Books


Monographs


Textbooks

Book Chapters

  • Zapranis, A., & Tsinaslanidis, P. (2012). Charting and weak-form market efficiency test: an empirical study on NASDAQ and NYSE components. In Essays in Honor of Prof. Dimitrios Papadopoulos. Thessaloniki, Greece.
  • Zapranis, A., & Tsinaslanidis, P. (2010). Identification of the head-and-shoulders technical analysis pattern with neural networks. In K. Diamantaras, W. Duch, & L. Iliadis (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6354 LNCS, pp. 130-136).
  • Zapranis, A., & Tsinaslanidis, P. (2010). A comprehensive review of hedge fund investment and trading strategies. In (pp. 289-322). Athens, Greece: University of Piraeus.
  • Zapranis, A., & Alexandridis, A. (2009). Model identification in wavelet neural networks framework. In L. Iliadis, I. Vlahavas, & M. Bramer (Eds.), Artificial Intelligence Applications and Innovations III. 5TH IFIP Advances in Information and Communication Technology (AIAI’2009) (Vol. 296, pp. 267-276). New York, NY, USA: Springer.
  • Zapranis, A., & Samolada, E. (2007). Can neural networks learn the “head and shoulders” technical analysis price pattern? Towards a methodology for testing the efficient market hypothesis. In J. Marques de Sa, L. A. Alexander, W. Duch, & D. P. Mantic (Eds.), Lecture Notes in Computer Science, 17th International Conference on Artificial Neural Networks, ICANN 2007 (Vol. 4669, pp. 516-526). Springer-Verlag.
  • Zapranis, A. (2006). Testing the random walk hypothesis with neural networks. In S. Kollias, A. Stafylopatis, W. Duch, & E. Oja (Eds.), Lecture Notes in Computer Science, 16th International Conference on Artificial Neural Networks, ICANN 2006 (Vol. 4132 LNCS, pp. 664-671). Berlin: Springer.
  • Zapranis, A., & Refenes, A. N. (2001). Neural Networks and Asset Allocation. In Essays in Honor of Late Professor Demetrios Kodosakis. Piraeus: University of Piraeus.
  • Zapranis, A., & Refenes, A. (2000). Neural Model Identification, Variable Selection and Model Adequacy. In D. Chikas (Ed.), Financial Analysis, Essay in Honor of Prof. Elli Thanopoulou. Athens.
  • Zapranis, A. D. (1999). Financial engineering with neural systems. A complete methodological framework. In K. Syriopoulos (Ed.), Financial Risk Management. Athens: Paratiritis.
  • Zapranis, A., Utans, J., & Refenes, A. (1997). Specification tests for neural networks: A case study in tactical asset allocation. In A. S. Weigent, Y. S. Abu-Mustafa, & A.-P. N. Refenes (Eds.), Decision Technologies for Financial Engineering, Progress in Neural Computing (pp. 262-276). Singapore: World Scientific Series Publishing.
  • Refenes, A.-P. N., Zapranis, A. D., & Utans, J. (1997). Neural model identification, variable selection and model adequacy. In A. Weigend, Y. S. Abu-Mustafa, & A.-P. N. Refenes (Eds.), Decision Technologies for Financial Engineering, Progress in Neural Computing (pp. 243-262). Singapore: World Scientific Publishing Co. Pte. Ltd.
  • Refenes, A. N., Zapranis, A. D., Connor, J. T., & Bunn, D. W. (1995). Neural networks in investment management. In P. Treleaven & S. Goonatilake (Eds.), Intelligent Systems for Finance and Business. John Wiley & Sons.
  • Refenes, A. N., Zapranis, A. D., Connor, J. T., & Bunn, D. W. (1995). Modelling stock returns with neural networks. In A. N. Refenes & D. W. Bunn (Eds.), Neural Networks in Quantitative Finance. John Wiley & Sons.
  • Refenes, A., Francis, G., & Zapranis, A. (1995). Modeling Stock Returns in the Framework of APT: A comparative study with Regression Models. In A. N. Refenes (Ed.), Neural Networks in the Capital Markets. John Wiley & Sons.
  • Refenes, A. N., & Zapranis, A. D. (1995). Investment management: Neural and regression models in tactical asset allocation. In M. A. Arbib (Ed.), The Handbook of Brain Theory and Neural Networks (pp. 491-495). Bradford Books/The MIT Press.
  • Refenes, A. N., Zapranis, A., & Bentz, Y. (1994). Modelling stock returns with neural networks. In P. G. Lisboa & M. Taylor (Eds.), Neural Networks Techniques and Applications. London, UK: Ellis Horwood.

