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All Journal Jurnal Matematika Buletin Udayana Mengabdi E-Jurnal Matematika Prosiding Seminar Nasional MIPA Jurnal Matematika Sains dan Teknologi
Komang Dharmawan
Prodi Matematika FMIPA Universitas Udayana
Agriculture, Biological Sciences & Forestry Education Mathematics Other

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MENENTUKAN HARGA OPSI DENGAN METODE MONTE CARLO BERSYARAT MENGGUNAKAN BARISAN KUASI ACAK FAURE PUTU WIDYA ASTUTI; KOMANG DHARMAWAN; KARTIKA SARI
E-Jurnal Matematika Vol 10 No 3 (2021)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2021.v10.i03.p334

Abstract

An option contract is a contract that gives the owner the right to sell or even to buy an asset at the predetermined price and period time. The conditional Monte Carlo is one of the several methods that is used to determine the option price which in the process uses random numbers with normal standard distribution. At the same time, the random number generator can be substituted by using a quasi-random sequence, as in Faure's quasi-random sequence. The aim of this study is to determine the contract price of the call option with the European type by applying the conditional Monte Carlo method. This method used the Faure quasi-random sequence and compared it with the method of Monte Carlo standard, Monte Carlo standard in using the quasi-random sequence of Faure, and conditional Monte Carlo. The results of this study showed that the call option calculated using the conditional Monte Carlo method using the quasi-random Faure sequence began to stabilize at the 5000th simulation for K = 32575 and K = 34725 and in the 10000th simulation for K = 33000 and K = 33950. Research also show that with the conditional Monte Carlo in using the quasi-random sequence of Faure is more stable. Therefore, it is obtained its real value faster than the Monte Carlo standard, Monte Carlo standard in using the quasi-random sequence of Faure, and conditional Monte Carlo. The MAPE value of conditional Monte Carlo in using the quasi-random sequences of Faure and the Monte Carlo standard is smaller than the Monte Carlo standard in using the quasi-random sequence of Faure, and conditional Monte Carlo. Therefore, it can be said to be more accurate when calculating the European type call option price at BBCA.JK stocks.
PENDAMPINGAN KEGIATAN EKSRAKURIKULER KIR DALAM UPAYA MENINGKATKAN KUALITAS SEKOLAH SMA DWIJENDRA DENPASAR Komang Dharmawan; Y. Ramona; N. N. Rupiasih; I G. A. Widagda
Buletin Udayana Mengabdi Vol 19 No 3 (2020): Buletin Udayana Mengabdi
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (207.27 KB)

Abstract

Youth Scientific Work (KIR) basically aims to trigger curiosity about natural phenomena related to science and technology. KIR can also increase the ability to think critically about natural phenomena and increase creativity that fosters creative ability and critical thinking. The purpose of this assistance is to introduce research methods for groups of teachers so students get better quality coaching. The mentoring method applied is In-House-Training, which is the implementation of mentoring at the relevant school. In this assistance 4 scientific works have been produced by high school students of Dwijendra Denpasar who are ready to be presented in KIR competitions both regionally and nationally.
PENENTUAN HARGA PREMI ASURANSI PERTANIAN BERBASIS INDEKS CURAH HUJAN DENGAN MENGGUNAKAN METODE PEMBANGKIT DISTRIBUSI EKSPONENSIAL CAMPURAN SAYID QOSIM; KOMANG DHARMAWAN; LUH PUTU IDA HARINI
E-Jurnal Matematika Vol 7 No 2 (2018)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2018.v07.i02.p196

Abstract

Agricultural insurance is an insurance in agriculture sector that is relatively newly introduced in Indonesia. Agricultural insurance based on rainfall index is one of the risk management tool to keep farmers in case of crop failure. This study aims to determine the steps in determining the value of rainfall index on agricultural insurance and calculate the value of agricultural insurance premiums based on simulated rainfall index by Stochastic weather generator with mixed exponential distribution. The results of this study provide value if the amount of rainfall 103,71 mm so that the amount of premium payments equal to Rp19.016, and if the rainfall is high 128.35 mm then the amount of premium payment equal to Rp1.088.000.
MENENTUKAN PORTOFOLIO OPTIMAL MENGGUNAKAN MODEL CONDITIONAL MEAN VARIANCE I GEDE ERY NISCAHYANA; KOMANG DHARMAWAN; I NYOMAN WIDANA
E-Jurnal Matematika Vol 5 No 3 (2016)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2016.v05.i03.p125

