.svg){kind=logo}
AN EFFECTIVE RULE-COMPLIANCE SIMULATION MODEL IN TRADING FOR EFFICIENT PORTFOLIO MANAGEMENT
Keywords:
investment technologies, pre-trade compliance, portfolio investment.DOI:
https://doi.org/10.17654/0972361724014Abstract
Effective investment portfolio management demands intricate strategies adhering to rigorous compliance and regulation rules. This paper delves into the realm of investment compliance practices, examining the transformative impact of technology. Crucially, it underscores the vital role played by a rule-based simulation model in addressing critical challenges faced by sophisticated investors and portfolio managers. The study explored the complexities of monitoring equity portfolios managed by multiple portfolio managers, ensuring adherence to shared compliance rules. The crux of this research is the introduction of the “KSU-PRE-Model,” a pioneering resource-sharing technology that empowers sophisticated investors integrated within a managed database accessible to portfolio managers, streamlining the compliance process. The model empowers sophisticated investors to tailor compliance rules within the system. Portfolio managers are equipped to validate their trade intentions against these rules, eliminating the need for post-trade cleansing phases. We validate the effectiveness and efficiency through a blend of qualitative and quantitative methods. Thematic analysis, grounded in qualitative methodologies, has facilitated a deep understanding of the “KSU-PRE-Model’s” effectiveness and efficiency compared with the existing models. This research contributes to the information system field by providing an innovative and effective rule-compliance model that harnesses the potential of investment technology, addressing critical challenges and paving the way for advanced AI-driven compliance solutions.
Received: November 13, 2023
Accepted: December 28, 2023
References
D. Pertiwi, S. Ronni Basana and M. Grace Yasinta, Decisions for stock investment among university students, SHS Web Conf., Vol. 76, 2020, p. 01005. doi: 10.1051/shsconf/20207601005.
S. Paluch et al., Stage-gate and agile development in the digital age: promises, perils, and boundary conditions, J. Bus. Res. 110 (2020), 495-501.
doi: 10.1016/j.jbusres.2019.01.063.
M. Cowling, R. Brown and A. Rocha, Did you save some cash for a rainy COVID-19 day? The crisis and SMEs, Int. Small Bus. J. Res. Entrep. 38(7) (2020), 593-604. doi: 10.1177/0266242620945102.
F. Wu, Land financialisation and the financing of urban development in China, Land Use Policy 112 (2022), 104412. doi: 10.1016/j.landusepol.2019.104412.
M. Rahman and S. S. Gan, Generation Y investment decision: an analysis using behavioural factors, Manag. Financ. 46(8) (2020), 1023-1041.
doi: 10.1108/MF-10-2018-0534.
M. Pompian, Behavioral Finance and Wealth Management: How to Build Optimal Portfolios that Account for Investor Biases, Wiley, 2012.
Puspa Pathak, A comparative analysis of capital structure of commercial banks (with Reference to Himalayan Bank and Bank of Kathmandu Limited) By Central Department of Management Registration No: 7-2-0463-0061-2012 in Partial Fulfillment of the Requirements for the D, 2019.
https://elibrary.tucl.edu.np/bitstream/123456789/1116/2/PuspaPathak.pdf.
Paul Langley, Finance/security/life, Finance and Society 3(2) (2017), 173-79. https://doi.org/10.2218/finsoc.v3i2.2576.
Laith Yousef Bani Hani, A study of financial planning and investment of individual, Int. J. Sci. Res. 9(11) (2020), 1268-1272.
https://www.ijsr.net/archive/v9i11/SR201123123117.pdf.
Raghavendra Rao Rentala, A research study on financial planning and investment behavior of individual investors of Tirupathi town, Andhra Pradesh, International Journal of Creative Research Thoughts 6(1) (2018), 1266-1273.
https://ijcrt.org/papers/IJCRT1802605.pdf.
Deloitte, Investment Compliance Monitoring, 2023.
https://www2.deloitte.com/us/en/pages/advisory/articles/investment-compliance-monitoring.html.
E. Holsapple, T. Ozawa and J. Olienyk, Foreign ‘Direct’ and ‘Portfolio’ investment in real estate: an eclectic paradigm, Journal of Real Estate Portfolio Management 12(1) (2006), 37-47.
