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All Journal Epsilon: Jurnal Matematika Murni dan Terapan Science and Technology Indonesia
Putri, Endah R.M.
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Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Decision Sciences, Operations Research & Management Environmental Science Materials Science & Nanotechnology Physics Transportation

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MODEL INVESTASI POLIS ASURANSI JIWA BERBONUS TIPE DWIGUNA DENGAN AMERICAN PUT OPTION Lissa, Hermei; Putri, Endah R.M.
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN (EPSILON: JOURNAL OF PURE AND APPLIED MATHEMATICS) Vol 18, No 1 (2024)
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/epsilon.v18i1.12625

Abstract

Insurance is a form of protection against the concept of risk transfer that may occur from an uncertain event. One type of insurance is life insurance. With the changing times, life insurance launched innovative products, one of which is endowment life insurance. Endowment life insurance is a type of life insurance that provides compensation benefits if the policy holder dies during the coverage period, as well as providing cash value and bonuses if the policy holder is still alive until the end of the period. This study aims to determine the fair price of insurance policies and the price of bonus life insurance policies. Determination of the value of the American put option with the binomial method using a numerical approach, the formulation of the portfolio model includes determining the model of the unit price with Geometric Brownian Motion, solving using Black-Scholes, determining the structure of the bonus life insurance policy with the formulation of a single premium payment, bonus rate, and benefits. then analyze the movement of the price of a reasonable bonus life insurance policy with a surrender option based on the age of the insured, technical rate, participation level, and volatility. The surrender value obtained is the difference between the value of the American Put option and the European Call Option. Based on the simulation, the conclusion of this analysis is that the price of the endowment type life insurance policy can be estimated using the binomial method at around 0.78 for a fair policy price and around 0.27 for a policy price with a surrender option. This gives an idea of the relative value of the policy price to the expected benefits under certain conditions, such as the death of the insured in the first year of the contract.
Carbon Price Prediction by Incorporating Fossil Fuel Prices Using Long Short-Term Memory with Temporal Pattern Attention (TPA-LSTM) Mujiono, Edo Priyo Utomo Putro; Mukhlash, Imam; Pradana, Yan Aditya; Putri, Endah R.M.; Irawan, Mohammad Isa
Science and Technology Indonesia Vol. 10 No. 3 (2025): July
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/sti.2025.10.3.856-865

Abstract

Reliable carbon price prediction can help to stabilize the carbon market, minimize financial risks for investors, and encourage innovation in green industries. The forecasts have a crucial role in reaching advanced goals for reducing emissions, aiding the shift toward an economy with reduced carbon emissions, and lessening the adverse effects of climate change overall. This paper proposes applications of LSTM with Temporal Pattern Attention (TPA-LSTM) to predict carbon price fluctuations. The prediction of carbon price fluctuations not only draws on its own historical information but also from its main predictors, including fossil fuel prices from 2018 to 2023. The TPA-LSTM method is a combined method that uses the LSTM layer as the initial input of the model. Furthermore, the output generated by the LSTM layer serves as the input to the TPA layer, which is then used to predict the carbon price for the following day. The model is tested by predicting the test data and calculating the evaluation results. The experimental results indicate that TPA-LSTM has surpassed other models in accuracy by showing better performance based on MSE, RMSE, MAE, and MAPE metrics.
Co-Authors Imam Mukhlash Lissa, Hermei Mohammad Isa Irawan Mujiono, Edo Priyo Utomo Putro YAN ADITYA PRADANA