Mohammad Mahdi Rounaghi

Personal Details

First Name:	Mohammad Mahdi
Middle Name:
Last Name:	Rounaghi
Suffix:
RePEc Short-ID:	pro1128
	[This author has chosen not to make the email address public]
	https://scholar.google.com/citations?user=QUet-UQAAAAJ&hl=en
Terminal Degree:	Department of Accounting; Mashhad Branch; Islamic Azad University (from RePEc Genealogy)

Affiliation

Research Scientist in Finance and Economics

https://scholar.google.com/citations?user=QUet-UQAAAAJ&hl=en
Iran, Mashhad

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Articles

1. Mohammad Arashi & Mohammad Mahdi Rounaghi, 2022. "Analysis of market efficiency and fractal feature of NASDAQ stock exchange: Time series modeling and forecasting of stock index using ARMA-GARCH model," Future Business Journal, Springer, vol. 8(1), pages 1-12, December.

   Cited by:

   1. Virginie Terraza & Aslı Boru İpek & Mohammad Mahdi Rounaghi, 2024. "The nexus between the volatility of Bitcoin, gold, and American stock markets during the COVID-19 pandemic: evidence from VAR-DCC-EGARCH and ANN models," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-34, December.
   2. Deniz Erer & Elif Erer & Selim Güngör, 2023. "The aggregate and sectoral time-varying market efficiency during crisis periods in Turkey: a comparative analysis with COVID-19 outbreak and the global financial crisis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-25, December.
   3. Haojun Pan & Yuxiang Tang & Guoqiang Wang, 2024. "A Stock Index Futures Price Prediction Approach Based on the MULTI-GARCH-LSTM Mixed Model," Mathematics, MDPI, vol. 12(11), pages 1-15, May.

2. Mahdi Moradi & Mehdi Jabbari Nooghabi & Mohammad Mahdi Rounaghi, 2021. "Investigation of fractal market hypothesis and forecasting time series stock returns for Tehran Stock Exchange and London Stock Exchange," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 662-678, January.

   Cited by:

   1. Emrah BALKAN & Umut UYAR, 2022. "The Fractal Structure of CDS Spreads: Evidence from the OECD Countries," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 106-121, April.
   2. Román Alejandro Mendoza Urdiales & Andrés García-Medina & José Antonio Nuñez Mora, 2021. "Measuring information flux between social media and stock prices with Transfer Entropy," PLOS ONE, Public Library of Science, vol. 16(9), pages 1-19, September.
   3. Mohammad Arashi & Mohammad Mahdi Rounaghi, 2022. "Analysis of market efficiency and fractal feature of NASDAQ stock exchange: Time series modeling and forecasting of stock index using ARMA-GARCH model," Future Business Journal, Springer, vol. 8(1), pages 1-12, December.
   4. Svogun, Daniel & Bazán-Palomino, Walter, 2022. "Technical analysis in cryptocurrency markets: Do transaction costs and bubbles matter?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
   5. Karim, Muhammad Mahmudul & Kawsar, Najmul Haque & Ariff, Mohamed & Masih, Mansur, 2022. "Does implied volatility (or fear index) affect Islamic stock returns and conventional stock returns differently? Wavelet-based granger-causality, asymmetric quantile regression and NARDL approaches," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 77(C).
   6. Oluwasegun B. Adekoya & Gabriel O. Oduyemi & Johnson A. Oliyide, 2021. "Price and volatility persistence of the US REITs market," Future Business Journal, Springer, vol. 7(1), pages 1-10, December.
   7. Nyanine Chuele Fonou-Dombeu & Josue Mbonigaba & Odunayo Magret Olarewaju & Bomi Cyril Nomlala, 2022. "Earnings quality measures and stock return volatility in South Africa," Future Business Journal, Springer, vol. 8(1), pages 1-15, December.
   8. Deniz Erer & Elif Erer & Selim Güngör, 2023. "The aggregate and sectoral time-varying market efficiency during crisis periods in Turkey: a comparative analysis with COVID-19 outbreak and the global financial crisis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-25, December.

