The impact of accounting disclosure on emerging stock market prediction in an unstable socio-political context

محفوظ في:
التفاصيل البيبلوغرافية
الحاوية / القاعدة:Accounting and Management Information Systems vol. 17, no. 3 (2018), p. 313
المؤلف الرئيسي: Kooli, Chaima
مؤلفون آخرون: Trabelsi, Raoudha, Tlili, Fethi
منشور في:
Bucharest Academy of Economic Studies
الموضوعات:
الوصول للمادة أونلاين:Citation/Abstract
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022 |a 2559-6004 
024 7 |a 10.24818/jamis.2018.03001  |2 doi 
035 |a 2117761987 
045 2 |b d20180101  |b d20181231 
084 |a 126519  |2 nlm 
100 1 |a Kooli, Chaima  |u Sfax Business School, Sfax University, Tunisia 
245 1 |a The impact of accounting disclosure on emerging stock market prediction in an unstable socio-political context 
260 |b Bucharest Academy of Economic Studies  |c 2018 
513 |a Journal Article 
520 3 |a The paper analyzes the impact of accounting disclosure on the prediction quality of stock market prices. The study also investigates whether a changing socio-political context affects the prediction quality. We focused on the Tunisian case, which has known a political turmoil in January 2011. Our sample includes 48,204 daily stock closing prices of 39 companies listed in Tunis Stock Exchange from 2009 to 2014. We used an Artificial Neural Network (ANN) with a Multi-layer Perceptron topology to predict the time series. The simulations showed that the average annual prediction error of the stock prices is the largest in the period relating to the January 2011 events. Thus, the country socio-political context impacts negatively the prediction quality of the stock market prices. Furthermore, the integration of an accounting variable improves the quality of the stock prices prediction for all the study periods, except the one that corresponds to the events of January 2011. In other words, it appears that accounting disclosure does not improve prices prediction quality in an unstable context. 
610 4 |a Bourse de Tunis Tehran Stock Exchange 
651 4 |a Italy 
651 4 |a Tunisia 
651 4 |a United States--US 
653 |a International conferences 
653 |a Markets 
653 |a Statistical mechanics 
653 |a Hypothesis testing 
653 |a Multilayers 
653 |a Books 
653 |a Politics 
653 |a Artificial neural networks 
653 |a Stock exchanges 
653 |a Time series 
653 |a Pricing 
653 |a Computer simulation 
653 |a Forecasting techniques 
653 |a Principal components analysis 
653 |a Studies 
653 |a Neural networks 
653 |a Variables 
653 |a Impact analysis 
653 |a Stock prices 
653 |a Earnings per share 
653 |a Book value 
653 |a Market prices 
653 |a Securities markets 
653 |a Accounting 
653 |a New stock market listings 
653 |a Simulation 
653 |a Literature reviews 
653 |a Artificial intelligence 
700 1 |a Trabelsi, Raoudha  |u Sfax Business School, Sfax University, Tunisia 
700 1 |a Tlili, Fethi  |u Tunis Higher School of Communication, Tunisia 
773 0 |t Accounting and Management Information Systems  |g vol. 17, no. 3 (2018), p. 313 
786 0 |d ProQuest  |t ABI/INFORM Global 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/2117761987/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch 
856 4 0 |3 Full Text  |u https://www.proquest.com/docview/2117761987/fulltext/embedded/6A8EOT78XXH2IG52?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/2117761987/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch