scholarly journals An Empirical Assessment of Alternative Methods of Variance-Covariance Matrix

2020 ◽  
Vol 9 (4) ◽  
pp. 390-401
Author(s):  
AHSEN SAGHIR ◽  
SYED MUHAMMAD ALI TIRMIZI
Keyword(s):  
Stock Exchange ◽  
Risk Behaviour ◽  
Minimum Variance ◽  
Additional Benefit ◽  
Alternative Methods ◽  
Portfolio Construction ◽  
Mean Square ◽  
Data Set ◽  
Portfolio Managers ◽  
Mean Variance

The current study aims at the estimation of a group of variance-covariance methods using the data set of the non-financial sector of the Pakistan stock exchange. The study compares nine covariance estimators using two assessment criteria of root mean square error and standard deviation of minimum variance portfolios to gauge on accuracy and effectiveness of estimators. The findings of the study based on RMSE and risk behaviour of MVPs suggest that portfolio managers receive no additional benefit for using more sophisticated measures against equally weighted variance-covariance estimators in the construction of portfolios. Keywords: Variance-Covariance Estimators, Portfolio Construction, Mean-Variance Optimization.

scholarly journals Shrinking the Variance-Covariance Matrix: Simpler is Better

2016 ◽  
Vol 21 (1) ◽  
pp. 1-21 ◽  
Author(s):  
Muhammad Husnain ◽  
Arshad Hassan ◽  
Eric Lamarque
Keyword(s):  
Root Mean Square Error ◽  
Covariance Matrix ◽  
Mean Square Error ◽  
Minimum Variance ◽  
Factor Models ◽  
The Philippines ◽  
Risk Profile ◽  
Additional Benefit ◽  
Mean Square ◽  
Weighted Portfolio

This study focuses on the estimation of the covariance matrix as an input to portfolio optimization. We compare 12 covariance estimators across four categories – conventional methods, factor models, portfolios of estimators and the shrinkage approach – applied to five emerging Asian economies (India, Indonesia, Pakistan, the Philippines and Thailand). We find that, in terms of the root mean square error and risk profile of minimum variance portfolios, investors gain no additional benefit from using the more complex shrinkage covariance estimators over the simpler, equally weighted portfolio of estimators in the sample countries.

scholarly journals The influence of volatility spill-overs and market beta on portfolio construction

2015 ◽  
Vol 18 (2) ◽  
pp. 277-290 ◽  
Author(s):  
André Heymans ◽  
Wayne Peter Brewer
Keyword(s):  
Stock Returns ◽  
The Other ◽  
Portfolio Construction ◽  
Investment Portfolio ◽  
Model Framework ◽  
Additional Measure ◽  
Market Beta ◽  
Portfolio Managers ◽  
Top 40 ◽  
Mean Variance

This study adds to Modern Portfolio Theory (MPT) by providing an additional measure to market beta in constructing a more efficient investment portfolio. The additional measure analyses the volatility spill-over effects among stocks within the same portfolio. Using intraday stock returns from five top-40 listed stocks on the JSE between July 2008 and April 2010, volatility spill-over effects were estimated with a residual- based test (aggregate shock [AS] model) framework. It is shown that when a particular stock attracted fewer volatility spill-over effects from the other stocks in the portfolio, the overall portfolio volatility decreased as well. In most cases market beta showcased similar results. Therefore, in order to construct a more efficient risk- adjusted portfolio, one requires both a portfolio that has a unit correlation with the market (beta-based), and stocks that showcase the least amount of volatility spill-over effects amongst one another. These results might assist portfolio managers to construct lower mean variance portfolios.

scholarly journals A New Adaptive Entropy Portfolio Selection Model

Entropy ◽  
2020 ◽  
Vol 22 (9) ◽  
pp. 951
Author(s):  
Ruidi Song ◽  
Yue Chan
Keyword(s):  
Portfolio Selection ◽  
Stock Exchange ◽  
Selection Model ◽  
Portfolio Performance ◽  
Entropy Model ◽  
Data Set ◽  
Entropy Measurement ◽  
Self Adaptation ◽  
Portfolio Selection Model ◽  
Mean Variance

In this paper, we propose an adaptive entropy model (AEM), which incorporates the entropy measurement and the adaptability into the conventional Markowitz’s mean-variance model (MVM). We evaluate the performance of AEM, based on several portfolio performance indicators using the five-year Shanghai Stock Exchange 50 (SSE50) index constituent stocks data set. Our outcomes show, compared with the traditional portfolio selection model, that AEM tends to make our investments more decentralized and hence helps to neutralize unsystematic risks. Due to the existence of self-adaptation, AEM turns out to be more adaptable to market fluctuations and helps to maintain the balance between the decentralized and concentrated investments in order to meet investors’ expectations. Our model applies equally well to portfolio optimizations for other financial markets.