3. Mohammad Mahdi Rounaghi & Hajer Jarrar & Leo-Paul Dana, 2021. "Implementation of strategic cost management in manufacturing companies: overcoming costs stickiness and increasing corporate sustainability," Future Business Journal, Springer, vol. 7(1), pages 1-8, December.

   Cited by:

   1. Jeng-Chieh Cheng & Jeen-Fong Li & Chi-Yo Huang, 2023. "Enablers for Adopting Restriction of Hazardous Substances Directives by Electronic Manufacturing Service Providers," Sustainability, MDPI, vol. 15(16), pages 1-45, August.
   2. Okharedia Goodheart Akhimien & Simon Ayo Adekunle, 2023. "Technological environment and sustainable performance of oil and gas firms: a structural equation modelling approach," Future Business Journal, Springer, vol. 9(1), pages 1-11, December.
   3. Ulrike Michel-Schneider, 2022. "Patenting - A Cost Management Perspective," Proceedings of Economics and Finance Conferences 12915571, International Institute of Social and Economic Sciences.
   4. Ismail Abdi Changalima & Ismail Juma Ismail & Alban Dismas Mchopa, 2021. "A review of the forms, rationale, and challenges of supplier development in public procurement: lessons for public buyers in Tanzania," Future Business Journal, Springer, vol. 7(1), pages 1-10, December.
   5. Mojtaba Hajian Heidary, 2022. "A system dynamics model of the impact of COVID-19 pandemic and foreign direct investment in the global supply chain," Future Business Journal, Springer, vol. 8(1), pages 1-9, December.
   6. Raghda Abdellatif Abdelkhalik Elsayed, 2023. "Exploring the financial consequences of biodiversity disclosure: how does biodiversity disclosure affect firms' financial performance?," Future Business Journal, Springer, vol. 9(1), pages 1-18, December.

4. Mohammad Mahdi Rounaghi, 2019. "Economic analysis of using green accounting and environmental accounting to identify environmental costs and sustainability indicators," International Journal of Ethics and Systems, Emerald Group Publishing Limited, vol. 35(4), pages 504-512, September.

   Cited by:

   1. Mohammad Mahdi Rounaghi & Hajer Jarrar & Leo-Paul Dana, 2021. "Implementation of strategic cost management in manufacturing companies: overcoming costs stickiness and increasing corporate sustainability," Future Business Journal, Springer, vol. 7(1), pages 1-8, December.
   2. Luluk Muhimatul Ifada & Romlah Jaffar, 2023. "Does Environmental Cost Expenditure Matter? Evidence from Selected Countries in the Asia-Pacific Region," Sustainability, MDPI, vol. 15(5), pages 1-16, February.
   3. Meidijati Meidijati & Yvonne Augustine, 2022. "The Effect of Tax Accounting, Green Accounting, and Carbon Accounting on Environmental, Social, and Governance Performance: Moderated by Green Intellectual Capital," Technium Social Sciences Journal, Technium Science, vol. 31(1), pages 371-387, May.
   4. Zhe Liu & Bertrum MacDonald, 2020. "New Policies and Evaluation System Needed to Address Environmental Concerns in China," Sustainability, MDPI, vol. 12(12), pages 1-3, June.
   5. Agus Joko Pramono & Suwarno & Firdaus Amyar & Renny Friska, 2023. "Sustainability Management Accounting in Achieving Sustainable Development Goals: The Role of Performance Auditing in the Manufacturing Sector," Sustainability, MDPI, vol. 15(13), pages 1-13, June.
   6. Siba Sankar Mohanty & Himanshu Mallik, 2022. "Discounting GDP for Pollution, Waste Generation and Natural Resources Depletion: A Comparative Analysis of selected High, Middle and Low income countries," Journal of Studies in Dynamics and Change (JSDC), ISSN: 2348-7038, Voices of Inclusive Change and Expressions- (VOICE) Trust, Dehradun, Uttarakhand, vol. 9(4), pages 13-27, October-D.
   7. Okharedia Goodheart Akhimien & Simon Ayo Adekunle, 2023. "Technological environment and sustainable performance of oil and gas firms: a structural equation modelling approach," Future Business Journal, Springer, vol. 9(1), pages 1-11, December.
   8. Lisna Lisnawati & Titik Aryati & Juniati Gunawan, 2024. "Implementation of digital innovation on sustainability performance: the moderating role of green accounting in the industrial sector," Eastern-European Journal of Enterprise Technologies, PC TECHNOLOGY CENTER, vol. 1(13 (127)), pages 59-68, February.

