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Prof. Francisco Guijarro
Universitat Politècnica de València

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0 Financial Markets
0 Trading Strategies
0 Valuation
0 operational research

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Journal article
Published: 24 August 2021 in Journal of Risk and Financial Management
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Market liquidity has an immediate impact on the execution of transactions in financial markets. Informed counterparty risk is often priced into market liquidity. This study investigates whether microblogging data, as a non-financial information tool, is priced along with market liquidity dimensions. The analysis is based on the Australian Securities Exchange (ASX), and from the results, we conclude that microblogging content in pessimistic periods has a higher impact on liquidity and its dimensions. On a daily basis, pessimistic investor sentiments lead to higher trading costs, illiquidity, a larger price dispersion and a lower trading volume.

ACS Style

Francisco Guijarro; Ismael Moya-Clemente; Jawad Saleemi. Market Liquidity and Its Dimensions: Linking the Liquidity Dimensions to Sentiment Analysis through Microblogging Data. Journal of Risk and Financial Management 2021, 14, 394 .

AMA Style

Francisco Guijarro, Ismael Moya-Clemente, Jawad Saleemi. Market Liquidity and Its Dimensions: Linking the Liquidity Dimensions to Sentiment Analysis through Microblogging Data. Journal of Risk and Financial Management. 2021; 14 (9):394.

Chicago/Turabian Style

Francisco Guijarro; Ismael Moya-Clemente; Jawad Saleemi. 2021. "Market Liquidity and Its Dimensions: Linking the Liquidity Dimensions to Sentiment Analysis through Microblogging Data." Journal of Risk and Financial Management 14, no. 9: 394.

Journal article
Published: 24 February 2021 in Mathematics
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This paper proposes the use of a goal programming model for the objective ranking of universities. This methodology has been successfully used in other areas to analyze the performance of firms by focusing on two opposite approaches: (a) one favouring those performance variables that are aligned with the central tendency of the majority of the variables used in the measurement of the performance, and (b) an alternative one that favours those different, singular, or independent performance variables. Our results are compared with the ranking proposed by two popular World University Rankings, and some insightful differences are outlined. We show how some top-performing universities occupy the best positions regardless of the approach followed by the goal programming model, hence confirming their leadership. In addition, our proposal allows for an objective quantification of the importance of each variable in the performance of universities, which could be of great interest to decision-makers.

ACS Style

Fernando García; Francisco Guijarro; Javier Oliver. A Multicriteria Goal Programming Model for Ranking Universities. Mathematics 2021, 9, 459 .

AMA Style

Fernando García, Francisco Guijarro, Javier Oliver. A Multicriteria Goal Programming Model for Ranking Universities. Mathematics. 2021; 9 (5):459.

Chicago/Turabian Style

Fernando García; Francisco Guijarro; Javier Oliver. 2021. "A Multicriteria Goal Programming Model for Ranking Universities." Mathematics 9, no. 5: 459.

Journal article
Published: 30 December 2020 in Entrepreneurship and Sustainability Issues
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ACS Style

Fernando García; Jairo González-Bueno; Francisco Guijarro; Javier Oliver. A multiobjective credibilistic portfolio selection model. Empirical study in the Latin American integrated market. Entrepreneurship and Sustainability Issues 2020, 8, 1027 -1046.

AMA Style

Fernando García, Jairo González-Bueno, Francisco Guijarro, Javier Oliver. A multiobjective credibilistic portfolio selection model. Empirical study in the Latin American integrated market. Entrepreneurship and Sustainability Issues. 2020; 8 (2):1027-1046.

Chicago/Turabian Style

Fernando García; Jairo González-Bueno; Francisco Guijarro; Javier Oliver. 2020. "A multiobjective credibilistic portfolio selection model. Empirical study in the Latin American integrated market." Entrepreneurship and Sustainability Issues 8, no. 2: 1027-1046.

Journal article
Published: 08 October 2020 in Technological and Economic Development of Economy
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The present research proposes a novel methodology to solve the problems faced by investors who take into consideration different investment criteria in a fuzzy context. The approach extends the stochastic mean-variance model to a fuzzy multiobjective model where liquidity is considered to quantify portfolio’s performance, apart from the usual metrics like return and risk. The uncertainty of the future returns and the future liquidity of the potential assets are modelled employing trapezoidal fuzzy numbers. The decision process of the proposed approach considers that portfolio selection is a multidimensional issue and also some realistic constraints applied by investors. Particularly, this approach optimizes the expected return, the risk and the expected liquidity of the portfolio, considering bound constraints and cardinality restrictions. As a result, an optimization problem for the constraint portfolio appears, which is solved by means of the NSGA-II algorithm. This study defines the credibilistic Sortino ratio and the credibilistic STARR ratio for selecting the optimal portfolio. An empirical study on the S&P100 index is included to show the performance of the model in practical applications. The results obtained demonstrate that the novel approach can beat the index in terms of return and risk in the analyzed period, from 2008 until 2018.

ACS Style

Fernando Garcia; Jairo González-Bueno; Francisco Guijarro; Javier Oliver; Rima Tamošiūnienė. MULTIOBJECTIVE APPROACH TO PORTFOLIO OPTIMIZATION IN THE LIGHT OF THE CREDIBILITY THEORY. Technological and Economic Development of Economy 2020, 26, 1165 -1186.

AMA Style

Fernando Garcia, Jairo González-Bueno, Francisco Guijarro, Javier Oliver, Rima Tamošiūnienė. MULTIOBJECTIVE APPROACH TO PORTFOLIO OPTIMIZATION IN THE LIGHT OF THE CREDIBILITY THEORY. Technological and Economic Development of Economy. 2020; 26 (6):1165-1186.

Chicago/Turabian Style

Fernando Garcia; Jairo González-Bueno; Francisco Guijarro; Javier Oliver; Rima Tamošiūnienė. 2020. "MULTIOBJECTIVE APPROACH TO PORTFOLIO OPTIMIZATION IN THE LIGHT OF THE CREDIBILITY THEORY." Technological and Economic Development of Economy 26, no. 6: 1165-1186.

Special issue paper
Published: 09 July 2020 in Expert Systems
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Automating chart pattern recognition is a relevant issue addressed by researchers and practitioners when designing a system that considers technical analysis for trading purposes. This article proposes the design of a trading system that takes into account any generic pattern that has been proven to be profitable in the past, without restricting the search to the specific technical patterns reported in the literature, hence the term generic pattern recognition . A fast version of dynamic time warping, the University College Riverside subsequence search suite (called the UCR suite), is employed for the pattern recognition task in an effort to produce trading signals in realistic timescales. This article evaluates the significance of the relation between the system's profitability and (a) the pattern length, (b) the take‐profit and stop‐loss levels and (c) the performance consensus of past patterns. The trading system is assessed under the mean–variance perspective by using 560 NYSE stocks. The results obtained by the different parameter configurations are reported, controlling for both data‐snooping and transaction costs. On average, the proposed system dominates the market index in the mean–variance sense. Although transaction costs reduce the profitability of the proposed trading system, 92.5% of the experiments are profitable if the analysis is reduced to the parameter values aligned with the technical analysis.

ACS Style

Prodromos Tsinaslanidis; Francisco Guijarro. What makes trading strategies based on chart pattern recognition profitable? Expert Systems 2020, e12596 .

AMA Style

Prodromos Tsinaslanidis, Francisco Guijarro. What makes trading strategies based on chart pattern recognition profitable? Expert Systems. 2020; ():e12596.

Chicago/Turabian Style

Prodromos Tsinaslanidis; Francisco Guijarro. 2020. "What makes trading strategies based on chart pattern recognition profitable?" Expert Systems , no. : e12596.

Journal article
Published: 20 April 2020 in Sustainability
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The environmental, social, and governance (ESG) rating of firms is a useful tool for stakeholders and investment decision-makers. This paper develops a rough set model to relate ESG scores to popular corporate financial performance measures. This methodology permits handling with information in an uncertain, ambiguous, and imperfect context. A large database was gathered, including ESG scores, as well as industry sector and financial variables for publicly traded European companies during the period 2013–2018. We carried out 500 simulations of the rough set model for different values in the discretization parameter and different grouping scenarios of firms regarding ESG scores. The results suggest that the variables considered are useful in the prediction of ESG rank when firms are clustered in three or four equally balanced groups. However, the prediction power vanishes when a larger number of groups is computed. This would suggest that industry sector and financial variables serve to find big differences across firms regarding ESG, but the significance of the model drops when small differences in ESG performance are scrutinized.

ACS Style

Fernando García; Jairo González-Bueno; Francisco Guijarro; Javier Oliver. Forecasting the Environmental, Social, and Governance Rating of Firms by Using Corporate Financial Performance Variables: A Rough Set Approach. Sustainability 2020, 12, 3324 .

AMA Style

Fernando García, Jairo González-Bueno, Francisco Guijarro, Javier Oliver. Forecasting the Environmental, Social, and Governance Rating of Firms by Using Corporate Financial Performance Variables: A Rough Set Approach. Sustainability. 2020; 12 (8):3324.

Chicago/Turabian Style

Fernando García; Jairo González-Bueno; Francisco Guijarro; Javier Oliver. 2020. "Forecasting the Environmental, Social, and Governance Rating of Firms by Using Corporate Financial Performance Variables: A Rough Set Approach." Sustainability 12, no. 8: 3324.

Journal article
Published: 14 April 2020 in Expert Systems with Applications
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The aim of this study is to devise a sector restructuring model in which all the decision making units (DMUs) satisfy a predefined global efficiency level. The proposal makes several realistic assumptions regarding the merging of DMUs under specific circumstances. The model computes the global efficiency target by giving preference to merging DMUs over saving inputs, hence considering that the affected stakeholders may be resistant to restructuring, and this resistance may have overall negative effects on the image and reputation of the companies and organizations. In addition, the number of constituents in the new entities can be limited by the decision maker after the restructuring process, so that the model also considers a constraint on cardinality. The proposal combines the inverse data envelopment analysis (InvDEA), which computes the merger’s input savings, and the genetic algorithm (GA), which solves the combinatorial problem of identifying the merging units. The proposal is illustrated by two examples from banking and higher education.

ACS Style

Francisco Guijarro; Mónica Martínez-Gómez; Delimiro Visbal-Cadavid. A model for sector restructuring through genetic algorithm and inverse DEA. Expert Systems with Applications 2020, 154, 113422 .

AMA Style

Francisco Guijarro, Mónica Martínez-Gómez, Delimiro Visbal-Cadavid. A model for sector restructuring through genetic algorithm and inverse DEA. Expert Systems with Applications. 2020; 154 ():113422.

Chicago/Turabian Style

Francisco Guijarro; Mónica Martínez-Gómez; Delimiro Visbal-Cadavid. 2020. "A model for sector restructuring through genetic algorithm and inverse DEA." Expert Systems with Applications 154, no. : 113422.

Journal article
Published: 31 March 2020 in International Journal of Environmental Research and Public Health
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Environmental valuation refers to a variety of techniques to assign monetary values to environmental impacts, especially non-market impacts. It has experienced a steady growth in the number of publications on the subject in the last 30 years. We performed a search for papers containing the term “environmental valuation” in the title, abstract, or keywords. The search was conducted with an online literature search engine of the Web of Science (WoS) electronic databases. A search of this database revealed that the term “environmental valuation” appeared for the first time in 1987. Since then a large number of studies have been published, including significant breakthroughs in theory and applications. In the present work 661 publications were selected for a review of the literature on environmental valuation over the period 1987–2019. This paper analyzes the evolution of the leading methodologies and authors, highlights the preference for the choice experiment method over the contingent valuation method, and shows that relatively few papers have had a strong impact on the researchers in this area.

ACS Style

Francisco Guijarro; Prodromos Tsinaslanidis. Analysis of Academic Literature on Environmental Valuation. International Journal of Environmental Research and Public Health 2020, 17, 2386 .

AMA Style

Francisco Guijarro, Prodromos Tsinaslanidis. Analysis of Academic Literature on Environmental Valuation. International Journal of Environmental Research and Public Health. 2020; 17 (7):2386.

Chicago/Turabian Style

Francisco Guijarro; Prodromos Tsinaslanidis. 2020. "Analysis of Academic Literature on Environmental Valuation." International Journal of Environmental Research and Public Health 17, no. 7: 2386.

Journal article
Published: 01 January 2020 in Finance, Markets and Valuation
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Forecasting the direction of stocks markets has become a popular research topic in recent years. Differentapproaches have been applied by researchers to address the prediction of market trends by consideringtechnical indicators and chart patterns from technical analysis. This paper compares the performanceof four machine learning algorithms to validate the forecasting ability of popular technical indicators inthe technological NASDAQ index. Since the mathematical formulas used in the calculation of technicalindicators comprise historical prices they will be related to the past trend of the market. We assume thatforecasting performance increases when the trend is computed on a longer time horizon. Our resultssuggest that the random forest outperforms the other machine learning algorithms considered in ourresearch, being able to forecast the 10-days ahead market trend, with an average accuracy of 80%.

ACS Style

R. Cervelló-Royo; F. Guijarro. Forecasting stock market trend: a comparison of machine learning algorithms. Finance, Markets and Valuation 2020, 6, 37 -49.

AMA Style

R. Cervelló-Royo, F. Guijarro. Forecasting stock market trend: a comparison of machine learning algorithms. Finance, Markets and Valuation. 2020; 6 (1):37-49.

Chicago/Turabian Style

R. Cervelló-Royo; F. Guijarro. 2020. "Forecasting stock market trend: a comparison of machine learning algorithms." Finance, Markets and Valuation 6, no. 1: 37-49.

Articles
Published: 18 December 2019 in Journal of the Operational Research Society
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This article deals with the mean-variance optimisation frontier problem when realistic constraints are considered. Our proposed methodology hybridises a heuristic algorithm with an exact solution approach. A genetic algorithm is applied for the identification of the assets in the portfolio, whilst the asset weights in the portfolios are obtained by a quadratic programming model. The proposed algorithmic framework produces a constrained frontier that actually fulfils the bound and cardinality constraints, unlike other proposals where the frontier is composed of several subfrontiers, each one considering the cardinality constraint but with different assets in each sub-frontier, thus violating the cardinality constraint. This brings us to propose a surrogate similarity measure for the optimisation of the constrained frontier, which differs from a previous proposal where no bound constraints were considered.

ACS Style

Francisco Guijarro; Prodromos Tsinaslanidis. A surrogate similarity measure for the mean-variance frontier optimisation problem under bound and cardinality constraints. Journal of the Operational Research Society 2019, 72, 564 -579.

AMA Style

Francisco Guijarro, Prodromos Tsinaslanidis. A surrogate similarity measure for the mean-variance frontier optimisation problem under bound and cardinality constraints. Journal of the Operational Research Society. 2019; 72 (3):564-579.

Chicago/Turabian Style

Francisco Guijarro; Prodromos Tsinaslanidis. 2019. "A surrogate similarity measure for the mean-variance frontier optimisation problem under bound and cardinality constraints." Journal of the Operational Research Society 72, no. 3: 564-579.

Journal article
Published: 17 December 2019 in International Journal of Environmental Research and Public Health
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This paper describes a study of the relationship between undesired road traffic externalities and residential price values in the Spanish city of Madrid. A large database was gathered, including the price and characteristics of 21,634 flats and road traffic intensity at 3904 different points across the city. The results obtained by a hedonic model suggest that both distance from the traffic measurement point and average daily traffic are significantly related to the price of residential properties, even after controlling for structural and neighbourhood variables. Distance to traffic areas has a positive impact on dwelling prices, whilst these are negatively related to traffic intensity.

ACS Style

Francisco Guijarro. Assessing the Impact of Road Traffic Externalities on Residential Price Values: A Case Study in Madrid, Spain. International Journal of Environmental Research and Public Health 2019, 16, 5149 .

AMA Style

Francisco Guijarro. Assessing the Impact of Road Traffic Externalities on Residential Price Values: A Case Study in Madrid, Spain. International Journal of Environmental Research and Public Health. 2019; 16 (24):5149.

Chicago/Turabian Style

Francisco Guijarro. 2019. "Assessing the Impact of Road Traffic Externalities on Residential Price Values: A Case Study in Madrid, Spain." International Journal of Environmental Research and Public Health 16, no. 24: 5149.