Pengaruh Reputasi Underwriter, Umur Perusahaan, dan Persentase Penawaran Saham 53 kepada Publik terhadap Underpricing

2016 ◽  
Vol 8 (1) ◽  
pp. 53-74
Author(s):  
Maria Jeanne ◽  
Chermian Eforis
Keyword(s):  
Initial Public Offering ◽  
Stock Price ◽  
Stock Exchange ◽  
Secondary Data ◽  
Secondary Market ◽  
Financial Statement ◽  
Data Set ◽  
Multiple Regression Method ◽  
Underwriter Reputation ◽  
Public Offering

The objective of this research is to obtain empirical evidence about the effect of underwriter reputation, company age, and the percentage of share’s offering to public toward underpricing. Underpricing is a phenomenon in which the current stock price initial public offering (IPO) was lower than the closing price of shares in the secondary market during the first day. Sample in this research was selected by using purposive sampling method and the secondary data used in this research was analyzed by using multiple regression method. The samples in this research were 72 companies conducting initial public offering (IPO) at the Indonesian Stock Exchange in the period January 2010 - December 2014; perform initial offering of shares; suffered underpricing; has a complete data set forth in the company's prospectus, IDX monthly statistics, financial statement and stock price site (e-bursa); and use Rupiah currency. Results of this research were (1) underwriter reputation significantly effect on underpricing; (2) company age do not effect on underpricing; and (3) the percentage of share’s offering to public do not effect on undepricing. Keywords: company age, the percentage of share’s offering to public, underpricing, underwriter reputation.

Evaluation for estimating of the PDF and the CDF of Generalized Inverted Exponential Distribution with Application in Industry

2020 ◽  
pp. 507-522
Author(s):  
Parisa Torkaman
Keyword(s):  
Least Squares ◽  
Exponential Distribution ◽  
Mean Squared Error ◽  
Weighted Least Squares ◽  
Real Data ◽  
Minimum Variance ◽  
Cumulative Distribution ◽  
Estimation Methods ◽  
Data Set ◽  
Better Than

The generalized inverted exponential distribution is introduced as a lifetime model with good statistical properties. This paper, the estimation of the probability density function and the cumulative distribution function of with five different estimation methods: uniformly minimum variance unbiased(UMVU), maximum likelihood(ML), least squares(LS), weighted least squares (WLS) and percentile(PC) estimators are considered. The performance of these estimation procedures, based on the mean squared error (MSE) by numerical simulations are compared. Simulation studies express that the UMVU estimator performs better than others and when the sample size is large enough the ML and UMVU estimators are almost equivalent and efficient than LS, WLS and PC. Finally, the result using a real data set are analyzed.

scholarly journals An Effective Adaptive Combination Strategy for Distributed Learning Network

2021 ◽  
Vol 11 (12) ◽  
pp. 5723
Author(s):  
Chundong Xu ◽  
Qinglin Li ◽  
Dongwen Ying
Keyword(s):  
Minimum Variance ◽  
Iteration Scheme ◽  
Estimation Problem ◽  
Lms Algorithm ◽  
Unbiased Estimation ◽  
Mean Square ◽  
Least Mean Square ◽  
Combination Strategy ◽  
Adaptive Combination ◽  
Diffusion Networks

In this paper, we develop a modified adaptive combination strategy for the distributed estimation problem over diffusion networks. We still consider the online adaptive combiners estimation problem from the perspective of minimum variance unbiased estimation. In contrast with the classic adaptive combination strategy which exploits orthogonal projection technology, we formulate a non-constrained mean-square deviation (MSD) cost function by introducing Lagrange multipliers. Based on the Karush–Kuhn–Tucker (KKT) conditions, we derive the fixed-point iteration scheme of adaptive combiners. Illustrative simulations validate the improved transient and steady-state performance of the diffusion least-mean-square LMS algorithm incorporated with the proposed adaptive combination strategy.

scholarly journals Household Wealth: Low-Yielding and Poorly Structured?

2021 ◽  
Vol 14 (3) ◽  
pp. 99
Author(s):  
Marc Peter Radke ◽  
Manuel Rupprecht
Keyword(s):  
Household Wealth ◽  
Financial Advisors ◽  
Investment Fund ◽  
Data Set ◽  
Public And Private ◽  
Consistent Manner ◽  
Widespread Belief ◽  
International Comparative ◽  
Real Returns ◽  
Mean Variance

In this paper, we present a newly generated data set on real returns of households’ aggregated asset holdings, which adds additional and more sophisticated information to existing relevant datasets in the literature. To do this, we draw on various datasets from public and private sources and then transform and combine them in a consistent manner that allows for international comparative and intertemporal analyses. Based on this, we address two current debates on the development of household wealth in the euro area that have been triggered by the low-interest environment. The first debate refers to the development of real yields on household wealth from 2000 to 2018, whereas the second debate deals with the mean-variance efficiency of household portfolios. Contrary to widespread belief, we find that yields on total wealth, which were largely dominated by non-financial assets’ yields, were mostly positive, although they exhibit a declining trend. Moreover, on average, overall real yields were significantly lower after 2008. Referring to portfolio efficiency, we find that current portfolios seem to be comparatively close to mean-variance efficiency. If households were to optimize their portfolios despite limited room for improvement, holdings of equity and investment fund shares should be reduced, contradicting common recommendations of financial advisors.

