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Journal articles on the topic 'Portfolio Return; Principal Component Analysis'

Author: Grafiati

Published: 5 June 2025

Last updated: 16 July 2025

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1

Wangdra, Ronald, and Syahril Effendi. "Penyusunan Portofolio Saham Lindung Nilai Berdasarkan Principal Component Analysis Pada Indeks LQ45 Indonesi." Prosiding Seminar Nasional Ilmu Sosial dan Teknologi (SNISTEK) 5 (September 28, 2023): 479–85. http://dx.doi.org/10.33884/psnistek.v5i.8122.

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Stock investment carries significant risks, making hedging strategies essential. Research on hedging in the Indonesian stock index is limited. This study aims to construct a hedging portfolio using a linear combination of principal components to create orthogonal components for stocks in the LQ45 index. A 5-year time series dataset from 2018 to 2022 is employed. Analysis reveals four principal components explaining 84% of the total data variance, with a Kaiser-Meyer-Olkin (KMO) value of 90%. This indicates successful separation of stocks with different cumulative return patterns, return profil

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Fahmi, Muhamad Shameer, Caroline Geetha, and Rosle Mohidin. "Measuring the Systematic Risk Factors in Malaysia Stock Market Returns: A Principal Component Analysis Approach." Malaysian Journal of Business and Economics (MJBE) 6, no. 1 (2019): 53. https://doi.org/10.51200/mjbe.v0i0.1936.

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ABSTRACT Stock market return was used as a leading indicator that measures the strength of the economy. The performance of stock market can be measured by stock market returns. However, the uncertainty in the stock market will cause systematic risk for investors. The aim of the paper to measures the systematic risk factors in Malaysia stock market. The study makes used of principal components analysis to construct a Kuala Lumpur Composite Index (KLCI) that serves a proxy variable of Malaysia stock market return and macroeconomic variables as sources of systematic risk factors. This paper used

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3

Xu, Junhao. "The Evolution of Portfolio Theory: Integrating Machine Learning with Markowitz Optimization." SHS Web of Conferences 218 (2025): 02023. https://doi.org/10.1051/shsconf/202521802023.

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Modern Portfolio Theory (MPT), developed by Harry Markowitz, transformed investment practices by wisely balancing risk and return. Nonetheless, its efficacy wanes in fluctuating financial markets due to its dependence on historical data and fixed assumptions. This paper investigates incorporating Machine Learning (ML) techniques into the traditional Markowitz optimization framework to enhance portfolio construction and risk management processes. It highlights the use of supervised learning for forecasting asset returns, unsupervised learning for asset clustering, and reinforcement learning for

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Pratama, Aditya Nugraha, Neva Satyahadewi, and Evy Sulistianingsih. "ANALYSIS OF OPTIMAL PORTFOLIO FORMATION ON IDX30 INDEXED STOCK WITH THE MEAN ABSOLUTE DEVIATION METHOD." BAREKENG: Jurnal Ilmu Matematika dan Terapan 18, no. 3 (2024): 1753–64. http://dx.doi.org/10.30598/barekengvol18iss3pp1753-1764.

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In investing in stocks, an investor must be able to form a stock portfolio to obtain optimal results. Factor analysis is one way to select stocks to form a portfolio. Factor analysis with Principal Component Analysis (PCA) extraction is used to summarize many variables into new smaller factors by producing the same information. The new factor formed is called a portfolio. This study aims to form an optimal portfolio using the Mean Absolute Deviation (MAD) method, which is an alternative to Markowitz optimization, and assess the stock portfolio's performance using the Sharpe index. This researc

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Rohilla, Amit, and Varun Bhandari. "Impact of investor sentiment on portfolio return: An ARDL approach." VEETHIKA-An International Interdisciplinary Research Journal 10, no. 2 (2024): 40–56. http://dx.doi.org/10.48001/veethika.2024.10.02.004.

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This paper pioneers an investigation into the intricate relationship between investor sentiment and BSE Sensex returns from January 2010 to December 2021. Employing 32 market and macroeconomic variables as proxies for investor sentiment, we utilized principal component analysis to distill these variables into 11 principal components with eigenvalues exceeding 1, thus creating investor sentiment sub-indices. Utilizing the Auto-Regressive Distributive Lag method, we aimed to elucidate the impact of sentiment on portfolio returns. Our findings reveal a significantly positive impact of sentiment o

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Amit, Rohilla. "Impact of Investor Sentiment on Portfolio Return -Do Economic and Market Conditions Matter?" Indian Journal of Economics and Finance (IJEF) 2, no. 2 (2022): 45–56. https://doi.org/10.54105/ijef.B2531.112222.

