PurposeMotivated by the recent theoretical rehabilitation of mean-variance analysis, the authors revisit the question of whether minimum variance (MinVar) or maximum Sharpe ratio (MaxSR) investment weights are preferable in practical portfolio formation.Design/methodology/approachThe authors answer this question with a focus on mainstream investors which can be modeled by a preference for simple portfolio optimization techniques, a tendency to cling to past asset characteristics and a strong interest in index products. Specifically, in a rolling-window approach, the study compares the out-of-sample performance of MinVar and MaxSR portfolios in two asset universes covering multiple asset classes (via investable indices and their subindices) and for two popular input estimation methods (full covariance and single-index model).FindingsThe authors find that, regardless of the setting, there is no statistically significant difference between MinVar and MaxSR portfolio performance. Thus, the choice of approach does not matter for mainstream investors. In addition, the analysis reveals that, contrary to previous research, using a single-index model does not necessarily improve out-of-sample Sharpe ratios.Originality/valueThe study is the first to provide an in-depth comparison of MinVar and MaxSR returns which considers (1) multiple asset classes, (2) a single-index model and (3) state-of-the-art bootstrap performance tests.
The purpose of this research is to determine the optimal portfolio for manufacturing entities listed on the Indonesian Sharia Stock Index based on a single index model test. The population of this research is manufacturing entities that have been listed in the Indonesian Sharia Stock Index on the Indonesia Stock Exchange for the Period 2019-2020. This study uses a purposive sampling technique using several criteria. Based on this technique, 31 entities meet the criteria. The results showed that the expected return was 5.65%, and the possible risk was 0.22% for 15 (fifteen) stocks included in the optimal portfolio category.
ABSTRAKTujuan penelitian ini adalah untuk mengetahui reaksi pasar modal Indonesia ketika terjadi peristiwa politik di Internasional. Perusahaan LQ45 periode Agustus 2020–Januari 2021 dipilih sebagai populasi dan sampel dengan menggunakan metode sample jenuh. Teknik single index model digunakan untuk mencari abnormal return. Periode jendela peristiwa lima belas hari, dan tiga puluh hari periode estimasi dengan teknik analisis data gabungan antara One Sample t-test, One Sample Wilcoxon Signed Rank Test, dan Paired Sample t-test. Hasil analisis menunjukan tidak terdapat imbal hasil tak normal yang signifikan di sekitar periode peristiwa, tetapi kondisi abnormal return sebelum dan sesudah peristiwa pilpres AS 2020 mengalami perbedaan yang signifikan. Terdapat trading volume activity yang signifikan selama lima belas hari di sekitar periode peristiwa tersebut. Terjadi reaksi di LQ45 pada abnormal return tetapi tidak signifikan dengan trading volume activity yang signifikan. Dengan mempertimbangkan kedua hal tersebut pada saat terjadinya suatu peristiwa politik, investor dapat mengambil sikap dengan menggunakan analisis mendalam tentang kecenderungan return yang terdapat di sebuah pasar modal. ABSTRACTThe purpose of this research is to determine the reaction of the Indonesian capital market when international political events occur. LQ45 companies for the period August 2020–January 2021 were selected as the population and sample, using the saturated sample method. With the single index model technique to find the abnormal return. The event window period is fifteen days, and the estimation period is thirty days with a combined data analysis technique between One Sample t-test, one sample Wilcoxon Signed Rank Test and Paired Sample t-test. The results of the analysis showed that there were no significant abnormal returns around the event period, but the abnormal return conditions before and after the 2020 US presidential election experienced significant differences. There was significant trading volume activity for fifteen days around the event period. There was a reaction in LQ45 on abnormal returns but not significant with significant trading volume activity. By considering these two things when a political event occurs, investors can take a stand by using an in-depth analysis of the trend of returns in a capital market.
The research dealt with a comparative study between some semi-parametric estimation methods to the Partial linear Single Index Model using simulation. There are two approaches to model estimation two-stage procedure and MADE to estimate this model. Simulations were used to study the finite sample performance of estimating methods based on different Single Index models, error variances, and different sample sizes , and the mean average squared errors were used as a comparison criterion between the methods were used. The results showed a preference for the two-stage procedure depending on all the cases that were used
This paper examines how to build a portfolio and assess the impact of the COVID-19 on portfolio performance using the Sharpe single index model. The research sample consists of ten high market capitalization stocks representing five price fractions of the population listed stocks on the Indonesia Stock Exchange during the COVID-19 outbreak from March 1 to May 31, 2020. The results show that there are four stocks that are included in the portfolio formation, namely CASA with a proportion of 50%, BNLI with a proportion of 26 %, UNVR with a proportion of 15%, and HMSP with a proportion of 9%. Based on portfolio performance testing using the Sharpe single index model, it is known that the portfolio during the COVID-19 has a negative Sharpe ratio, meaning that portfolio performance is underperforming. The findings provide evidence that COVID-19 has had a negative impact on the stock market so that many investors have suffered losses on their portfolios. The implications of findings are that investors must evaluate portfolio performance and restructure the formation of new portfolios by considering the COVID-19 pandemic outbreak as a systematic risk factor that can determine the expected returns.