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All Journal Jambura Journal of Mathematics Jurnal Akuntansi dan Keuangan
Syifa Fauzia
IPB University
Economics, Econometrics & Finance Mathematics

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Perbandingan Metode KNN, Naive Bayes, dan Regresi Logistik Binomial dalam Pengklasifikasian Status Ekonomi Negara N. K. Kutha Ardana; Ruhiyat Ruhiyat; Nurfatimah Amany; Teofilus Kevin Irawan; Raymond Raymond; Rizalius Karunia; Syifa Fauzia
Jambura Journal of Mathematics Vol 5, No 2: August 2023
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34312/jjom.v5i2.21103

Abstract

The classification of a country's economic status as developed or developing often involves factors such as life expectancy and its underlying variables. This research aims to compare the performance of three machine learning algorithms, namely KNN (K-Nearest Neighbors), naive Bayes, and binomial logistic regression, in classifying the economic status of countries as developed or developing. The data used in this study is "Life Expectancy (WHO) Fixed," obtained from the Kaggle website. The first statistical analysis conducted was Principal Component Analysis (PCA) using 16 predictor variables. PCA resulted in three principal components capable of explaining 71.41% of the variance, which were subsequently used in the KNN, naive Bayes, and binomial logistic regression methods. The analysis results from the KNN, naive Bayes, and binomial logistic regression methods produced F1-scores of 100\%, 98.19%, and 97.36%, respectively.
Stock Hedging Using Strangle Strategy on Vanilla Options and Capped Options Donny Citra Lesmana; David Vijanarco Martal; Unika Nabila; Syifa Fauzia; Raymond Raymond; Zidni Kamal Hasan; M Ridwan Aprizky
Jurnal Akuntansi dan Keuangan Vol. 26 No. 1 (2024): MAY 2024
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.9744/jak.26.1.47-55

Abstract

The financial market often experiences unexpected fluctuations that can impact stock values. Therefore, investors require hedging strategies to protect their investment values from unwanted price fluctuations. This study compares the hedging results using the strangle strategy on Vanilla options and Capped options on Micron Technology, Inc. (MU) stock. The methods used are Monte Carlo simulation and Black Scholes Merton to calculate the option prices. The research results indicate that the strangle strategy on Vanilla options has unlimited maximum profit potential, whereas on Capped options, the profit is capped above. However, the potential maximum loss on Capped options is lower than that on Vanilla options. Therefore, Capped options are preferred for hedging the MU stock. The research yields significant practical and theoretical benefits. Practically, it offers investors insights into more effective hedging choices for risk management and profit potential in the stock market. Opting for capped options allows investors to control risk better while preserving profit potential. Theoretically, the study enhances our understanding of cost efficiency and risk profiles across various options strategies, making a vital contribution to financial literature.
Co-Authors David Vijanarco Martal Donny Citra Lesmana M Ridwan Aprizky N. K. Kutha Ardana Nurfatimah Amany Raymond Raymond Rizalius Karunia Ruhiyat Teofilus Kevin Irawan Unika Nabila Zidni, Hasan