapat jangka panjang spillover volatilitas antar saham BBCA dan BBRI. Hal ini mengindikasikan bahwa volatilitas return BBCA hanya berdampak signifikan terhadap persistensi jangka panjang volatilitas return BBRI tanpa berpengaruh signifikan terhadap penyesuaian jangka pendek volatilitas return BBRI. ......Investment is a common activity for many people who want to save their wealth in the hope of getting a profit one day. One investment instrument that is often used is stocks. Because stocks are known as financial data that are very volatile movements between times cause the error variance is not constant or heteroscedasticity. So in modeling stock returns, a Multivariate Generalized Autoregressive Heteroscedatic (GARCH) model was developed that can model more than one variable simultaneously and can be used on heteroscedasticity data. The Dynamic Conditional Correlation-Multivariate Generalized Autoregressive Heteroscedatic (DCC-MGARCH) model is used to determine the volatility relationship between stocks and their movements. The stock issuers modeled are PT Bank Central Asia (BBCA) and PT Bank Rakyat Indonesia (BBRI) because they are listed as top-ranked stocks that have a large market capitalization and are listed in the LQ45 index. Furthermore, DCC MGARCH(1,1) is used to model the returns of both stocks simultaneously. In addition, the significance of the Dynamic Conditional Correlation parameter shows that there is only a long-term volatility spillover between BBCA and BRI stocks. This indicates that the volatility of BBCA return has a significant impact on the long-term persistence of BBRI return volatility without having a significant effect on the short-term adjustment of BBRI return volatility.

Abstrak :
This study aims to provide a scientific contribution to the feasibility of metal backed cryptocurrencies as a medium of exchange to pay zakat. To understand the dynamics and mechanisms of metal backed cryptocurrencies, the autoregressive conditional heteroscedasticity and generalized conditional heteroscedasticity (Arch Garch) methods were used. The metal backed cryptocurrencies used for this research are Bitcoin Gold, GoldFinch, Gold Coin, Digix Gold Token, E-Dinar Coin, Gold-Money, and E-Gold. Our analysis finds that even though these are metal backed cryptocurrencies, the volatility is high. Gold-Money has a long-term volatility 67 times higher than the volatility of gold, while E-Gold has eight times the volatility of gold. As a result, due to high levels of volatility, metal backed cryptocurrencies are not suitable as a medium for zakat payment.