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<strong>Abstract:</strong> Purpose: In a first of its kind, this paper tries to explore the relationship between investors sentiment and BSE Sensex return over the period January 2010 to December 2021 and under different market and economic conditions. Design/Methodology/Approach: The paper uses 32 market and macroeconomic variables as proxy to the investor sentiment. Principal component analysis has been used and the first 11 principal components with eigenvalue more than 1, have been selected to create investor sentiment sub-indices. Weighted/generalized least squares (GLS) method has been u

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Zoričić, Davor, Denis Dolinar, and Zrinka Lovretin Golubić. "Factor-Based Optimization of a Fundamentally-Weighted Portfolio in the Illiquid and Undeveloped Stock Market." Journal of Risk and Financial Management 13, no. 12 (2020): 302. http://dx.doi.org/10.3390/jrfm13120302.

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In this paper, the possibility of using fundamental weighting as a tool to intentionally tilt a portfolio toward specific and unobservable risk factors in the illiquid and undeveloped Croatian stock market is explored. Thus far, fundamental-weighting has been shown to be able to outperform the cap-weighted index in such environments but no attempt regarding control for implicit factor exposure of such portfolios has been reported. Therefore, in this study principal component analysis is performed to capture the underlying risk factors of the fundamentally-weighted portfolio in order to optimiz

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Rohilla, Amit. "Impact of Investor Sentiment on Portfolio Return - Do Economic and Market Conditions Matter?" Indian Journal of Economics and Finance 2, no. 2 (2022): 45–56. http://dx.doi.org/10.54105/ijef.b2531.112222.

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In a first of its kind, this paper tries to explore the relationship between investors sentiment and BSE Sensex return over the period January 2010 to December 2021 and under different market and economic conditions. Design/Methodology/Approach: The paper uses 32 market and macroeconomic variables as proxy to the investor sentiment. Principal component analysis has been used and the first 11 principal components with eigenvalue more than 1, have been selected to create investor sentiment sub-indices. Weighted/generalized least squares (GLS) method has been used to achieve the objectives of the

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9

Back, Andrew D., and Andreas S. Weigend. "A First Application of Independent Component Analysis to Extracting Structure from Stock Returns." International Journal of Neural Systems 08, no. 04 (1997): 473–84. http://dx.doi.org/10.1142/s0129065797000458.

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This paper explores the appliation of a signal processing technique known as independent component analysis (ICA) or blind source separation to multivariate financial time series such as a portfolio of stocks. The key idea of ICA is to linearly map the observed multivariate time series into a new space of statistically independent components (ICs). We apply ICA to three years of daily returns of the 28 largest Japanese stocks and compare the results with those obtained using principal component analysis. The results indicate that the estimated ICs fall into two categories, (i) infrequent large

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Meric, Ilhan, Joe Kim, Lewis Coopersmith, and Gulser Meric. "Co-Movements of Pacific-Basin Stock Markets: Portfolio Diversification Implications." Journal of International Business and Economy 8, no. 2 (2007): 11–34. http://dx.doi.org/10.51240/jibe.2007.2.2.

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This paper studies the co-movements of and the linkages between twelve Pacific-Basin stock markets during the June 1995-May 2005 period. We use the principal components analysis (PCA) technique to group the stock markets into statistically significant principal components in terms of the similarities of their index return movements. The rolling correlation analysis results show that correlation between the Pacific-Basin stock markets has considerable time-varying volatility. The Granger causality test results indicate that the weekly index returns of most Pacific-Basin stock markets are weak-f

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Uchiyama, Yusuke, Takanori Kadoya, and Kei Nakagawa. "Complex Valued Risk Diversification." Entropy 21, no. 2 (2019): 119. http://dx.doi.org/10.3390/e21020119.

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Risk diversification is one of the dominant concerns for portfolio managers. Various portfolio constructions have been proposed to minimize the risk of the portfolio under some constraints, including expected returns. We propose a portfolio construction method that incorporates the complex valued principal component analysis into the risk diversification portfolio construction. The proposed method was verified to outperform the conventional risk parity and risk diversification portfolio constructions.

