Di Asih I Maruddani - Academia.edu (original) (raw)

Papers by Di Asih I Maruddani

Research paper thumbnail of VALUE at RISK (VaR) DAN CONDITIONAL VALUE at RISK (CVaR) DALAM PEMBENTUKAN PORTOFOLIO BIVARIAT MENGGUNAKAN COPULA GUMBEL

Jurnal Gaussian

One way to minimize risk in investing is to form of portfolio by combining several stocks.Value a... more One way to minimize risk in investing is to form of portfolio by combining several stocks.Value at Risk (VaR) is a method for estimating risk but has a weakness that is VaR is incoherent because it does not have the subadditivity. To overcome the weakness of VaR, Conditional Value at Risk (CVaR) can use. Stock data is generally volatile, so ARIMA-GARCH is used to model it. The selection of ARIMA models on R software can be automatically using the auto.arima() function. Then Copula Gumbel is a method for modeling joint distribution and flexible because it does not require the assumption of normality and has the best sensitivity to high risk so that it is suitable for use in stock data.The first step in this research is to modeling Copula Gumbel-GARCH with the aim to calculate VaR and CVaR on the portfolio of PT Bank Mandiri Tbk (BMRI) and PT Indo Tambangraya Megah Tbk (ITMG). At the confidence level 99%, 95%, and 90% obtained the VaR results sequentially amounted to 3.977073%; 2.5461...

Research paper thumbnail of Valuasi Compound Option Put on Put Tipe Eropa

Jurnal Gaussian, Aug 7, 2014

Options are one of the form of investment which a contract that gives the right (not obligation) ... more Options are one of the form of investment which a contract that gives the right (not obligation) to the option holder to buy (call options) or sell (put options) the underlying asset by a certain date for a certain price. Option price is a reflection of the intrinsic value of the option and any additional amount over intrinsic value. One type of options that are traded is compound options. Compound option model is introduced by Robert Geske in 1979. Compound options are options on options. Compound option put on a put is put option where the underlying assets are another put option. The compound option put on put will be exercised on the first exercise date only if the value of the put option on that date is less than the first stike price. An empirical study using compound option put on a put stocks of Apple Inc which is strike price compound option US$ 560, strike price put option US$ 585, with the first exercise date on March 28, 2014 and the second exercise date on May 17, 2014. The theoritical price of compound option put on put on stocks of Apple Inc is US$ 501.4566. .

Research paper thumbnail of Penentuan Valuasi Portofolio Obligasi Dengan Credit Metrics Dan Monte Carlo Simulation

Jurnal Gaussian, Aug 9, 2013

The capital market is one way to get funding for the company and as a medium to strengthen corpor... more The capital market is one way to get funding for the company and as a medium to strengthen corporate finance position. One of the instruments that are traded than stocks are bonds. The advantage of this instrument because it is easy and rapid acquisition of funds to beused for the operations of the corporate and the period of payment is longer. Bond investment must be noticed valuations and credit risk, with calculating the valuation can be estimate bonds credit risk. Credit Metrics is a reduced form model to estimate the risk of displacement of ratings. The risk not only occur when corporate rating be default but also if the rating upgrade or downgrade. For the determination of the portfolio valuation can be used Monte Carlo simulation using generate scenarios corporate ratings. Empirical study can be used for three bonds there are

Research paper thumbnail of Klasifikasi Status Kemiskinan Rumah Tangga Dengan Algoritma C5.0 DI Kabupaten Pemalang

Jurnal Gaussian, 2021

Pemalang regency is a district which has amount of poverty around 16.04%. One of the effort that ... more Pemalang regency is a district which has amount of poverty around 16.04%. One of the effort that must be improved in tackling poverty is increasing the accuracy of the government program’s target. The improvement of target accuracy is expected to give the better impact on the welfare of the population. This study classified the poverty status of households in Pemalang regency using C5.0 Algorithm. The poverty status of households is divided into two classes, namely poor and non-poor. There was an imbalance of data in both classes. Data imbalances were handled by using Synthetic Minority Oversampling Technique (SMOTE). From the research that has been done, SMOTE application in classification of household poverty status affected the evaluation value of the model. Previously the model could not classify the minority class and after using SMOTE the model produced an average value of sensitivity 25.80%. SMOTE application increased the average value of specificity from 91.16% to 94.91%. H...

Research paper thumbnail of Klasifikasi Perubahan Harga Obligasi Korporasi DI Indonesia Menggunakan Metode Naive Bayes Classification

Jurnal Gaussian, Apr 29, 2016

Bond is a medium-long term debt securities which can be sold and contains a pledge from the issue... more Bond is a medium-long term debt securities which can be sold and contains a pledge from the issuer to pay interest for a certain period and repayment of the principal debt at a specified time to the bonds buyer. Bonds price changes any time, it could be beneficial or give disadvantage to investors. Investors should know the best conditions to buy bonds on a discount, or sell them at a premium price. By classify the changing of bonds price, it could help investors to gain optimum return. One method is Naive Bayes classification. In theory, It has the minimum error rate in comparison to all other classifiers. Bayes is a simple probabilistic-based prediction technique which based on the application of Bayes theorem with strong independence assumptions. Before classifying, preprocessing data is required as a stage feature selection. In this case, the Mann Whitney test can be done to choose the independent features of each class. Validation technique in use is k-fold cross validation. Based on analysis, we gained average accuracy at 78,52% and 21,8% error. With high accuracy and quite low error, it means that the Naïve Bayes method works quite well on classifying the corporate bonds price changes in Indonesia.