H. Markowitz, Portfolio selection, J. Finance 7(1) (1952), 77-91.
F. Black and R. Litterman, Global portfolio optimization, Financial Analysts Journal 48(5) (1992), 28-43.
A. Ling, J. Sun and M. Wang, Robust multi-period portfolio selection based on downside risk with asymmetrically distributed uncertainty set, European Journal of Operational Research 285(1) (2020), 81-95.
B. I. Lev and A. Srivastava, Explaining the demise of value investing, SSRN Electron. J. (2019), doi: 10.2139/ssrn.3442539.
S. Gu, B. T. Kelly and D. Xiu, Empirical asset pricing via machine learning, SSRN Electronic Journal (2018), 2223-2273.
P. Krueger, Z. Sautner and L. T. Starks, The importance of climate risks for institutional investors, A. Karolyi, ed., The Review of Financial Studies 33(3) (2020), 1067-1111.
D. Kahneman and A. Tversky, Prospect theory: an analysis of decision under risk, Econometrica 47(2) (1979), 263.
D. Aschwanden, J. E. Strickhouser, A. A. Sesker, J. H. Lee, M. Luchetti, Y. Stephan, A. R. Sutin and A. Terracciano, Psychological and behavioral responses to coronavirus disease 2019: the role of personality, European Journal of Personality 35(1) (2021), 51-66.
R. O. Michaud, D. N. Esch and R. O. Michaud, In defense of portfolio optimization: what if we can forecast?: a comment, Financial Analysts Journal 76(2) (2020), 104-105.
D. Busch, MiFID II and MiFIR: stricter rules for the EU financial markets, Law and Financial Markets Review 11(2-3) (2017), 126-142.
S. R. Park and J. Y. Jang, The impact of ESG management on investment decision: institutional investors’ perceptions of country-specific ESG criteria, International Journal of Financial Studies 9(3) (2021), 48.
A. Palm, Innovation systems for technology diffusion: an analytical framework and two case studies, Technological Forecasting and Social Change 182 (2022), 121821.
A. Freij, Regulatory change impact on technology and associated mitigation capabilities, Technology Analysis and Strategic Management 34(12) (2022), 1418-1431.
S. S. D. Gnana, S. Kumar, A. Benazir and B. Lalita, Making ESG work: examining the changing ESG regulations in India, Research Trends in Commerce and Management 2(4) (2022), 208-217.
D.-F. Wang, Q.-L. Dong, Z.-M. Peng, S. Khan and A. Tarasov, The green logistics impact on international trade: evidence from developed and developing countries, Sustainability 10(7) (2018), 2235.
Deloitte, Investment Compliance Monitoring, 2023.
https://www2.deloitte.com/us/en/pages/advisory/articles/investment-compliance-monitoring.html.
U. Kumar, D. Galar, A. Parida, C. Stenstrom and L. Berges, Maintenance performance metrics: a state-of-the-art review, J. Qual. Maint. Eng. 19(3) (2013), 233-277. doi: 10.1108/JQME-05-2013-0029.
Dirk-Jan Fokkens, A practical approach to maintenance performance measurement, 2015.
[Online]. Available: https://essay.utwente.nl/66694/1/Fokkens_MA_MB.pdf.
T. C. W. Lin, Compliance, technology, and modern finance, Brooklyn J. Corp. Financ. Commer. Law 11(1) (2016), 160-182.
[Online]. Available: https://brooklynworks.brooklaw.edu/cgi/viewcontent.cgi? referer=&httpsredir=1&article=1225&context=bjcfcl.
Doug Dannemiller, J. Lynette DeWitt and Ankur Gajjaria, Building regulatory-ready organizations, 2017.
[Online]. Available: https://www2.deloitte.com/us/en/insights/industry/financial-services/regulatory-and-compliance-risk-investment-management-firms.html.
D. Hoffmann, F. Ahlemann and S. Reining, Reconciling alignment, efficiency, and agility in IT project portfolio management: recommendations based on a revelatory case study, Int. J. Proj. Manag. 38(2) (2020), 124-136.
doi: 10.1016/j.ijproman.2020.01.004.
A. Papazafeiropoulou and K. Spanaki, Understanding governance, risk and compliance information systems (GRC IS): the experts view, Inf. Syst. Front. 18(6) (2016), 1251-1263. doi: 10.1007/s10796-015-9572-3.
M. B. Imerman and F. J. Fabozzi, Cashing in on innovation: a taxonomy of FinTech, J. Asset Manag. 21(3) (2020), 167-177.
doi: 10.1057/s41260-020-00163-4.