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DU, Juan. "Empirical differences between the overnight and day trading hour returns." China Finance Review International 8, no. 3 (2018): 315–31. http://dx.doi.org/10.1108/cfri-10-2017-0213.

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Purpose The purpose of this paper is to provide a stable model which covers market information of return to examine the empirical differences between the returns during night and day in Chinese commodity futures market. Design/methodology/approach Commodity indices are constructed using principal components analysis to represent the market returns for day and night trading in the Chinese commodity futures market. Then VAR models are employed to predict the commodity indices’ returns and squared returns. Findings The symmetric VAR model failed to model the market returns since the asymmetric ef

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Chiriac, Silviu Cornel Virgil. "THE IMPACT OF REAL ESTATE INVESTMENTS ON THE PERFORMANCE OF THE ENTITIES LISTED AT THE BVB." Annals of the University of Oradea. Economic Sciences 30, no. 30 (1) (2021): 177–86. http://dx.doi.org/10.47535/1991auoes30(1)019.

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The current paper is part of a wider study which aims at identifying the determining factors of the performances of the entities in the real estate field and the setting up of a composite index of the companies’ performances based on a sample of 29 companies listed at the BVB Bucharest (Bucharest Stock Exchange) in the year 2019 using one of the multidimensional data analysis techniques, the principal component analysis. The descriptive analysis, the principal component analysis for setting up the composite index of the companies performances were applied within the study in order to highlight

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Rahmat Budi Santoso, Erawati Kartika, and Ika Listyawati. "Portfolio Diversification Opportunities On The Asean 5 Stock Market And Sectoral Stock Indexes On The Indonesian Stock Exchange." INTERNATIONAL CONFERENCE ON DIGITAL ADVANCE TOURISM, MANAGEMENT AND TECHNOLOGY 1, no. 1 (2023): 155–65. http://dx.doi.org/10.56910/ictmt.v1i1.59.

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 This study aims to examine portfolio diversification opportunities on the stock markets of Indonesia, Singapore, Malaysia, Thailand, and the Philippines, as well as sectoral stock price indices on the Indonesian Stock Exchange. The data used is the closing daily price index for the period January 2021 – October 2023. The analysis method uses principal component analysis. The results show that the first forming component includes the Indonesian stock market and its sectoral stock price index. The second component is filled by the stock markets of Singapore, Malaysia, Thailand, and the Ph

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Shigemoto, Hideto, and Takayuki Morimoto. "Forecasting High-Dimensional Covariance Matrices Using High-Dimensional Principal Component Analysis." Axioms 11, no. 12 (2022): 692. http://dx.doi.org/10.3390/axioms11120692.

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We modify the recently proposed forecasting model of high-dimensional covariance matrices (HDCM) of asset returns using high-dimensional principal component analysis (PCA). It is well-known that when the sample size is smaller than the dimension, eigenvalues estimated by classical PCA have a bias. In particular, a very small number of eigenvalues are extremely large and they are called spiked eigenvalues. High-dimensional PCA gives eigenvalues which correct the biases of the spiked eigenvalues. This situation also happens in the financial field, especially in situations where high-frequency an

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Kulikov, Alexander, Dmitriy Polozov, and Nikita Volkov. "Long-term investment optimization based on Markowitz diversification." Business Informatics 18, no. 3 (2024): 56–69. http://dx.doi.org/10.17323/2587-814x.2024.3.56.69.

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The article introduces a long-term investment algorithm that identifies optimal solutions in lower dimensional spaces constructed through principal component analysis or kernel principal component analysis. Portfolio weights optimization is carried out using the Markowitz method. Hyperparameters of the model include window size, smoothing parameter, rebalancing period and the fraction of explained variance in dimensionality reduction methods. The algorithm presented incorporates weights regularization taking into account portfolio rebalancing transaction costs. Hyperparameters’ selection is ba

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Stanciu, Cristian Valeriu, and Andrei Cristian Spulbar. "Financial Integration of the European Union Financial Markets. A PCA Approach." Studies in Business and Economics 19, no. 3 (2024): 241–56. https://doi.org/10.2478/sbe-2024-0054.

