SINVLIO: using semantics and fuzzy logic to provide individual investment portfolio recommendations

Portfolio selection addresses the problem of how to diversify investments in the most efficient and profitable way possible. Portfolio selection is a field of study that has been broached from several perspectives, including, among others, recommender systems. This paper presents SINVLIO (Semantic INVestment portfoLIO), a tool based on semantic technologies and fuzzy logic techniques that recommends investments grounded in both psychological aspects of the investor and traditional financial parameters of the investments. The results are very encouraging and reveal that SINVLIO makes good recommendations, according to the high degree of agreement between SINVLIO and expert recommendationsThis work is supported by the Spanish Ministry of Industry, Tourism, and Commerce under the projects SONAR2 (TSI-020100-2008-665) and the Spanish Ministry of Science and Innovation under the project “FINANCIAL LINKED OPEN DATA REASONING AND MANAGEMENT FOR WEB SCIENCE” (TIN2011-27405).Publicad

Nordic welfare financiers made global portfolio investors : institutional change in pension fund governance in Sweden and Finland

Pension funds have lately emerged as an essential field of study in various disciplines within social sciences. Political economists, economic geographers and some social policy researchers have studied the role of pension funds very broadly for instance in context of labour market relations, economic development and financial systems. Yet comparative studies in social and public policy have for long studied pension funding mostly in respect to its role in pension systems and reforms, and to the effects of investment returns to the development of retirement income benefits. Whereas the comparative studies have mostly focused on the savings and ‘liability side’ (e.g. pension benefits) of pension funds, in this paper, we conduct a comparative analysis on the politics of ‘the asset side’. It is argued that the economic and social consequences of the usage of pension capital need to be understood as intrinsic parts of pension regimes that cannot be left outside classification of these regimes in social sciences. Our comparative analysis studies the historical regulative institutional development paths of pension fund investment governance in Finnish (TEL/TyEL) and Swedish (ATP/AP, PPM) first pillar, second tier pension systems. The time period of the analysis is from the establishment of these systems in late 1950s and early 1960s to the recent reforms of last few years. Both systems have developed so that the role of financier of national economy has decreased and the role of more global portfolio investor increased over time. We argue, however, that there have been very significant differences between the institutional development paths leading to the new investor roles. The Swedish model has included more paradigmatic qualitative changes in the whole pension regime whereas the changes in Finnish pension fund governance have been rather parametric and quantitative. The financial crisis of 2007–08 has also illustrated some essential differences between the current systems

Combining DRSA decision-rules with FCA-based DANP evaluation for financial performance improvements

This study proposes a combined method to integrate soft computing techniques and multiple criteria decision making (MCDM) methods to guide semiconductor companies to improve financial performance (FP) – based on logical reasoning. The complex and imprecise patterns of FP changes are explored by dominance-based rough set approach (DRSA) to find decision rules associated with FP changes. Companies may identify its underperformed criterion (gap) to conduct formal concept analysis (FCA) – by implication rules – to explore the source criteria regarding the underperformed gap. The source criteria are analysed by decision making trial and evaluation laboratory (DEMATEL) technique to explore the cause-effect relationship among the source criteria for guiding improvements; in the next, DEMATEL-based analytical network process (DANP) can provide the influential weights to form an evaluation model, to select or rank improvement plans. To illustrate the proposed method, the financial data of a real semiconductor company is used as an example to show the involved processes: from performance gaps identification to the selection of five assumed improvement plans. Moreover, the obtained implication rules can integrate with DEMATEL analysis to explore directional influences among the critical criteria, which may provide rich insights and managerial implications in practice. First published online: 17 Sep 201

PB-ADVISOR: A private banking multi-investment porfolio.

Private banking is a business area in which the investor requires tailor-made advice. Because of the current market situation, investors are requiring answers to difficult questions and looking for assurance from wealth managers. Private bankers need to have deep knowledge about an innumerable list of products and their characteristics as well as the suitability of each product for the client’s characteristics to be able to offer an optimal portfolio according to client expectations. Client and portfolio diversity calls for new recommendation and advice systems focused on their specific characteristics. This paper presents PB-ADVISOR, a system aimed at recommending investment portfolios based on fuzzy and semantic technologies to private bankers. The proposed system provides private bankers with a powerful tool to support their decision process and help deal with complex investment portfolios. The system has been evaluated in a real scenario obtaining promising results

Exploring the Technology Input and Economy Output in Chinese National Innovation Demonstration Zone Based on Rough Set Theory