Abstract

When the returns of stock prices show the existence of autocorrelation and heteroscedasticity, then conditional mean variance models are suitable method to model the behavior of the stocks. In this thesis, the implementation of the conditional mean variance model to the autocorrelated and heteroscedastic return was discussed. The aim of this thesis was to assess the effect of the autocorrelated and heteroscedastic returns to the optimal solution of a portfolio. The margin of four stocks, Fortune Mate Indonesia Tbk (FMII.JK), Bank Permata Tbk (BNLI.JK), Suryamas Dutamakmur Tbk (SMDM.JK) dan Semen Gresik Indonesia Tbk (SMGR.JK) were estimated by GARCH(1,1) model with standard innovations following the standard normal distribution and the t-distribution.  The estimations were used to construct a portfolio. The portfolio optimal was found when the standard innovation used was t-distribution with the standard deviation of 1.4532 and the mean of 0.8023 consisting of 0.9429 (94%) of FMII stock, 0.0473 (5%) of  BNLI stock, 0% of SMDM stock, 1% of  SMGR stock.
PENENTUAN KEPUTUSAN INVESTASI SAHAM MENGGUNAKAN CAPITAL ASSET PRICING MODEL (CAPM) DENGAN PENAKSIR PARAMETER STOKASTIK ICHA WINDA DIAN SAFIRA; KOMANG DHARMAWAN; DESAK PUTU EKA NILAKUSMAWATI
E-Jurnal Matematika Vol 10 No 4 (2021)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2021.v10.i04.p351

Abstract

CAPM is a method of determining efficient or inefficient stocks based on the differences between individual returns and expected returns based on the CAPM’s positive value for efficient and negative value for inefficient stocks. The move to share prices in the process can influence investors's decisions in investing funds, so that it can be formulated in stochastic differential equations that form the Geometric Brownian Motion model (GBM). The purpose of the study is to determine return value using the CAPM based on share estimates and historical stock prices. The study uses secondary data that data a monthly closing of stock prices from December 2017 to December 2020. The GBG model's estimated stock price is used to determine the expected value return using the CAPM. In this case, it is called CAPM-Stochastic. Then the results of the CAPM-Stochastic was compared to the results of the CAPM-Historical to define efficient stocks and inefficient stocks. The results of research using CAPM-Stochastic obtained that HMSP, ICBP, KLBF, and WOOD shares are efficient stock while UNVR shares are inefficient. The results of CAPM-Historical obtained that HMSP, ICBP, KLBF, and UNVR shares are inefficient stocks and WOOD is an efficient stocks.
ANALISIS RISIKO PORTOFOLIO MENGGUNAKAN METODE SIMULASI MONTE CARLO CONTROL VARIATES IRENE MAYLINDA PANGARIBUAN; KOMANG DHARMAWAN; I WAYAN SUMARJAYA
E-Jurnal Matematika Vol 10 No 4 (2021)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2021.v10.i04.p342

Abstract

Value at Risk (VaR) is a method to measure the maximum loss with a certain level of confidence in a certain period. Monte Carlo simulation is the most popular method of calculating VaR. The purpose of this study is to demonstrate control variates method as a variance reduction method that can be applied to estimate VaR. Moreover, it is to compare the results with the normal VaR method or analytical VaR calculation. Control variates method was used to find new returns from all stocks which are used as estimators of the control variates. The new returns were then used to define parameters needed to generate N random numbers. Furthermore, the generated numbers were used to find the VaR value. The method was then applied to estimate a portfolio of the game and esports company stocks that are EA, TTWO, AESE, TCEHY, and ATVI . The results show Monte Carlo simulation gives VaR of US$41.6428 within 1000 simulation, while the analytical VaR calculation or normal VaR method gives US$30.0949.
PENENTUAN NILAI KONTRAK OPSI TIPE BINARY PADA KOMODITS KAKAO MENGGUNAKAN METODE QUASI MONTE CARLO DENGAN BARISAN BILANGAN ACAK FAURE DEWA AYU AGUNG PUTRI RATNASARI; KOMANG DHARMAWAN; DESAK PUTU EKA NILAKUSMAWATI
E-Jurnal Matematika Vol 6 No 4 (2017)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2017.v06.i04.p168