5. Rounaghi, Mohammad Mahdi & Nassir Zadeh, Farzaneh, 2016. "Investigation of market efficiency and Financial Stability between S&P 500 and London Stock Exchange: Monthly and yearly Forecasting of Time Series Stock Returns using ARMA model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 10-21.

   Cited by:

   1. Darko B. Vukovic & Vladislav Ugolnikov & Moinak Maiti, 2021. "Sell‐side analysts' recommendations a value or noise," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 3134-3151, April.
   2. Kamaladdin Fataliyev & Aneesh Chivukula & Mukesh Prasad & Wei Liu, 2021. "Stock Market Analysis with Text Data: A Review," Papers 2106.12985, arXiv.org, revised Jul 2021.
   3. K. Hafsal & Anandarao Suvvari & S. Raja Sethu Durai, 2020. "Efficiency of Indian banks with non-performing assets: evidence from two-stage network DEA," Future Business Journal, Springer, vol. 6(1), pages 1-9, December.
   4. Lee, Minhyuk & Song, Jae Wook & Kim, Sondo & Chang, Woojin, 2018. "Asymmetric market efficiency using the index-based asymmetric-MFDFA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 1278-1294.
   5. Jujie Wang & Yinan Liao & Zhenzhen Zhuang & Dongming Gao, 2021. "An Optimal Weighted Combined Model Coupled with Feature Reconstruction and Deep Learning for Multivariate Stock Index Forecasting," Mathematics, MDPI, vol. 9(21), pages 1-20, October.
   6. Mohammad Arashi & Mohammad Mahdi Rounaghi, 2022. "Analysis of market efficiency and fractal feature of NASDAQ stock exchange: Time series modeling and forecasting of stock index using ARMA-GARCH model," Future Business Journal, Springer, vol. 8(1), pages 1-12, December.
   7. Ionel Jianu & Iulia Jianu, 2018. "The Share Price and Investment: Current Footprints for Future Oil and Gas Industry Performance," Energies, MDPI, vol. 11(2), pages 1-15, February.
   8. Svogun, Daniel & Bazán-Palomino, Walter, 2022. "Technical analysis in cryptocurrency markets: Do transaction costs and bubbles matter?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
   9. Muhammad Usman Khurram & Kashif Hamid & Rana Shahid Imdad Akash, 2019. "Market Efficiency, Financial Integration, And Shock Transmission (Empirical Evidence From D-8 Economies)," Baltic Journal of Economic Studies, Publishing house "Baltija Publishing", vol. 5(4).
   10. E, Jianwei & Bao, Yanling & Ye, Jimin, 2017. "Crude oil price analysis and forecasting based on variational mode decomposition and independent component analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 484(C), pages 412-427.
   11. Mahdi Moradi & Mehdi Jabbari Nooghabi & Mohammad Mahdi Rounaghi, 2021. "Investigation of fractal market hypothesis and forecasting time series stock returns for Tehran Stock Exchange and London Stock Exchange," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 662-678, January.
   12. Weijia Shao & Lukas Friedemann Radke & Fikret Sivrikaya & Sahin Albayrak, 2021. "Adaptive Online Learning for the Autoregressive Integrated Moving Average Models," Mathematics, MDPI, vol. 9(13), pages 1-30, June.
   13. Anders Nõu & Darya Lapitskaya & Mustafa Hakan Eratalay & Rajesh Sharma, 2021. "Predicting Stock Return And Volatility With Machine Learning And Econometric Models: A Comparative Case Study Of The Baltic Stock Market," University of Tartu - Faculty of Economics and Business Administration Working Paper Series 135, Faculty of Economics and Business Administration, University of Tartu (Estonia).
   14. Traianos-Ioannis Theodorou & Alexandros Zamichos & Michalis Skoumperdis & Anna Kougioumtzidou & Kalliopi Tsolaki & Dimitris Papadopoulos & Thanasis Patsios & George Papanikolaou & Athanasios Konstanti, 2021. "An AI-Enabled Stock Prediction Platform Combining News and Social Sensing with Financial Statements," Future Internet, MDPI, vol. 13(6), pages 1-22, May.

