Elli Pagourtzi

Real estate appraisal: a review of valuation methods

The valuation of real estate is a central tenet for all businesses. Land and property are factors of production and, as with any other asset, the value of the land flows from the use to which it is put, and that in turn is dependent upon the demand (and supply) for the product that is produced. Valuation, in its simplest form, is the determination of the amount for which the property will transact on a particular date. However, there is a wide range of purposes for which valuations are required. These range from valuations for purchase and sale, transfer, tax assessment, expropriation, inheritance or estate settlement, investment and financing. The objective of the paper is to provide a brief overview of the methods used in real estate valuation. Valuation methods can be grouped as traditional and advanced. The traditional methods are regression models, comparable, cost, income, profit and contractor’s method. The advanced methods are ANNs, hedonic pricing method, spatial analysis methods, fuzzy logic and ARIMA models.

Real estate valuation with artificial intelligence approaches

Real Estate valuation in urban areas is a very difficult task that has absorbed the interest of many academics in the past years. Many qualitative and quantitative variables affect the value of an estate in urban areas. As a result, multivariate models are more suitable in the appraisal process. One of the most common approaches is multiple linear regression technique (MLR) that is always used as a benchmark in various studies. A very promising way of dealing with uncertainty in real estate analysis and producing sufficient evaluations is the use of Artificial Neural Networks (ANNs). Also, an expert method combining the strengths of MLR and ANN is tried out successfully. The purpose of this study is to compare these approaches on the basis of the data from the Attica urban area in Greece.

Architecture for a real estate analysis information system using GIS techniques integrated with fuzzy theory

Real Estate analysis in urban area is an important and very difficult task. The value of a property is primarily determined by its location. Thus a geographical information system (GIS) is of great importance in the evaluation process. In the last decade a very promising approach of dealing uncertainty in real estate analysis is Fuzzy theory due to the need of handling the large number of qualitative and quantitative variables that affect the value of an estate. This paper discusses the architecture for a decision support system for Real Estate analysis based on GIS techniques integrated with Fuzzy theory. In order to evaluate the system data were used from the urban area of P. Faliro in Attica basin of Greece.

A study of financial volatility forecasting techniques in the FTSE/ASE 20 index

Forecasting financial market volatility is an important task that has absorbed the interest of many academics in the late twentieth and early twenty-first centuries. This strong interest of the academic world reflects the importance of volatility in several financial and business activities. Volatility forecast, crucially affects investment choice and is the most important parameter affecting prices of market listed options, of which trading volume has proliferated in the last years. The purpose of this article is to compare various volatility forecasting approaches using data on the Greek FTSE/ASE 20 stock index.

Remote access to group expertise: an essential e-operation for SMEs

Remote access for Small and Medium Enterprises (SMEs) to group expertise is a key service for efficient decision support. E-tools that could provide such services would enhance the decision-making process and at the same time provide a value-for-money solution; also they are very easy to assemble. E-tools reserve very limited time of their daily workload, thus facilitating participation in such decision support tasks; not to mention that virtual attendance reduces the impact of group bias. This study presents a web-based application of a semi-Delphi approach, using modern three-tier architecture, providing real-time group decision making features.

The advanced forecasting information system PYTHIA: An application in real estate time series

Purpose – The main scope of the paper is to demonstrate the capabilities of PYTHIA forecasting platform, to compare time series forecasting techniques, which were used to forecast mortgage loans in UK, and to show how PYTHIA can be useful for a bank.Design/methodology/approach – The paper outlines the methods used to forecast the time series data, which are included in PYTHIA. Theta, the time‐series used to forecast average mortgage loan prices, were grouped in: all buyers – average loan prices in UK; first‐time buyers – average loan prices in UK; and home‐movers – average loan prices in UK. The case of all buyers – average loan prices in UK, was presented in detail.Findings – After the comparison of the methods, the best forecasts are produced by WINTERS and this is maybe due to the fact that there is seasonality in the data. The Theta method comes next in the row and generally produces good forecasts with small mean absolute percentage errors. In order to tell with grater certainty which method produces...

Project management and financial monitoring in public sector: an information support system

This research introduces a specialised information support system that was designed and implemented for project management and financial monitoring in public sector of funded projects, under the Greek National Strategic Reference Framework (NSRF). Its goal was to ensure effective data monitoring and controlling for the Ministry of National Defense. The proposed system incorporates electronic finance features in terms of financial monitoring and reporting, resulting in optimised effectiveness and efficiency, through strict management along the project life cycle, and improved financial performance. The system adopts private sectors management styles and techniques, contributing thus in the process of public sector reengineering.

INSTALLING AN ERP SYSTEM WITH A METHODOLOGY BASED ON THE PRINCIPLES OF GOAL DIRECTED PROJECT MANAGEMENT

This paper describes a generic methodology to support the process of modelling, adaptation and implementation (MAI) of Enterprise Resource Planning Systems (ERPS) based on the principles of goal directed project management (GDPM). The proposed methodology guides the project manager through specific stages in order to successfully complete the ERPS implementation. The development of the proper MAI methodology is deemed necessary because it will simplify the installation process of ERPS. The goal directed project management method was chosen since it provides a way of focusing all changes towards a predetermined goal. The main stages of the methodology are the promotion and preparation steps, the proposal, the contract, the implementation and the completion. The methodology was applied as a pilot application by a major ERPS development company. Important benefits were the easy and effective guidance for all installation and analysis stages, the faster installation for the ERPS and the control and cost reduction for the installation, in terms of time, manpower, technological equipment and other resources.

Security policy model for an MIS designed for the defence sector

The design of a management information system (MIS) for the purposes of a defence industry could be rather difficult and complex as the managed data are of prime importance for the strategic planning of the country. Therefore, a large amount of parameters should be considered in order to build a solid and proof system with a specific security policy and standards. This paper studies the design and the security policy for a MIS referring to an industry specialised in the repair of telecommunication parts for the Ministry of Defence.