Research paper thumbnail of Copula Frank Untuk Perhitungan Value at Risk Portofolio Bivariat Pada Model Exponential Generalized Autoregressive Conditional Heteroscedasticity

Jurnal Gaussian, 2021

Stocks are one type of investment that promises return for investors but often carries a high ris... more Stocks are one type of investment that promises return for investors but often carries a high risk. Value at Risk (VaR) is a measuring tool that can calculate the amount of the worst loss that occurs in a stock portfolio with a certain level of confidence and within a certain time period. In general, financial data have a high volatility value, which causes the residuals are not normally distributed. ARCH/GARCH modoel is used to solve the heteroscedasticity problem. If the data also have an asymmetric effect, it is modelled with Exponential GARCH model. Copula-Frank is part of the Archimedian copula which is used to solve empirical cases. The data on this study were BBCA and KLBF stock price return data in the observation period 30 December 2011 – 6 December 2019. Furthermore, to test the validity of the VaR model, a backtesting test will be carried out using the Kupiec Test. The results showed that the best model used for BBCA stocks was ARIMA (1,0,1) EGARCH (1,1) and for KLBF stoc...

Research paper thumbnail of ARMA-GARCH model for value-at-risk (VaR) prediction on stocks of PT. Astra Agro Lestari.Tbk

PT. Astra Agro Lestari Tbk (AALI) is one of the plantation companies with the largest market capi... more PT. Astra Agro Lestari Tbk (AALI) is one of the plantation companies with the largest market capitalization in Indonesia. AALI stocks traded on the stock exchange have fairly fluctuating value and volatility of stock returns are not constant (heteroskedastic). One of the risk measurements that can be used to predict the risk of stock investing is Value-at-Risk (VaR). In conditions that are heteroskedastic stock returns, risk prediction can be done with the VaR ARCH/GARCH and VaR ARCH/GARCH combination model. Empirical studies were carried out on AALI stocks for the period of August 2, 2012 until October 1, 2019. The results obtained showed that the best model was ARIMA (0,0,1)-GARCH (1,2) with AIC value of -4.9793 and MSE of 0.00005. At the 95% trust level, the VaR ARCH/ARCH value was -0.3464.

Research paper thumbnail of PENGUKURAN KINERJA PORTOFOLIO OPTIMAL CAPITAL ASSET PRICING MODEL (CAPM) DAN ARBITRAGE PRICING THEORY (APT) (Studi Kasus : Saham-saham LQ45)

Jurnal Gaussian, 2018

Investing is placing money or funds in the hope of obtaining additional or specific gains on the ... more Investing is placing money or funds in the hope of obtaining additional or specific gains on the money or funds. The capital market is one place to invest in the financial field of interest to investor. This is because the capital market gives investor the freedom to choose securities traded in the capital market in accordance with the wishes of investor. Investor are included in risk averter, that means investor will always try to avoid risk. To avoid risk, investor try to diversify their investment. Diversification concept commonly used is portfolio. To maximize the return to be earned, the investor will invest his funds into several stocks in order to earn a greater profit. Capital Asset Pricing Model (CAPM) is a balance model that describes the relation of a risk with return more simply because it uses only one variable to describe the risk. Arbitrage Pricing Theory (APT) is a balance model that used many risk variables to see the relation of risk and return. With both models wi...

Research paper thumbnail of PENGUKURAN RISIKO GLUE-VALUE-AT-RISK PADA DATA DISTRIBUSI ELLIPTICAL (Studi Kasus: Data Saham PT Indocement Tunggal Prakarsa Tbk, PT Unilever Indonesia Tbk, PT United Tractors Tbk, Periode 1 Juni 2018 – 29 November 2019)

Jurnal Gaussian, 2020

Risk measurement is carried out to determine the risk. Popular methods that can be used to measur... more Risk measurement is carried out to determine the risk. Popular methods that can be used to measure risk at a confidence level are Value-at-Risk (VaR) and Tail-Value-at-Risk (TVaR). A Risk measurement should satisfy: translation invariance, positive homogenicity, monocity and subadditivity. VaR does not satisfy one of coherent axioms, namely subadditivity. TVaR is considered capable of overcoming VaR problems, but it’s too large for a risk measure. Glue-Value-at-Risk (GlueVaR) is a method that can overcome these problems because it can be valued between VaR and TVaR and fulfills four coherent axioms. In this paper GlueVaR used in the elliptical distribution for normal distribution to measure the risk of the stock of PT Indocement Tunggal Prakarsa Tbk (INTP), PT Unilever Indonesia Tbk (UNVR), and PT United Tractors Tbk (UNTR) for the period June 1st 2018 – 29th November 2019. After knowing the stock return is normally distributed and used confidence levels of α = 95% and β = 98%, a hi...

Research paper thumbnail of Pengukuran Risiko Kredit Obligasi Korporasi Dengan Credit Value at Risk (Cvar) Dan Optimalisasi Portofolio Menggunakan Metode Mean Variance Efficient Portfolio (Mvep)

Getting benefits of many kinds of coupon is not the only advantage of bond investment, but also i... more Getting benefits of many kinds of coupon is not the only advantage of bond investment, but also it gives potential risks such as credit risk. Credit risk originates from the fact that counterparties may be unable to fulfill their contractual obligations. Credit Value at Risk (CVaR) is introduced as a method to calculate bond credit risk if default occurs. CVaR is defined as the most significant credit loss which occurs unexpectedly at the selected level of confidence, measured as the deviation of Expected Credit Loss (ECL). To construct optimal bond portfolio requires Mean variance Efficient Portfolio (MVEP) method. MVEP is defined as the portfolio with minimum variance among all possible portfolios that can be formed. This study case has been constructed through two bonds, bond VI of Jabar Banten Bank (BJB) year 2009 serial B and bond of BTPN Bank I year 2009 serial B. Based on the R programming output, the obtained results for bonds with a rating idAA BJB, has a positive CVaR val...

