scholarly journals Analyzing Financial Health of the SMES Listed in the AERO Market of Bucharest Stock Exchange Using Principal Component Analysis

2020 ◽  
Vol 12 (9) ◽  
pp. 3726
Author(s):  
Claudia Diana Sabău-Popa ◽  
Ramona Simut ◽  
Laurențiu Droj ◽  
Corneliu Cristian Bențe
Keyword(s):  
Principal Component Analysis ◽  
Stock Exchange ◽  
Small And Medium Enterprises ◽  
Score Function ◽  
Principal Component ◽  
Component Analysis ◽  
Financial Health ◽  
Rates Of Return ◽  
Financial Index ◽  
Composite Financial Index

In this paper we aimed to build a composite financial index for measuring the financial health of the companies listed in the AERO (Alternative exchange in Romania) market of the Bucharest Stock Exchange. We used a principal component analysis in order to build this composite financial index using the rates of return, liquidity and the management of 25 companies listed in the AERO market for the period 2011–2018. We conceived this composite indicator as a score function that established according to the numerical values that result from its application when a company was financially healthy, when it had a poor financial health and when it was financially stable. In order to test the financial health of the selected SMEs (small and medium enterprises), we used the one sample t-test under the model of the study and the three classifications of Z (Z < 0—companies with poor financial health, 0 ≤ Z ≤ 0.5—companies with good financial health and Z > 0.5—companies with very good financial health). In this study we also aimed to identify the possible correlations between the solvency rate and the financial health index and between solvency rate and the evolution of some economic and financial measures of the companies’ activities. The results of the regression analysis using panel data showed a positive and statistically significant relation between solvency and the three rates (rates of return, of liquidity and of management, respectively) determined using the analysis of the principal components. The former model of the solvency rate identified correctly 94.9% of the SMEs with poor financial health, 40% of the SMEs with stable financial health and 72.2% of the SMEs with good financial health.

scholarly journals Penerapan Cara Produksi Pangan yang Baik pada Industri Kecil Menengah (IKM) yang Telah Tersertifikasi Halal LPPOM MUI Provinsi DKI Jakarta

2020 ◽  
Vol 5 (4) ◽  
pp. 197
Author(s):  
Maryam Jameelah ◽  
Nafisah Eka Puteri
Keyword(s):  
Principal Component Analysis ◽  
Small And Medium Enterprises ◽  
Principal Component ◽  
Component Analysis ◽  
The Body ◽  
Observation Data ◽  
Knowledge Level ◽  
Safety Level ◽  
Purposive Sampling ◽  
Medium Enterprises

<p><em>Abstrak</em> - <strong>Sertifikasi Halal suatu produk pangan tentu meningkatkan kepercayaan konsumen pada produk pangan tersebut. Akan tetapi, kriteria ‘halal’ tidaklah cukup jika tidak memperhatikan aspek ‘thoyyib’. Masyarakat umumnya mengira bahwa pangan bersertifikat halal sebagai pangan yang ‘thoyyib’. Aspek ‘thoyyib’ yang dimaksudkan adalah aman dikonsumsi dan telah melalui tahapan atau prosedur yang sesuai, sehingga diharapkan tidak menimbulkan efek penyakit bagi konsumen. Penelitian ini bertujuan untuk memperoleh deskripsi mengenai penerapan cara produksi pangan yang baik pada industri kecil menengah produk minuman dan bahan minuman yang telah tersertifikasi halal. Pada penelitian ini metode survei dilakukan dengan teknik purposive sampling. Data yang diamati berupa pengetahuan pemilik mengenai CPPB (Cara Produksi Pangan yang Baik) dan ketercapaian penerapan CPPB, terutama pada fasilitas sanitasi, higienitas proses produksi, serta pengawasan proses produksi. Teknik pengumpulan data dilakukan dengan wawancara dan observasi dengan bantuan kuesioner, panduan wawancara, dan lembar observasi. Data dianalisis dengan teknik analisis deskriptif melalui penyajian berbentuk grafik, tabel dan narasi. Data hubungan penerapan CPPB dan sertifikasi halal diolah menggunakan XLSTAT dengan Principal Component Analysis (PCA). Hasil analisa menunjukkan bahwa sertifikasi halal pada IKM tidak hanya mencerminkan aspek “halal” tetapi dapat pula mencerminkan aspek “thoyyib” produk yang dihasilkan. Sementara itu, tingkat pengetahuan pemilik IKM tidak dapat mencerminkan tingkat keamanan pangan yang diimplementasikan selama proses produksi. Hal ini dapat disebabkan oleh kurangnya kesadaran pemilik dan penanggungjawab IKM dan tidak adanya pengawasan oleh lembaga atau badan yang bertanggungjawab akan kulitas produk.</strong></p><p><em>Abstract</em> – <strong>Consumer trust in food products may increase with halal claims on the product. However, ‘halal’ is different from ‘thoyyib’. People assume that halal food is ‘thoyyib’. ‘Thoyyib’ means good to consume and health for the body. This study aimed to obtain the description of Good Manufacturing Practice (GMP) on Small and Medium Enterprises (SMEs) holding Halal certification. To gain the purpose, the purposive sampling method was applied to this research. The level of IRTP and knowledge level of GMP were observed. Data were collected by interview and observation. Data were analyzed by descriptive analysis using the graph, table, and narration. Correlation of GMP implementation and the halal claim was provided by Principal Component Analysis (PCA) using XLSTAT. Results showed that halal claims on SMEs may reflect the safety of the product. Halal-claimed food might be classified as ‘thoyyib’ food. However, the knowledge level of the owner can not reflect the food safety level of the product.</strong></p><p><em><strong>Keywords</strong><strong> - </strong>CPPB, Halal Certificate, LPPOM MUI, Small and Medium Enterprises (SMEs)</em></p>