6. Zahedi, Javad & Rounaghi, Mohammad Mahdi, 2015. "Application of artificial neural network models and principal component analysis method in predicting stock prices on Tehran Stock Exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 178-187.

   Cited by:

   1. Sujin Pyo & Jaewook Lee & Mincheol Cha & Huisu Jang, 2017. "Predictability of machine learning techniques to forecast the trends of market index prices: Hypothesis testing for the Korean stock markets," PLOS ONE, Public Library of Science, vol. 12(11), pages 1-17, November.
   2. U, JuHyok & Lu, PengYu & Kim, ChungSong & Ryu, UnSok & Pak, KyongSok, 2020. "A new LSTM based reversal point prediction method using upward/downward reversal point feature sets," Chaos, Solitons & Fractals, Elsevier, vol. 132(C).
   3. Zhang, Yongjie & Chu, Gang & Shen, Dehua, 2021. "The role of investor attention in predicting stock prices: The long short-term memory networks perspective," Finance Research Letters, Elsevier, vol. 38(C).
   4. Elfadil A. Mohamed & Ibrahim Elsiddig Ahmed & Riyadh Mehdi & Hanan Hussain, 2021. "Impact of corporate performance on stock price predictions in the UAE markets: Neuro‐fuzzy model," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 28(1), pages 52-71, January.
   5. Hemmat Esfe, Mohammad & Rostamian, Hossein & Esfandeh, Saeed & Afrand, Masoud, 2018. "Modeling and prediction of rheological behavior of Al2O3-MWCNT/5W50 hybrid nano-lubricant by artificial neural network using experimental data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 625-634.
   6. Guo, Qingran & Ahmed, Khalid & Ding, Cuicui & Khan, Bareerah, 2024. "How the pandemic-led volatility in the natural resource commodity indices affect U.S and China markets," Resources Policy, Elsevier, vol. 90(C).
   7. Arezoo Hatefi Ghahfarrokhi & Mehrnoush Shamsfard, 2019. "Tehran Stock Exchange Prediction Using Sentiment Analysis of Online Textual Opinions," Papers 1909.03792, arXiv.org, revised Sep 2019.
   8. Mohammad Arashi & Mohammad Mahdi Rounaghi, 2022. "Analysis of market efficiency and fractal feature of NASDAQ stock exchange: Time series modeling and forecasting of stock index using ARMA-GARCH model," Future Business Journal, Springer, vol. 8(1), pages 1-12, December.
   9. Rashmi Chaudhary & Priti Bakhshi & Hemendra Gupta, 2020. "Volatility in International Stock Markets: An Empirical Study during COVID-19," JRFM, MDPI, vol. 13(9), pages 1-17, September.
   10. Rounaghi, Mohammad Mahdi & Nassir Zadeh, Farzaneh, 2016. "Investigation of market efficiency and Financial Stability between S&P 500 and London Stock Exchange: Monthly and yearly Forecasting of Time Series Stock Returns using ARMA model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 10-21.
   11. Nahida Akter & Ashadun Nobi, 2018. "Investigation of the Financial Stability of S&P 500 Using Realized Volatility and Stock Returns Distribution," JRFM, MDPI, vol. 11(2), pages 1-10, April.
   12. Arezoo Hatefi Ghahfarrokhi & Mehrnoush Shamsfard, 2020. "Tehran stock exchange prediction using sentiment analysis of online textual opinions," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 27(1), pages 22-37, January.
   13. J. Gavin & M. Crane, 2021. "Community Detection in Cryptocurrencies with Potential Applications to Portfolio Diversification," Papers 2108.09763, arXiv.org.
   14. Jian Huang & Huazhang Liu, 2019. "Examination and Modification of Multi-Factor Model in Explaining Stock Excess Return with Hybrid Approach in Empirical Study of Chinese Stock Market," JRFM, MDPI, vol. 12(2), pages 1-30, May.
   15. Samitas, Aristeidis & Kampouris, Elias & Kenourgios, Dimitris, 2020. "Machine learning as an early warning system to predict financial crisis," International Review of Financial Analysis, Elsevier, vol. 71(C).
   16. Niu, Zibo & Demirer, Riza & Suleman, Muhammad Tahir & Zhang, Hongwei & Zhu, Xuehong, 2024. "Do industries predict stock market volatility? Evidence from machine learning models," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 90(C).
   17. Liu, Keyan & Zhou, Jianan & Dong, Dayong, 2021. "Improving stock price prediction using the long short-term memory model combined with online social networks," Journal of Behavioral and Experimental Finance, Elsevier, vol. 30(C).
   18. Mahdi Moradi & Mehdi Jabbari Nooghabi & Mohammad Mahdi Rounaghi, 2021. "Investigation of fractal market hypothesis and forecasting time series stock returns for Tehran Stock Exchange and London Stock Exchange," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 662-678, January.
   19. Ehsan Hoseinzade & Saman Haratizadeh & Arash Khoeini, 2019. "U-CNNpred: A Universal CNN-based Predictor for Stock Markets," Papers 1911.12540, arXiv.org.
   20. Rostamian, Hossein & Lotfollahi, Mohammad Nader, 2020. "Statistical modeling of aspirin solubility in organic solvents by Response Surface Methodology and Artificial Neural Networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
   21. Manel Hamdi & Walid Chkili, 2019. "An artificial neural network augmented GARCH model for Islamic stock market volatility: Do asymmetry and long memory matter?," Working Papers 13, Economic Research Forum, revised 21 Aug 2019.