Research paper thumbnail of Pengaruh Data Ekstrim Aset Perusahaan Pada Valuasi Obligasi

Asumsi dasar yang sering digunakan pada valuasi obligasi merupakan penggunaan asumsi pada model B... more Asumsi dasar yang sering digunakan pada valuasi obligasi merupakan penggunaan asumsi pada model Black-Scholes-Merton. Terdapat dua asumsi yang kurang tepat digunakan dalam investasi praktis obligasi, yaitu data aset perusahaan tidak mengikuti distribusi Normal, dalam hal ini memiliki data ekstrem yang diperlihatkan dengan keberadaan jump . Selain itu pemberian kupon secara periodik merupakan hal yang wajar dalam kontrak obligasi. Paper ini akan membahas secara matematis valuasi obligasi dalam hal ini memberikan nilai ekspektasi modal perusahaan dan kemungkinan kebangkrutan perusahaan yang diakibatkan perusahaan tidak mampu membayar kembali hutang obligasinya pada saat jatuh tempo. Untuk menagkap adanya jump pada data aset perusahaan, geometric Brownian motion dengan jump diffusion merupakan model yang tepat. Sedangkan pembentukan serial pemberian kupon dapat dilakukan dengan pendekatan compound option . Penerapan kasus ini adalah dengan melakukan analisis pada Obligasi Berkelanjutan...

Research paper thumbnail of Model ARCH dan GARCH untuk Mengukur Volatilitas Harga Saham PT HM Sampoerna Tbk Indonesia (Pengukuran Volatilitas Harga Saham)

Penelitian-penelitian mengenai peramalan pada financial time series menunjukkan bahwa perilaku er... more Penelitian-penelitian mengenai peramalan pada financial time series menunjukkan bahwa perilaku error peramalan mengalami masalah autokorelasi pada variansi ut. Engle (1982) membangun model Autoregressive Conditional Heteroscedasticity (ARCH). Ide kunci dari model ARCH ini adalah variansi e pada waktu t (yaitu σt2) tergantung pada besarnya kuadrat error pada waktu ke t-1, yaitu et [1]. Bollerslev (1986) mengembangkan model ARCH ke dalam bentuk umum, yaitu Generalized Autoregressive Conditional Heteroscedasticity (GARCH). Bollerslev menyatakan bahwa variansi error tidak hanya tergantung pada error periode lalu tetapi juga variansi error dari periode lalu. Penelitian ini membahas adanya efek ARCH dan GARCH pada masalah volatilitas data Return Saham PT HM Sampoerna Indonesia Tbk periode 1 Januari 2004 sampai 30 Desember 2005. Dengan metode BoxJenkins, diperoleh Model ARIMA(1,0,1) dengan rumus: RSAHAM = -0.975978 AR(1) + 0.989613 MA(1) Menggunakan Metode Maksimum Likelihood diperoleh bah...

Research paper thumbnail of PENERAPAN ANALISIS KLASTER K-MODES DENGAN VALIDASI DAVIES BOULDIN INDEX DALAM MENENTUKAN KARAKTERISTIK KANAL YOUTUBE DI INDONESIA (Studi Kasus: 250 Kanal YouTube Indonesia Teratas Menurut Socialblade)

YouTube is one of the most popular online platforms today. The popularity of YouTube has makes it... more YouTube is one of the most popular online platforms today. The popularity of YouTube has makes it an effective advertising medium. In April 2019, Socialblade released the top 250 YouTube channels in Indonesia based on their gradations with various characteristics. YouTube channel data will be grouped into several clusters to make it easier for advertisers to choose channels with characteristics as needed. The purpose of this study is to determine the best number of clusters and determine their characteristics. The method used is the k-Modes cluster analysis with values k = 3, 4, 5, ..., 8. The k-Modes method can group objects that have categorical type variables into relatively homogeneous groups. The best number of clusters (k) can be checked using the Davies Bouldin Index (DBI). Based on the analysis carried out, obtained the best number of six clusters with a Davies-Bouldin Index value of 1.080509. The most recommended cluster for advertising is cluster 6, which has grade A chara...

Research paper thumbnail of ARIMA-GARCH Model and ARIMA-GARCH Ensemble for Value-at-Risk Prediction on Stocks Portfolio

Stocks portfolio is a form of investment that can be used to minimize the risk of loss. In a stoc... more Stocks portfolio is a form of investment that can be used to minimize the risk of loss. In a stock portfolio, the value at risk (VaR) can be predicted through the portfolio return. If portfolio return variance is heteroscedastic risk prediction can be done by using VaR with ARIMA-GARCH or Ensemble ARIMA-GARCH model approach. Furthermore, the accuracy of VaR is tested through backtesting test. In this study, the portfolio formed from Astra Agro Lestari Ltd (AALI) and Indofood Ltd (INDF) stocks from 10/02/2012 to 10/01/2019. The results showed that the best model is ARIMA(0,0,[3])-GARCH(1,2) with AIC of -5.604 and MSE 1.874e-07.At confidence level of 95% and 1 day holding period, the VaR of the ARIMA(0,0,[3])-GARCH(1,2) was -0.3464. Based on the backtesting test, it is proven to be very accurate to predict the value of loss risk because the value of the violation ratio (VR) is equal to 0.

Research paper thumbnail of Value at Risk Pada Portofolio Saham Dengan Copula Ali-Mikhail-Haq

Jurnal Gaussian, 2019

Investment is one alternative to increase assets in the future. Investors can invest in a portfol... more Investment is one alternative to increase assets in the future. Investors can invest in a portfolio to reduce the level of risk. Value at Risk (VaR) is a measuring tool that can calculate the worst loss over a given time period at a given confidence level. GARCH (Generalized Autoregressive Conditional Heteroskedasticity) is used to model data with high volatility. The teory of copula is a powerful tool for modeling joint distribution for any marginal distributions. Ali-Mikhail-Haq copula from Archimedean copula family can be applied to data with dependencies τ between -0.1817 to 0.3333. This research uses Ali-Mikhail-Haq copula with a Monte Carlo simulation to calculate a bivariate portfolio VaR from a combination stocks of PT Pembangunan Perumahan Tbk. (PTPP), PT Bank Tabungan Negara Tbk. (BBTN), and PT Jasa Marga Tbk. (JSMR) in the period of March 3, 2014 - March 1, 2019. The results of VaR calculation on bivariate portfolio for next 1 day period obtained the lowest VaR is owned b...