Journals

  • Messis, P., Alexandridis, A., & Zapranis, A. (2019). Testing and comparing conditional risk‐return relationship with a new approach in the cross‐sectional framework. International Journal of Finance & Economics.
  • Messis, P., & Zapranis, A. (2016). Forecasting time-varying daily betas: a new nonlinear approach. Managerial Finance, 42 (2), 54-73.
  • Messis, P., & Zapranis, A. (2014). Herding towards higher moment CAPM, contagion of herding and macroeconomic shocks: Evidence from five major developed markets. Journal of Behavioral and Experimental Finance, 4, 1-13.
  • Messis, P., & Zapranis, A. (2014). Herding behavior and volatility in the Athens Stock Exchange. Journal of Risk Finance, 15, 572-590.
  • Messis, P., & Zapranis, A. (2014). Asset pricing with time-varying betas for stocks traded on S &P 500. Applied Economics, 46, 4508-4518.
  • Alexandridis, A., & Zapranis, A. (2013). Wind Derivatives: Modelling and Pricing. Computational Economics, 41, 299-326.
  • Alexandridis, A. K., & Zapranis, A. D. (2013). Wavelet neural networks: a practical guide. Neural Networks, 42, 1-27.
  • Zapranis, A., & Tsinaslanidis, P. E. (2012). Identifying and evaluating horizontal support and resistance levels: An empirical study on US stock markets. Applied Financial Economics, 22 (19), 1571-1585.
  • Zapranis, A., & Tsinaslanidis, P. E. (2012). A novel, rule-based technical pattern identification mechanism: Identifying and evaluating saucers and resistant levels in the US stock market. Expert Systems with Applications, 39, 6301-6308.
  • Zapranis, A., & Alexandridis, A. (2011). Modelling and forecasting cumulative average temperature and heating degree day indices for weather derivative pricing. Neural Computing and Applications, 20 (6), 787-801.
  • Zapranis, A., & Alexandridis, A. (2009). Weather derivatives pricing: Modelling the seasonal residual variance of an Ornstein-Uhlenbeck temperature process with neural networks. Neurocomputing, 73, 37-48.
  • Zapranis, A., & Alexandridis, A. (2009). Modelling and forecasting CAT and HDD indices for weather derivative pricing. Communications in Computer and Information Science, 43 CCIS, 210-222.
  • Zapranis, A., & Alexandridis, A. (2009). Forecasting cash money withdrawals using wavelet analysis and wavelet neural networks. International Journal of Financial Economics and Econometrics.
  • Zapranis, A., & Alexandridis, A. (2008). Modelling the temperature time-dependent speed of mean reversion in the context of weather derivatives pricing. Applied Mathematical Finance, 15, 355-386.
  • Zapranis, A., & Livanis, S. (2008). Forecasting the day-ahead electricity price in Nord Pool with neural networks: Some preliminary results. Value Invest Magazine, 50-68.
  • Zapranis, A. (2006). Inefficient markets and technical analysis: An empirical study. Investment Research and Analysis Journal, 1, 16-28.
  • Zapranis, A., & Livanis, E. (2005). Handling prediction uncertainty of neural network models. WSEAS Transactions on Computers, 4 (7), 718-727.
  • Zapranis, A., & Sivridis, S. (2003). Extending Vasicek with neural regression. Neural Network World, 13, 187-210.
  • Zapranis, A., & Ginoglou, D. (2000). Predicting corporate failure with neural networks: the Greek case. Journal of Financial Management and Analysis, 13.
  • Refenes, A.-P. N., & Zapranis, A. D. (1999). Neural model identification, variable selection and model adequacy. Journal of Forecasting, 18, 299-332.
  • Refenes, A. N., Bentz, Y., Bunn, D. W., Burgess, A. N., & Zapranis, A. D. (1997). Financial time series modelling with discounted least squares backpropagation. Neurocomputing, 14 (2), 123-138.
  • Refenes, A. N., Zapranis, A., & Kollias, C. (1995). External security determinants of Greek military expenditure: An empirical investigation using neural networks. Defense and Peace Economics, 6, 27-41.
  • Refenes, A. N., Zapranis, A., & Francis, G. (1994). Stock performance modelling using neural networks: A comparative study with regression models. Neural Networks, 7 (2), 375-388.

