Abstract: Software applications have become crucial to the aerospace industry, providing a wide range of functionalities and capabilities used during the design, manufacturing and support of aircraft. However, as this criticality increases, so too does the risk for business operations when facing a software failure. Hence, there is a need for new methodologies to be developed to support aerospace companies in effectively managing their software portfolios, avoiding the hazards of business disruption and additional costs. This paper aims to provide a definition of operational software maturity, and how this can be used to assess software operational behaviour, as well as a view on the different aspects that drive software maturity within the aerospace industry. The key research question addressed is, how can operational software maturity monitoring assist the aerospace industry in effectively managing large software portfolios? This question has been addressed by conducting an in depth review of current literature, by working closely with aerospace professionals and by running an industry case study within a major aircraft manufacturer. The results are a software maturity model composed of a set of drivers and a prototype tool used for the testing and validation of the research findings. By utilising these methodologies to assess the operational maturity of software applications in aerospace, benefits in maintenance activities and operations disruption avoidance have been observed, supporting business cases for system improvement.
Abstract: Recent years have seen an increasing number of patent disputes due to excessive competition in the global market and a reduced technology life-cycle; this has increased the risk of investment in technology development. While many global companies have started developing a methodology to identify promising technologies and assess for decisions, the existing methodology still has some limitations. Post hoc assessments of the new technology are not being performed, especially to determine whether the suggested technologies turned out to be promising. For example, in existing quantitative patent analysis, a patent’s citation information has served as an important metric for quality assessment, but this analysis cannot be applied to recently registered patents because such information accumulates over time. Therefore, we propose a new technology assessment model that can replace citation information and positively affect technological development based on post hoc analysis of the patents for promising technologies. Additionally, we collect customer reviews on a target technology to extract keywords that show the customers’ needs, and we determine how many keywords are covered in the new technology. Finally, we construct a portfolio (based on a technology assessment from patent information) and a customer-based marketability assessment (based on review data), and we use them to visualize the characteristics of the new technologies.
Abstract: Rapid population growth and urbanization is creating pressure throughout the world. This has a dramatic effect on a lot of elements which include water, food, transportation, energy, infrastructure etc. as few of the key services. Built environment sector is growing concurrently to meet the needs of urbanization. Due to such large scale development of buildings, there is a need for them to be monitored and managed efficiently. Along with appropriate management, climate adaptation is highly crucial as well because buildings are one of the major sources of greenhouse gas emission in their operation phase. Buildings to be adaptive need to provide a triple bottom approach to sustainability i.e., being socially, environmentally and economically sustainable. Hence, in order to deliver these sustainability outcomes, there is a growing understanding and thrive towards switching to green buildings or renovating new ones as per green standards wherever possible. Academic institutions in particular have been following this trend globally. This is highly significant as universities usually have high occupancy rates because they manage a large building portfolio. Also, as universities accommodate the future generation of architects, policy makers etc., they have the potential of setting themselves as a best industry practice model for research and innovation for the rest to follow. Hence their climate adaptation, sustainable growth and performance management becomes highly crucial in order to provide the best services to users. With the objective of evaluating appropriate management mechanisms within academic institutions, a feasibility study was carried out in a recent 5-Star Green Star rated university building (housing the School of Construction) in Victoria (south-eastern state of Australia). The key aim was to understand the behavioral and social aspect of the building users, management and the impact of their relationship on overall building sustainability. A survey was used to understand the building occupant’s response and reactions in terms of their work environment and management. A report was generated based on the survey results complemented with utility and performance data which were then used to evaluate the management structure of the university. Followed by the report, interviews were scheduled with the facility and asset managers in order to understand the approach they use to manage the different buildings in their university campuses (old, new, refurbished), respective building and parameters incorporated in maintaining the Green Star performance. The results aimed at closing the communication and feedback loop within the respective institutions and assist the facility managers to deliver appropriate stakeholder engagement. For the wider design community, analysis of the data highlights the applicability and significance of prioritizing key stakeholders, integrating desired engagement policies within an institution’s management structures and frameworks and their effect on building performance
Abstract: The paper presents the results and industrial
applications in the production setup period estimation based on
industrial data inherited from the field of polymer cutting. The
literature of polymer cutting is very limited considering the number
of publications. The first polymer cutting machine is known since the
second half of the 20th century; however, the production of polymer
parts with this kind of technology is still a challenging research topic.
