scholarly journals PENERAPAN METODEEXPECTED SHORTFALLPADA PENGUKURAN RISIKO INVESTASI SAHAM DENGAN VOLATILITAS MODEL GARCH

2019 ◽  
Vol 8 (1) ◽  
pp. 184-193
Author(s):  
Nurul Fitria Fitria Rizani ◽  
Mustafid Mustafid ◽  
Suparti Suparti
Keyword(s):  
At Risk ◽  
Value At Risk ◽  
Stock Price ◽  
Garch Model ◽  
Expected Shortfall ◽  
Conditional Heteroskedasticity ◽  
Investment Risk ◽  
Stock Investment ◽  
Autoregressive Conditional Heteroskedasticity ◽  
High Volatility

One of the methods that can be used to measure stock investment risk is Expected Shortfall (ES). ES is an expectation of risk size which value is greater than Value at Risk (VaR), ES has characteristics of sub-additive and convex. The Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model is used to model stock data that has high volatility. Calculating ES is done with data that shows deviations from normality using Cornish-Fisher's expansion. This researchapplies the ES at the closing stock price of PT Astra International Tbk. (ASII), PT Bank Negara Indonesia (Persero) Tbk. (BBNI), and PT Indocement Tunggal Prakarsa Tbk. (INTP) for the period of 11 February 2013 - 31 March 2019. Based on the volatility of GARCH (1,1) analysis, we find ES calculation for each stock by 95% level  confidence. The ES for ASII shares is 4.1%, greater than the VaR value which isonly 2.64%.The ES for BBNI shares is 4.38%, greater than it’s VaR value which is only 2,86%. The ES for INTP shares is 6.22%, which is also greater than it’s VaR value which is only3,99%. The greather of VaR then Thegreather of ES obtained.Keywords: Expected Shortfall, Value at Risk, GARCH

EXPECTED SHORTFALL PADA PORTOFOLIO OPTIMAL DENGAN METODE SINGLE INDEX MODEL (Studi Kasus pada Saham IDX30)

2021 ◽  
Vol 10 (2) ◽  
pp. 269-278
Author(s):  
Eis Kartika Dewi ◽  
Dwi Ispriyanti ◽  
Agus Rusgiyono
Keyword(s):  
At Risk ◽  
Value At Risk ◽  
Market Price ◽  
Expected Shortfall ◽  
Optimal Portfolio ◽  
Share Price ◽  
Single Index ◽  
Index Model ◽  
Single Index Model ◽  
Stock Investment

Stock investment is a commitment to a number of funds in marketable securities which shows proof of ownership of a company with the aim of obtaining profits in the future. For obtaining optimal returns from stock investments, investors are expected to form optimal portfolios. The optimal portfolio formation using the Single Index Model is based on the observation that a stock fluctuates in the direction of the market price. It shows that most stocks tend to experience price increases if the market share price rises, and vice versa. Selection of optimal portfolio-forming stocks on IDX30 using the Single Index Model method produces 4 stocks, that are BRPT (Barito Pacific Tbk.) with weight 31.134%, ICBP (Indofood CBP Sukses Makmur Tbk.) 17.138%, BBCA (Bank Central Asia Tbk.) 51.331% and SMGR (Semen Indonesia (Persero) Tbk.) 0.397%. Every investment must have a risk, for that investors need to calculate the possible risks that occur before investing. To calculate risk, Expected Shortfall (ES) is used as a measure of risk that is better than Value at Risk (VaR) because ES fulfill the subadditivity. At the 95% confidence level, the ES value is 23.063% while the VaR value is 10.829%. This means that the biggest possible risk that an optimal portfolio investor will receive using the Single Index Model for the next five weeks is 23.063%.Keywords : Portfolio, Single Index Model, Expected Shortfall, Value at Risk.

scholarly journals Risk Analysis of Gold Sale Price and Investment of Antam Shares Using Expected Shortfall in Pandemic Covid-19

