Aghnitama, R. D., Aufa, A. R., & Hersugondo, H. (2021). Market Capitalization dan Profitabilitas Perusahaan dengan FAR, AGE, EPS, dan PBV Sebagai Variabel Kontrol. 
Jurnal Akuntansi Dan Manajemen, 
18(02), 01–11. Retrieved from 
https://doi.org/10.36406/jam.v18i02.392
Amédée-Manesme, C. -O., Barthélémy, F., & Maillard, D. (2019). Computation of the Corrected Cornish–Fisher Expansion Using the Response Surface Methodology: Application to VaR and CVaR. 
Annals of Operations Research, 
281(1–2), 423–453. Retrieved from 
https://doi.org/10.1007/s10479-018-2792-4
Ansari, J., & Rüschendorf, L. (2020). Upper Risk Bounds in Internal Factor Models with Constrained Specification Sets. 
Probability, Uncertainty and Quantitative Risk, 
5(1), 3. Retrieved from 
https://doi.org/10.1186/s41546-020-00045-y
Bernard, C., Denuit, M., & Vanduffel, S. (2018). Measuring Portfolio Risk Under Partial Dependence Information. 
Journal of Risk and Insurance, 
85(3), 843–863. 
https://doi.org/10.1111/jori.12165
Bernard, C., Rüschendorf, L., & Vanduffel, S. (2017). Value-at-Risk Bounds with Variance Constraints. 
Journal of Risk and Insurance, 
84(3), 923–959. Retrieved from 
https://doi.org/10.1111/jori.12108
Bouhadjar, M., Zeghdoudi, H., & Remita, M. R. (2016). On Stochastic Orders and their Applications: Policy Limits and Deductibles. 
Applied Mathematics & Information Sciences, 
10(4), 1385–1392. Retrieved from 
https://doi.org/10.18576/amis/100417
Chen, X., Liu, Q., & Tong, X. T. (2022). Dimension Independent Excess Risk by Stochastic Gradient Descent. 
Electronic Journal of Statistics, 
16(2). 
https://doi.org/10.1214/22-EJS2055
Cheung, K. C., & Vanduffel, S. (2013). Bounds for Sums of Random Variables When the Marginal Distributions and the Variance of the Sum Are Given. 
Scandinavian Actuarial Journal, 
2013(2), 103–118. Retrieved from 
https://doi.org/10.1080/03461238.2011.558186
Christoph, G., Monakhov, M. M., & Ulyanov, V. V. (2020). Second-Order Chebyshev–Edgeworth and Cornish–Fisher Expansions for Distributions of Statistics Constructed from Samples with Random Sizes. 
Journal of Mathematical Sciences, 
244(5), 811–839. Retrieved from 
https://doi.org/10.1007/s10958-020-04655-x
Dhaene, J., Linders, D., Schoutens, W., & Vyncke, D. (2014). A Multivariate Dependence Measure for Aggregating Risks. 
Journal of Computational and Applied Mathematics, 
263, 78–87. Retrieved from 
https://doi.org/10.1016/j.cam.2013.12.010
Fernandez, M., Almaazmi, M. M., & Joseph, R. (2020). Foreign Direct Investment In Indonesia: An Analysis From Investors Perspective. 
International Journal of Economics and Financial Issues, 
10(5), 102–112. Retrieved from 
https://doi.org/10.32479/ijefi.10330
Florea, A., Păltănea, E., & Bălă, D. (2015). Convex Ordering Properties and Applications. 
Journal of Mathematical Inequalities, 
4, 1245–1257. Retrieved from 
https://doi.org/10.7153/jmi-09-95
Hadiyoso, A., Firdaus, M., & Sasongko, H. (2016). Building an Optimal Portfolio on Indonesia Sharia Stock Index (ISSI). 
Bisnis & Birokrasi Journal, 
22(2). Retrieved from 
https://doi.org/10.20476/jbb.v22i2.5699
Hanbali, H., Dhaene, J., & Linders, D. (2022). Dependence Bounds for the Difference of Stop-Loss Payoffs on the Difference of Two Random Variables. 
Insurance: Mathematics and Economics, 
107, 22–37. Retrieved from 
https://doi.org/10.1016/j.insmatheco.2022.07.008
Hersugondo, H., Ghozali, I., Handriani, E., Trimono, T., & Pamungkas, I. D. (2022). Price Index Modeling and Risk Prediction of Sharia Stocks in Indonesia. 
Economies, 
10(1), 17. Retrieved from 
https://doi.org/10.3390/economies10010017
Irsan, M. Y. T., Priscilla, E., & Siswanto, S. (2022). Comparison of Variance Covariance and Historical Simulation Methods to Calculate Value At Risk on Banking Stock Portfolio. 
Jurnal Matematika, Statistika Dan Komputasi, 
19(1), 241–250. Retrieved from 
https://doi.org/10.20956/j.v19i1.21436
Jain, A. K., & Gupta, B. B. (2018). Towards Detection of Phishing Websites on Client-Side Using Machine Learning Based Approach. 