Abstract

Contract options are the most important part of an investment strategy. An option is a contract that entitles the owner or holder to sell an asset on a designated maturity date. A binary or asset-or-nothing option is an option in which the option holder will perform or not the option. There are many methods used in determining the option contract value, one of this is the Monte Carlo Quasi method of the Faure random. The purpose of this study is to determine the value of binary type option contract using the Quasi Monte Carlo method of the Faure random and compare with the Monte Carlo method. The results of this study indicate that the option contract calculated by the Monte Carlo Quasi method results in a more fair value. Monte Carlo method simulation 10.000 generate standard error is 0.9316 and the option convergence at 18.9144. While Quasi Monte Carlo simulation 3000 generate standard error is 0.09091 and the option convergence at 18.8203. This show the Quasi Monte Carlo method reaches a faster convergent of Monte Carlo method.
ANALISIS SENSITIVITAS HARGA OPSI MENGGUNAKAN METODE GREEK BLACK SCHOLES DEVI NANDITA. N; KOMANG DHARMAWAN; DESAK PUTU EKA NILAKUSMAWATI
E-Jurnal Matematika Vol 7 No 2 (2018)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2018.v07.i02.p197

Abstract

Sensitivity analysis can be used to carry out hedging strategies. The sensitivity value measures how much the price change of the option influenced by some parameters. The aim of this study is to determine the sensitivity analysis of the buying price of European option by using the Greek method on Black Scholes Formula. From this study we get the values of delta, gamma, theta, vega, and rho. The values of deltas, gamma, vega, and rho are positive, which means that the value of the option is more sensitive than the corresponding parameter. The most sensitive value of gamma is obtained when the stock price approaches the strike price and approaches the expiry date. The value of theta obtained is negative and hence the most sensitive theta value is when the value is getting smaller. While, the most sensitive value of vega is obtained when the stock price is close to the strike price and is far from the expiry date. The most sensitive value of rho is obtained when the stock price gets bigger and farther from the expiry date.
PERHITUNGAN VaR PORTOFOLIO SAHAM MENGGUNAKAN DATA HISTORIS DAN DATA SIMULASI MONTE CARLO WAYAN ARTHINI; KOMANG DHARMAWAN; LUH PUTU IDA HARINI
E-Jurnal Matematika Volume 1, No 1, Tahun 2012
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2012.v01.i01.p001

Abstract

Value at Risk (VaR) is the maximum potential loss on a portfolio based on the probability at a certain time.  In this research, portfolio VaR values calculated from historical data and Monte Carlo simulation data. Historical data is processed so as to obtain stock returns, variance, correlation coefficient, and variance-covariance matrix, then the method of Markowitz sought proportion of each stock fund, and portfolio risk and return portfolio. The data was then simulated by Monte Carlo simulation, Exact Monte Carlo Simulation and Expected Monte Carlo Simulation. Exact Monte Carlo simulation have same returns and standard deviation  with historical data, while the Expected Monte Carlo Simulation satistic calculation similar to historical data. The results of this research is the portfolio VaR  with time horizon T=1, T=10, T=22 and the confidence level of 95 %, values obtained VaR between historical data and Monte Carlo simulation data with the method exact and expected. Value of VaR from both Monte Carlo simulation is greater than VaR historical data.
ESTIMASI VALUE AT RISK MENGGUNAKAN VOLATILITAS DISPLACED DIFFUSION MIRANDA NOVI MARA DEWI; KOMANG DHARMAWAN; KARTIKA SARI
E-Jurnal Matematika Vol 8 No 4 (2019)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2019.v08.i04.p268

