Measuring systemic risk contribution: The leave-one-out z-score method

2020 ◽  
Vol 36 ◽  
pp. 101316
Author(s):  
Xiping Li ◽  
David Tripe ◽  
Chris Malone ◽  
David Smith
Keyword(s):  
Systemic Risk ◽  
Z Score ◽  
Score Method ◽  
Risk Contribution ◽  
Leave One Out

scholarly journals Analysis of China Commercial Banks’ Systemic Risk Sustainability through the Leave-One-Out Approach

2019 ◽  
Vol 12 (1) ◽  
pp. 203 ◽  
Author(s):  
Xiaoming Zhang ◽  
Chunyan Wei ◽  
Stefano Zedda
Keyword(s):  
Theoretical Analysis ◽  
Commercial Bank ◽  
Systemic Risk ◽  
Commercial Banks ◽  
Financial Reform ◽  
Existing Problems ◽  
Regulation And Supervision ◽  
Risk Contribution ◽  
Contagion Risk ◽  
Leave One Out

One of the main issues in the recent Chinese financial reform is aimed at effectively measuring systemic risk and taking appropriate measures to ensure its sustainability and prevent new crises. In this paper, we firstly introduced the present macro-prudential policies implied in China and pointed out the existing problems. Secondly, we analyzed the banks’ assets riskiness and the banks’ probability to default, then, by means of a leave-one-out model, we measured each commercial bank systemic risk contribution. Thirdly, based on comprehensive empirical results and theoretical analysis, we provided some references for macro-prudential regulation and supervision. Results show that systemic risk is increasing in 2013–2017, in particular with reference to contagion risk, with a specific concentration within joint-stock commercial banks, suggesting a specific attention of regulators and supervisors for this category.

Financial Statement Ratio Analysis to Predict Bankruptcy nn Company Registered in BEI - Jakarta (Altman Z-Score Method and Zmijewski)

2020 ◽  
Vol 3 (3) ◽  
pp. 122
Author(s):  
Andi Silvan
Keyword(s):  
Financial Distress ◽  
Stock Exchange ◽  
Good Condition ◽  
Financial Statement ◽  
Depth Information ◽  
Z Score ◽  
Industrial Manufacturing ◽  
Financial Difficulties ◽  
A Value ◽  
Score Method

AbstractThis study takes the topic of predicting corporate bankruptcies. This research dqlam use traditional methods Altman Z-Score and Zmijewski. The purpose of this study was to obtain in-depth information about predicting bankruptcy of companies that are not necessarily directly to bankruptcy, but there is financial distress.Based on the results of research conducted on the four (4) non industrial manufacturing company listed on the Indonesia Stock Exchange (BEI). Obtaining the value z-score represents the average company are in good condition, which means no financial distress. Acquisition value of x-score has a value of less than 0 (zero) which means that the company is in good condition and is predicted not experiencing financial difficulties. This study led to the conclusion that the Altman Z-Score and Zmijewski method can be used to predict corporate bankruptcy. Keywords: Financial Ratios, Bankruptcy, Company.

scholarly journals Fast Ways to Detect Outliers

2021 ◽  
Vol 3 (1) ◽  
pp. 66-73
Author(s):  
Emad Obaid Merza ◽  
Nashaat Jasim Mohammed
Keyword(s):  
Normal Distribution ◽  
Forest Fires ◽  
Confusion Matrix ◽  
Test Method ◽  
Z Score ◽  
Distribution Method ◽  
The Third ◽  
Data Points ◽  
Score Method ◽  
Zero Values

The occurrence of tremendous developments in the field of data has led to the formation of huge volumes of data, and it is normal that this leads to the presence of outliers in this data for many reasons, which may have small or large values ​​compared to the rest of the normal data, and the presence of outliers in the data affects the statistical analysis of this data, so we must try to reduce its impact in various ways. On the other hand, the presence of outliers ​​may be of great benefit, for example knowledge of geological activities that precede natural disasters such as (earthquakes, forest fires, floods ... etc.). Therefore, detection of outliers is of great importance in various fields. In this research, we aim to develop easy methods for detecting outliers in big data, as the problem that this research addresses is that many of the newly developed methods for detecting outliers suffer from computational complexity or are efficient when the sample size is small. An experimental approach was used in this research by suggesting three methods for detecting outliers, the first method is based on standard deviation and was tested and compared with the normal distribution method and the z-score method. The second method depends on the maximum and minimum value of the data, and the third method depends on the range between successive data points. The results of second and third methods are compared with Hample's Test method result. The accuracy of the results is measured based on the confusion matrix. The results of the proposed methods test showed the conformity of the first method with the results of the normal distribution method and the Z-Score method, as well as the superiority of the third method over the Hample's test method. In this paper, it was concluded that the Hample's test method suffers from a serious weakness when the zero values in the data constitute more than 50% of the number of elements.

