OCI-CBR: A hybrid model for decision support in preference-aware investment scenarios
- Pérez-Pons, María Eugenia 1
- Parra-Dominguez, Javier 1
- Hernández, Guillermo 1
- Bichindaritz, Isabelle 2
- Corchado, Juan M.
-
1
Universidad de Salamanca
info
-
2
State University of New York at Oswego
info
ISSN: 0957-4174
Año de publicación: 2023
Volumen: 211
Páginas: 118568
Tipo: Artículo
Otras publicaciones en: Expert Systems with Applications
Resumen
This article proposes an adaptable hybrid model for recommending effective investments in different scenarios. Currently, a wide variety of methodologies are used for company valuation, especially those that take into account financial statements. However, for private held companies, there is no method that would be capable of predicting, with full certainty, the future success of an investment. The Optimal Capital Investment Case-Base Reasoning (OCI-CBR) consists of a case-based reasoning system that uses a classification algorithm to prune the case base according to a projected increase in certain company attributes. Once the cases have been pruned and the case is fed with the most profitable investment opportunities, the case-based reasoning system recommends optimal investments to potential investors. The complete model is conceived as an intelligent hybrid model that optimizes the case base by employing different algorithms for data retrieval and reuse. The system makes recommendations based on the investor’s preferences and the investment decisions of other investors with similar profiles or interests.
Referencias bibliográficas
- Aamodt, (1994), AI Communications, 7, pp. 39, 10.3233/AIC-1994-7104
- Arroyo, (2019), IEEE Access, 7, pp. 124233, 10.1109/ACCESS.2019.2938659
- Benjamin, (1999)
- Bessière, (2020), Venture Capital, 22, pp. 135, 10.1080/13691066.2019.1599188
- Block, (2019), Journal of Corporate Finance, 10.1016/j.jcorpfin.2019.05.009
- Böhm, (2017)
- Bontempi, (2016), Economics of Innovation and New Technology, 25, pp. 240, 10.1080/10438599.2015.1076197
- Bridge, (2005), The Knowledge Engineering Review, 20, pp. 315, 10.1017/S0269888906000567
- Cochrane, (2005), Journal of Financial Economics, 75, pp. 3, 10.1016/j.jfineco.2004.03.006
- Corchado, J. M. (1997). Adaptive hybrid system architecture for forecasting. In Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on innovative applications of artificial intelligence (pp. 808–808).
- Corchado, (2004), pp. 1
- Cronqvist, (2015), Journal of Financial Economics, 117, pp. 333, 10.1016/j.jfineco.2015.04.006
- Fernández, (2007), IESE Business School, 449
- Fiet, (1995), Journal of Business Venturing, 10, pp. 195, 10.1016/0883-9026(94)00039-W
- Fried, (1994), Financial Management, pp. 28, 10.2307/3665619
- Gompers, (2020), Journal of Financial Economics, 135, pp. 169, 10.1016/j.jfineco.2019.06.011
- Granz, (2020), pp. 105
- Guenther, (2018), Small Business Economics, 50, pp. 289, 10.1007/s11187-016-9834-6
- Haines, (2003), Journal of Small Business & Entrepreneurship, 16, pp. 13, 10.1080/08276331.2003.10593306
- Hill, (1980), Journal of Financial and Quantitative Analysis, 15, pp. 595, 10.2307/2330401
- Iruarrizaga, (2013), Investigaciones Regionales-Journal of Regional Research, pp. 179
- Jeng, (2000), Journal of Corporate Finance, 6, pp. 241, 10.1016/S0929-1199(00)00003-1
- Kaplan, (2005), The Journal of Finance, 60, pp. 1791, 10.1111/j.1540-6261.2005.00780.x
- Kerr, (2014), Review of Financial Studies, 27, pp. 20, 10.1093/rfs/hhr098
- Landström, (2016)
- Li, (2011), Journal of Business Venturing, 26, pp. 239, 10.1016/j.jbusvent.2009.08.001
- Lieber, (2004), The Journal of Private Equity, 7, pp. 72, 10.3905/jpe.2004.391051
- Madill, (2005), Venture Capital, 7, pp. 107, 10.1080/1369106042000316341
- Mason, (2002), Entrepreneurship & Regional Development, 14, pp. 271, 10.1080/08985620210142011
- Mason, (2004), International Small Business Journal, 22, pp. 227, 10.1177/0266242604042377
- McKenzie, (2017)
- Pal, (2000), Decision Support Systems, 27, pp. 411, 10.1016/S0167-9236(99)00083-4
- Panousi, (2012), The Journal of Finance, 67, pp. 1113, 10.1111/j.1540-6261.2012.01743.x
- Paul, (2007), Venture Capital, 9, pp. 107, 10.1080/13691060601185425
- Petersen, M. A., & Schoeman, I. (2008). Modeling of banking profit via return-on-assets and return-on-equity. In Proceedings of the world congress on engineering (vol. 2) (pp. 1–6).
- Peterson, (2018), The British Accounting Review, 50, pp. 539, 10.1016/j.bar.2018.03.001
- Prentzas, (2007), Expert Systems, 24, pp. 97, 10.1111/j.1468-0394.2007.00423.x
- Ragothaman, (2003), Information Systems Frontiers, 5, pp. 401, 10.1023/B:ISFI.0000005653.53641.b3
- Ramadani, (2009), Strategic Change: Briefings in Entrepreneurial Finance, 18, pp. 249, 10.1002/jsc.852
- Haro-de Rosario, (2014), Small Business Economics, 43, pp. 229, 10.1007/s11187-014-9541-0
- San José, (2005), Venture Capital, 7, pp. 149, 10.1080/13691060500063392
- Serrano-Cinca, (2013), Decision Support Systems, 54, pp. 1245, 10.1016/j.dss.2012.11.015
- Sirower, (1998), Journal of Applied Corporate Finance, 11, pp. 107, 10.1111/j.1745-6622.1998.tb00652.x
- Stedler, (2003), Venture Capital: An International Journal of Entrepreneurial Finance, 5, pp. 269, 10.1080/1369106032000126596
- Tyebjee, (1984), Management Science, 30, pp. 1051, 10.1287/mnsc.30.9.1051
- Van Dijk, (2010)
- Van Osnabrugge, (2000)
- Van Setten, (2004), pp. 13
- Visa, (2011), MAICS, 710, pp. 120
- Wei, (2008), pp. 187
- White, (2017), Venture Capital, 19, pp. 183, 10.1080/13691066.2017.1290889
- Wilson, (2011)
- Wong, (2002)