The previous study about the relationship between technology input and economy output was mainly concentrated on their linear or functional formulation, while little on the data independencies between them. This study explored the data independencies between technology input and economy output of Chinese National Innovation Demonstration Zone based on Rough Sets Theory, for the purpose of conducting a new way to understand the unstructured relation between technology input and economy output, as well as to promoting the effective combination of technology and economy output of Chinese National Innovation Demonstration Zone, which was the most important part of national innovation system of China. The Rough Set Theory was applied to analyze the 8 Chinese National Innovation Demonstration Zone’s technology input and economy output data from 2007 to 2014. The result demonstrated that: (1) of the economy output indicators, ratio of technical income to total income, ratio of net profit to total income and export were not combined effectively with the technology input, while total income, technical income, net profit and taxes submitted had been combined with the technology input very significantly; (2) of the technology input indicators, all of them had shown the linkage with economy output indicators significantly, and expenditure on R&D activities was the most important one; (3) an two factor theory effect might existed between the technology input and economy output, senior and middle level professional qualifications, personal engaged in R&D activities and expenditure on R&D activities were the hygiene factors, ratio of expenditure on R&D activities to personal engaged in R&D activities and ratio of expenditure on R&D activities to total income were motivation factors. Keywords: Chinese National Innovation Demonstration Zone, Technology input indicators, Economy output indicators, Combination effectiveness, Rough Set Theor

A Conceptual Model of Investor Behavior

Based on a survey of behavioral finance literature, this paper presents a descriptive model of individual investor behavior in which investment decisions are seen as an iterative process of interactions between the investor and the investment environment. This investment process is influenced by a number of interdependent variables and driven by dual mental systems, the interplay of which contributes to boundedly rational behavior where investors use various heuristics and may exhibit behavioral biases. In the modeling tradition of cognitive science and intelligent systems, the investor is seen as a learning, adapting, and evolving entity that perceives the environment, processes information, acts upon it, and updates his or her internal states. This conceptual model can be used to build stylized representations of (classes of) individual investors, and further studied using the paradigm of agent-based artificial financial markets. By allowing us to implement individual investor behavior, to choose various market mechanisms, and to analyze the obtained asset prices, agent-based models can bridge the gap between the micro level of individual investor behavior and the macro level of aggregate market phenomena. It has been recognized, yet not fully explored, that these models could be used as a tool to generate or test various behavioral hypothesis.behavioral finance;financial decision making;agent-based artificial financial markets;cognitive modeling;investor behavior

Interaction of market and credit risk: an analysis of inter-risk correlation and risk aggregation

In this paper we investigate the interaction between a credit portfolio and another risk type, which can be thought of as market risk. Combining Merton-like factor models for credit risk with linear factor models for market risk, we analytically calculate their interrisk correlation and show how inter-risk correlation bounds can be derived. Moreover, we elaborate how our model naturally leads to a Gaussian copula approach for describing dependence between both risk types. In particular, we suggest estimators for the correlation parameter of the Gaussian copula that can be used for general credit portfolios. Finally, we use our findings to calculate aggregated risk capital of a sample portfolio both by numerical and analytical techniques. -- Die Berechnung einer bankweit aggregierten Risikokennzahl (normalerweise ausgedrückt durch das ökonomische Kapital) ist ein äußerst wichtiger Bestandteil eines modernen Risikocontrollings and als solches von besonderer Bedeutung für bankinterne als auch regulatorische Zwecke. Eine wichtige Frage dabei betrifft die Behandlung von risikoreduzierenden Diversifikationseffekten, die als Folge der Geschäftsstrategie einer Bank (z.B. durch Produktdiversifikation oder geografische Diversifikation) auftreten können. Solche Diversifikationseffekte stellen einen Wettbewerbsvorteil dar, den Banken deshalb bei der Bestimmung ihrer Kapitaladäquanz mit einbeziehen wollen. Auch die Bankenaufsicht erkennt in ihren Ausführungen über die bankinternen Kapitalbeurteilungsverfahren nach den Grundsätzen der zweiten Säule von Basel II die Existenz von Diversifikationseffekten an. Bei der praktischen Berechnung des Diversifikationseffektes unterscheidet man oft zwischen Intrarisiko- und Interrisikodiversifikation. Letztere behandelt die Diversifikation innerhalb einer Risikoart (z.B. Markt- oder Kreditrisiko), wohingegen Interrisiko-Diversifikation die Diversifikation zwischen verschiedenen Risikoarten beschreibt und meist durch eine Interrisiko-Korrelationsmatrix erfasst wird.Risk aggregation,Inter-risk correlation,economic capital,ICAAP,diversification

Property management strategies for institutional investors in the '90s

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Architecture, 1996.Includes bibliographical references (leaves 91-92).by John A. Willand.M.S