<mets:mets OBJID="eprint_78689" LABEL="Eprints Item" xsi:schemaLocation="http://www.loc.gov/METS/ http://www.loc.gov/standards/mets/mets.xsd http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-3.xsd" xmlns:mets="http://www.loc.gov/METS/" xmlns:mods="http://www.loc.gov/mods/v3" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><mets:metsHdr CREATEDATE="2026-10-08T17:56:40Z"><mets:agent ROLE="CUSTODIAN" TYPE="ORGANIZATION"><mets:name>Institutional Repository UIN Sunan Kalijaga Yogyakarta</mets:name></mets:agent></mets:metsHdr><mets:dmdSec ID="DMD_eprint_78689_mods"><mets:mdWrap MDTYPE="MODS"><mets:xmlData><mods:titleInfo><mods:title>ANALISIS RISIKO PORTOFOLIO OPTIMAL BERBASIS SINGLE INDEX MODEL MENGGUNAKAN VALUE AT RISK (VAR) DENGAN METODE HISTORICAL SIMULATION (STUDI KASUS: SAHAM IDX30 PERIODE JANUARI 2025 – DESEMBER 2025)</mods:title></mods:titleInfo><mods:name type="personal"><mods:namePart type="given">NIM.: 22106010061</mods:namePart><mods:namePart type="family">Dinda Kusuma Sari</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:abstract>A portfolio is a collection of assets used to diversify and manage&#13;
investment risk. An optimal portfolio is needed to obtain a combination of&#13;
stocks that maximizes returns while minimizing risk. This study aims to analyze&#13;
optimal portfolio formation using the Single Index Model (SIM), determine stock&#13;
investment weights, and measure portfolio risk using Value at Risk (VaR) with the&#13;
Historical Simulation approach. The data consist of daily closing prices of IDX30&#13;
stocks and the IHSG from January to December 2025. Stocks were initially selected&#13;
based on an expected return greater than the risk-free rate (E(Ri) &gt; Rf ), followed&#13;
by selecting stocks with Excess Return to Beta (ERB) greater than or equal to the&#13;
cut-off point (ERB ≥ C∗). The results show that eight stocks were selected to&#13;
form the optimal portfolio namely BRPT, ANTM, ASII, UNVR, INCO, MDKA,&#13;
MBMA, and MEDC. The two largest investment weights were BRPT at 38.59%,&#13;
with an expected return of 0.6174%, and ANTM at 30.98%, with an expected return&#13;
of 0.3595%. SIM simplifies parameter estimation while considering market factors,&#13;
but is limited to a single market factor. Historical Simulation requires no specific&#13;
distributional assumption but depends on historical data quality. VaR increases with&#13;
the investment horizon due to the square-root-of-time rule. At a 95% confidence&#13;
level, one-day VaR was Rp3,184,844 and was valid based on the Kupiec POF test.</mods:abstract><mods:classification authority="lcc">510 Mathematics (Matematika)</mods:classification><mods:originInfo><mods:dateIssued encoding="iso8061">2026-08-03</mods:dateIssued></mods:originInfo><mods:originInfo><mods:publisher>UIN SUNAN KALIJAGA YOGYAKARTA;FAKULTAS SAINS DAN TEKNOLOGI</mods:publisher></mods:originInfo><mods:genre>Thesis</mods:genre></mets:xmlData></mets:mdWrap></mets:dmdSec><mets:amdSec ID="TMD_eprint_78689"><mets:rightsMD ID="rights_eprint_78689_mods"><mets:mdWrap MDTYPE="MODS"><mets:xmlData><mods:useAndReproduction>
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