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Abstract European stock markets are a complex and dynamic terrain, requiring sophisticated methods of analysis to understand their degree of interconnectedness and integration. The paper investigates the financial integration of European Union (EU) financial markets using a dynamic Principal Component Analysis (PCA) approach. By calculating the Financial Integration Index (FII) from daily stock market index returns and volatilities, we provide a comprehensive analysis of the integration trends over the past two decades across three distinct groups: the EU-27, the Eurozone, and the Non-Eurozone

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18

Zaimovic, Azra, Almira Arnaut-Berilo, and Arnela Mustafic. "Portfolio Diversification in the South-East European Equity Markets." South East European Journal of Economics and Business 12, no. 1 (2017): 126–35. http://dx.doi.org/10.1515/jeb-2017-0010.

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AbstractDiversification potential enables investors to manage their risk and decrease risk exposure. Good diversification policy is a safety net that prevents a portfolio from losing its value. A well-diversified portfolio consists of different categories of property with low correlations, while highly correlated markets have the feature of low possibilities for diversification. The biggest riddle in the world of investments is to find the optimal portfolio within a set of available assets with limited capital. There are numerous studies and mathematical models that deal with portfolio investm

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Angraini, Lestari Ayu, Novita Sari Hutasoit, and Gracia Shinta Ugut. "Sentimen Investor, Faktor Fundamental Makroekonomi dan Excess Return Pasar Saham di Indonesia." Jurnal Bisnis dan Manajemen 9, no. 1 (2022): 27–34. http://dx.doi.org/10.26905/jbm.v9i1.7178.

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This study aims to examine the effect of investor sentimen and macroeconomic fundamentals on excess returns which are useful for decision making in optimizing portfolios. This study used the aggregate market with the aim of knowing the entire stock market in Indonesia, and used daily data during 2020 with a total of 242 data according to the number of trading days in 2020. This study used trading volume, advance-decline ratio, market turnover, share turnover for sentiment investor indicators. SBI Interest Rate, SP500 Index, and exchange rate were used as indicators of macroeconomic fundamental

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20

Patel, Versha, S. Amilan, and P. Vairasigamani. "The relationship of market sentiment and sector return across time and frequency – a wavelet coherence analysis." Economics and Finance Letters 12, no. 2 (2025): 388–402. https://doi.org/10.18488/29.v12i2.4255.

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Investment diversification is a strategic approach to mitigating risks by spreading assets across various sectors. Each sector has its unique temperament when it comes to market sentiment. Certain sectors are more prone to being influenced by sentiment, while others are less so. Conventional approaches often overlook the dynamic interaction between market sentiment and sector returns. The study utilized data from the Bombay Stock Exchange and National Stock Exchange, including all sectoral indices of the BSE from April 2008 to June 2023. A composite sentiment index was developed using Principa

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Du, Shengwu, and Travis D. Nesmith. "Portfolio Margining Using PCA Latent Factors." Finance and Economics Discussion Series, no. 2025-016 (February 2025): 1. https://doi.org/10.17016/feds.2025.016.

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Filtered historical simulation ( FHS )—a simple method of calculating Value-at-Risk that reacts quickly to changes in market volatility—is a popular method for calculating margin at central counterparties. However, FHS does not address how correlation can vary through time. Typically, in margin systems, each risk factor is filtered individually so that the computational burden increases linearly as the number of risk factors grows. We propose an alternative method that filters historical returns using latent risk factors derived from principal component analysis. We compare this method’s perfo

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Haixu, Liu, Zhang Yong, Li Hui, Mao Tianjun, Zheng Wenhui, and Li Jiao. "Probabilistic Calibration and Genetic Algorithm-based Bank Credit Strategies for MSMEs and Enlightenment to Tobacco Enterprise Management." Tobacco Regulatory Science 7, no. 6 (2021): 5726–40. http://dx.doi.org/10.18001/trs.7.6.56.

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Objectives: To further strengthen the role of Micro, Small and Medium Enterprises (MSMEs) in maintaining the vitality of national economy, governments around the world introduced many special policies. They kept guiding the banking industry to increase the support for MSMEs and reduce their financing difficulties in banks. Basing on the analysis of the bank's credit strategy for small and medium-sized enterprises of similar size, this paper gives the management strategy for small and medium-sized enterprises in tobacco industry to obtain bank credit when they cannot expand their turnover. In t

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Lettau, Martin, and Markus Pelger. "Factors That Fit the Time Series and Cross-Section of Stock Returns." Review of Financial Studies 33, no. 5 (2020): 2274–325. http://dx.doi.org/10.1093/rfs/hhaa020.

