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Valuasi One Period Coupon Bond dengan Aset Mengikuti Model Geometric Brownian Motion with Jump Diffusion Meiliawati Aniska; Di Asih I Maruddani; Suparti Suparti
Indonesian Journal of Applied Statistics Vol 3, No 2 (2020)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v3i2.43149

Abstract

One period coupon bond gives coupon once a bond life together with the principal debt. If the firm’s asset value on maturity date is insufficient to meet the debtholder’s claim, then the firm is stated as default. The well-known model for predicting default probability is KMV-Merton model. Under this model, it is assumed that the return on the firm’s assets is distributed normally and their behaviour can be described with the Geometric Brownian Motion (GBM) formula. In practice, most of the financial data tend to have heavy-tailed distribution. It indicates that the data contain some extreme values. GBM with Jump is a popular model to capture the extreme values. In this paper, we evaluate a corporate bond which has some extreme condition in their asset value and predicts the default probability in the maturity date. Empirical studies were carried out on bond that is issued by CIMB Niaga Bank that has a payment due in November 2020. The result shows that modelling the asset value is more appropriate by using GBM with Jump rather than GBM modelling. Estimation to CIMB Niaga Bank equity in November 2020 is IDR 246,533,573,844,229.00. The liability of this company is IDR 4,205,751,155,771.00. The prediction of CIMB Niaga Bank default probability is 1.065812 ´ 10-8 at the bond maturity. It indicates that the company is considered capable of fulfilling the obligations at the maturity date.Keywords: jump diffusion, extreme value, probability default, equity, liability
EXPECTED SHORTFALL DENGAN SIMULASI MONTE-CARLO UNTUK MENGUKUR RISIKO KERUGIAN PETANI JAGUNG Rita Rahmawati; Agus Rusgiyono; Abdul Hoyyi; Di Asih I Maruddani
MEDIA STATISTIKA Vol 12, No 1 (2019): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (526.428 KB) | DOI: 10.14710/medstat.12.1.117-128

Abstract

In risk management, risk measurement plays an important role in allocating capital as well as in controlling (and avoiding) worse risk. Estimating the risk value can be done by using a risk measure. The most popular method for evaluating risk is Value at Risk (VaR). But VaR does not fulfill the coherency as a measure of risk effectiveness. In this paper, we propose Expected Shortfall (ES) which has coherency nature. ES is defined as the conditional expectation of losses beyond VaR of the same confidence level over the same holding period. For measuring ES, we use Monte-Carlo Simulation Method. This method is applied for measuring risk that will be faced by corn’s farmers due to the changes in corn prices in Pemalang city. The results show that the ES value is 0.085472 at 95% confidence level and one-month holding period. This number means that a farmer will face 8.5472% of investment as maximum loss exceeding of VaR.
PERHITUNGAN VALUE AT RISK DENGAN PENDEKATAN THRESHOLD AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY-GENERALIZED EXTREME VALUE Mutik Dian Prabaning Tyas; Di Asih I Maruddani; Rita Rahmawati
MEDIA STATISTIKA Vol 12, No 1 (2019): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (537.145 KB) | DOI: 10.14710/medstat.12.1.73-85

Abstract

Stock is the most popular type of financial asset investment. Before buying a stock, an investor must estimate the risks which will be received. Value at Risk (VaR) is one of the methods that can be used to measure the level of risk. When investing in stock, if an investor wants to earn high returns, then he must be prepared to face higher risks. Most of stock return data have volatility clustering characteristic or there are cases of heteroscedasticity and the distribution of stock returns has heavy tail. One of the time series models that can be used to overcome the problem of heteroscedasticity is the ARCH/GARCH model, while the method for analyzing heavy tail data is Extreme Value Theory (EVT). In this study used an asymmetrical ARCH model with the Threshold ARCH (TARCH) and EVT methods with Generalized Extreme Value (GEV) to calculate VaR of the stock return from PT Bumi Serpong Damai Tbk for the period of September 2012 to October 2018. The best chosen model is AR([3])–TARCH(1). At the 95% confidence level, the maximum loss an investor will be received within the next day by using the TARCH-GEV calculation is 0.18%.
EXPECTED SHORTFALL DENGAN EKSPANSI CORNISH-FISHER UNTUK ANALISIS RISIKO INVESTASI SEBELUM DAN SESUDAH PANDEMI COVID-19 DILENGKAPI GUI R Reyuli Andespa; Di Asih I Maruddani; Tarno Tarno
Jurnal Gaussian Vol 11, No 2 (2022): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.v11i2.35457