Research paper thumbnail of OPTIMASI REGRESI LOGISTIK MENGGUNAKAN ALGORITMA GENETIKA UNTUK PEMODELAN FAKTOR-FAKTOR YANG MEMPENGARUHI PENGGOLONGAN KREDIT BANK (Studi Kasus: Debitur di PT BPR Gunung Lawu Klaten Periode Tahun 2017)

Jurnal Gaussian, 2019

Credit is the greatest asset managed by banks and also the most dominant contributor to the bank’... more Credit is the greatest asset managed by banks and also the most dominant contributor to the bank’s income. But in its implementation, the provision of credit to the public is at risk for non-performing loans. For this reason, creditors try to minimize the occurrence of non-performing loans by predicting credit risk appropriately. In this study, modeling the factors that influence credit classification at PT BPR Gunung Lawu is useful for predicting the credit risk of prospective debtors. Modeling are done using logistic regression and genetic algorithms. Factors suspected of influencing credit classification include age, gender, marital status, education, home ownership, employment, net income, tenor, type of business, type of loan, type of loan interest, and loan size. Estimated model parameters obtained from logistic regression were optimized using genetic algorithms. The fitness function used is pseudo or and MSE. The best model is generated by modeling with genetic algorithms b...

Research paper thumbnail of Pembentukan Portofolio Optimal Dengan Metode Resampled Efficient Frontier Untuk Perhitungan Value at Risk Dilengkapi Aplikasi Gui Matlab

Jurnal Gaussian, 2019

The purpose of investors in investing is to get a return, but investors also have to bear the ris... more The purpose of investors in investing is to get a return, but investors also have to bear the risks that might exist. There are 3 types of investors in investment based on their preference for risk, namely risk aversion (risk averter), moderate risk takers (risk moderate), and high risk takers (risk takers). To obtain an optimal portfolio for each type of investor, the Resampled Efficient Frontier Method is used with Monte Carlo Simulation as much as 700 times, to obtain more parameter estimates. The results of the Resampled Efficient Frontier from Efficient Frontier will take 51 efficient points to determine the optimal portfolio for each type of investor. The efficient point taken is the 1st, 26th and 51st efficient points for the investor risk averter type, risk moderate, and risk taker. To determine the estimated loss in investment, the VaR value is calculated based on the monthly return data of BBNI, UNTR, INKP, and KLBF shares for the period February 2013 to March 2017, with a...

Research paper thumbnail of Modeling stock prices in a portfolio using multidimensional geometric brownian motion

Journal of Physics: Conference Series, 2018

View the article online for updates and enhancements. Content from this work may be used under th... more View the article online for updates and enhancements. Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.

Research paper thumbnail of Estimasi Parameter Model Regresi Non Stasionerdengan Variabel Dependen Lag : Studi Kasus Padaperkembangan Ekspor Indonesia Ke Jepangtahun 1980 - 2000

The clasiccal regression model was devised to handle relationship between stationary variables. B... more The clasiccal regression model was devised to handle relationship between stationary variables. But, many economic variables that frequently faced by econometricians when dealing with time series data, are nonstationary variables. This clearly places severe restrictions on their analysis by standard regression method. In this paper, we study regression models with a lagged dependent variable when both the dependent and independent variables are nonstationary, and the regression model is not cointegrated. In particular, we discuss the limiting properties of least squares estimates of the parameters in such regression models. We show that the estimate of the lagged dependent variable tends to unity and the estimates of the independent variables tend to zero. The results might also allow us to investigate the growth of export from Indonesian to Japan.

Research paper thumbnail of Analisis Hasil Ujian Nasional Tingkat Sma DI Kabupaten Banyumas Tingkat Sma DI Kabupaten Banyumas Menggunakan Analisis Cluster Dan Biplot

Evaluasi pendidikan dilakukan dalam rangka pengendalian mutu pendidikan secara nasional. Salah sa... more Evaluasi pendidikan dilakukan dalam rangka pengendalian mutu pendidikan secara nasional. Salah satu bentuk evaluasi pendidikan adalah dengan diadakannya ujian nasional. Untuk meningkatkan kualitas pendidikan nasional dibuatlah Rintisan Sekolah Bertaraf Internasional (RSBI). Status RSBI tersebut tidak dapat menjamin prestasi nilai Ujian Nasional (UN) meningkat sehingga perlu dilakukan penelitian untuk mengevaluasi SMA-SMA yang ada di Kabupaten Banyumas. Penelitian ini bertujuan untuk mengetahui SMA-SMA yang perlu lebih ditingkatkan lagi mutu pendidikannya sehingga perlu dilakukan pengelompokan terhadap-SMA-SMA di Kabupaten Banyumas. Pengelompokan ini perlu dilakukan karena beragamnya mutu dari ke 32 SMA yang ada di Kabupaten Banyumas sehingga hal ini menunjukkan tidak meratanya mutu dari SMA-SMA yang ada di Kabupaten Banyumas sehingga perlu dilakukan pengelompokan untuk memudahkan dalam pemberian bantuan terhadap SMA-SMA yang dinilai mempunyai kualitas rendah. Penelitian ini dilakukan dengan cara mengelompokkan SMA-SMA di Kabupaten Banyumas menjadi 3 kelompok. Analisis yang digunakan untuk pengelompokannya adalah analisis cluster dengan metode average linkage. Selanjutnya untuk mengetahui posisi SMA-SMA di Kabupaten Banyumas di lakukan analisis biplot. Adapun manfaat yang di dapat dari penelitian ini adalah dapat di deskripsikan SMA-SMA di Kabupaten Banyumas dan karakteristik nilai ujian nasional tahun 2010 untuk daerah Kabupaten Banyumas. Hasil yang diperoleh dari penelitian ini adalah berdasarkan nilai ujian nasional tahun 2010 diketahui bahwa SMA bukan RSBI mampu bersaing dengan SMA RSBI untuk Kabupaten Banyumas. Kata Kunci : Analisis Cluster, Biplot, ujian nasional 2010