The products of the applying industrial partner must met high
technical requirements, as they are used in medical, measurement
instrumentation and painting industry branches. Typically, 20% of
these parts are new work, which means every five years almost the
entire product portfolio is replaced in their low series manufacturing
environment. Consequently, it requires a flexible production system,
where the estimation of the frequent setup periods' lengths is one of
the key success factors. In the investigation, several (input)
parameters have been studied and grouped to create an adequate
training information set for an artificial neural network as a base for
the estimation of the individual setup periods. In the first group,
product information is collected such as the product name and
number of items. The second group contains material data like
material type and colour. In the third group, surface quality and
tolerance information are collected including the finest surface and
tightest (or narrowest) tolerance. The fourth group contains the setup
data like machine type and work shift. One source of these
parameters is the Manufacturing Execution System (MES) but some
data were also collected from Computer Aided Design (CAD)
drawings. The number of the applied tools is one of the key factors
on which the industrial partners’ estimations were based previously.
The artificial neural network model was trained on several thousands
of real industrial data. The mean estimation accuracy of the setup
periods' lengths was improved by 30%, and in the same time the
deviation of the prognosis was also improved by 50%. Furthermore,
an investigation on the mentioned parameter groups considering the
manufacturing order was also researched. The paper also highlights
the manufacturing introduction experiences and further
improvements of the proposed methods, both on the shop floor and
on the quotation preparation fields. Every week more than 100 real
industrial setup events are given and the related data are collected.
Abstract: This paper analyses the effect of adding Bitcoin, to the portfolio (stocks, bonds, Baltic index, MXEF, gold, real estate and crude oil) of an international investor by using daily data available from 2nd of July, 2010 to 2nd of August, 2016. We conclude that adding Bitcoin to portfolio, over the course of the considered period, always yielded a higher Sharpe ratio. This means that Bitcoin’s returns offset its high volatility. This paper, recognizing the fact that Bitcoin is a relatively new asset class, gives the readers a basic idea about the working of the virtual currency, the increasing number developments in the financial industry revolving around it, its unique features and the detailed look into its continuously growing acceptance across different fronts (Banks, Merchants and Countries) globally. We also construct optimal portfolios to reflect the highly lucrative and largely unexplored opportunities associated with investment in Bitcoin.
Abstract: Electricity has an indispensable role in human daily life, technological development and economy. It is a special product or service that should be instantaneously generated and consumed. Sources of the world are limited so that effective and efficient use of them is very important not only for human life and environment but also for technological and economic development. Competitive electricity market is one of the important way that provides suitable platform for effective and efficient use of electricity. Besides benefits, it brings along some risks that should be carefully managed by a market player like Electricity Generation Company. Risk management is an essential part in market players’ decision making. In this paper, risk management through diversification is applied with the help of Value at Risk methods for case studies. Performance of optimal electricity sale solutions are measured and the portfolio performance has been evaluated via Sharpe-Ratio, and compared with conventional approach. Biennial historical electricity price data of Turkish Day Ahead Market are used to demonstrate the approach.
Abstract: Transport infrastructure assets are key components of the national asset portfolio. The decision to invest in a new infrastructure in transports could take from a few years to some decades. This is mainly because of the need to reserve and spent many capitals, the long payback period, the number of the stakeholders involved in decision process and –many times- the investment and business risks are high. Therefore, the decision assessment framework is an essential challenge linked with the key decision factors meet the stakeholder expectations highlighting project trade-offs, financial risks, business uncertainties and market limitations. This paper examines the decision process for new transport infrastructure projects in cross border regions, where a wide range of stakeholders with different expectation is involved. According to a consequences analysis systemic approach, the relationship of transport infrastructure development, economic system development and stakeholder expectation is analyzed. Adopting the on system of system methodological approach, the decision making framework, variables, inputs and outputs are defined, highlighting the key shareholder’s role and expectations. The application provides the methodology outputs presenting the proposed decision framework for a strategic railway project in north Greece deals with the upgrade of the existing railway corridor connecting Greece, Turkey and Bulgaria.
Abstract: Electricity plays an indispensable role in human life and the economy. It is a unique product or service that must be balanced instantaneously, as electricity is not stored, generation and consumption should be proportional. Effective and efficient use of electricity is very important not only for society, but also for the environment. A competitive electricity market is one of the best ways to provide a suitable platform for effective and efficient use of electricity. On the other hand, it carries some risks that should be carefully managed by the market players. Risk management is an essential part in market players’ decision making. In this paper, risk management through diversification is applied with the help of Markowitz’s Mean-variance, Down-side and Semi-variance methods for a case study. Performance of optimal electricity sale solutions are measured and evaluated via Sharpe-Ratio, and the optimal portfolio solutions are improved. Two years of historical weekdays’ price data of the Turkish Day Ahead Market are used to demonstrate the approach.
