arXiv subjects

Marcel Ausloos

Publications and source records attributed to Marcel Ausloos.

At least 37 records · Page 2Linked to original sources

arXiv2022

An Intrinsic Entropy Model for Exchange-Traded Securities

This article introduces an intrinsic entropy model that can be used as an indicator to gauge investor interest in a given exchange-traded security, along with the state of the general market corroborated by individual security trade data. Although the syntagma of intrinsic entropy might sound somehow pleonastic, since entropy itself characterizes the fundamentals of a system, we would like to make a clear distinction between entropy models based on the values that a random variable may take and the model that we propose, which employs actual stock exchange trading data. The model we propose for intrinsic entropy does not include any exogenous factor that could influence the level of entropy. The intrinsic entropy signals whether the market is inclined to buy the security or rather to sell it. We further explore the usage of the intrinsic entropy model for algorithmic trading, in order to demonstrate the value of our model in assisting investors in the selection of the intraday stock portfolio, along with timely generated signals to support the buy / sell decision making process. The test results provide empirical evidence that the proposed intrinsic entropy model can be used as an indicator to evaluate the direction and intensity of intraday trading activity of an exchange-traded security. The data used for the test consisted of historical intraday transactions executed on The Bucharest Stock Exchange (BVB).

q-fin.MF↗

arXiv2022

A Volatility Estimator of Stock Market Indices Based on the Intrinsic Entropy Model

Grasping the historical volatility of stock market indices and accurately estimating are two of the major focuses of those involved in the financial securities industry and derivative instruments pricing. This paper presents the results of employing the intrinsic entropy model as a substitute for estimating the volatility of stock market indices. Diverging from the widely used volatility models that take into account only the elements related to the traded prices, namely the open, high, low, and close prices of a trading day (OHLC), the intrinsic entropy model takes into account the traded volumes during the considered time frame as well. We adjust the intraday intrinsic entropy model that we introduced earlier for exchange-traded securities in order to connect daily OHLC prices with the ratio of the corresponding daily volume to the overall volume traded in the considered period. The intrinsic entropy model conceptualizes this ratio as entropic probability or market credence assigned to the corresponding price level. The intrinsic entropy is computed using historical daily data for traded market indices (S&P 500, Dow 30, NYSE Composite, NASDAQ Composite, Nikkei 225, and Hang Seng Index). We compare the results produced by the intrinsic entropy model with the volatility estimates obtained for the same data sets using widely employed industry volatility estimators. The intrinsic entropy model proves to consistently deliver reliable estimates for various time frames while showing peculiarly high values for the coefficient of variation, with the estimates falling in a significantly lower interval range compared with those provided by the other advanced volatility estimators.

q-fin.MF↗

arXiv2022

The Cross-Sectional Intrinsic Entropy. A Comprehensive Stock Market Volatility Estimator

To take into account the temporal dimension of uncertainty in stock markets, this paper introduces a cross-sectional estimation of stock market volatility based on the intrinsic entropy model. The proposed cross-sectional intrinsic entropy (CSIE) is defined and computed as a daily volatility estimate for the entire market, grounded on the daily traded prices: open, high, low, and close prices (OHLC), along with the daily traded volume for all symbols listed on The New York Stock Exchange (NYSE) and The National Association of Securities Dealers Automated Quotations (NASDAQ). We perform a comparative analysis between the time series obtained from the CSIE and the historical volatility as provided by the estimators: close-to-close, Parkinson, Garman-Klass, Rogers-Satchell, Yang-Zhang, and intrinsic entropy (IE), defined and computed from historical OHLC daily prices of the Standard & Poor's 500 index (S&P500), Dow Jones Industrial Average (DJIA), and the NASDAQ Composite index, respectively, for various time intervals. Our study uses approximately 6000 day reference points, starting on 1 Jan. 2001, until 23 Jan. 2022, for both the NYSE and the NASDAQ. We found that the CSIE market volatility estimator is consistently at least 10 times more sensitive to market changes, compared to the volatility estimate captured through the market indices. Furthermore, beta values confirm a consistently lower volatility risk for market indices overall, between 50% and 90% lower, compared to the volatility risk of the entire market in various time intervals and rolling windows.