Telecommunication Systems, 
68(4), 687–700. Retrieved from 
https://doi.org/10.1007/s11235-017-0414-0
Kumar, C. D. N., & Srinivasan, S. (2014). PDF of the Random Variable When Its Distribution Function Changes after the Change Points. 
Applied Mathematical Sciences, 
8, 337–343. Retrieved from 
https://doi.org/10.12988/ams.2014.311627
Ortega-Jiménez, P., Sordo, M. A., & Suárez-Llorens, A. (2021). Stochastic Comparisons of Some Distances between Random Variables. 
Mathematics, 
9(9), 981. Retrieved from 
https://doi.org/10.3390/math9090981
Radović, M., Radukić, S., & Njegomir, V. (2018). The Application of the Markowitz’s Model in Efficient Portfolio Forming on the Capital Market in the Republic of Serbia. 
Economic Themes, 
56(1), 17–34. Retrieved from 
https://doi.org/10.2478/ethemes-2018-0002
Ridha, M. R., & Budi, N. (2020). The Effect of Foreign Direct Investment, Human Development and Macroeconomic Condition on Economic Growth: Evidence from Indonesia. 
Journal of Indonesian Applied Economics, 
8(2), 46–54. Retrieved from 
https://jiae.ub.ac.id/index.php/jiae/article/view/299
Salsabila, A., & Hasnawati, S. (2018). Value-at-Risk and Expected Returns of Portfolio (Companies Listed on LQ45 Index Period 2013–2016). 
KnE Social Sciences, 
3(10). Retrieved from 
https://doi.org/10.18502/kss.v3i10.3407
Sumaji, Y. M. P., Hsu, W.-H. L., & Salim, U. (2017). Analysis of Market Rısk in Stock Investment Usıng Value at Rısk Method (Study on Manufacturıng Companıes in Lq-45 Lısted on Indonesıa Stock Exchange). 
Asia Pacific Management and Business Application, 
6(1), 1–14. Retrieved from 
https://doi.org/10.21776/ub.apmba.2017.006.01.1
Sun X., Dhaene, J., & Vanmaele M. (2018). Efficient Computation of the Optimal Strikes in the Comonotonic Upper Bound for an Arithmetic Asian Option. 
International Journal of Applied Mathematics and Statistics, 
57(4), 95–106. Retrieved from 
https://doi.org/10.1016/S0167-6687(99)00051-7
Tarno, T., Maruddani, D. A. I., Rahmawati, R., Hoyyi, A., Trimono, T., & Munawar, M. (2020). ARIMA-GARCH Model and ARIMA-GARCH Ensemble for Value-at-Risk Prediction on Stocks Portfolio. 
Preprints, 1–14. Retrieved from 
https://share.google/bKWDXhnB7mOSGAtKz
Tarno, T., Trimono, T., Maruddani, D. A. I., Wilandari, Y., & Utami, R. S. (2022a). Risk Assessment of Stocks Portfolio through Ensemble Arma-Garch and Value at Risk (Case Study: Indf.Jk and Icbp.Jk Stock Price). 
Media Statistika, 
14(2), 125–136. Retrieved from 
https://doi.org/10.14710/medstat.14.2.125-136
Tarno, T., Trimono, T., Maruddani, D. A. I., Wilandari, Y., & Utami, R. S. (2022b). Risk Assessment Of Stocks Portfolio Through Ensemble Arma-Garch And Value At Risk (Case Study: Indf.Jk And Icbp.Jk Stock Price). 
Media Statistika, 
14(2), 125–136. Retrieved from 
https://doi.org/10.14710/medstat.14.2.125-136
Trimono, Susilo, A., Handayani, D., & Syuhada, K. (2019). Bounds of Adj-TVaR Prediction for Aggregate Risk. 
Indonesian Journal of Pure and Applied Mathematics., 
1(1), 1–7. Retrieved from 
https://doi.org/10.15408/inprime.v1i1.12788
Westgaard, S., Frydenberg, S., Andersen Sveinsson, J., & Aaløkken, M. (2020). Performance of Value-At-Risk Averaging in the Nordic Power Futures Market. 
The Journal of Energy Markets. Retrieved from 
https://doi.org/10.21314/JEM.2020.207
Zanfelicce, R. L., & Rabechini Jr, R. (2021). The Influence of Risk Management on the Project Portfolio Success – Proposal of a Risk Intensity Matrix. 
Gestão & Produção, 
28(2). Retrieved from 
https://doi.org/10.1590/1806-9649-2020v28e5264
Zhou, M., Dhaene, J., & Yao, J. (2018). An Approximation Method for Risk Aggregations and Capital Allocation Rules Based on Additive Risk Factor Models. 
Insurance: Mathematics and Economics, 
79, 92–100. Retrieved from 
https://doi.org/10.1016/j.insmatheco.2018.01.002
Zhou, R., & Palomar, D. P. (2021). Solving High-Order Portfolios via Successive Convex Approximation Algorithms. 
IEEE Transactions on Signal Processing, 892–904. Retrieved from 
https://share.google/zqlbjcLYEfcaCOhCg