scholarly journals Archetypal Analysis and DEA Model, Their Application on Financial Data and Visualization with PHATE

Entropy ◽  
2022 ◽  
Vol 24 (1) ◽  
pp. 88
Author(s):  
Urszula Grzybowska ◽  
Marek Karwański
Keyword(s):  
Stock Exchange ◽  
Dimensional Space ◽  
Investment Strategies ◽  
Financial Indicators ◽  
Archetypal Analysis ◽  
New Approach ◽  
Macroeconomic Analysis ◽  
Warsaw Stock Exchange ◽  
Low Dimensional ◽  
Insight Into

One of the goals of macroeconomic analysis is to rank and segment enterprises described by many financial indicators. The segmentation can be used for investment strategies or risk evaluation. The aim of this research was to distinguish groups of similar objects and visualize the results in a low dimensional space. In order to obtain clusters of similar objects, the authors applied a DEA BCC model and archetypal analysis for a set of companies described by financial indicators and listed on the Warsaw Stock Exchange. The authors showed that both methods give consistent results. To get a better insight into the data structure as well as a visualization of the similarities between objects, the authors used a new approach called the PHATE algorithm. It allowed the results of DEA and archetypal analysis to be visualized in a low dimensional space.

scholarly journals Are the Key Persons in Companies also their Key Assets? Evidence from a Transition Economy

2020 ◽  
Vol 31 (5) ◽  
pp. 536-546
Author(s):  
Katarzyna Byrka-Kita ◽  
Mateusz Czerwiński ◽  
Renata Gola
Keyword(s):  
Positive Reaction ◽  
Succession Planning ◽  
Transition Economy ◽  
Stock Exchange ◽  
Investment Strategies ◽  
Upper Echelons Theory ◽  
Warsaw Stock Exchange ◽  
A Company ◽  
Investor Reaction ◽  
Practical Implications

This study examines how published information about the death of a key person in a company has affected its market valuation as listed on the Warsaw Stock Exchange during the period 2005–2017. We find that investors reacted negatively and statistically significantly to information about the death of a key person. Furthermore, we confirmed a positive reaction to the loss of a so-called “entrenched CEO”. The same pattern of investor reaction is observed in more mature markets. These findings seem to support the upper echelons theory and entrenchment hypothesis. The obtained results not only contribute to the development of the theory, but also have significant practical implications. Primarily, investors should take into account such events when they are implementing investment strategies. Further, these results suggest that Polish firms need to undertake more formal succession planning for their executives.

scholarly journals Environmental issues as a non-financial reporting area using the example of selected companies listed on the Warsaw Stock Exchange

2020 ◽  
Vol 64 (9) ◽  
pp. 45-56
Author(s):  
Hanna Czaja-Cieszyńska
Keyword(s):  
Financial Reporting ◽  
Raw Materials ◽  
Stock Exchange ◽  
Secondary Data ◽  
Environmental Issues ◽  
Financial Indicators ◽  
Financial Reports ◽  
Warsaw Stock Exchange ◽  
Financial Disclosures ◽  
The Impact

The purpose of this article is to assess the comparability of non-financial disclosures on the impact of economic activity on the natural environment in reports of selected companies listed on the Warsaw Stock Exchange. The ten largest listed companies listed in the WIG-20 index were selected for the study. The analysis of the reports was based on the following disclosure categories: Materials and raw materials, Fuels and energy, Water, Biodiversity, Emissions to the atmosphere, Waste and Effluents, and Others. Within these categories, 14 key environmental non-financial indicators were defined. The empirical study carried out confirmed that the non-financial reports analyzed in all of the seven categories of disclosures were not fully comparable. The research methods used were: literature studies, analysis of legal regulations, analysis of secondary data, as well as methods of induction and synthesis.

scholarly journals Are polish healthcare stocks defensive?

2017 ◽  
Vol 6 (326) ◽  
Author(s):  
Bartłomiej Krzeczewski
Keyword(s):  
Stock Exchange ◽  
Point Of View ◽  
Healthcare Sector ◽  
Investment Strategies ◽  
Healthcare Industry ◽  
Daily Data ◽  
Warsaw Stock Exchange ◽  
Beta Coefficient ◽  
Stock Indexes ◽  
Risk Ratios

The main aim of this article is to verify whether the companies operating in Polish healthcare industry could be included into the group of so called defensive companies. The value of such companies during recession does not decline or the declines are significantly lower compared to the major stock indexes. The analysis carried out in the article is conducted amongst companies from healthcare sector listed on the Warsaw Stock Exchange (WSE). In the article an analysis is presented comparing risk ratios of defensive stocks and whole stock market such as beta coefficient (β). The analysis is based on daily data intervals from the period 2012–2014. The article is based on the assumption that Polish healthcare industry companies may be portrayed as defensive and the results of the study suggest to support this point of view. Therefore, the stocks of such companies can be considered by investors as interesting assets for building diversified portfolios and working on investment strategies.