Abstract

Value at Risk (VaR) is a measure of risk that is able to calculate the worst possible loss that can occurs to stock prices with a certain level of confidence and within a certain period of time. The purpose of this study was to determine the VaR estimate from PT. Indonesian Telecommunications by using Displaced Diffusion volatility. The Displaced Diffusion Model is a stochastic volatility model that describes changes in a financial asset assuming volatility is not constant, but follows a stochastic process. Displaced Diffusion model are capable of modelling skewed implied volatility structures and frequently applied by interest rate quants. Based on the estimation of Displaced Diffusion volatility, it is found that volatility for PT. Indonesian Telecommunications is 0.010168 and VaR estimation using Displaced Diffusion volatility with a confidence level of 95 percent of 1.63%.
Co-Authors A.A DWI MARSITA ANGGRAENI AULIA ATIKA PRAWIBTA SUHARTO DERY MAULANA DESAK PUTU DEVI DAMIYANTI Desak Putu Eka Nilakusmawati DEVI NANDITA. N DEWA AYU AGUNG PUTRI RATNASARI ELVINA LIADI G. K Gandhiadi G. K. Gandhiadi GEDE SUMENDRA HERLINA HIDAYATI I G. A. Widagda I GEDE ARYA DUTA PRATAMA I GEDE ERY NISCAHYANA I GEDE RENDIAWAN ADI BRATHA I Gusti Ayu Made Srinadi I GUSTI AYU MITA ERMIA SARI I GUSTI PUTU NGURAH MAHAYOGA I KOMANG GDE SUKARSA I KOMANG TRY BAYU MAHENDRA I NYOMAN BRYAN ANDIKA I Nyoman Widana I Putu Eka Nila Kencana I PUTU OKA PARAMARTHA I PUTU YUDHI PRATAMA I Wayan Sumarjaya I WAYAN WIDHI DIRGANTARA ICHA WINDA DIAN SAFIRA IDA AYU EGA RAHAYUNI IDA AYU GDE KHASMANA PUTRI IDA AYU PUTU CANDRA DEWI IKHSAN AKBAR INTAN AWYA WAHARIKA INTAN LESTARI IRENE MAYLINDA PANGARIBUAN KADEK FRISCA AYU DEVI KADEK INTAN SARI KADEK MIRA PITRIYANTI Kartika Sari Kartika Sari Ketut Jayanegara LUH HENA TERECIA WISMAWAN PUTRI LUH PUTU IDA HARINI Luh Putu Ratna Sundari LUSIA EMITRIANA MAGOL MADE ASIH MAKBUL MUFLIHUNALLAH MERARY SIANIPAR MIRANDA NOVI MARA DEWI N. N. Rupiasi NABILA NUR JANNAH NI KADEK NITA SILVANA SUYASA NI KADEK PUSPITAYANTI Ni Ketut Tari Tastrawati NI LUH NIKASARI NI LUH PUTU KARTIKA WATI Ni Luh Putu Suciptawati Ni Made Asih NI MADE NITA ASTUTI NI NYOMAN AYU ARTANADI Ni Nyoman Rupiasih NI PUTU AYUNDA SURYA DEWI NI PUTU WIDYA ISWARI DEWI NI WAYAN UCHI YUSHI ARI SUDINA PUTU AMANDA SETIAWANI PUTU AYU DENI PUTU IKA OKTIYARI LAKSMI PUTU MIRAH PURNAMA D. PUTU SAVITRI DEVI PUTU WIDYA ASTUTI RISKA YUNITA SAYID QOSIM SORAYA SARAH AFIFAH TJOKORDA BAGUS OKA Tjokorda Bagus Oka VIAN RISKA AYUNING TYAS VIKY AMELIAH WAYAN ARTHINI WIRYA SEDANA Yan Ramona YOHANA Th.V. SERAN YOSEVA AGUNG PRIHANDINI