q-fin.ST↗

arXiv2022

Are We Standing on Unreliable Shoulders? The Effect of Retracted Papers Citations on Previous and Subsequent Published Papers: A Study of the Web of Science Database

The present research attempts to identify the impact of retracted papers on previous or subsequent papers. We consider the 5693 retracted papers from 1975 to 2020 indexed in the Web of Science database based on bibliometric methods. We use HistCite, Excel, and SPSS software as technical means. The findings suggest a significant difference between the average number of retracted and unretracted papers when cited in retracted papers. Furthermore, there is a significant difference between the average number of unretracted and retracted papers citing retracted papers. The reasons for the retraction of an article may not be the previous retracted papers, yet unretracted papers may be retracted later because of referring to (many) retracted papers. It is deduced that proprietors of citation databases should carefully focus on these papers by checking references to each new paper citing previously retracted papers.

cs.DL↗

arXiv2022

Economic Freedom: The Top, the Bottom, and the Reality. I. 1997-2007

We recall the historically admitted prerequisites of Economic Freedom (EF). We have examined 908 data points for the Economic Freedom of the World (EFW) index and 1884 points for the Index of Economic Freedom (IEF); the studied periods are 2000-2006 and 1997-2007, respectively, thereby following the Berlin wall collapse, and including Sept. 11, 2001. After discussing EFW index and IEF, in order to compare the indices, one needs to study their overlap in time and space. That leaves 138 countries to be examined over a period extending from 2000 to 2006, thus 2 sets of 862 data points. The data analysis pertains to the rank-size law technique. It is examined whether the distributions obey an exponential or a power law. A correlation with the country Gross Domestic Product (GDP), an admittedly major determinant of EF, follows, distinguishing regional aspects, i.e. defining 6 continents. Semi-log plots show that the EFW-rank relationship is exponential for countries of high rank ($\ge 20$); overall the log-log plots point to a behaviour close to a power law. In contrast, for the IEF, the overall ranking has an exponential behaviour; but the log-log plots point to the existence of a transitional point between two different power laws, i.e., near rank 10. Moreover, log-log plots of the EFW index relationship to country GDP is characterised by a power law, with a rather stable exponent ($γ\simeq 0.674$) as a function of time. In contrast, log-log plots of the IEF relationship with the country's gross domestic product point to a downward evolutive power law as a function of time. Markedly the two studied indices provide different aspects of EF.

econ.GN↗

arXiv2022

An Intergenerational Issue: The Equity Issues due to Public-Private Partnerships. The Critical Aspect of the Social Discount Rate Choice for Future Generations

This paper investigates the impact of Social Discount Rate (SDR) choice on intergenerational equity issues caused by Public-Private Partnerships (PPPs) projects. Indeed, more PPPs mean more debt being accumulated for future generations leading to a fiscal deficit crisis. The paper draws on how the SDR level taken today distributes societies on the Social Welfare Function (SWF). This is done by answering two sub-questions: (i) What is the risk of PPPs debts being off-balance sheet? (ii) How do public policies, based on the envisaged SDR, position society within different ethical perspectives? The answers are obtained from a discussion of the different SDRs (applied in the UK for examples) according to the merits of the pertinent ethical theories, namely libertarian, egalitarian, utilitarian and Rawlsian. We find that public policymakers can manipulate the SDR to make PPPs looking like a better option than the traditional financing form. However, this antagonises the Value for Money principle. We also point out that public policy is not harmonised with ethical theories. We find that at present (in the UK), the SDR is somewhere between weighted utilitarian and Rawlsian societies in the trade-off curve. Alas, our study finds no evidence that the (UK) government is using a sophisticated system to keep pace with the accumulated off-balance sheet debts. Thus, the exact prediction of the final state is hardly made because of the uncertainty factor. We conclude that our study hopefully provides a good analytical framework for policymakers in order to draw on the merits of ethical theories before initiating public policies like PPPs.

econ.GN↗

arXiv2021

Retracted papers by Iranian authors: Causes, journals, time lags, affiliations, collaborations