Journal article
Published: 10 December 2019 in Sustainability
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Microblogging services can enrich the information investors use to make financial decisions on the stock markets. As liquidity has immediate consequences for a trader’s movements, this risk is an attractive area of interest for both academics and those who participate in the financial markets. This paper focuses on market liquidity and studies the impact on liquidity and trading costs of the popular Twitter microblogging service. Sentiment analysis extracted from Twitter and different popular liquidity measures were gathered to analyze the relationship between liquidity and investors’ opinions. The results, based on the analysis of the S&P 500 Index, found that the investors’ mood had little influence on the spread of the index.

ACS Style

Francisco Guijarro; Ismael Moya-Clemente; Jawad Saleemi. Liquidity Risk and Investors’ Mood: Linking the Financial Market Liquidity to Sentiment Analysis through Twitter in the S&P500 Index. Sustainability 2019, 11, 7048 .

AMA Style

Francisco Guijarro, Ismael Moya-Clemente, Jawad Saleemi. Liquidity Risk and Investors’ Mood: Linking the Financial Market Liquidity to Sentiment Analysis through Twitter in the S&P500 Index. Sustainability. 2019; 11 (24):7048.

Chicago/Turabian Style

Francisco Guijarro; Ismael Moya-Clemente; Jawad Saleemi. 2019. "Liquidity Risk and Investors’ Mood: Linking the Financial Market Liquidity to Sentiment Analysis through Twitter in the S&P500 Index." Sustainability 11, no. 24: 7048.

Journal article
Published: 10 August 2019 in International Journal of Environmental Research and Public Health
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Countries are encouraged to integrate environmental performance metrics by covering the key value-drivers of sustainable development, such as environmental health and ecosystem vitality. The proper measurement of environmental trends provides a foundation for policymaking, which should be addressed by considering the multicriteria nature of the problem. This paper proposes a goal programming model for ranking countries according to the multidimensional nature of their environmental performance metrics by considering 10 issue categories and 24 performance indicators. The results will provide guidance to those countries that aspire to become leaders in environmental performance.

ACS Style

Francisco Guijarro. A Multicriteria Model for the Assessment of Countries’ Environmental Performance. International Journal of Environmental Research and Public Health 2019, 16, 2868 .

AMA Style

Francisco Guijarro. A Multicriteria Model for the Assessment of Countries’ Environmental Performance. International Journal of Environmental Research and Public Health. 2019; 16 (16):2868.

Chicago/Turabian Style

Francisco Guijarro. 2019. "A Multicriteria Model for the Assessment of Countries’ Environmental Performance." International Journal of Environmental Research and Public Health 16, no. 16: 2868.

Withdrawal
Published: 01 July 2019 in Expert Systems with Applications: X
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ACS Style

Francisco Guijarro; Mónica Martínez-Gómez; Delimiro Visbal-Cadavid. WITHDRAWN: A combined genetic algorithm and inverse data envelopment analysis model for target setting in mergers. Expert Systems with Applications: X 2019, 1 .

AMA Style

Francisco Guijarro, Mónica Martínez-Gómez, Delimiro Visbal-Cadavid. WITHDRAWN: A combined genetic algorithm and inverse data envelopment analysis model for target setting in mergers. Expert Systems with Applications: X. 2019; ():1.

Chicago/Turabian Style

Francisco Guijarro; Mónica Martínez-Gómez; Delimiro Visbal-Cadavid. 2019. "WITHDRAWN: A combined genetic algorithm and inverse data envelopment analysis model for target setting in mergers." Expert Systems with Applications: X , no. : 1.

Journal article
Published: 21 November 2018 in Technological and Economic Development of Economy
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Intraday trading rules require accurate information about the future short term market evolution. For that reason, next-day market trend prediction has attracted the attention of both academics and practitioners. This interest has increased in recent years, as different methodologies have been applied to this end. Usually, machine learning techniques are used such as artificial neural networks, support vector machines and decision trees. The input variables of most of the studies are traditional technical indicators which are used by professional traders to implement investment strategies. We analyse if these indicators have predictive power on the German DAX-30 stock index by applying a hybrid fuzzy neural network to predict the one-day ahead direction of index. We implement different models depending on whether all the indicators and oscillators are used as inputs, or if a linear combination of them obtained through a factor analysis is used instead. In order to guarantee for the robustness of the results, we train and apply the HyFIS models on randomly selected subsamples 10,000 times. The results show that the reduction of the dimension through the factorial analysis generates more profitable and less risky strategies.