scholarly journals ANALISIS FINANCIAL DISTRESS PADA PT TUNAS BARU LAMPUNG TBK DI BURSA EFEK INDONESIA

2017 ◽  
Vol 13 (2) ◽  
pp. 129-141
Author(s):  
Umi Ambarwati ◽  
Sudarwati Sudarwati ◽  
Rochmi Widayanti
Keyword(s):  
Financial Distress ◽  
Stock Exchange ◽  
Financial Ratios ◽  
Z Score ◽  
Effective Strategies ◽  
Operational Costs ◽  
Score Method

This article aims to analyze the health of the company in PT Tunas Baru Lampung TBK in Indonesia Stock Exchange. The data comes from PT Tunas Baru Lampung TBK in 2013-2015. The methods used are Altman Z-Score, Springate, Zmijewski and Fulmer methods. The results of the study show that there are differences in predicted bankruptcy results between the Altman Z-score method, Springate, Zmijewski and Fulmer. This is due to differences in the use of financial ratios and criteria bankruptcy between Altman Z-score, Springate, Zmijewski and Fulmer. For that company is expected to increase sales, perform effective strategies, reduce operational costs to be more efesian so that companies can meet the company's health criteria.   Artikel ini bertujuan untuk menganalisis kesehatan perusahaan pada PT Tunas Baru Lampung TBK di Bursa Efek Indonesia. Data berasal dari PT Tunas Baru Lampung TBK pada tahun 2013-2015. Metode yang digunakan adalah metode Altman Z-Score, Springate, Zmijewski dan Fulmer. Hasil penelitian menunjukkan adanya perbedaan hasil prediksi kebangkrutan antara metode Altman Z-score, Springate, Zmijewski dan Fulmer. Hal ini karena adanya perbedaan penggunaan rasio keuangan dan kriteria kebangkrutan antara Altman Z-score, Springate, Zmijewski dan Fulmer. Untuk itu perusahaan diharapkan meningkatkan penjualan, melakukan strategi yang efektif, menekan biaya operasional agar lebih efesian sehingga perusahaan dapat memenuhi kriteria kesehatan perusahaan.

scholarly journals Analisis Tingkat Kebangkrutan Pada Perusahaan Asuransi Yang Terdaftar Di Bursa Efek Indonesia

2019 ◽  
Vol 9 (2) ◽  
pp. 28
Author(s):  
Mikha Novalina Sinaga ◽  
Frendy A. O. Pelleng ◽  
Joanne V. Mangindaan
Keyword(s):  
Financial Management ◽  
Research Study ◽  
Stock Exchange ◽  
Insurance Companies ◽  
Z Score ◽  
Prediction Analysis ◽  
Financial Condition ◽  
Management Problems ◽  
Score Method ◽  
A Company

The purpose of this research study is to determine the result of prediction analysis of potential bankruptcy on eleven insurance companies sector which has been listed in Indonesia Stock Exchange year 2015 to 2018. Bankruptcy is a condition when a company experiences insufficient funds to run its business. Bankruptcy is uncertainty about the ability of a company to continue its operations if the financial condition held has decreased. In fact, not all companies experience financial management problems that often lead to bankruptcy. Based on the result and conclusions of the analysis using Altman Z-Score method that: in 2015-2018 there were several companies that were safe, namely: PT. Bina Dana Arta Insurance Tbk, PT. Harta Aman Pratama Insurance Tbk, PT. Jasa Tania Insurance Tbk, PT Indonesian reinsurance airline Tbk, PT. Panin Insurance Tbk, PT. Panin Financial Tbk, PT Victoria Insurance Tbk. Then there are companies that in 2015- 2017 are healthy but in 2018 in prone conditions, namely: PT. Bintang Insurance Tbk,and PT. Multi Artha Guna Insurance Tbk, but different from PT. Mitra Maparya Insurance Tbk which in 2015 was in vulnerable condition but in 2016-2018 is safe. And PT. Ramayana from 2015-2018 is in vulnerable condition.

scholarly journals PENGARUH FAKTOR INTERNAL DAN FAKTOR MAKROEKONOMI TERHADAP STABILITAS BANK UMUM SYARIAH DI INDONESIA PERIODE 2012-2018