Abstract

In financial analysis, risk measurement is critical. Stocks are a sort of financial asset investment that is in high demand by investors. Expected Shortfall is one of the strategies used to assess stock investing risk (ES). ES is a risk metric that considers losses in excess of the Value at Risk (VaR). Cornish-Fisher Expansion (ECF) is used to calculate ES with data that deviates from normality and takes into account skewness and kurtosis values. This study used data from the closing price of Sri Rejeki Isman Tbk (SRIL) shares before and during the Covid-19 Pandemic (14 January 2019 to 18 May 2021), with non-normally distributed returns. According to the calculations, the risk that investors will bear using the ES ECF value for the next day before the Covid-19 Pandemic is 1.1752 and after the Covid-19 Pandemic is 3.3177% at a 95% confidence level. The risk that investors will bear for the next day before the Covid-19 Pandemic is 5.8928%, and after the Covid-19 Pandemic is 10.3703%, based on a 99% confidence level. The findings of the study reveal that the higher the amount of trust, the higher the risk.
PEMBENTUKAN PORTOFOLIO SAHAM OPTIMAL DENGAN MEAN ABSOLUTE DEVIATION PADA DATA SAHAM JAKARTA ISLAMIC INDEX Alifia Hana Linda Rachmawati; Mustafid Mustafid; Di Asih I Maruddani
Jurnal Gaussian Vol 11, No 2 (2022): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.v11i2.35471

Abstract

In 2017 to 2020 the Jakarta Islamic Index (JII) showed a positive trend and was quite stable compared to the LQ45 index. The selection of the JII stock index in this study is intended to obtain maximum profits. Investors are expected to create a series of portfolios to get maximum profit. One of the ways to identify stocks for portfolio formation is to use factor analysis. Factor analysis is used to summarize a large number of variables into new, smaller factors. This new factor is called the portfolio. The Mean Absolute Deviation (MAD) method is used for the formation of an optimal portfolio as well as an improvement on the Markowitz method in terms of non-linear (quadratic) mathematical models. The MAD method is the mean of the absolute value of the deviation between the realized return and the expected return. The optimization technique used in the MAD portfolio is the simplex method. Optimizing the objective function by constraining the set of constraints on the simplex method is done by forming a simplex table. Based on the processing using the simplex method, the investment weight for each of the stocks that make up the first portfolio is 30% CPIN shares; 29.23% of JPFA's shares; 10.77% shares of SMGR; and 30% shares in UNVR. Meanwhile, the investment weight of the constituent stocks for the second portfolio is 30% ACES shares; 10% of ERAA's shares; 30% of INCO's shares; 30% of PGAS shares; and 0% WIKA shares. The results of portfolio performance evaluation show that portfolio 2 is better than portfolio 1, by looking at the Sharpe Index for portfolio 2 of 0.0135629 and portfolio 1 of -0.0281177.
PENGARUH KONVEKSITAS TERHADAP SENSITIVITAS HARGA JUAL DAN DELTA-NORMAL VALUE AT RISK (VAR) PORTOFOLIO OBLIGASI PEMERINTAH MENGGUNAKAN DURASI EKSPONENSIAL Putri Devitasari; Di Asih I Maruddani; Puspita Kartikasari
Jurnal Gaussian Vol 11, No 4 (2022): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.11.4.532-541

Abstract

Bonds are one of the investment instruments issued by the issuer as proof of debt.  Bond investment is relatively safe, but it is possible for investors to experience losses. Investors should always consider that trading a bond is always risky. One of the important bond risks is interest risk. The concept of duration can only explain well for small changes in interest rates but cannot explain well for large changes in interest rates. The estimation of the duration concept will have a larger calculation error with the greater changes in market interest rates that occur so it is necessary to add convexity to improve accuracy. This study aims to estimate the risk of government bonds based on the estimation of bond prices with the effect of convexity. Several studies have shown that exponential duration can predict bond prices more accurately than Macau duration. Exponential duration with convexity will be applied in this study to measure the accurate value of bond prices caused by changes in interest rates. The Delta-Normal VaR portfolio method is used to calculate risk based on estimated bond prices in the form of a portfolio. The formation of this portfolio aims to reduce the losses suffered by investors. This method is applied to four Indonesian government bonds with codes FR0056, FR0059, FR0074, and FR0080. The results showed that the bonds portfolio FR0056 and FR0074 had the smallest risk compared to other portfolios with a weight proportion of 15% for bonds FR0056 and 85% for bonds FR0074.
IMPLEMENTATION OF STOCHASTIC MODEL FOR RISK ASSESSMENT ON INDONESIAN STOCK EXCHANGE Di Asih I Maruddani; Trimono Trimono; Mas'ad Mas'ad
MEDIA STATISTIKA Vol 15, No 2 (2022): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/medstat.15.2.151-162