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Abstract We propose a new method for estimating latent asset pricing factors that fit the time series and cross-section of expected returns. Our estimator generalizes principal component analysis (PCA) by including a penalty on the pricing error in expected returns. Our approach finds weak factors with high Sharpe ratios that PCA cannot detect. We discover five factors with economic meaning that explain well the cross-section and time series of characteristic-sorted portfolio returns. The out-of-sample maximum Sharpe ratio of our factors is twice as large as with PCA with substantially smaller

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Gao, Yingtai, Xinyue Ma, and Han Liu. "Comparison Between Two Methods in Measuring Investor Sentiment." Advances in Economics, Management and Political Sciences 202, no. 1 (2025): 144–54. https://doi.org/10.54254/2754-1169/2024.25092.

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This study examines the influence of two distinct investor sentiment indicestext mining-based and principal component analysis (PCA)-derivedon the returns of stocks listed on China's STAR Market during the COVID-19 pandemic. By analyzing Huo and Wu's empirical findings, our comparative evaluation using daily measurement of investor sentiment based on PCA approach concludes that the text mining-based sentiment index surpasses the PCA-based counterpart in terms of both effectiveness and accuracy. The daily measurement we used in this paper is constructed by overnight return rate of individual st

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He, Weidong, and Jiahe Yu. "Research on the Synthesis of Hong Kong NFT Index Using Principal Component Analysis and Index Prediction Based on LSTM-Modified ARMA-GARCH Model." Advances in Economics, Management and Political Sciences 55, no. 1 (2023): 59–76. http://dx.doi.org/10.54254/2754-1169/55/20230962.

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With the advent of the Web3.0 era, virtual assets have gained prominence in individuals asset portfolios, making Non-Fungible Tokens (NFTs) increasingly significant within the financial trading landscape. To address the issue of multicollinearity in regression analysis, this paper employs Principal Component Analysis (PCA) to perform dimensionality reduction on five correlated foundational sectors. Moreover, to enhance the accuracy and reliability of predictive outcomes, the study combines the Long Short-Term Memory (LSTM) model with the Autoregressive Moving Average-Generalized Autoregressive

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Lee, Hyemin. "Analysis of the Applicability of Dimensionality Reduction Techniques in Stock Portfolio Construction." Korean Data Analysis Society 26, no. 6 (2024): 1869–80. https://doi.org/10.37727/jkdas.2024.26.6.1869.

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This study aims to overcome the limitations of previous research that utilized only a small number of financial indicators and proposes a method to comprehensively utilize all available financial data at the time of investment. To implement this effectively, we propose a Sliced Inverse Regression (SIR) model, a form of sufficient dimension reduction. In this study, we compare the returns of portfolios constructed using dimensionality reduction with those of market indices (KOSPI, KOSDAQ) and portfolios based on previous research (small-cap stocks, low PBR). The results indicate that the portfo

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Jothimani, Dhanya, Ravi Shankar, and Surendra S. Yadav. "A PCA-DEA framework for stock selection in Indian stock market." Journal of Modelling in Management 12, no. 3 (2017): 386–403. http://dx.doi.org/10.1108/jm2-09-2015-0073.

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Purpose Portfolio optimization is the process of making an investment decision on a set of assets to realize high returns with low risk. It has three major stages: asset selection, asset weighting and asset management. Asset selection is an important phase because it influences asset allocation and ultimately affects the returns of a portfolio. Today, there is an increase in the number of listings on a stock exchange. Therefore, it is important for an investor to screen and select stocks for investment. This study focuses on the first stage of the portfolio optimization problem, namely, asset

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Basilio, Marcio Pereira, Jéssica Galdino de Freitas, Milton George Fonseca Kämpffe, and Ricardo Bordeaux Rego. "Investment portfolio formation via multicriteria decision aid: a Brazilian stock market study." Journal of Modelling in Management 13, no. 2 (2018): 394–417. http://dx.doi.org/10.1108/jm2-02-2017-0021.