scholarly journals Statistical and computational techniques for extraction of underlying systematic risk factors: a comparative study in the Mexican Stock Exchange

2021 ◽  
Vol 13 (2) ◽  
pp. 513-543
Author(s):  
Rogelio ◽  
Salvador Torra Porras ◽  
Enric Monte Moreno
Keyword(s):  
Risk Factors ◽  
Principal Component Analysis ◽  
Stock Exchange ◽  
Systematic Risk ◽  
Principal Component ◽  
Component Analysis ◽  
Computational Techniques ◽  
Arbitrage Pricing Theory ◽  
Pricing Theory ◽  
Systematic Risk Factors

This paper compares the dimension reduction or feature extraction techniques, e.g., Principal Component Analysis, Factor Analysis, Independent Component Analysis and Neural Networks Principal Component Analysis, which are used as techniques for extracting the underlying systematic risk factors driving the returns on equities of the Mexican Stock Exchange, under a statistical approach to the Arbitrage Pricing Theory. We carry out our research according to two different perspectives. First, we evaluate them from a theoretical and matrix scope, making a parallelism among their particular mixing and demixing processes, as well as the attributes of the factors extracted by each method. Secondly, we accomplish an empirical study in order to measure the level of accuracy in the reconstruction of the original variables.

scholarly journals Variable Reduction and Determinants of Working Capital Management on Profits for Ghanaian Banks

2016 ◽  
Vol 12 (7) ◽  
pp. 316
Author(s):  
Abeku Atta Asare-Kumi ◽  
Kwasi Adjepong Darkwah ◽  
Ezekiel N. N. Nortey ◽  
Charlotte Chapman-Wardy
Keyword(s):  
Risk Factors ◽  
Principal Component Analysis ◽  
Credit Risk ◽  
Stock Exchange ◽  
Principal Component ◽  
Component Analysis ◽  
Capital Management ◽  
Working Capital ◽  
Working Capital Management ◽  
Several Variables

Today, several factors has contributed to the profitability of Banks. Data collected on these factors often has several variables. It is a non-trivial exercise to determine which of the factors that significantly influences the profits of Banks. This paper adopts the use of Principal Component Analysis (PCA) on the several variables expected to influence the working capital management on the profits of banks of the Ghana Stock Exchange (GSE). Fifteen of the several variables captured by the GSE which affect working capital management on profit were grouped into four factors using the principal component analysis. Results of the PCA identifies Convertibility factors, Risk Factor, Short term Liquidity, Operational factors, and Credit Risk factors to be the determinants of bank profits. Consequently, these factors are used to fit a linear regression model in identifying the most significant factors. Apart from credit risk factors, all the other factors were found to be significant predictors of the profit of Ghanaian banks. Investors, stakeholders, and managers of banks can use these factors to monitor and evaluate their working capital in generating profits.