A New Approach for Analyzing Stock Market Stress Based on the Warsaw Stock Exchange in 2005–2019

2021 ◽  
pp. 1-17
Author(s):  
Daniel Kosiorowski ◽  
Jerzy P. Rydlewski ◽  
Tadeusz Klecha ◽  
Dominik Mielczarek
Keyword(s):  
Stock Market ◽  
Stock Exchange ◽  
New Approach ◽  
Warsaw Stock Exchange

scholarly journals PREDICTING FINANCIAL DISTRESS FOR ROMANIAN COMPANIES

2018 ◽  
Vol 24 (6) ◽  
pp. 2318-2337 ◽  
Author(s):  
Gheorghe Ruxanda ◽  
Cătălina Zamfir ◽  
Andreea Muraru
Keyword(s):  
Financial Distress ◽  
Prediction Accuracy ◽  
Stock Exchange ◽  
Support Vector ◽  
Financial Indicators ◽  
New Approach ◽  
Linear Classifier ◽  
Vector Machines ◽  
Components Analysis ◽  
Bayesian Logistic Regression

Using a moderately large number of financial ratios, we tried to build models for classifying the companies listed on the Bucharest Stock Exchange into low and high risk classes of financial distress. We considered four classification techniques: Support Vector Machines, Decision Trees, Bayesian logistic regression and Fisher linear classifier, out of which the first two proved to have the highest prediction accuracy. Classifiers were trained and tested on randomly drown samples and on four different databases built starting from the initial financial indicators. As the literature related to the topic on Romanian data is very scarce, our study, by using a variety of methods and combining feature selection and principal components analysis, brings a new approach to predicting financial distress for Romanian companies.

scholarly journals Mechanical Stretch Inhibition Sensitizes Proprioceptors to Compressive Stresses

2021 ◽  
Author(s):  
Ravi Das ◽  
Li-Chun Lin ◽  
Frederic Català-Castro ◽  
Nawaphat Malaiwong ◽  
Neus Sanfeliu ◽  
...  
Keyword(s):  
Dimensional Space ◽  
Mechanical Stretch ◽  
C Elegans ◽  
Compressive Stresses ◽  
Tension And Compression ◽  
Low Dimensional ◽  
Spectrin Network ◽  
Insight Into

AbstractA repetitive gait cycle is an archetypical component within the behavioural repertoire of many if not all animals including humans. It originates from mechanical feedback within proprioceptors to adjust the motorprogram during locomotion and thus leads to a periodic orbit in a low dimensional space. Here, we investigate the mechanics, molecules and neurons responsible for proprioception in Caenorhabditis (C.) elegans to gain insight into how mechanosensation shapes the orbital trajectory to a well-defined limit cycle. We used genome editing, force spectroscopy and multiscale modeling and found that alternating tension and compression with the spectrin network of a single proprioceptor encodes body posture and informs TRP-4/NOMPC and TWK-16/TREK2 homologs of mechanosensitive ion channels during locomotion. In contrast to a widely accepted model of proprioceptive ‘stretch’ reception, we found that proprioceptors activated under compressive stresses in vivo and in vitro, and speculate that this property is conserved across function and species.

scholarly journals Network-Specific Variational Auto-Encoder for Embedding in Attribute Networks

2019 ◽  
Author(s):  
Di Jin ◽  
Bingyi Li ◽  
Pengfei Jiao ◽  
Dongxiao He ◽  
Weixiong Zhang
Keyword(s):  
Information Integration ◽  
Dimensional Space ◽  
Gaussian Mixture ◽  
Superior Performance ◽  
Network Structures ◽  
New Approach ◽  
Network Topologies ◽  
Node Attributes ◽  
Novel Method ◽  
Low Dimensional