Conferences

  • Messis, P., Alexandridis, A., & Zapranis, A. (2019). The herding effects on systematic risk. Proceedings from 18th Annual Conference of the Hellenic Finance and Accounting Association (HFAA), Athens.
  • Messis, P., Alexandridis, A., & Zapranis, A. (2018). Are arbitrageurs’ actions associated with beta changes? Proceedings from 17th Annual Conference of the Hellenic Finance and Accounting Association (HFAA), Piraeus.
  • Messis, P., Alexandridis, A., & Zapranis, A. (2015). Cross-sectional conditional risk return analysis in the sorted beta framework: A novel Two Factor Model. Proceedings from 14th Hellenic Finance and Accounting Association Conference, Athens, Greece.
  • Messis, P., Alexandridis, A., & Zapranis, A. (2014). Testing and comparing conditional CAPM with a new approach in the cross-sectional framework. Proceedings from International work-conference on Time Series, Granada, Spain.
  • Tsinaslanidis, P., Alexandridis, A., Zapranis, A., & Livanis, E. (2014). Dynamic time warping as a similarity measure: Applications in Finance. Proceedings from Finance and Accounting Association Conference, Volos, Greece.
  • Alexandridis, A., Zapranis, A., Livanis, E., & Tsinaslanidis, P. (2013). Business failure prediction using neural networks and wavelet neural networks. Proceedings from 12th Hellenic Finance and Accounting Association (HFAA), Thessaloniki, Greece.
  • Zapranis, A., & Tsinaslanidis, P. (2012). Testing the generalized efficacy of technical analysis with bootstrapped aggregated regression trees. Proceedings from 4th International Conference in Accounting and Finance, Corfu, Greece.
  • Alexandridis, A., & Zapranis, A. (2012). Modelling and pricing European temperature in the context of weather derivative pricing. Proceedings from 4th International Conference on Accounting and Finance, Corfu, Greece.
  • Messis, P., Zapranis, A., & Kollias, C. (2012). Herding towards Higher Moment CAPM, contagion of herding and macroeconomic shocks: Evidence from five major developed markets. Proceedings from Proc. of 5th International Conference MAF 2012, Mathematical and Statistical Methods for Actuarial Sciences and Finance, Venice, Italy.
  • Messis, P., Zapranis, A., & Kollias, C. (2012). Forecasting beta coefficients applying a different approach for stocks traded on S &P 500. Proceedings from 3rd Conference in Banking and Financial Engineering, Athens, Greece.
  • Messis, P., Zapranis, A., & Kollias, C. (2012). Asset pricing with nonlinear betas: Evidence from S &P 500. Proceedings from 4th International Conference in Accounting & Finance.
  • Zapranis, A., & Alexandridis, A. (2011). Wind derivatives: Modelling and pricing. Proceedings from 1st International Conference of the Financial Engineering and Banking Society (F.E.B.S), Chania, Greece.
  • Zapranis, A., & Tsinaslanidis, P. (2010). A behavioral view of the Head-and-Shoulders technical analysis pattern. Proceedings from 3rd International Conference in Accounting and Finance (ICAF), Skiathos, Greece.
  • Zapranis, A., & Tsinaslanidis, P. (2009). An examination of the head and shoulders technical pattern a support of the technical analysis’s subjective nature. Proceedings from 45th Meeting of the EURO Working Group on Financial Modelling., Chania, Greece.
  • Soubeniotis, D., Tambakoudis, I., & Zapranis, A. (2008). The wealth effects of completed and uncompleted mergers and tender offers to target shareholders in USA, United Kingdom and Europe. Proceedings from 2nd International Conference on Accounting and Finance, Thessaloniki, Greece.
  • Zapranis, A., & Tsinaslanidis, P. (2008). Head and shoulders pattern recognition in stochastic processes. Proceedings from 2nd International Conference on Accounting and Finance, Thessaloniki, Greece.
  • Zapranis, A., & Alexandridis, A. (2008). Forecasting cash money withdrawals using wavelet analysis and wavelet neural networks. Proceedings from 5th International Conference on Advances in Applied Financial Economics (AFE), Samos, Greece.
  • Zapranis, A., & Alexandridis, A. (2007). Weather derivatives pricing: Modeling the seasonal residual variance of an Ornstein-Uhlenbeck temperature process with neural networks. Proceedings from 10th International Conference on Engineering Applications of Neural Networks (EANN), Thessaloniki, Greece.
  • Zapranis, A., & Alexandridis, A. (2007). Wavelet neural networks for weather derivatives pricing. Proceedings from 6th Hellenic Finance and Accounting Association Conference (HFAA), Patra, Greece.
  • Zapranis, A., & Alexandridis, A. (2007). Modelling temperature time-dependent mean reversion with neural networks in the context of derivatives pricing. Proceedings from 8th Hellenic European Research on Computer Mathematics and its Applications Conference (HERCMA) 2007. Computational Advances in Finance and Management, Athens, Greece.