Emanuel Derman, Models.Behaving.Badly.: Why Confusing Illusion with Reality can Lead to Disaster, on Wall Street and in Life, John Wiley & Sons, 2012, p. 24. [Online]. Available: https://www.amazon.in/Models-Behaving-Badly-Confusing-Illusion-Reality-Disaster/dp/1439164991.
Arto Tolonen, Hanna Kropsu-Vehkapera and Harri Haapasalo, Product portfolio management - current challenges and preconditions, Int. J. Perform. Meas. 4(2) (2014), 69-90. [Online]. Available:
https://www.researchgate.net/profile/Arto-Tolonen/publication/277837634_ Product_Portfolio_Management_-_Current_challenges_and_preconditions/links/ 5575474e08aeb6d8c0194dcf/Product-Portfolio-Management-Current-challenges-and-preconditions.pdf.
M. B. Haugh and A. W. Lo, Computational challenges in portfolio management, Comput. Sci. Eng. 3(3) (2001), 54-59. doi: 10.1109/5992.919267.
L. Ilie, Challenges for financial managers in a changing economic environment, Procedia Econ. Financ. 27 (2015), 726-730.
doi: 10.1016/S2212-5671(15)01054-0.
M. A. M. Al Janabi, Risk management in trading and investment portfolios, J. Emerg. Mark. Financ. 11(2) (2012), 189-229. doi: 10.1177/0972652712454516.
R. Gao and X. Yu, How to measure capital investment efficiency: a literature synthesis, Account. Financ. 60(1) (2020), 299-334. doi: 10.1111/acfi.12343.
J. M. Garcia Lara, B. Garcia Osma and F. Penalva, Accounting conservatism and firm investment efficiency, J. Account. Econ. 61(1) (2016), 221-238.
doi: 10.1016/j.jacceco.2015.07.003.
G. C. Biddle, G. Hilary and R. S. Verdi, How does financial reporting quality relate to investment efficiency? J. Account. Econ. 48(2-3) (2009), 112-131.
doi: 10.1016/j.jacceco.2009.09.001.
D. H. B. Phan, C. M. Tee and V. T. Tran, Do different types of political connections affect corporate investments? Evidence from Malaysia, Emerg. Mark. Rev. 42 (2020), 100667. doi: 10.1016/j.ememar.2019.100667.
Philip Sinnadurai, Ravichandran Subramaniam and Susela Devi, The influence of government shareholding on dividend policy in Malaysia, Int. J. fuzzy Syst. 9(3) (2021), 1-28. [Online]. Available:
https://ideas.repec.org/a/gam/jijfss/v9y2021i3p49-d632588.html
https://cpb-us-w2.wpmucdn.com/sites.udel.edu/dist/a/855/files/2020/08/ Rebalancing-Strategies.pdf.
J. R. Ritter and I. Welch, A review of IPO activity, pricing, and allocations, J. Finance 57(4) (2002), 1795-1828. doi: 10.1111/1540-6261.00478.
J. J. Korczak, P. Lipinski and P. Roger, Evolution Strategy in Portfolio Optimization, Springer Berlin Heidelberg, 2002, pp. 156-167.
doi: 10.1007/3-540-46033-0_13.
F. Allen and R. Karjalainen, Using genetic algorithms to find technical trading rules, J. Financ. Econ. 51(2) (1999), 245-271.
doi: 10.1016/S0304-405X(98)00052-X.
K.-S. Shin and Y.-J. Lee, A genetic algorithm application in bankruptcy prediction modeling, Expert Syst. Appl. 23(3) (2002), 321-328.
doi: 10.1016/S0957-4174(02)00051-9.
B. A. Jain and B. N. Nag, Artificial neural network models for pricing initial public offerings, Decis. Sci. 26(3) (1995), 283-302.
doi: 10.1111/j.1540-5915.1995.tb01430.x.
Downloads
Published
Issue
Section
License
Copyright (c) 2024 Pushpa Publishing House, Prayagraj, India
This work is licensed under a Creative Commons Attribution 4.0 International License.
____________________________
Attribution: Credit Pushpa Publishing House as the original publisher, including title and author(s) if applicable.
No Derivatives: Modifying or creating derivative works not allowed without written permission.
Contact Pushpa Publishing House for more info or permissions.
Journal Impact Factor: 