2020 ◽  
Vol 7 (11) ◽  
pp. 2062
Author(s):  
Dian Rizqi Lestari ◽  
Noven Suprayogi
Keyword(s):  
Panel Data ◽  
Gross Domestic Product ◽  
Interest Rates ◽  
Commercial Bank ◽  
Commercial Banks ◽  
Annual Report ◽  
Domestic Product ◽  
Z Score ◽  
Score Method ◽  
Size Efficiency

ABSTRAKPenelitian ini bertujuan untuk mengetahui pengaruh ukuran bank, efisiensi, capital buffer, PDB, Inflasi, dan suku bunga terhadap tingkat stabilitas Bank Umum Syariah di Indonesia periode 2012-2018. Penelitian ini menggunakan data panel dan metode z-score dalam mengukur stabilitas. Data diambil dari website resmi Badan Pusat Statistik (BPS) dan annual report masing masing bank umum syariah. Hasil penelitian ini menunjukkan variabel ukuran bank (size), efisiensi, capital buffer, PDB (Produk Domestik Bruto), inflasi dan suku bunga (BI rate) secara simultan memiliki pengaruh yang signifikan. Kata Kunci: Stabilitas, Bank Umum Syariah, ukuran bank, efisiensi, capital buffer, PDB, Inflasi, suku bunga ABSTRACTThis study aims to determine the effect of bank size, efficiency, capital buffer, GDP, inflation, and interest rates on the level of stability of Sharia Commercial Banks in Indonesia for the period of 2012-2018. This study uses panel data and z-score method in measuring stability. This study used data obtained from the official website of the Central Statistics Agency and the annual report of each Islamic commercial bank. The results of this study indicate that the variable of bank size, efficiency, capital buffer, GDP (Gross Domestic Product), inflation and interest rates (BI rate) simultaneously have a significant effect.Keywords: Stability, Sharia Commercial Banks, bank size, efficiency, capital buffer, GDP, inflation, and interest rates

scholarly journals Enhancing Classification Performance of fNIRS-BCI by Identifying Cortically Active Channels Using the z-Score Method

Sensors ◽  
2020 ◽  
Vol 20 (23) ◽  
pp. 6995
Author(s):  
Hammad Nazeer ◽  
Noman Naseer ◽  
Aakif Mehboob ◽  
Muhammad Jawad Khan ◽  
Rayyan Azam Khan ◽  
...  
Keyword(s):  
Open Access ◽  
Motor Imagery ◽  
Mental Arithmetic ◽  
State Of The Art ◽  
Brain Activity ◽  
Channel Selection ◽  
Classification Performance ◽  
Finger Tapping ◽  
Z Score ◽  
Score Method

A state-of-the-art brain–computer interface (BCI) system includes brain signal acquisition, noise removal, channel selection, feature extraction, classification, and an application interface. In functional near-infrared spectroscopy-based BCI (fNIRS-BCI) channel selection may enhance classification performance by identifying suitable brain regions that contain brain activity. In this study, the z-score method for channel selection is proposed to improve fNIRS-BCI performance. The proposed method uses cross-correlation to match the similarity between desired and recorded brain activity signals, followed by forming a vector of each channel’s correlation coefficients’ maximum values. After that, the z-score is calculated for each value of that vector. A channel is selected based on a positive z-score value. The proposed method is applied to an open-access dataset containing mental arithmetic (MA) and motor imagery (MI) tasks for twenty-nine subjects. The proposed method is compared with the conventional t-value method and with no channel selected, i.e., using all channels. The z-score method yielded significantly improved (p < 0.0167) classification accuracies of 87.2 ± 7.0%, 88.4 ± 6.2%, and 88.1 ± 6.9% for left motor imagery (LMI) vs. rest, right motor imagery (RMI) vs. rest, and mental arithmetic (MA) vs. rest, respectively. The proposed method is also validated on an open-access database of 17 subjects, containing right-hand finger tapping (RFT), left-hand finger tapping (LFT), and dominant side foot tapping (FT) tasks.The study shows an enhanced performance of the z-score method over the t-value method as an advancement in efforts to improve state-of-the-art fNIRS-BCI systems’ performance.

DOES THE Z-SCORE METHOD RESOLVE THE NEONATAL MORTALITY PARADOX?

Epidemiology ◽  
2004 ◽  
Vol 15 (4) ◽  
pp. S157
Author(s):  
Enrique Schisterman ◽  
Miguel Hernan ◽  
Sonia Hernandez-Diaz
Keyword(s):  
Neonatal Mortality ◽  
Z Score ◽  
Score Method
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