  • Zapranis, A., & Livanis, E. (2007). Forecasting the day-ahead electricity price in nord pool with neural networks: Some preliminary results. Proceedings from 6th Hellenic Finance and Accounting Association Conference (HFAA), Patra, Greece.
  • Zapranis, A. (2007). Assessing quality in higher education of regional public universities: Lessons from the past, steps to the future. 2nd Athens International Conference on University Assessment.
  • Zapranis, A., & Alexandridis, A. (2006). Wavelet analysis and weather derivatives pricing. Proceedings from Hellenic Finance and Accounting Association (HFFA) Conference, Thessaloniki, Greece.
  • Zapranis, A. (2006). Testing the independent increments random walk hypothesis: Learning technical trading rules with neural networks. 26th International Symposium on Forecasting.
  • Zapranis, A. (2003). Sampling variability schemes for neural models. Proceedings from the 7th Hellenic European Research on Computer Mathematics and Its Applications Conference (HERCMA) 2003., Athens, Greece.
  • Zapranis, A. (2002). Estimating adaptive to heterogeneous noise confidence intervals for neural networks. Proceedings from 50th Anniversary Financial Conference, Finance and Credit Department, D. Tsenov Academy of Economics, Svistov, Bulgaria.
  • Zapranis, A., & Haramis, G. (2001). Obtaining locally identified models: The irrelevant Connection Elimination Scheme. Proceedings from 5th Hellenic European Research on Computer Mathematics and its Applications (HERCMA), Athens, Greece.
  • Zapranis, A., & Ginoglou, D. (2000). Predicting corporate failure: The Greek case. Proceedings from Emerging Issues in International Accounting, Niagara Falls, Ontario, USA.
  • Zapranis, A., & Ginoglou, D. (2000). Modelling the systematic component of ARIMA residuals with neural models: An application to the Athens Stock Exchange General Index. Proceedings from 3rd Annual Conference on European Dimensions in Economics and Management for the Countries in Transition, Sofia, Bulgaria.
  • Zapranis, A., & Ginoglou, D. (2000). Hedging short positions on index call options: An application to the Greek FTSE-ASE 20 Index Options. Proceedings from International Scientific Conference on Internationalization and Globalization of Business, Svistov, Bulgaria.
  • Lyroudi, K., & Zapranis, A. (2000). A comparison of traditional and contemporary liquidity measures using neural networks. Proceedings from 31st Annual Meeting of the Decision Sciences Institute (DSI), Orlando, Florida, USA.
  • Zapranis, A. D. (1999). Predicting S &P 500 daily returns using technical indicators. The neural networks perspective - A structured approach. Proceedings from Advanced Investment Technologies ’99, Queensland, Australia.
  • Zapranis, A., Utans, J., & Refenes, A. (1996). Specification Tests for Neural Networks: A Case Study in Tactical Asset Allocation. Proceedings from Neural Networks in the Capital Markets (NnCM) ‘96, Pasadena, CA, USA.
  • Zapranis, A. D., & Refenes, A. N. (1994). Neural networks in tactical asset allocation: Towards a methodology for hypothesis testing and confidence intervals. Proceedings from Neural Networks in the Capital Markets (NnCM) ‘94, Caltech, Pasadena, CA, USA.
  • Refenes, A., Bentz, Y., Bunn, D. W., Burgess, A. N., & Zapranis, A. (1994). Back propagation with discounted least squares and its application to financial time series modelling. Proceedings from Neural Networks in the Capital Markets (NnCM) ‘94, Caltech, Pasadena, CA, USA.
  • Refenes, A., Bentz, Y., Bunn, D. W., Burgess, A. N., & Zapranis, A. (1994). Back propagation with differential least squares and its application to time series modelling. Proceedings from Snowbird ‘94, USA.
  • Refenes, A. N., Azema-Barac, M., & Zapranis, A. D. (1993). Stock ranking: Neural networks vs multiple linear regression. Proceedings from IEEE International Conference on Neural Networks - Conference Proceedings, San Francisco, CA, USA.
  • Bentz, Y., Zapranis, A., & Refenes, A. N. (1993). Predicting and analyzing the performance of the French stock market. Proceedings from Workshop on Neural Network Applications and Tools, Liverpool, England.
  • Refenes, A. N., Zapranis, A. D., & Bentz, Y. (1993). Modelling stock returns with neural networks. Proceedings from Neural Networks in the Capital Markets (NnCM) ‘93, London Business School, London, UK.
  • Refenes, A. N., Kollias, C., & Zapranis, A. (1993). Arms race modelling using neural networks: A case study. Proceedings from 2nd Turkish Artificial Intelligence and Neural Networks Symposium, Bogazici University, Istanbul, Turkey.

Lecture Notes

  • Zapranis, A. (2003). Portfolio management and information systems (in Greek). Lecture Notes.
  • Zapranis, A. (2002). Financial derivatives (in Greek). Lecture Notes.
  • Zapranis, A. (2002). Forecasting and risk management techniques (in Greek). Lecture Notes.
  • Zapranis, A. (1999). Computer applications in Finance (in Greek). Lecture Notes.

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