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PurposeThe purpose of this paper is to identify how multicriteria decision aid (MCDA) can assist the investment portfolios formation, increasing the reliability of decision-making.Design/methodology/approachTo develop this paper, a simulation-based approach is used. Information about the assets traded on the spot market of the São Paulo Stock Exchange - BM&FBOVESPA was selected. They had 100 per cent participation in the 246 trading sessions carried out in 2015 and had an average number of business/day greater or equal to 1,000. The stratification resulted in the selection of 111 assets. A

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Wei, Xiaolu, and Hongbing Ouyang. "Carbon price prediction based on a scaled PCA approach." PLOS ONE 19, no. 1 (2024): e0296105. http://dx.doi.org/10.1371/journal.pone.0296105.

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Carbon price prediction is of great importance to regulators and participants in the carbon trading market. It is the basis for developing policies related to the carbon trading market and stabilizing that market. Considering the numerous factors that influence carbon prices in China, dimensionality reduction is needed to improve the prediction accuracy and efficiency. However, the traditional dimensionality reduction methods fail to fully consider the role of influencing factors, which has certain limitations. In this paper, a new dimensionality reduction method, namely scaled principal compo

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Bessler, Wolfgang, and Dominik Wolff. "Portfolio Optimization with Sector Return Prediction Models." Journal of Risk and Financial Management 17, no. 6 (2024): 254. http://dx.doi.org/10.3390/jrfm17060254.

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We analyze return predictability for U.S. sectors based on fundamental, macroeconomic, and technical indicators and analyze whether return predictions improve tactical asset allocation decisions. We study the out-of-sample predictive power of individual variables for forecasting sector returns and analyze multivariate predictive regression models, including OLS, regularized regressions, principal component regressions, the three-pass regression filter, and forecast combinations. Using an out-of-sample Black–Litterman portfolio optimization framework and employing predicted returns as investors

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Morimoto, Kai, Masahiro Saito, Satoshi Inose, Atsushi Kannari, and Tomoya Suzuki. "Principal Component Analysis for the Nonlinear Portfolio Model." Journal of Signal Processing 18, no. 4 (2014): 177–80. http://dx.doi.org/10.2299/jsp.18.177.

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Ritesh Kumar. "Hedging Basis Risk in Power Portfolio Using Principal Component Analysis." Communications on Applied Nonlinear Analysis 32, no. 1 (2025): 409–16. https://doi.org/10.52783/cana.v32.4615.

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There has been many studies about hedging power prices but most of them are limited to Power price at hub. This paper studies the Basis Risks in power portfolio more specifically it explain the Basis Risks present in a Power portfolio, the limitations of hedging these risks and develops a framework to hedge the Basis Risk using Principal Component Analysis framework.Keywords: English for Nurses, Needs analysis, Task-based syllabus,

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Laddha, Kartikay, Vidhi Kapoor, and Siba Panda. "Portfolio construction and weight optimisation using principal component analysis." International Journal of Forensic Software Engineering 1, no. 4 (2022): 314. http://dx.doi.org/10.1504/ijfse.2022.123957.

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Panda, Siba, Kartikay Laddha, and Vidhi Kapoor. "Portfolio construction and weight optimisation using principal component analysis." International Journal of Forensic Software Engineering 1, no. 1 (2021): 1. http://dx.doi.org/10.1504/ijfse.2021.10043971.

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Alexandrova, Matilda. "A PRINCIPAL COMPONENT ANALYSIS OF PROJECT PORTFOLIO MANAGEMENT PRACTICES." Ekonomicko-manazerske spektrum 11, no. 2 (2018): 96–105. http://dx.doi.org/10.26552/ems.2018.2.96-105.

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Alemanni, Barbara, Mario Maggi, and Pierpaolo Uberti. "Unleveraged Portfolios and Pure Allocation Return." Journal of Risk and Financial Management 14, no. 11 (2021): 550. http://dx.doi.org/10.3390/jrfm14110550.

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In asset management, the portfolio leverage affects performance, and can be subject to constraints and operational limitations. Due to the possible leverage aversion of the investors, the comparison between portfolio performances can be incomplete or misleading. We propose a procedure to unleverage the mean-variance efficient portfolios to satisfy a leverage requirement. We obtain a class of unleveraged portfolios that are homogeneous in terms of leverage, so therefore properly comparable. The proposed unleverage procedure permits isolating the pure allocation return, i.e., the return componen

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Shim, Kyung-Sik, Jae-Joon Ahn, and Kyong-Joo Oh. "Multi-currencies portfolio strategy using principal component analysis and logistic regression." Journal of the Korean Data and Information Science Society 23, no. 1 (2012): 151–59. http://dx.doi.org/10.7465/jkdi.2012.23.1.151.