This study aims to analyze 343 retraction notices indexed in the Scopus database, published in 2001-2019, related to scientific articles (co-)written by at least one author affiliated with an Iranian institution. In order to determine reasons for retractions, we merged this database with the database from Retraction Watch. The data were analyzed using Excel 2016 and IBM-SPSS version 24.0, and visualized using VOSviewer software. Most of the retractions were due to fake peer review (95 retractions) and plagiarism (90). The average time between a publication and its retraction was 591 days. The maximum time-lag (about 3,000 days) occurred for papers retracted due to duplicate publications; the minimum time-lag (fewer than 100 days) was for papers retracted due to ''unspecified cause'' (most of these were conference papers). As many as 48 (14%) of the retracted papers were published in two medical journals: Tumor Biology (25 papers) and Diagnostic Pathology (23 papers). From the institutional point of view, Islamic Azad University was the inglorious leader, contributing to over one-half (53.1%) of retracted papers. Among the 343 retraction notices, 64 papers pertained to international collaborations with researchers from mainly Asian and European countries; Malaysia having the most retractions (22 papers). Since most retractions were due to fake peer review and plagiarism, the peer review system appears to be a weak point of the submission/publication process; if improved, the number of retractions would likely drop because of increased editorial control.

cs.DL↗

arXiv2021

Stock index futures trading impact on spot price volatility. The CSI 300 studied with a TGARCH model

A TGARCH modeling is argued to be the optimal basis for investigating the impact of index futures trading on spot price variability. We discuss the CSI-300 index (China-Shanghai-Shenzhen-300-Stock Index) as a test case. The results prove that the introduction of CSI-300 index futures (CSI-300-IF) trading significantly reduces the volatility in the corresponding spot market. It is also found that there is a stationary equilibrium relationship between the CSI-300 spot and CCSI-300-IF markets. A bidirectional Granger causality is also detected. ''Finally'', it is deduced that spot prices are predicted with greater accuracy over a 3 or 4 lag day time span.

q-fin.ST↗

arXiv2021

Tsallis entropy for cross-shareholding network configurations

In this work, we develop the Tsallis entropy approach for examining the cross-shareholding network of companies traded on the Italian stock market. In such a network, the nodes represent the companies, and the links represent the ownership. Within this context, we introduce the out-degree of the nodes -- which represents the diversification -- and the in-degree of them -- capturing the integration. Diversification and integration allow a clear description of the industrial structure formed by the considered companies. The stochastic dependence of diversification and integration is modelled through copulas. We argue that copulas are well suited for modelling the joint distribution. The analysis of the stochastic dependence between integration and diversification by means of the Tsallis entropy gives a crucial information on the reaction of the market structure to the external shocks, - on the basis of some relevant cases of dependence between the considered variables. In this respect, the considered entropy framework provides insights on the relationship between in-degree and out-degree dependence structure and market polarisation or fairness. Moreover, the interpretation of the results in the light of the Tsallis entropy parameter gives relevant suggestions for policymakers who aim at shaping the industrial context for having high polarisation or fair joint distribution of diversification and integration. Furthermore, a discussion of possible parametrisations of the in-degree and out-degree marginal distribution, -- by means of power laws or exponential functions, -- is also carried out. An empirical experiment on a large dataset of Italian companies validates the theoretical framework.

physics.soc-ph↗

arXiv2021

Benford's laws tests on S&P500 daily closing values and the corresponding daily log-returns both point to huge non-conformity