Research paper thumbnail of VALUE at RISK (VaR) DAN CONDITIONAL VALUE at RISK (CVaR) DALAM PEMBENTUKAN PORTOFOLIO BIVARIAT MENGGUNAKAN COPULA GUMBEL

Jurnal Gaussian

One way to minimize risk in investing is to form of portfolio by combining several stocks.Value a... more One way to minimize risk in investing is to form of portfolio by combining several stocks.Value at Risk (VaR) is a method for estimating risk but has a weakness that is VaR is incoherent because it does not have the subadditivity. To overcome the weakness of VaR, Conditional Value at Risk (CVaR) can use. Stock data is generally volatile, so ARIMA-GARCH is used to model it. The selection of ARIMA models on R software can be automatically using the auto.arima() function. Then Copula Gumbel is a method for modeling joint distribution and flexible because it does not require the assumption of normality and has the best sensitivity to high risk so that it is suitable for use in stock data.The first step in this research is to modeling Copula Gumbel-GARCH with the aim to calculate VaR and CVaR on the portfolio of PT Bank Mandiri Tbk (BMRI) and PT Indo Tambangraya Megah Tbk (ITMG). At the confidence level 99%, 95%, and 90% obtained the VaR results sequentially amounted to 3.977073%; 2.5461...

Research paper thumbnail of Valuasi Compound Option Put on Put Tipe Eropa

Jurnal Gaussian, Aug 7, 2014

Options are one of the form of investment which a contract that gives the right (not obligation) ... more Options are one of the form of investment which a contract that gives the right (not obligation) to the option holder to buy (call options) or sell (put options) the underlying asset by a certain date for a certain price. Option price is a reflection of the intrinsic value of the option and any additional amount over intrinsic value. One type of options that are traded is compound options. Compound option model is introduced by Robert Geske in 1979. Compound options are options on options. Compound option put on a put is put option where the underlying assets are another put option. The compound option put on put will be exercised on the first exercise date only if the value of the put option on that date is less than the first stike price. An empirical study using compound option put on a put stocks of Apple Inc which is strike price compound option US$ 560, strike price put option US$ 585, with the first exercise date on March 28, 2014 and the second exercise date on May 17, 2014. The theoritical price of compound option put on put on stocks of Apple Inc is US$ 501.4566. .

Research paper thumbnail of Penentuan Valuasi Portofolio Obligasi Dengan Credit Metrics Dan Monte Carlo Simulation

Jurnal Gaussian, Aug 9, 2013

The capital market is one way to get funding for the company and as a medium to strengthen corpor... more The capital market is one way to get funding for the company and as a medium to strengthen corporate finance position. One of the instruments that are traded than stocks are bonds. The advantage of this instrument because it is easy and rapid acquisition of funds to beused for the operations of the corporate and the period of payment is longer. Bond investment must be noticed valuations and credit risk, with calculating the valuation can be estimate bonds credit risk. Credit Metrics is a reduced form model to estimate the risk of displacement of ratings. The risk not only occur when corporate rating be default but also if the rating upgrade or downgrade. For the determination of the portfolio valuation can be used Monte Carlo simulation using generate scenarios corporate ratings. Empirical study can be used for three bonds there are

Research paper thumbnail of Klasifikasi Status Kemiskinan Rumah Tangga Dengan Algoritma C5.0 DI Kabupaten Pemalang

Jurnal Gaussian, 2021

Pemalang regency is a district which has amount of poverty around 16.04%. One of the effort that ... more Pemalang regency is a district which has amount of poverty around 16.04%. One of the effort that must be improved in tackling poverty is increasing the accuracy of the government program’s target. The improvement of target accuracy is expected to give the better impact on the welfare of the population. This study classified the poverty status of households in Pemalang regency using C5.0 Algorithm. The poverty status of households is divided into two classes, namely poor and non-poor. There was an imbalance of data in both classes. Data imbalances were handled by using Synthetic Minority Oversampling Technique (SMOTE). From the research that has been done, SMOTE application in classification of household poverty status affected the evaluation value of the model. Previously the model could not classify the minority class and after using SMOTE the model produced an average value of sensitivity 25.80%. SMOTE application increased the average value of specificity from 91.16% to 94.91%. H...

Research paper thumbnail of Klasifikasi Perubahan Harga Obligasi Korporasi DI Indonesia Menggunakan Metode Naive Bayes Classification

Jurnal Gaussian, Apr 29, 2016

Bond is a medium-long term debt securities which can be sold and contains a pledge from the issue... more Bond is a medium-long term debt securities which can be sold and contains a pledge from the issuer to pay interest for a certain period and repayment of the principal debt at a specified time to the bonds buyer. Bonds price changes any time, it could be beneficial or give disadvantage to investors. Investors should know the best conditions to buy bonds on a discount, or sell them at a premium price. By classify the changing of bonds price, it could help investors to gain optimum return. One method is Naive Bayes classification. In theory, It has the minimum error rate in comparison to all other classifiers. Bayes is a simple probabilistic-based prediction technique which based on the application of Bayes theorem with strong independence assumptions. Before classifying, preprocessing data is required as a stage feature selection. In this case, the Mann Whitney test can be done to choose the independent features of each class. Validation technique in use is k-fold cross validation. Based on analysis, we gained average accuracy at 78,52% and 21,8% error. With high accuracy and quite low error, it means that the Naïve Bayes method works quite well on classifying the corporate bonds price changes in Indonesia.

