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Ekspektasi Maksimum Percentage Drawdown pada data Saham PT. Mayora Tbk dengan simulasi Monte Carlo

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  • Additional Information
    • Publication Information:
      UIN Imam Bonjol Padang
    • Publication Date:
      2021
    • Abstract:
      A drawdown is a tool for defining trading strategies for commodities, stocks, and investments. This analysis is one way of monitoring the decline in asset value over a certain period of time. This journal will discuss PT.MayoraTbk stock trading strategy. By analyzing the observed drawdown in the specified time period. The drawdown analysis here uses the feedback control on PT.MayoraTbk stock trading is assumed to follow the geometric Brownian motion. The data obtained is tested whether the data meets Brown's motion assumptions. Then the maximum drawdown expectation is determined at the selected time interval. An estimate is carried out for the maximum expected drawdown percentage of the share value. To test the validity of the estimation results, a Monte Carlo simulation is carried out. Monte Carlo simulation with the term Sampling Simulation or Monte Carlo Sampling Technique. This simulation sampling illustrates the possible use of sample data using the Monte Carlo method and also the distribution can be known or estimated. This simulation uses existing data (historical data) that is actually used in a simulation that includes inventory or sampling with a known and determined probability distribution, so this Monte Carlo simulation can be used. The basic idea of this Monte Carlo simulation is to generate or generate a value to form a model of the variables and study it.
    • File Description:
      application/pdf
    • Relation:
      https://ejournal.uinib.ac.id/jurnal/index.php/jostech/article/view/2440/pdf_1; https://ejournal.uinib.ac.id/jurnal/index.php/jostech/article/view/2440
    • Accession Number:
      10.15548/jostech.v1i1.2440
    • Online Access:
      https://doi.org/10.15548/jostech.v1i1.2440
      https://ejournal.uinib.ac.id/jurnal/index.php/jostech/article/view/2440
    • Rights:
      Copyright (c) 2021 JOSTECH: Journal of Science and Technology ; https://creativecommons.org/licenses/by-nc-sa/4.0
    • Accession Number:
      edsbas.6CB50DB