Abstract: Today, insurers may use the yield curve as an indicator
evaluation of the profit or the performance of their portfolios;
therefore, they modeled it by one class of model that has the ability
to fit and forecast the future term structure of interest rates. This class
of model is the Nelson-Siegel-Svensson model. Unfortunately, many
authors have reported a lot of difficulties when they want to calibrate
the model because the optimization problem is not convex and has
multiple local optima. In this context, we implement a hybrid Particle
Swarm optimization and Nelder Mead algorithm in order to minimize
by least squares method, the difference between the zero-coupon
curve and the NSS curve.
Abstract: To increase the quality of learning, teacher and learner need mutual effort for realization of educational value. For this purpose, we need to manage the co-creational education among teacher and learners. In this research, we try to find a feature of co-creational education. To be more precise, we analyzed learners’ reports by natural language processing, and extract some features that describe the state of the co-creational education.
Abstract: Project Portfolio Management (PPM) is an essential
component of an organisation’s strategic procedures, which requires
attention of several factors to envisage a range of long-term outcomes
to support strategic project portfolio decisions. To evaluate overall
efficiency at the portfolio level, it is essential to identify the
functionality of specific projects as well as to aggregate those
findings in a mathematically meaningful manner that indicates the
strategic significance of the associated projects at a number of levels
of abstraction. PPM success is directly associated with the quality of
decisions made and poor judgment increases portfolio costs. Hence,
various Multi-Criteria Decision Making (MCDM) techniques have
been designed and employed to support the decision-making
functions. This paper reviews possible options to enhance the
decision-making outcomes in organisational portfolio management
processes using the Analytic Hierarchy Process (AHP) both from
academic and practical perspectives and will examine the usability,
certainty and quality of the technique. The results of the study will
also provide insight into the technical risk associated with current
decision-making model to underpin initiative tracking and strategic
portfolio management.
Abstract: In this paper we present a classification of the various technologies applied for the solution of the portfolio selection problem according to the discipline and the methodological framework followed. We provide a concise presentation of the emerged categories and we are trying to identify which methods considered obsolete and which lie at the heart of the debate. On top of that, we provide a comparative study of the different technologies applied for efficient portfolio construction and we suggest potential paths for future work that lie at the intersection of the presented techniques.
Abstract: This paper examines the relationship between
corporate governance rating and stock prices of 26 Turkish firms
listed in Turkish stock exchange (Borsa Istanbul) by using panel data
analysis over five-year period. The paper also investigates the stock
performance of firms with governance rating with regards to the
market portfolio (i.e. BIST 100 Index) both prior and after
governance scoring began. The empirical results show that there is no
relation between corporate governance rating and stock prices when
using panel data for annual variation in both rating score and stock
prices. Further analysis indicates surprising results that while the
selected firms outperform the market significantly prior to rating, the
same performance does not continue afterwards.
Abstract: As technology-based service industries grow
drastically worldwide; companies are recognizing the importance of
market preoccupancy and have made an effort to capture a large
market to gain the upper hand. To this end, a focus on patents can be
used to determine the properties of a technology, as well as to capture
advantages in technical skills, in comparison with the firm’s
competitors. However, technology-based services largely depend not
only on their technological value but also their economic value, due
to the recognized worth that is passed to a plurality of users. Thus, it
is important to determine whether there are any competitors in the
target areas and what services they provide in any field. Despite this
importance, little effort has been made to systematically benchmark
competitors in order to identify business opportunities. Thus, this
study aims to not only identify each position of technology-centered
service companies in complex market dynamics, but also to discover
new business opportunities. For this, we try to consider both
technology and market environments simultaneously by utilizing
patent data as a representative proxy for technology and trademark
dates as an index for a firm’s target goods and services. Theoretically,
this is one of the earliest attempts to combine patent data and
trademark data to analyze corporate strategies. In practice, the
research results are expected to be used as a decision criterion to
diagnose the economic value that companies can obtain by entering
the market, as well as the technological value to be passed onto their
customers. Thus, the proposed approach can be useful to support
effective technology and business strategies in a firm.
Abstract: Modern Portfolio Theory (MPT) according to
Markowitz states that investors form mean-variance efficient
portfolios which maximizes their utility. Markowitz proposed the
standard deviation as a simple measure for portfolio risk and the
lower semi-variance as the only risk measure of interest to rational
investors. This paper uses a third volatility estimator based on
intraday data and compares three efficient frontiers on the Croatian
Stock Market. The results show that range-based volatility estimator
outperforms both mean-variance and lower semi-variance model.
Abstract: Constructing a portfolio of investments is one of the
most significant financial decisions facing individuals and
institutions. In accordance with the modern portfolio theory
maximization of return at minimal risk should be the investment goal
of any successful investor. In addition, the costs incurred when
setting up a new portfolio or rebalancing an existing portfolio must
be included in any realistic analysis.