Research paper thumbnail of Copula Frank Untuk Perhitungan Value at Risk Portofolio Bivariat Pada Model Exponential Generalized Autoregressive Conditional Heteroscedasticity

Jurnal Gaussian, 2021

Stocks are one type of investment that promises return for investors but often carries a high ris... more Stocks are one type of investment that promises return for investors but often carries a high risk. Value at Risk (VaR) is a measuring tool that can calculate the amount of the worst loss that occurs in a stock portfolio with a certain level of confidence and within a certain time period. In general, financial data have a high volatility value, which causes the residuals are not normally distributed. ARCH/GARCH modoel is used to solve the heteroscedasticity problem. If the data also have an asymmetric effect, it is modelled with Exponential GARCH model. Copula-Frank is part of the Archimedian copula which is used to solve empirical cases. The data on this study were BBCA and KLBF stock price return data in the observation period 30 December 2011 – 6 December 2019. Furthermore, to test the validity of the VaR model, a backtesting test will be carried out using the Kupiec Test. The results showed that the best model used for BBCA stocks was ARIMA (1,0,1) EGARCH (1,1) and for KLBF stoc...

Research paper thumbnail of ARMA-GARCH model for value-at-risk (VaR) prediction on stocks of PT. Astra Agro Lestari.Tbk

PT. Astra Agro Lestari Tbk (AALI) is one of the plantation companies with the largest market capi... more PT. Astra Agro Lestari Tbk (AALI) is one of the plantation companies with the largest market capitalization in Indonesia. AALI stocks traded on the stock exchange have fairly fluctuating value and volatility of stock returns are not constant (heteroskedastic). One of the risk measurements that can be used to predict the risk of stock investing is Value-at-Risk (VaR). In conditions that are heteroskedastic stock returns, risk prediction can be done with the VaR ARCH/GARCH and VaR ARCH/GARCH combination model. Empirical studies were carried out on AALI stocks for the period of August 2, 2012 until October 1, 2019. The results obtained showed that the best model was ARIMA (0,0,1)-GARCH (1,2) with AIC value of -4.9793 and MSE of 0.00005. At the 95% trust level, the VaR ARCH/ARCH value was -0.3464.

Research paper thumbnail of PENGUKURAN KINERJA PORTOFOLIO OPTIMAL CAPITAL ASSET PRICING MODEL (CAPM) DAN ARBITRAGE PRICING THEORY (APT) (Studi Kasus : Saham-saham LQ45)

Jurnal Gaussian, 2018

Investing is placing money or funds in the hope of obtaining additional or specific gains on the ... more Investing is placing money or funds in the hope of obtaining additional or specific gains on the money or funds. The capital market is one place to invest in the financial field of interest to investor. This is because the capital market gives investor the freedom to choose securities traded in the capital market in accordance with the wishes of investor. Investor are included in risk averter, that means investor will always try to avoid risk. To avoid risk, investor try to diversify their investment. Diversification concept commonly used is portfolio. To maximize the return to be earned, the investor will invest his funds into several stocks in order to earn a greater profit. Capital Asset Pricing Model (CAPM) is a balance model that describes the relation of a risk with return more simply because it uses only one variable to describe the risk. Arbitrage Pricing Theory (APT) is a balance model that used many risk variables to see the relation of risk and return. With both models wi...

Research paper thumbnail of PENGUKURAN RISIKO GLUE-VALUE-AT-RISK PADA DATA DISTRIBUSI ELLIPTICAL (Studi Kasus: Data Saham PT Indocement Tunggal Prakarsa Tbk, PT Unilever Indonesia Tbk, PT United Tractors Tbk, Periode 1 Juni 2018 – 29 November 2019)

Jurnal Gaussian, 2020

Risk measurement is carried out to determine the risk. Popular methods that can be used to measur... more Risk measurement is carried out to determine the risk. Popular methods that can be used to measure risk at a confidence level are Value-at-Risk (VaR) and Tail-Value-at-Risk (TVaR). A Risk measurement should satisfy: translation invariance, positive homogenicity, monocity and subadditivity. VaR does not satisfy one of coherent axioms, namely subadditivity. TVaR is considered capable of overcoming VaR problems, but it’s too large for a risk measure. Glue-Value-at-Risk (GlueVaR) is a method that can overcome these problems because it can be valued between VaR and TVaR and fulfills four coherent axioms. In this paper GlueVaR used in the elliptical distribution for normal distribution to measure the risk of the stock of PT Indocement Tunggal Prakarsa Tbk (INTP), PT Unilever Indonesia Tbk (UNVR), and PT United Tractors Tbk (UNTR) for the period June 1st 2018 – 29th November 2019. After knowing the stock return is normally distributed and used confidence levels of α = 95% and β = 98%, a hi...

Research paper thumbnail of Pengukuran Risiko Kredit Obligasi Korporasi Dengan Credit Value at Risk (Cvar) Dan Optimalisasi Portofolio Menggunakan Metode Mean Variance Efficient Portfolio (Mvep)

Getting benefits of many kinds of coupon is not the only advantage of bond investment, but also i... more Getting benefits of many kinds of coupon is not the only advantage of bond investment, but also it gives potential risks such as credit risk. Credit risk originates from the fact that counterparties may be unable to fulfill their contractual obligations. Credit Value at Risk (CVaR) is introduced as a method to calculate bond credit risk if default occurs. CVaR is defined as the most significant credit loss which occurs unexpectedly at the selected level of confidence, measured as the deviation of Expected Credit Loss (ECL). To construct optimal bond portfolio requires Mean variance Efficient Portfolio (MVEP) method. MVEP is defined as the portfolio with minimum variance among all possible portfolios that can be formed. This study case has been constructed through two bonds, bond VI of Jabar Banten Bank (BJB) year 2009 serial B and bond of BTPN Bank I year 2009 serial B. Based on the R programming output, the obtained results for bonds with a rating idAA BJB, has a positive CVaR val...