2021 ◽  
Vol 17 (3) ◽  
pp. 428-437
Author(s):  
Dwi Sulistiowati ◽  
Maya Sari Syahrul ◽  
Ilham Dangu Rianjaya
Keyword(s):  
Value At Risk ◽  
Stock Price ◽  
Financial Analysis ◽  
Measurement Model ◽  
Gold Price ◽  
Conditional Heteroskedasticity ◽  
Sale Price ◽  
High Increase ◽  
Investment Funds ◽  
Stock Investment

The Covid-19 pandemic caused the price of gold produced by PT Aneka Tambang (Antam) to experience a high increase following the world gold price, while stock investment decreased. Measuring risk is significant in financial analysis; this is related to investment funds, which are quite large and narrow about public funds. This study analyzes the risk data on Antam gold price and Antam stock closing price with an estimated Shortfall (ES). The method used to measure the risk of investing in stocks is ES. ES is the expectation of a conditional loss that exceeds Value at Risk (VaR). To compute ES data showing deviations from normality and Cornish-Fisher expansion. The volatility measurement model used is the autoregressive conditional heteroskedasticity (ARCH) and generalized ARCH (GARCH) model.This study found that the ES value of Antam gold price was smaller than Antam stock price.

scholarly journals Model ARIMA-GARCH Pada Peramalan Harga Saham PT. Jasa Marga (Persero)

2021 ◽  
Vol 3 (3) ◽  
pp. 164-170
Author(s):  
Fransisca Trisnani Ardikha Putri ◽  
Etik Zukhronah ◽  
Hasih Pratiwi
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Moving Average ◽  
Garch Model ◽  
Conditional Heteroskedasticity ◽  
Autoregressive Integrated Moving Average ◽  
Autoregressive Conditional Heteroskedasticity

Abstract– PT Jasa Marga is a great reputation company, the leader in comparable businesses, has a steady income, and paying dividends consistently. This paper aims to find the best model to forecast stock price of PT Jasa Marga using ARIMA-GARCH. The data used is daily stock price of PT Jasa Marga from March 2020 to March 2021. Autoregressive Integrated Moving Average (ARIMA) is a method that can be used to forecast stock prices. However, an economical data tend to have heteroscedasticity problems, one of the methods used to overcome them is Generalized Autoregressive Conditional Heteroskedasticity (GARCH). Future stock price of PT Jasa Marga is forecasted with ARIMA-GARCH model.  The data is modeled with ARIMA first, if there is heteroscedasticity, combine the model with GARCH model. The result of this study indicated that ARIMA (1, 1, 1) – GARCH (2, 2) is the best model, with MAPE 1,5647 Abstrak– PT Jasa Marga adalah perusahaan yang reputasinya baik, terdepan di perusahaan-perusahaan sejenis, stabil pendapatannya, dan pembayaran devidennya konsisten. Paper ini bertujuan untuk mencari model terbaik dalam meramalkan harga saham PT Jasa Marga menggunakan ARIMA-GARCH. Data harga saham yang diolah yaitu data sekunder dari PT Jasa Marga pada Maret 2020 hingga Maret 2021. Autoregressive Integrated Moving Average (ARIMA) sebagai metode yang dapat dimanfaatkan guna meramalkan harga saham. Akan tetapi, data tentang ekonomi cenderung memiliki masalah heteroskedastisitas, metode yang umum dipakai untuk mengatasinya adalah Generalized Autoregressive Conditional Heteroskedasticity (GARCH). Harga saham PT Jasa Marga diramalkan dengan model ARIMA-GARCH.  Data terlebih dahulu dimodelkan dengan ARIMA, jika didapati adanya heteroskedastisitas, maka model tersebut dikombinasikan dengan GARCH. Penelitian ini menghasilkan ARIMA (1,1,1)-GARCH(2,2) sebagai model terbaik dengan MAPE 1,5647.

scholarly journals VALUE AT RISK PADA PORTOFOLIO SAHAM DENGAN COPULA ALI-MIKHAIL-HAQ

2019 ◽  
Vol 8 (4) ◽  
pp. 543-556
Author(s):  
Delsy Nurutsaniyah ◽  
Tatik Widiharih ◽  
Di Asih I Maruddani
Keyword(s):  
At Risk ◽  
Monte Carlo ◽  
Confidence Level ◽  
Value At Risk ◽  
Joint Distribution ◽  
Conditional Heteroskedasticity ◽  
Model Data ◽  
Time Period ◽  
High Volatility ◽  
Measuring Tool