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Syamala, Sudhakara Reddy, and Kavita Wadhwa. "Financial Crisis and International Portfolio Diversification: A Principal Component Analysis Approach." Theoretical Economics Letters 06, no. 02 (2016): 338–46. http://dx.doi.org/10.4236/tel.2016.62038.

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CHEN, J., C. CHANG, J. HOU, and Y. LIN. "Dynamic proportion portfolio insurance using genetic programming with principal component analysis☆." Expert Systems with Applications 35, no. 1-2 (2008): 273–78. http://dx.doi.org/10.1016/j.eswa.2007.06.030.

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Boitan, Iustina Alina. "Sustainable stock market indices: A comparative assessment of performance." Journal of Research in Emerging Markets 2, no. 1 (2020): 7–14. http://dx.doi.org/10.30585/jrems.v2i1.410.

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The paper focuses on the sustainability stock market indices and investigates whether there is evidence of synchronization between the price return provided by sustainability indices calculated for various geographic regions. Due to data availability constraints, the analysis had been performed only for the Dow Jones Sustainability Indices family, which comprises six types of indices. It had been considered the daily price return time series recorded in the last 10 years (November 30, 2010 – July 26, 2019) by each of the six Dow Jones Sustainability Indices, and it had been applied to the Prin

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Todorova, Zornitsa. "Firm returns and network centrality." Risk Governance and Control: Financial Markets and Institutions 9, no. 3 (2019): 74–82. http://dx.doi.org/10.22495/rgcv9i3p6.

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Using methods from graph theory and network analysis, this paper identifies, visualizes and analyzes a correlation network of residual stock returns for more than 5,000 US-based publicly traded firms. Building on prior work by Billio et al. (2012), the paper computes a systemic measure of network centrality using principal components analysis. Two main questions are addressed: 1) What is the empirical relationship between expected stock returns and network centrality? and 2) Does network centrality have predictive power to identify firms, which are most at risk during systemic events? First, t

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Guinda, María, and Ritabrata Bhattacharyya. "Using Principal Component Analysis on Crypto Correlations to Build a Diversified Portfolio." International Journal of Cryptocurrency Research 1, no. 1 (2021): 26. http://dx.doi.org/10.51483/ijccr.1.1.2021.26-50.

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Shenjere, Paidamoyo Aurleen, Sune Ferreira-Schenk, and Fabian Moodley. "Does Investor Sentiment Influence South African ETF Flows During Different Market Conditions?" Economies 13, no. 1 (2025): 10. https://doi.org/10.3390/economies13010010.

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The exponential growth in popularity of ETFs over the last three decades has solidified ETFs as an essential component of many investors’ portfolios. Investor sentiment is one of the factors that influence market returns of ETFs during times of market volatility. This article highlights the gap in the literature by examining the role sentiment plays in ETF volatility and providing a more comprehensive understanding of how sentiment interacts with market conditions to affect ETF pricing in the South African context. This article aims to determine the effect of investor sentiment on JSE-listed E

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Jiang, Hao Hao. "Supplier Selection Based on the Principal Component Analysis." Applied Mechanics and Materials 94-96 (September 2011): 2265–69. http://dx.doi.org/10.4028/www.scientific.net/amm.94-96.2265.

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Today’s construction quality signifies a lot to the tomorrow’s rate of return on investment for the project. The supplier selection has a pivotal role in engineering management; it occupies an important place for ensuring the construction quality in the project construction activities. So choosing suitable suppliers has become to be an important development strategy of the modern construction enterprise. The principal component analysis, one of the multivariate statistical analyses, particularly applicable to this kind of problem. This article systematically discusses this method of choice and

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Atahau, Apriani Dorkas Rambu, Robiyanto Robiyanto, and Andrian Dolfriandra Huruta. "Co-Movement of Indonesian State-Owned Enterprise Stocks." Economies 11, no. 2 (2023): 46. http://dx.doi.org/10.3390/economies11020046.