Research paper thumbnail of Pengaruh Data Ekstrim Aset Perusahaan Pada Valuasi Obligasi

Asumsi dasar yang sering digunakan pada valuasi obligasi merupakan penggunaan asumsi pada model B... more Asumsi dasar yang sering digunakan pada valuasi obligasi merupakan penggunaan asumsi pada model Black-Scholes-Merton. Terdapat dua asumsi yang kurang tepat digunakan dalam investasi praktis obligasi, yaitu data aset perusahaan tidak mengikuti distribusi Normal, dalam hal ini memiliki data ekstrem yang diperlihatkan dengan keberadaan jump . Selain itu pemberian kupon secara periodik merupakan hal yang wajar dalam kontrak obligasi. Paper ini akan membahas secara matematis valuasi obligasi dalam hal ini memberikan nilai ekspektasi modal perusahaan dan kemungkinan kebangkrutan perusahaan yang diakibatkan perusahaan tidak mampu membayar kembali hutang obligasinya pada saat jatuh tempo. Untuk menagkap adanya jump pada data aset perusahaan, geometric Brownian motion dengan jump diffusion merupakan model yang tepat. Sedangkan pembentukan serial pemberian kupon dapat dilakukan dengan pendekatan compound option . Penerapan kasus ini adalah dengan melakukan analisis pada Obligasi Berkelanjutan...

Research paper thumbnail of Model ARCH dan GARCH untuk Mengukur Volatilitas Harga Saham PT HM Sampoerna Tbk Indonesia (Pengukuran Volatilitas Harga Saham)

Penelitian-penelitian mengenai peramalan pada financial time series menunjukkan bahwa perilaku er... more Penelitian-penelitian mengenai peramalan pada financial time series menunjukkan bahwa perilaku error peramalan mengalami masalah autokorelasi pada variansi ut. Engle (1982) membangun model Autoregressive Conditional Heteroscedasticity (ARCH). Ide kunci dari model ARCH ini adalah variansi e pada waktu t (yaitu σt2) tergantung pada besarnya kuadrat error pada waktu ke t-1, yaitu et [1]. Bollerslev (1986) mengembangkan model ARCH ke dalam bentuk umum, yaitu Generalized Autoregressive Conditional Heteroscedasticity (GARCH). Bollerslev menyatakan bahwa variansi error tidak hanya tergantung pada error periode lalu tetapi juga variansi error dari periode lalu. Penelitian ini membahas adanya efek ARCH dan GARCH pada masalah volatilitas data Return Saham PT HM Sampoerna Indonesia Tbk periode 1 Januari 2004 sampai 30 Desember 2005. Dengan metode BoxJenkins, diperoleh Model ARIMA(1,0,1) dengan rumus: RSAHAM = -0.975978 AR(1) + 0.989613 MA(1) Menggunakan Metode Maksimum Likelihood diperoleh bah...

Research paper thumbnail of PENERAPAN ANALISIS KLASTER K-MODES DENGAN VALIDASI DAVIES BOULDIN INDEX DALAM MENENTUKAN KARAKTERISTIK KANAL YOUTUBE DI INDONESIA (Studi Kasus: 250 Kanal YouTube Indonesia Teratas Menurut Socialblade)

YouTube is one of the most popular online platforms today. The popularity of YouTube has makes it... more YouTube is one of the most popular online platforms today. The popularity of YouTube has makes it an effective advertising medium. In April 2019, Socialblade released the top 250 YouTube channels in Indonesia based on their gradations with various characteristics. YouTube channel data will be grouped into several clusters to make it easier for advertisers to choose channels with characteristics as needed. The purpose of this study is to determine the best number of clusters and determine their characteristics. The method used is the k-Modes cluster analysis with values k = 3, 4, 5, ..., 8. The k-Modes method can group objects that have categorical type variables into relatively homogeneous groups. The best number of clusters (k) can be checked using the Davies Bouldin Index (DBI). Based on the analysis carried out, obtained the best number of six clusters with a Davies-Bouldin Index value of 1.080509. The most recommended cluster for advertising is cluster 6, which has grade A chara...

Research paper thumbnail of ARIMA-GARCH Model and ARIMA-GARCH Ensemble for Value-at-Risk Prediction on Stocks Portfolio

Stocks portfolio is a form of investment that can be used to minimize the risk of loss. In a stoc... more Stocks portfolio is a form of investment that can be used to minimize the risk of loss. In a stock portfolio, the value at risk (VaR) can be predicted through the portfolio return. If portfolio return variance is heteroscedastic risk prediction can be done by using VaR with ARIMA-GARCH or Ensemble ARIMA-GARCH model approach. Furthermore, the accuracy of VaR is tested through backtesting test. In this study, the portfolio formed from Astra Agro Lestari Ltd (AALI) and Indofood Ltd (INDF) stocks from 10/02/2012 to 10/01/2019. The results showed that the best model is ARIMA(0,0,[3])-GARCH(1,2) with AIC of -5.604 and MSE 1.874e-07.At confidence level of 95% and 1 day holding period, the VaR of the ARIMA(0,0,[3])-GARCH(1,2) was -0.3464. Based on the backtesting test, it is proven to be very accurate to predict the value of loss risk because the value of the violation ratio (VR) is equal to 0.

Research paper thumbnail of Value at Risk Pada Portofolio Saham Dengan Copula Ali-Mikhail-Haq

Jurnal Gaussian, 2019

Investment is one alternative to increase assets in the future. Investors can invest in a portfol... more Investment is one alternative to increase assets in the future. Investors can invest in a portfolio to reduce the level of risk. Value at Risk (VaR) is a measuring tool that can calculate the worst loss over a given time period at a given confidence level. GARCH (Generalized Autoregressive Conditional Heteroskedasticity) is used to model data with high volatility. The teory of copula is a powerful tool for modeling joint distribution for any marginal distributions. Ali-Mikhail-Haq copula from Archimedean copula family can be applied to data with dependencies τ between -0.1817 to 0.3333. This research uses Ali-Mikhail-Haq copula with a Monte Carlo simulation to calculate a bivariate portfolio VaR from a combination stocks of PT Pembangunan Perumahan Tbk. (PTPP), PT Bank Tabungan Negara Tbk. (BBTN), and PT Jasa Marga Tbk. (JSMR) in the period of March 3, 2014 - March 1, 2019. The results of VaR calculation on bivariate portfolio for next 1 day period obtained the lowest VaR is owned b...