In this paper rebalancing an investment portfolio in the presence of
transaction costs on the Croatian capital market is analyzed. The
model applied in the paper is an extension of the standard portfolio
mean-variance optimization model in which transaction costs are
incurred to rebalance an investment portfolio. This model allows
different costs for different securities, and different costs for buying
and selling. In order to find efficient portfolio, using this model, first,
the solution of quadratic programming problem of similar size to the
Markowitz model, and then the solution of a linear programming
problem have to be found. Furthermore, in the paper the impact of
transaction costs on the efficient frontier is investigated. Moreover, it
is shown that global minimum variance portfolio on the efficient
frontier always has the same level of the risk regardless of the amount
of transaction costs. Although efficient frontier position depends of
both transaction costs amount and initial portfolio it can be concluded
that extreme right portfolio on the efficient frontier always contains
only one stock with the highest expected return and the highest risk.
Abstract: The financial crises caused a collapse in prices of
most asset classes, raising the attention on alternative investments
such as sukuk, a smaller, fast growing but often misunderstood
market. We study diversification benefits of sukuk, their correlation
with other asset classes and the effects of their inclusion in
investment portfolios of institutional and retail investors, through a
comprehensive comparison of their risk/return profiles during and
after the financial crisis.
We find a beneficial performance adjusted for the specific
volatility together with a lower correlation especially during the
financial crisis. The distribution of sukuk returns is positively skewed
and leptokurtic, with a risk/return profile similarly to high yield
bonds. Overall, our results suggest that sukuk present diversification
opportunities, a significant volatility-adjusted performance and lower
correlations especially during the financial crisis.
Our findings are relevant for a number of institutional investors.
Long term investors, such as life insurers would benefit from sukuk’s
protective features during financial crisis yet keeping return and
growth opportunities, whereas banks would gain due to their role of
placers, advisors, market makers or underwriters.
Abstract: One of the most important tasks in the risk
management is the correct determination of probability of default
(PD) of particular financial subjects. In this paper a possibility of
determination of financial institution’s PD according to the creditscoring
models is discussed. The paper is divided into the two parts.
The first part is devoted to the estimation of the three different
models (based on the linear discriminant analysis, logit regression
and probit regression) from the sample of almost three hundred US
commercial banks. Afterwards these models are compared and
verified on the control sample with the view to choose the best one.
The second part of the paper is aimed at the application of the chosen
model on the portfolio of three key Czech banks to estimate their
present financial stability. However, it is not less important to be able
to estimate the evolution of PD in the future. For this reason, the
second task in this paper is to estimate the probability distribution of
the future PD for the Czech banks. So, there are sampled randomly
the values of particular indicators and estimated the PDs’ distribution,
while it’s assumed that the indicators are distributed according to the
multidimensional subordinated Lévy model (Variance Gamma model
and Normal Inverse Gaussian model, particularly). Although the
obtained results show that all banks are relatively healthy, there is
still high chance that “a financial crisis” will occur, at least in terms
of probability. This is indicated by estimation of the various quantiles
in the estimated distributions. Finally, it should be noted that the
applicability of the estimated model (with respect to the used data) is
limited to the recessionary phase of the financial market.
Abstract: Technical analysis comprised by various technical indicators is a holistic way of representing price movement of stocks in the market. Various forms of indicators have evolved from the primitive ones in the past decades. There have been many attempts to introduce volume as a major determinant to determine strong patterns in market forecasting. The law of demand defines the relationship between the volume and price. Most of the traders are familiar with the volume game. Including the time dimension to the law of demand provides a different visualization to the theory. While attempting the same, it was found that there are different thresholds in the market for different companies. These thresholds have a significant influence on the price. This article is an attempt in determining the thresholds for companies using the three dimensional graphs for optimizing the portfolios. It also emphasizes on the magnitude of importance of volumes as a key factor for determining of predicting strong price movements, bullish and bearish markets. It uses a comprehensive data set of major companies which form a major chunk of the Indian automotive sector and are thus used as an illustration.
Abstract: A brief review of the empirical studies on the methodology of the stock market decision support would indicate that they are at a threshold of validating the accuracy of the traditional and the fuzzy, artificial neural network and the decision trees. Many researchers have been attempting to compare these models using various data sets worldwide. However, the research community is on the way to the conclusive confidence in the emerged models. This paper attempts to use the automotive sector stock prices from National Stock Exchange (NSE), India and analyze them for the intra-sectorial support for stock market decisions. The study identifies the significant variables and their lags which affect the price of the stocks using OLS analysis and decision tree classifiers.