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According to portfolio theory, diversifying investment to several stocks with negative correlations may reduce portfolio risk. In contrast, combining stocks with similar movement (co-movement) has no impact on portfolio risk reduction. This study aims to examine state-owned enterprise stock co-movement in Indonesia using orthogonal generalized auto-regressive conditional heteroscedasticity (O-GARCH) to help investors selectively choose stocks in a portfolio to reduce portfolio risks. Saturation sampling was used since all state-owned enterprise stocks listed on the Indonesian Stock Exchange we

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Soto, Paula Andrea, and Juan Carlos Ruilova Teran. "Arbitragem Estatística: Uma Abordagem por VECM." Brazilian Review of Finance 15, no. 4 (2018): 537. http://dx.doi.org/10.12660/rbfin.v15n4.2017.65761.

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This work develops a statistical arbitrage model which was tested on the Brazilian stock market. Prices were modeled using VECM (Vector Error Correction Models) to create a self-financing, market-neutral, long/short trading strategy. In this strategy, deviations in the long-term equilibrium of prices are identified in order to create buy and sell signals. Portfolios with common trends were selected by means of Principal Component Analysis. The viability of this strategy was empirically addressed using simulations on these portfolios. Its performance was also compared to other long/short tradin

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Sorana, Vatavu. "Determinants of Return on Assets in Romania: A Principal Component Analysis." Timisoara Journal of Economics and Business 8, s1 (2015): 32–47. http://dx.doi.org/10.1515/tjeb-2015-0003.

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Abstract This paper examines the impact of capital structure, as well as its determinants on the financial performance of Romanian companies listed on the Bucharest Stock Exchange. The analysis is based on cross sectional regressions and factor analysis, and it refers to a ten-year period (2003-2012). Return on assets (ROA) is the performance proxy, while the capital structure indicator is debt ratio. Regression results indicate that Romanian companies register higher returns when they operate with limited borrowings. Among the capital structure determinants, tangibility and business risk have

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HARPA, RODICA, CRISTINA PIROI, IRINA CRISTIAN, and MIRELA BLAGA. "Sensory analysis and Principal Component Analysis: a sustainable approach for quality control of stretch denim fabrics." Industria Textila 73, no. 05 (2022): 519–29. http://dx.doi.org/10.35530/it.073.05.202130.

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This study proposes a simplified approach to optimise the portfolio of denim manufacturers by reducing the cost of unattractive or undifferentiated assortments for future consumers based on their ability to perceive and discriminate sensory comfort. A key factor in a successful textile value chain is end consumers, who can be considered naive evaluators when it comes to sensory analysis, as they tend to touch apparel fabrics to perceive the sensory comfort they feel when wearing them. In this context, 16 naive assessors were recruited to quantitatively characterise six bipolar sensory attribut

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Saeed Hassan Chowdhury, Shah. "Idiosyncratic volatility, investor sentiment, and returns of the GCC stock markets." Investment Management and Financial Innovations 18, no. 4 (2021): 190–202. http://dx.doi.org/10.21511/imfi.18(4).2021.17.

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Standard finance theory suggests that idiosyncratic volatility should not influence stock returns. In reality, if investors are unable to achieve efficient diversification, such risk may affect stock returns. The purpose of the study is to examine the presence of idiosyncratic volatility and sentiment in the stock markets of the GCC (Gulf Cooperation Council) countries. Monthly idiosyncratic volatility is estimated using the Fama-French three-factor model. A unified sentiment proxy for each market is created by employing Principal Component Analysis (PCA). Then, Ordinary Least Squares (OLS) re

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Chen, David M., and Li-Ling Yang. "An Empirical Test of a Resources Deployment Portfolio (RDP) Approach to Business Group ROE Decomposition." Review of Pacific Basin Financial Markets and Policies 12, no. 04 (2009): 695–720. http://dx.doi.org/10.1142/s0219091509001812.

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This study proposes a resources deployment portfolio (RDP) approach to decomposing return on equity (ROE) for business analysis. The five components are return on operating equity (RoOE), return on financial equity (RoFE), return on other equity (RoXE), return on influencing equity (RoIE), and R&D intensiveness (R&DI). Empirical results demonstrate that RDP decomposition offers substantial improvement over DuPont decomposition in explaining market valuation. Confirming the perceived sustainability, RoOE is the most consistently significant component for both long-term and short-term va

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