Efficiency Analysis of Optimal Portfolio Selection for Stocks in LQ45 Index

Devianto, Dodi; Maiyastri,; Randy,; Hamidi, Masyhuri; Maryati, Sri; Ahmad, Afridian Wirahadi

doi:10.1109/icaiti.2018.8686713

Cited by 7 publications

(6 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Semakin tinggi nilai Indeks Sharpe, Jensen, dan Treynor maka makin bagus kinerja saham tersebut dan portofolio yang terdiri dari saham dengan nilai indeks tinggi dapat dikatakan portofolio optimal berdasarkan indeks kinerja keuangan. Dalam membentuk portofolio, investor harus mengetahui bagaimana membentuk portofolio yang baik yang membawa return yang besar ke tingkat risiko tertentu dari berbagai kumpulan dan jenis portofolio [3]. Investor akan memilih portofolio yang efisien dan optimal.…”

Section: Pendahuluanunclassified

See 1 more Smart Citation

Pembentukan Portofolio Optimal Berdasarkan Indeks Kinerja Keuangan Pada Saham Lq-45

Mutiasalisa¹,

Devianto²,

Hg³

2021

Jurnal Matematika UNAND

Self Cite

View full text Add to dashboard Cite

Investasi adalah suatu bentuk penanaman dana guna memberikan keuntungan tingkat pengembalian (return) baik pada masa sekarang atau dan dimasa depan. Saham adalah sebuah bukti kepemilikian nilai sebuah perusahaan. Saham merupakan salah satu instrumen investasi yang paling menarik karena memiliki mobilitas yang tinggi. Indeks kinerja keuangan yang dimaksud adalah Indeks Sharpe, Treynor dan Jensen dimana merupakan metode yang digunakan untuk mengukur kinerja keuangan suatu saham, sehingga ketiga metode tersebut dapat digunakan sebagai dasar untuk membuat sebuah portofolio. Portofolio adalah sekelompok instrumen investasi yang dipilih sebagai objek investasi dari seorang investor atau sebuah perusahaan investasi. Pada Penelitian ini data yang digunakan adalah return dari 45 saham berindeks LQ-45 pada periode Februari 2020 - Juli 2020. Menurut hasil perhitungan nilai Indeks Sharpe, Treynor dan Jensen dapat ditarik kesimpulan bahwa saham yang memiliki kinerja keuangan terbaik adalah Sarana Menara Nusantara Tbk (TOWR), Kalbe Farma Tbk (KLBF), Surya Citra Media Tbk (SCMA), Aneka Tambang (Persero) Tbk (ANTM), dan Ace Hardware Indonesia Tbk (ACES). Ketika saham yang berkinerja keuangan baik menurut Indeks Sharpe, Treynor dan Jensen disatukan sebagai sebuah portofolio maka dapat dikatakan portofolio tersebut adalah portofolio optimal berdasarkan indeks kinerja keuangan.Kata Kunci: Indeks Sharpe, Indeks Treynor, Indeks Jensen

show abstract

Section: Pendahuluanunclassified

“…Investor akan memilih portofolio yang efisien dan optimal. Portofolio yang efisien dapat diartikan sebagai portofolio yang dapat memberikan risiko terkecil dengan expected return tertentu [3]. Portofolio optimal adalah portofolio dengan kombinasi expected return dan risiko terbaik [3].…”

Section: Pendahuluanunclassified

Pembentukan Portofolio Optimal Berdasarkan Indeks Kinerja Keuangan Pada Saham Lq-45

Mutiasalisa¹,

Devianto²,

Hg³

2021

Jurnal Matematika UNAND

Self Cite

View full text Add to dashboard Cite

show abstract

“…They have had a significant impact on many sectors, such as business, education, employment, technology, and thus on the economy [2][3]. Investment is the placement of the number of funds at a certain time in the hope of making profits in the future [4]. LQ45 is an Indonesia Stock Exchange Index (ISX) made up of 45 companies that meet certain criteria to target investors to select certain stocks [5].…”