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 by bivariate portfolio between PTPP and JSMR with a weight of 30% and 70% at confidence level of 99%, 95%, and 90% respectively are 4.014%, 2.545%, and 1.876%.Keywords: Value at Risk, GARCH, Ali-Mikhail-Haq Copula, Monte Carlo

Several Extended CAViaR Models and Their Applications to the VaR Forecasting of the Security Markets

2016 ◽  
Vol 20 (4) ◽  
pp. 590-596
Author(s):  
Xiaorong Yang ◽  
◽  
Chun He ◽  
Jie Chen
Keyword(s):  
At Risk ◽  
Value At Risk ◽  
Security Market ◽  
Conditional Heteroskedasticity ◽  
Model Stability ◽  
Threshold Autoregressive ◽  
Security Markets ◽  
Autoregressive Conditional Heteroskedasticity ◽  
Out Of Sample ◽  
Conditional Autoregressive

The conditional autoregressive Value-at-Risk (CAViaR) model, as a conditional autoregressive specification for calculating the Value-at-Risk (VaR) of the security market, has been receiving more and more attentions in recent years. As asymmetry may have a significant influence on the markets and the returns may have an autoregressive mean, this study proposes some extended CAViaR models, including asymmetric indirect threshold autoregressive conditional heteroskedasticity (TARCH) model and indirect generalized autoregressive conditional heteroskedasticity (GARCH) model with an autoregressive mean. We also present two types of CAViaR-Volatility models by adding the volatility term as an exogenous explanatory variable. Our empirical results indicate that extended models perform more effectively on out-of-sample predictions, as both forecasting effect and model stability have been improved. In addition, we find that the forecasting effect is better at the lower quantile (1%) than at the higher quantile (5%); a possible explanation is that extreme market information has more impact on VaR. In addition, there is negative correlation between volatility and VaR; VaR decreases as volatility increases.

scholarly journals COPULA FRANK UNTUK PERHITUNGAN VALUE AT RISK PORTOFOLIO BIVARIAT PADA MODEL EXPONENTIAL GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY

2022 ◽  
Vol 10 (4) ◽  
pp. 562-572
Author(s):  
Eka Anisha ◽  
Di Asih I Maruddani ◽  
Suparti Suparti
Keyword(s):  
At Risk ◽  
Value At Risk ◽  
Stock Price ◽  
Var Model ◽  
Asymmetric Effect ◽  
Time Period ◽  
High Volatility ◽  
Measuring Tool ◽  
Stock Portfolio ◽  
Autoregressive Conditional Heteroscedasticity

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 stocks was ARIMA (1,0,1) EGARCH (1,2). The amount of risk with a 95% confidence level used a combination of the EGARCH and Copula-Frank models was 2.233% of today's investment. Based on the backtesting test used the Kupiec Test, the VaR model of the portfolio obtained was declared valid.

scholarly journals Studi Perbandingan Nilai Value at Risk Antara Saham Berbasis Syariah Dengan Saham Non Syariah Periode 2010-2012

2016 ◽  
Vol 3 (1) ◽  
pp. 26-36
Author(s):  
Fransissco Nicolas Sapari ◽  
Agus Zainul Arifin
Keyword(s):  
At Risk ◽  
Capital Market ◽  
Value At Risk ◽  
Garch Model ◽  
Stock Investment ◽  
Risk Characteristic

This study aimed to empirically compare the risk between sharia and non-sharia based stock investment. The Sharia stocks are refereed to stocks that issued by companies listed in LQ-45, whereas the non-sharia stocks are defined as stocks that are issued by companies listed in Jakarta Indonesia Index (JII) between 2011 and 2012. In total, there were 25 companies listed in LQ-45 and 15 companies listed in JII which were involved in this study. This study used GARCH model to estimate the risk of every individual stock. The result showed that there was a difference in risk between sharia and non-sharia based stock. This study also documented that non-Sharia based stocks were more risky than Sharia-based stodcks. Finally, this study provides information on risk characteristic in Indonesia Capital Market.

Sign in / Sign up

Export Citation Format

Share Document