Network embedding (NE) maps a network into a low-dimensional space while preserving intrinsic features of the network. Variational Auto-Encoder (VAE) has been actively studied for NE. These VAE-based methods typically utilize both network topologies and node semantics and treat these two types of data in the same way. However, the information of network topology and information of node semantics are orthogonal and are often from different sources; the former quantifies coupling relationships among nodes, whereas the latter represents node specific properties. Ignoring this difference affects NE. To address this issue, we develop a network-specific VAE for NE, named as NetVAE. In the encoding phase of our new approach, compression of network structures and compression of node attributes share the same encoder in order to perform co-training to achieve transfer learning and information integration. In the decoding phase, a dual decoder is introduced to reconstruct network topologies and node attributes separately. Specifically, as a part of the dual decoder, we develop a novel method based on a Gaussian mixture model and the block model to reconstruct network structures. Extensive experiments on large real-world networks demonstrate a superior performance of the new approach over the state-of-the-art methods.

scholarly journals The Momentum Effect Exemplifies The Influence of Investors’ Irrational Behaviour on Changing Prices of Shares and Stocks: An Analysis of The Momentum Effect on The Warsaw Stock Exchange

e-Finanse ◽  
2015 ◽  
Vol 11 (1) ◽  
pp. 56-64 ◽  
Author(s):  
Paweł Merło ◽  
Patryk Konarzewski
Keyword(s):  
Capital Markets ◽  
Stock Exchange ◽  
January Effect ◽  
Strong Impact ◽  
Investment Strategies ◽  
Momentum Effect ◽  
Return Rates ◽  
Time Period ◽  
New Information ◽  
Warsaw Stock Exchange

Abstract An efficient market should not show any anomalies. When new information reaches a market which is efficient, it should automatically translate into prices of assets, which ought to eliminate the possibility of gaining an advantage over other investors, thus preventing excess profits. However, studies on capital markets indicate that in reality it is possible to earn unusually high profits by taking advantage of certain anomalies which occur on a given market. Among such anomalies there is the momentum effect. This study performed on the Stock Exchange in Warsaw has shown that the momentum effect occurred throughout the entire analyzed time period. Positive returns demonstrated for investment strategies based on the momentum effect were unexplainable by the classical theory of finances. A correlation was found between the economic situation on the stock exchange and portfolio return rates, but it was too weak to attribute the effect to a single decisive factor. In addition, the returns from investments based on the momentum effect were statistically higher in January than in the other months, which was caused by the January effect, stimulating the occurrence of statistically higher returns at the beginning of a year rather than later on during the analyzed period of time. Research in this field carried out in other countries justifies the claim that there are many irrational factors which together create the momentum effect on the stock exchange. Thus, it is possible to conclude that irrational decisions may have strong impact on the pricing of stocks on the capital market. The momentum effect persisted throughout the entire analyzed period, although its power changed cyclically, which coincides with results of research carried out in other countries. The fact that the momentum effect did not disappear may suggest that the factors involved in its creation are an indispensable part of the market, and this seems to undermine the commonly accepted hypothesis about the efficiency of capital markets.

scholarly journals Cluster Appearance Glyphs: A Methodology for Illustrating High-Dimensional Data Patterns in 2-D Data Layouts

Information ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 3
Author(s):  
Jenny Hyunjung Lee ◽  
Darius Coelho ◽  
Klaus Mueller
Keyword(s):  
Dimensional Space ◽  
High Dimensional Data ◽  
File Systems ◽  
High Dimensional ◽  
Program Execution ◽  
Dimensional Scaling ◽  
Feature Descriptors ◽  
Low Dimensional ◽  
Data Layouts ◽  
Insight Into

Two-dimensional space embeddings such as Multi-Dimensional Scaling (MDS) are a popular means to gain insight into high-dimensional data relationships. However, in all but the simplest cases these embeddings suffer from significant distortions, which can lead to misinterpretations of the high-dimensional data. These distortions occur both at the global inter-cluster and the local intra-cluster levels. The former leads to misinterpretation of the distances between the various N-D cluster populations, while the latter hampers the appreciation of their individual shapes and composition, which we call cluster appearance. The distortion of cluster appearance incurred in the 2-D embedding is unavoidable since such low-dimensional embeddings always come at the loss of some of the intra-cluster variance. In this paper, we propose techniques to overcome these limitations by conveying the N-D cluster appearance via a framework inspired by illustrative design. Here we make use of Scagnostics which offers a set of intuitive feature descriptors to describe the appearance of 2-D scatterplots. We extend the Scagnostics analysis to N-D and then devise and test via crowd-sourced user studies a set of parameterizable texture patterns that map to the various Scagnostics descriptors. Finally, we embed these N-D Scagnostics-informed texture patterns into shapes derived from N-D statistics to yield what we call Cluster Appearance Glyphs. We demonstrate our framework with a dataset acquired to analyze program execution times in file systems.

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