Predictive view of the value relevance of earnings in India

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hajam Abid Bashir ◽  
Manish Bansal ◽  
Dilip Kumar
Keyword(s):  
Capital Investment ◽  
Stock Return ◽  
Value Relevance ◽  
Stock Exchange ◽  
Predictive Ability ◽  
Cash Flows ◽  
Data Set ◽  
Content Type ◽  
Uniform Sample ◽  
Reported Earnings

Purpose This study aims to examine the value relevance of earnings in terms of predicting the value variables such as cash flow, capital investment (CI), dividend and stock return under the Indian institutional settings. Design/methodology/approach The study used panel Granger causality tests to examine causality relationships among variables and panel data regression models to check the statistical associations between earnings and value variables. Findings Based on a data set of 7,280 Bombay Stock Exchange-listed firm-years spanning over ten years from March 2009 to March 2018, the results show higher sensitivity of earnings toward cash flows, CI, divided and stock return and vice-versa. Further, the findings deduced from the empirical results demonstrate that earnings are positively related to value variables. Overall, the results established that earnings are value-relevant and have predictive ability to forecast the value variables that facilitate investors in portfolio valuation. The results are consistent with the predictive view of the value relevance of earnings. Several robustness checks confirm these results. Originality/value This study brings new empirical evidence from a distinct capital market, India, and provides a new facet to the value relevance debate in terms of its prediction view. The study is among earlier attempts that jointly measure the ability of earnings in forecasting different value variables by taking a uniform sample of firms at the same period. Hence, the study provides a comprehensive view of the predictive ability of reported earnings.

A MODIFIED RATIO TYPE ESTIMATOR OF FINITE POPULATION MEAN UNDER STRATIFIED RANDOM SAMPLING SCHEME

2021 ◽  
pp. 58-60
Author(s):  
Naziru Fadisanku Haruna ◽  
Ran Vijay Kumar Singh ◽  
Samsudeen Dahiru
Keyword(s):  
Mean Square Error ◽  
Random Sampling ◽  
Minimum Mean Square Error ◽  
Real Life ◽  
Population Data ◽  
Auxiliary Variable ◽  
Mean Square ◽  
Data Set ◽  
Population Mean ◽  
The Mean

In This paper a modied ratio-type estimator for nite population mean under stratied random sampling using single auxiliary variable has been proposed. The expression for mean square error and bias of the proposed estimator are derived up to the rst order of approximation. The expression for minimum mean square error of proposed estimator is also obtained. The mean square error the proposed estimator is compared with other existing estimators theoretically and condition are obtained under which proposed estimator performed better. A real life population data set has been considered to compare the efciency of the proposed estimator numerically.

scholarly journals Observed and estimated leaf appearance of landrace and improved maize cultivars

2017 ◽  
Vol 48 (1) ◽  
Author(s):  
Josana Andreia Langner ◽  
Nereu Augusto Streck ◽  
Angelica Durigon ◽  
Stefanía Dalmolin da Silva ◽  
Isabel Lago ◽  
...  
Keyword(s):  
Root Mean Square Error ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Sowing Date ◽  
Mean Square ◽  
Data Set ◽  
Growing Seasons ◽  
Maize Cultivars ◽  
Maize Varieties ◽  
Leaf Appearance

ABSTRACT: The objective of this study was to compare the simulations of leaf appearance of landrace and improved maize cultivars using the CSM-CERES-Maize (linear) and the Wang and Engel models (nonlinear). The coefficients of the models were calibrated using a data set of total leaf number collected in the 11/04/2013 sowing date for the landrace varieties ‘Cinquentinha’ and ‘Bico de Ouro’ and the simple hybrid ‘AS 1573PRO’. For the ‘BRS Planalto’ variety, model coefficients were estimated with data from 12/13/2014 sowing date. Evaluation of the models was with independent data sets collected during the growing seasons of 2013/2014 (Experiment 1) and 2014/2015 (Experiment 2) in Santa Maria, RS, Brazil. Total number of leaves for both landrace and improved maize varieties was better estimated with the Wang and Engel model, with a root mean square error of 1.0 leaf, while estimations with the CSM-CERES-Maize model had a root mean square error of 1.5 leaf.

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