The so-called Benford's laws are of frequent use in order to observe anomalies and regularities in data sets, in particular, in election results and financial statements. Yet, basic financial market indices have not been much studied, if studied at all, within such a perspective. This paper presents features in the distributions of S\&P500 daily closing values and the corresponding daily log returns over a long time interval, [03/01/1950 - 22/08/2014], amounting to 16265 data points. We address the frequencies of the first, second, and first two significant digits counts and explore the conformance to Benford's laws of these distributions at five different (equal size) levels of disaggregation. The log returns are studied for either positive or negative cases. The results for the S&P500 daily closing values are showing a huge lack of non-conformity, whatever the different levels of disaggregation. Some "first digits" and "first two digits" values are even missing. The causes of this non-conformity are discussed, pointing to the danger in taking Benford's laws for granted in huge databases, whence drawing "definite conclusions". The agreements with Benford's laws are much better for the log returns. Such a disparity in agreements finds an explanation in the data set itself: the inherent trend in the index. To further validate this, daily returns have been simulated calibrating the simulations with the observed data averages and tested against Benford's laws. One finds that not only the trend but also the standard deviation of the distributions are relevant parameters in concluding about conformity with Benford's laws.

q-fin.ST↗

arXiv2020

If Global or Local Investor Sentiments are Prone to Developing an Impact on Stock Returns, is there an Industry Effect?

This paper investigates the heterogeneous impacts of either Global or Local Investor Sentiments on stock returns. We study 10 industry sectors through the lens of 6 (so called) emerging countries: China, Brazil, India, Mexico, Indonesia and Turkey, over the 2000 to 2014 period. Using a panel data framework, our study sheds light on a significant effect of Local Investor Sentiments on expected returns for basic materials, consumer goods, industrial, and financial industries. Moreover, our results suggest that from Global Investor Sentiments alone, one cannot predict expected stock returns in these markets.

econ.GN↗

arXiv2020

Insider trading in the run-up to merger announcements. Before and after the UK's Financial Services Act 2012

After the 2007/2008 financial crisis, the UK government decided that a change in regulation was required to amend the poor control of financial markets. The Financial Services Act 2012 was developed as a result in order to give more control and authority to the regulators of financial markets. Thus, the Financial Conduct Authority (FCA) succeeded the Financial Services Authority (FSA). An area requiring an improvement in regulation was insider trading. Our study examines the effectiveness of the FCA in its duty of regulating insider trading through utilising the event study methodology to assess abnormal returns in the run-up to the first announcement of mergers. Samples of abnormal returns are examined on periods, under regulation either by the FSA or by the FCA. Practically, stock price data on the London Stock Exchange from 2008-2012 and 2015-2019 is investigated. The results from this study determine that abnormal returns are reduced after the implementation of the Financial Services Act 2012; prices are also found to be noisier in the period before the 2012 Act. Insignificant abnormal returns are found in the run-up to the first announcement of mergers in the 2015-2019 period. This concludes that the FCA is efficient in regulating insider trading.

q-fin.GN↗

arXiv2020

Simple approaches on how to discover promising strategies for efficient enterprise performance, at time of crisis in the case of SMEs : Voronoi clustering and outlier effects perspective

This paper analyzes the connection between innovation activities of companies -- implemented before a financial crisis -- and their performance -- measured after such a time of crisis. Pertinent data about companies listed in the STAR Market Segment of the Italian Stock Exchange is analyzed. Innovation is measured through the level of investments in total tangible and intangible fixed assets in 2006-2007, while performance is captured through growth -- expressed by variations of sales or of total assets, -- profitability -- through ROI or ROS evolution, - and productivity -- through asset turnover or sales/employee in the period 2008-2010. The variables of interest are analyzed and compared through statistical techniques and by adopting a cluster analysis. In particular, a Voronoi tessellation is implemented in a varying centroids framework. In accord with a large part of the literature, we find that the behavior of the performance of the companies is not univocal when they innovate. The statistical outliers are the best cases in order to suggest efficient strategies. In brief, it is found that a positive rate of investments is preferable.

q-fin.ST↗

arXiv2020

Challenging Practical Features of Bitcoin by the Main Altcoins

We study the fundamental differences that separate: Litecoin; Bitcoin Gold; Bitcoin Cash; Ethereum; and Zcash from Bitcoin, and draw analysis to how these features are appreciated by the market, to ultimately make an inference as to how future successful cryptocurrencies may behave. We use Google Trend data, as well as price, volume and market capitalization data sourced from coinmarketcap.com to support this analysis. We find that Litecoin's shorter block times offer benefits in commerce, but drawbacks in the mining process through orphaned blocks. Zcash holds a niche use for anonymous transactions, benefitting areas of the world lacking in economic freedom. Bitcoin Cash suffers from centralization in the mining process, while the greater decentralization of Bitcoin Gold has generally left it to stagnate. Ether's greater functionality offers the greatest threat to Bitcoin's dominance in the market. A coin that incorporates several of these features can be technically better than Bitcoin, but the first-to-marketadvantage of Bitcoin should keep its dominant position in the market.