Research paper thumbnail of OPTIMASI REGRESI LOGISTIK MENGGUNAKAN ALGORITMA GENETIKA UNTUK PEMODELAN FAKTOR-FAKTOR YANG MEMPENGARUHI PENGGOLONGAN KREDIT BANK (Studi Kasus: Debitur di PT BPR Gunung Lawu Klaten Periode Tahun 2017)

Jurnal Gaussian, 2019

Credit is the greatest asset managed by banks and also the most dominant contributor to the bank’... more Credit is the greatest asset managed by banks and also the most dominant contributor to the bank’s income. But in its implementation, the provision of credit to the public is at risk for non-performing loans. For this reason, creditors try to minimize the occurrence of non-performing loans by predicting credit risk appropriately. In this study, modeling the factors that influence credit classification at PT BPR Gunung Lawu is useful for predicting the credit risk of prospective debtors. Modeling are done using logistic regression and genetic algorithms. Factors suspected of influencing credit classification include age, gender, marital status, education, home ownership, employment, net income, tenor, type of business, type of loan, type of loan interest, and loan size. Estimated model parameters obtained from logistic regression were optimized using genetic algorithms. The fitness function used is pseudo or and MSE. The best model is generated by modeling with genetic algorithms b...

Research paper thumbnail of Pembentukan Portofolio Optimal Dengan Metode Resampled Efficient Frontier Untuk Perhitungan Value at Risk Dilengkapi Aplikasi Gui Matlab

Jurnal Gaussian, 2019

The purpose of investors in investing is to get a return, but investors also have to bear the ris... more The purpose of investors in investing is to get a return, but investors also have to bear the risks that might exist. There are 3 types of investors in investment based on their preference for risk, namely risk aversion (risk averter), moderate risk takers (risk moderate), and high risk takers (risk takers). To obtain an optimal portfolio for each type of investor, the Resampled Efficient Frontier Method is used with Monte Carlo Simulation as much as 700 times, to obtain more parameter estimates. The results of the Resampled Efficient Frontier from Efficient Frontier will take 51 efficient points to determine the optimal portfolio for each type of investor. The efficient point taken is the 1st, 26th and 51st efficient points for the investor risk averter type, risk moderate, and risk taker. To determine the estimated loss in investment, the VaR value is calculated based on the monthly return data of BBNI, UNTR, INKP, and KLBF shares for the period February 2013 to March 2017, with a...

Research paper thumbnail of Modeling stock prices in a portfolio using multidimensional geometric brownian motion

Journal of Physics: Conference Series, 2018

View the article online for updates and enhancements. Content from this work may be used under th... more View the article online for updates and enhancements. Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.

Research paper thumbnail of Estimasi Parameter Model Regresi Non Stasionerdengan Variabel Dependen Lag : Studi Kasus Padaperkembangan Ekspor Indonesia Ke Jepangtahun 1980 - 2000

The clasiccal regression model was devised to handle relationship between stationary variables. B... more The clasiccal regression model was devised to handle relationship between stationary variables. But, many economic variables that frequently faced by econometricians when dealing with time series data, are nonstationary variables. This clearly places severe restrictions on their analysis by standard regression method. In this paper, we study regression models with a lagged dependent variable when both the dependent and independent variables are nonstationary, and the regression model is not cointegrated. In particular, we discuss the limiting properties of least squares estimates of the parameters in such regression models. We show that the estimate of the lagged dependent variable tends to unity and the estimates of the independent variables tend to zero. The results might also allow us to investigate the growth of export from Indonesian to Japan.

Research paper thumbnail of Analisis Hasil Ujian Nasional Tingkat Sma DI Kabupaten Banyumas Tingkat Sma DI Kabupaten Banyumas Menggunakan Analisis Cluster Dan Biplot

Evaluasi pendidikan dilakukan dalam rangka pengendalian mutu pendidikan secara nasional. Salah sa... more Evaluasi pendidikan dilakukan dalam rangka pengendalian mutu pendidikan secara nasional. Salah satu bentuk evaluasi pendidikan adalah dengan diadakannya ujian nasional. Untuk meningkatkan kualitas pendidikan nasional dibuatlah Rintisan Sekolah Bertaraf Internasional (RSBI). Status RSBI tersebut tidak dapat menjamin prestasi nilai Ujian Nasional (UN) meningkat sehingga perlu dilakukan penelitian untuk mengevaluasi SMA-SMA yang ada di Kabupaten Banyumas. Penelitian ini bertujuan untuk mengetahui SMA-SMA yang perlu lebih ditingkatkan lagi mutu pendidikannya sehingga perlu dilakukan pengelompokan terhadap-SMA-SMA di Kabupaten Banyumas. Pengelompokan ini perlu dilakukan karena beragamnya mutu dari ke 32 SMA yang ada di Kabupaten Banyumas sehingga hal ini menunjukkan tidak meratanya mutu dari SMA-SMA yang ada di Kabupaten Banyumas sehingga perlu dilakukan pengelompokan untuk memudahkan dalam pemberian bantuan terhadap SMA-SMA yang dinilai mempunyai kualitas rendah. Penelitian ini dilakukan dengan cara mengelompokkan SMA-SMA di Kabupaten Banyumas menjadi 3 kelompok. Analisis yang digunakan untuk pengelompokannya adalah analisis cluster dengan metode average linkage. Selanjutnya untuk mengetahui posisi SMA-SMA di Kabupaten Banyumas di lakukan analisis biplot. Adapun manfaat yang di dapat dari penelitian ini adalah dapat di deskripsikan SMA-SMA di Kabupaten Banyumas dan karakteristik nilai ujian nasional tahun 2010 untuk daerah Kabupaten Banyumas. Hasil yang diperoleh dari penelitian ini adalah berdasarkan nilai ujian nasional tahun 2010 diketahui bahwa SMA bukan RSBI mampu bersaing dengan SMA RSBI untuk Kabupaten Banyumas. Kata Kunci : Analisis Cluster, Biplot, ujian nasional 2010