Distributed Decision Blockchain-Secured Support System to Enhance Stock Market Investment Process

Author(s):  
Elena Hernández-Nieves ◽  
José A. García-Coria ◽  
Sara Rodríguez-González ◽  
Ana B. Gil-González
2021 ◽  
Vol 26 (1) ◽  
pp. 87-93
Author(s):  
Sandeep Patalay ◽  
Madhusudhan Rao Bandlamudi

Investing in stock market requires in-depth knowledge of finance and stock market dynamics. Stock Portfolio Selection and management involve complex financial analysis and decision making policies. An Individual investor seeking to invest in stock portfolio is need of a support system which can guide him to create a portfolio of stocks based on sound financial analysis. In this paper the authors designed a Financial Decision Support System (DSS) for creating and managing a portfolio of stock which is based on Artificial Intelligence (AI) and Machine learning (ML) and combining the traditional approach of mathematical models. We believe this a unique approach to perform stock portfolio, the results of this study are quite encouraging as the stock portfolios created by the DSS are based on strong financial health indices which in turn are giving Return on Investment (ROI) in the range of more than 11% in the short term and more than 61% in the long term, therefore beating the market index by a factor of 15%. This system has the potential to help millions of Individual Investors who can make their financial decisions on stocks and may eventually contribute to a more efficient financial system.


2021 ◽  
pp. 127-161
Author(s):  
Kieran Heinemann

The question of whether ordinary people should own stocks and shares has a long political trajectory in Britain. When the idea of creating a property-owning democracy of small shareholders took shape in the interwar period, there was still a consensus among Britain’s political elites that ordinary people should stay away from the stock market. By the end of the century, however, politicians welcomed the fact that there were more private shareholders in Britain than trade union members. In the post-war decades, wider share ownership had some supporters in all major parties, but no government took legislative action because schemes were difficult to reconcile with the mixed economy. Eventually, the economic hardship of the 1970s brought a noticeable shift in attitudes towards mass participation in the stock market. Conservative politicians, journalists, and businessmen of the increasingly influential New Right advocated a return to economic individualism that was motivated by a perceived decline of allegedly middle-class, bourgeois, or ‘Victorian’ values. This ‘declinism’ shaped Thatcherite plans in opposition for a new tax code that would encourage direct involvement with capitalist enterprise. Throughout the decades, however, policymakers and advocates of wider share ownership realized that stock market investment not only lent itself to an exercise in bourgeois values of thrift and deferred gratification, but could also foster speculation and gambling. The line between prudent saving, beneficial investment, and speculative risk-taking always proved difficult to draw and crossing it demanded careful communication.


2019 ◽  
Vol 59 (S2) ◽  
pp. 2017-2044 ◽  
Author(s):  
Jingjing Yang ◽  
Yuan Xin ◽  
Xiao Jun

Author(s):  
Tina Comes ◽  
Niek Wijngaards ◽  
Michael Hiete ◽  
Claudine Conrado ◽  
Frank Schultmann

Decision-making in emergency management is a challenging task as the consequences of decisions are considerable, the threatened systems are complex and information is often uncertain. This paper presents a distributed system facilitating better-informed decision-making in strategic emergency management. The construction of scenarios provides a rationale for collecting, organising, and processing information. The set of scenarios captures the uncertainty of the situation and its developments. The relevance of scenarios is ensured by gearing the scenario construction to assessing alternatives, thus avoiding time-consuming processing of irrelevant information. The scenarios are constructed in a distributed setting allowing for a flexible adaptation of reasoning (principles and processes) to both the problem at hand and the information available. This approach ensures that each decision can be founded on a coherent set of scenarios. The theoretical framework is demonstrated in a distributed decision support system by orchestrating experts into workflows tailored to each specific decision.


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