q-fin.GN↗

arXiv2020

Hagiotoponyms in France: Saint popularity, like a herding phase transition

A spectacular order-order-like transition is presented in the distribution of hagiotoponyms in France. Data analysis and displays distinguish male and female cases. The respective hapax values point to a very large variety of saints with a specific devotion. The most popular ones are St. Martin and the apostles. The less popular ones are not so well known. These features are explained in terms of herding in agent behaviors: people have either preferred popular saints with supposedly good links to God, whence a herding behavior, or (non-herding) agents have preferred to name their local human settlement through a reference to some holy person(s) with more local specificities -- yet with moral or religious leadership, and conjectured to have good contact with God, whence at least locally defined as a saint.

physics.soc-ph↗

arXiv2020

Valuation Models Applied to Value-Based Management. Application to the Case of UK Companies with Problems

Many still rightly wonder whether accounting numbers affect business value. Basic questions are why? and how? I aim at promoting an objective choice on how optimizing the most suitable valuation methods under a value-based management framework through some performance measurement systems. First, I present a comprehensive review of valuation methods. Three valuations methods, (i) Free Cash Flow Valuation Model (FCFVM), (ii) Residual Earning Valuation Model (REVM) and (iii) Abnormal Earning Growth Model (AEGM), are presented. I point out to advantages and limitations. As applications, the proofs of the findings are illustrated on three study cases: Marks & Spencer's business pattern (size and growth prospect), which had a recently advertised valuation problem, and two comparable companies, Tesco and Sainsbury's, all three chosen for multiple-based valuation. For the purpose, two value drivers are chosen, EnV/EBIT (entity value/earnings before interests and taxes) and the corresponding EnV/Sales. Thus, the question whether accounting numbers through models based on mathematical economics truly affect business value has an answer: Maybe, yes.

q-fin.GN↗

arXiv2020

Corporate Governance and Firms Financial Performance in the United Kingdom

The objective of this study is to examine empirically the impact of good corporate governance on financial performance of United Kingdom non-financial listed firms. Agency theory and stewardship theory serve as the bases of a conceptual model. Five corporate governance mechanisms are examined on two financial performance indicators, return on assets (ROA) and Tobin's Q, employing cross-sectional regression methodology. The conclusion drawn from empirical test so performed on 252 firms listed on London Stock Exchange for the year 2014 indicates a positive or a negative relationship, but also sometimes no effect, of corporate governance mechanisms impact on financial performance. The implications are discussed. Thereby, so distinguishing effects due to causes, we present a proof that, when the right corporate governance mechanisms are chosen, the finances of a firm can be improved. The results of this research should have some implication on academia and policy makers thoughts.

q-fin.GN↗

arXiv2020

Words ranking and Hirsch index for identifying the core of the hapaxes in political texts

This paper deals with a quantitative analysis of the content of official political speeches. We study a set of about one thousand talks pronounced by the US Presidents, ranging from Washington to Trump. In particular, we search for the relevance of the rare words, i.e. those said only once in each speech -- the so-called hapaxes. We implement a rank-size procedure of Zipf-Mandelbrot type for discussing the hapaxes' frequencies regularity over the overall set of speeches. Starting from the obtained rank-size law, we define and detect the core of the hapaxes set by means of a procedure based on an Hirsch index variant. We discuss the resulting list of words in the light of the overall US Presidents' speeches. We further show that this core of hapaxes itself can be well fitted through a Zipf-Mandelbrot law and that contains elements producing deviations at the low ranks between scatter plots and fitted curve -- the so-called king and vice-roy effect. Some socio-political insights are derived from the obtained findings about the US Presidents messages.

cs.CL↗