7. Rounaghi, Mohammad Mahdi & Abbaszadeh, Mohammad Reza & Arashi, Mohammad, 2015. "Stock price forecasting for companies listed on Tehran stock exchange using multivariate adaptive regression splines model and semi-parametric splines technique," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 625-633.

   Cited by:

   1. Manickavasagam, Jeevananthan & Visalakshmi, S. & Apergis, Nicholas, 2020. "A novel hybrid approach to forecast crude oil futures using intraday data," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
   2. Bartoš, Erik & Pinčák, Richard, 2017. "Identification of market trends with string and D2-brane maps," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 57-70.
   3. Mohammad Arashi & Mohammad Mahdi Rounaghi, 2022. "Analysis of market efficiency and fractal feature of NASDAQ stock exchange: Time series modeling and forecasting of stock index using ARMA-GARCH model," Future Business Journal, Springer, vol. 8(1), pages 1-12, December.
   4. Rounaghi, Mohammad Mahdi & Nassir Zadeh, Farzaneh, 2016. "Investigation of market efficiency and Financial Stability between S&P 500 and London Stock Exchange: Monthly and yearly Forecasting of Time Series Stock Returns using ARMA model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 10-21.
   5. Mahdi Moradi & Mehdi Jabbari Nooghabi & Mohammad Mahdi Rounaghi, 2021. "Investigation of fractal market hypothesis and forecasting time series stock returns for Tehran Stock Exchange and London Stock Exchange," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 662-678, January.

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