scholarly journals Statistical and computational techniques for extraction of underlying systematic risk factors: a comparative in the Mexican stock exchange

2021 ◽  
Vol 13 (2) ◽  
pp. 237-268
Author(s):  
Rogelio ◽  
Salvador Torra Porras ◽  
Enric Monte Moreno
Keyword(s):  
Risk Factors ◽  
Principal Component Analysis ◽  
Stock Exchange ◽  
Systematic Risk ◽  
Principal Component ◽  
Component Analysis ◽  
Computational Techniques ◽  
Arbitrage Pricing Theory ◽  
Pricing Theory ◽  
Systematic Risk Factors

This paper compares the dimension reduction or feature extraction techniques, e.g., Principal Component Analysis, Factor Analysis, Independent Component Analysis and Neural Networks Principal Component Analysis, which are used as techniques for extracting the underlying systematic risk factors driving the returns on equities of the Mexican Stock Exchange, under a statistical approach to the Arbitrage Pricing Theory. We carry out our research according to two different perspectives. First, we evaluate them from a theoretical and matrix scope, making a parallelism among their particular mixing and demixing processes, as well as the attributes of the factors extracted by each method. Secondly, we accomplish an empirical study in order to measure the level of accuracy in the reconstruction of the original variables.

scholarly journals Functional Principal Components Analysis of Shanghai Stock Exchange 50 Index

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Zhiliang Wang ◽  
Yalin Sun ◽  
Peng Li
Keyword(s):  
Principal Component Analysis ◽  
Statistical Analysis ◽  
Stock Exchange ◽  
Financial Time Series ◽  
Principal Component ◽  
Functional Space ◽  
Component Analysis ◽  
Functional Principal Component Analysis ◽  
Linear Transformations ◽  
Functional Principal Component

The main purpose of this paper is to explore the principle components of Shanghai stock exchange 50 index by means of functional principal component analysis (FPCA). Functional data analysis (FDA) deals with random variables (or process) with realizations in the smooth functional space. One of the most popular FDA techniques is functional principal component analysis, which was introduced for the statistical analysis of a set of financial time series from an explorative point of view. FPCA is the functional analogue of the well-known dimension reduction technique in the multivariate statistical analysis, searching for linear transformations of the random vector with the maximal variance. In this paper, we studied the monthly return volatility of Shanghai stock exchange 50 index (SSE50). Using FPCA to reduce dimension to a finite level, we extracted the most significant components of the data and some relevant statistical features of such related datasets. The calculated results show that regarding the samples as random functions is rational. Compared with the ordinary principle component analysis, FPCA can solve the problem of different dimensions in the samples. And FPCA is a convenient approach to extract the main variance factors.

scholarly journals Assessing Commonality in Liquidity with Principal Component Analysis: The Case of the Warsaw Stock Exchange

2020 ◽  
Vol 13 (12) ◽  
pp. 328
Author(s):  
Joanna Olbryś ◽  
Elżbieta Majewska
Keyword(s):  
Principal Component Analysis ◽  
Stock Market ◽  
Principal Components ◽  
Central And Eastern Europe ◽  
Stock Exchange ◽  
Principal Component ◽  
Component Analysis ◽  
Market Model ◽  
Latent Factors ◽  
Warsaw Stock Exchange

The studies concerning commonality in liquidity on emerging markets in Central and Eastern Europe are scarce and, in particular, they do not utilize the Principal Component Analysis (PCA) to identify latent factors in liquidity. Therefore, the main aim of this research is to assess commonality in liquidity on the Warsaw Stock Exchange (WSE) with the use of the PCA to extract common components of liquidity across a sample of stocks, and from a set of several liquidity proxies. The robustness tests within the whole sample and sub-periods are provided. The PCA results reveal that common latent factors in liquidity estimates exist on the Polish stock market, and three principal components are sufficient to substitute for the seven liquidity proxies utilized in this research. The regressions using these three principal components of liquidity proxies as latent factors in the market model of liquidity indicate no evidence of co-movements in liquidity on the WSE. The results are homogenous for all investigated periods so no reason has been found to reject the research hypothesis that commonality in liquidity does not exist on the Polish stock market. To the best of the authors’ knowledge, no similar research has been conducted for the WSE thus far.

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