Abstract

Currently, financial assets become an alternative choice for investors in Indonesia to get maximum profits. The Indonesia Stock Exchange is the official capital market in Indonesia which is a place for trading financial assets. Stocks are listed as the most preferred financial asset by investors. In reality, stock investment is not a risk-free investment. The main risk that investors should face is the loss risk. This kind of risk can occur at any time. From that problem, this study aims to do risk assessment on the Indonesian stock market. The evaluation will be started with stock price index prediction using the Stochastic model (Geometric Brownian Motion Model and Jump Diffusion). Then, the result from that processes will be used to get loss risk prediction through the Adjusted Expected Shortfall model. By using the historical price of JKSE index from 01/08/21 to 31/08/22, Jump Diffusion is the best model to predict the JKSE index with MAPE value is 1.08%. Then, at the 95% confidence level and 1-day holding period, the expected loss risk using Adjusted Expected Shortfall model on 09/01/2022 is -0.02978.
PENGUKURAN NILAI RISIKO PORTOFOLIO SAHAM PADA INDEKS LQ45 DI BIDANG TELEKOMUNIKASI MENGUNAKAN METODE KOPULA CLAYTON Salsabila Syifa Binsanno; Sudarno Sudarno; Di Asih I Maruddani
Jurnal Gaussian Vol 12, No 1 (2023): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.12.1.81-91

Abstract

The characteristic of copula is non strict on certain distribution assumptions, can explain nonlinier relationship, and easily construct distribution through the marginals that do not need to come from the same distribution family. Copula will be useful for stock data that has price charts fluctuate rapidly and risk will always follow in investing. The relation between risk and copula in this study is to calculate the risk value in the stock portfolio using VaR with the generation of Monte Carlo simulation through Clayton copula on four companies engaged in telecommunications sector, namely EXCL.JK (PT XL Axiata Tbk), TLKM.JK (PT Telekomunikasi Indonesia Tbk), TOWR.JK (PT Sarana Menara Nusantara Tbk), and TBIG.JK (PT Tower Bersama Infrastructure Tbk) for period 2 January 2020 to 31 December 2021. This study resulted that the selected stock portfolios are EXCL and TBIG which had the highest risk value of -0,062741 at 99% confidence level, so when an investor will invest Rp100.000.000,00 the maximum estimated risk is Rp.6.274.100 within one day.
GLUE VALUE AT RISK UNTUK MENGUKUR RISIKO PADA PORTOFOLIO OPTIMAL DENGAN METODE MULTI INDEX MODEL Nur Khofifah; Agus Rusgiyono; Di Asih I Maruddani
Jurnal Gaussian Vol 12, No 1 (2023): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.12.1.116-125

Abstract

Creating a portfolio is one method of reducing risk. One of the best portfolio decisions is made by Multi Index Model. Multi Index Model is a method that makes use of multiple variables that impact stock returns. Before making an investment, risk measurement must be considered. Calculation of risk on a portfolio will be more accurate if it is calculated using Glue Value at Risk, because it satisfies the property of subadditivity, which is one of the coherence properties of a risk measure that reflects the idea that risk can reduce by diversification. The stocks used in this study are 4 stocks that are members of SRI-KEHATI stock group in the period January 2017 – December 2021. The factors used are Composite Stock Price Index (JCI), and Rupiah to USD exchange rate. According to the study's findings, the best portfolio consist of four stocks: BBRI (Bank Rakyat Indonesia Tbk.) (17.82%), KLBF (Kalbe Farma Tbk.) (56.66%), UNTR (United Tractors Tbk.) (24.13%), and WIKA (Wijaya Karya Tbk.) (1.39%). The confidence levels of  and , the distortion function height is  and  are used, the GlueVaR value for the stock portfolio is 10.476%. 
PENGARUH SKEWNESS DAN KURTOSIS DALAM MODEL VALUASI OBLIGASI Abdurakhman Abdurakhman; Di Asih I Maruddani
MEDIA STATISTIKA Vol 11, No 1 (2018): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (229.702 KB) | DOI: 10.14710/jhp.%v.%i.82-88

Abstract

The Gram-Charlier expansion, where skewness and kurtosis directly appear as parameters, has become popular in finance as a generalization of the normal density. Non-normal skewness and kurtosis of underlying asset of bond issuer company are significantly contributes to the phenomenon of volatility smile. Hermite polynomial is used to get an expansion of the probability distribution. In this paper, Gram-Charlier model is applied to BTPN Bond which is issued in 2017. The result showed that Gram-Charlier model is more consistent than Black-Scholes model when the skewness and kurtosis are taken into account.Keywords: Skewness, Kurtosis, Gram-Charlier, Hermite polynomial