Section: Introductionmentioning

confidence: 99%

Prediction of LQ45 Index in Indonesia Stock Exchange: A Comparative Study of Machine Learning Techniques

Syukur¹,

Istiawan²

2021

IJIES

View full text Add to dashboard Cite

LQ45 is an Indonesia Stock Exchange Index (ISX) incorporate of 45 companies that meet certain criteria to target investors for selecting certain stocks. The prediction of stock price direction in the financial world is a major issue. The implementation of machine learning and other algorithms for market price analysis and forecasting is a very promising field. Different types of classification algorithms were used to predict the stock market. However, when individual studies are considered separately there is no clear consensus that algorithms work best. In this research, a comparison framework is proposed, which aims to benchmark the performance of a wide range of classification models and use them to predict the LQ45 index. The data in this research contains the transaction level and capitalization size are obtained from the Indonesian Stock Exchange (ISX). For analysis purposes, we set out 10 classifiers that can be used to build classification models and test their performance in the LQ45 dataset. The performance criterion chosen to measure this effect is accuracy, recall, and precision. The results showed that the random forest algorithm had the best performance for predicting the LQ45 index. Whilst the classification and regression trees, C4.5, support vector machine, and logistic regression algorithms also perform well. Besides, the models based on traditional statisticalbased learners that are Naïve Bayes and linear discriminant analysis seem to underperform for predicting the LQ45 index. These results are not only beneficial to enrichment the machine learning techniques literature but also have a significant influence on the stock market prediction in terms of the ability to predict the LQ45 index.

show abstract

“…In forecasting time series model, many researches which used linear and linear model in the recent years. In financial case, to choose the optimal portfolio for stocks also can be modeled as explained in [2]. While the financial performance of Islamic Rural Banks can be applied by using clustering analysis as described in [3].…”

Section: Introductionmentioning

confidence: 99%

Hybrid Model of Seasonal ARIMA-ANN to Forecast Tourist Arrivals through Minangkabau International Airport

Yollanda¹,

Devianto²

2020

Proceedings of the Proceedings of the 1st International Conference on Statistics and Analytics, ICSA 2019, 2-3 August 2019, Bog

Self Cite

View full text Add to dashboard Cite

The number of tourist arrivals forecasting is required for the future development of tourism industry to improve the economic growth. The number tourist arrivals data can be analyzed by building a model so that it will help to find out the number of tourist arrivals in the next period which is through Minangkabau International Airport. The linear model that is used is Seasonal Autoregressive Integrated Moving Average (SARIMA) used and continued to build a nonlinear model of the residual SARIMA model using Artificial Neural Network (ANN). In this research, SARIMA model which obtained is SARIMA (1, 0, 1) (1, 1, 0) 12. But, residual of SARIMA model has not been fulfilled an autocorrelation assumption so that it isproposed a new model of SARIMA-ANN. The residual model of SARIMA is built using the ANN model architecture with 2-2-2-1 network topology. The performance rate of time series model of tourist arrivals which is the data started on January 2012 until March 2019 is measured using Mean Absolute Percentage Error (MAPE). Based on the MAPE value of 17.1770% indicates that the model obtained having good performance to forecast the number of tourist arrivals through Minangkabau International Airport in the future.

show abstract

Efficiency Analysis of Optimal Portfolio Selection for Stocks in LQ45 Index

Cited by 7 publications

References 17 publications

Pembentukan Portofolio Optimal Berdasarkan Indeks Kinerja Keuangan Pada Saham Lq-45

Pembentukan Portofolio Optimal Berdasarkan Indeks Kinerja Keuangan Pada Saham Lq-45

Prediction of LQ45 Index in Indonesia Stock Exchange: A Comparative Study of Machine Learning Techniques

Hybrid Model of Seasonal ARIMA-ANN to Forecast Tourist Arrivals through Minangkabau International Airport

Contact Info

Product

Resources

About