ACS Style

Fernando García; Francisco Guijarro; Javier Oliver; Rima Tamošiūnienė. HYBRID FUZZY NEURAL NETWORK TO PREDICT PRICE DIRECTION IN THE GERMAN DAX-30 INDEX. Technological and Economic Development of Economy 2018, 24, 2161 -2178.

AMA Style

Fernando García, Francisco Guijarro, Javier Oliver, Rima Tamošiūnienė. HYBRID FUZZY NEURAL NETWORK TO PREDICT PRICE DIRECTION IN THE GERMAN DAX-30 INDEX. Technological and Economic Development of Economy. 2018; 24 (6):2161-2178.

Chicago/Turabian Style

Fernando García; Francisco Guijarro; Javier Oliver; Rima Tamošiūnienė. 2018. "HYBRID FUZZY NEURAL NETWORK TO PREDICT PRICE DIRECTION IN THE GERMAN DAX-30 INDEX." Technological and Economic Development of Economy 24, no. 6: 2161-2178.

Journal article
Published: 21 November 2018 in Technological and Economic Development of Economy
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Intraday trading rules require accurate information about the future short term market evolution. For that reason, next-day market trend prediction has attracted the attention of both academics and practitioners. This interest has increased in recent years, as different methodologies have been applied to this end. Usually, machine learning techniques are used such as artificial neural networks, support vector machines and decision trees. The input variables of most of the studies are traditional technical indicators which are used by professional traders to implement investment strategies. We analyse if these indicators have predictive power on the German DAX-30 stock index by applying a hybrid fuzzy neural network to predict the one-day ahead direction of index. We implement different models depending on whether all the indicators and oscillators are used as inputs, or if a linear combination of them obtained through a factor analysis is used instead. In order to guarantee for the robustness of the results, we train and apply the HyFIS models on randomly selected subsamples 10,000 times. The results show that the reduction of the dimension through the factorial analysis generates more profitable and less risky strategies.

ACS Style

Fernando García; Francisco Guijarro; Javier Oliver; Rima Tamošiūnienė. HYBRID FUZZY NEURAL NETWORK TO PREDICT PRICE DIRECTION IN THE GERMAN DAX-30 INDEX. Technological and Economic Development of Economy 2018, 24, 2161 -2178.

AMA Style

Fernando García, Francisco Guijarro, Javier Oliver, Rima Tamošiūnienė. HYBRID FUZZY NEURAL NETWORK TO PREDICT PRICE DIRECTION IN THE GERMAN DAX-30 INDEX. Technological and Economic Development of Economy. 2018; 24 (6):2161-2178.

Chicago/Turabian Style

Fernando García; Francisco Guijarro; Javier Oliver; Rima Tamošiūnienė. 2018. "HYBRID FUZZY NEURAL NETWORK TO PREDICT PRICE DIRECTION IN THE GERMAN DAX-30 INDEX." Technological and Economic Development of Economy 24, no. 6: 2161-2178.

Data descriptor
Published: 03 November 2018 in Data
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The current economical recovery is driven by expansions in many countries, with a global economic growth of 3.6% in 2017. However, some countries are still struggling with vulnerable forms of employment and high unemployment rates. Official statistics in Spain reveal that women and older people constitutes the core of structural unemployment, and are persistently being excluded from employment recovery. This paper contributes with a database that includes jobseekers’ characteristics, enrollment on training initiatives for unemployed and employment contracts for the Valencian region in Spain. Analysing the relation between the involved variables can help researchers to shed light on which characteristics are positively related to employment and then encourage political decision makers to promote initiatives to support vulnerable groups.

ACS Style

Francisco Guijarro. Characteristics of Unemployed People, Training Attendance and Job Searching Success in the Valencian Region (Spain). Data 2018, 3, 47 .

AMA Style

Francisco Guijarro. Characteristics of Unemployed People, Training Attendance and Job Searching Success in the Valencian Region (Spain). Data. 2018; 3 (4):47.

Chicago/Turabian Style

Francisco Guijarro. 2018. "Characteristics of Unemployed People, Training Attendance and Job Searching Success in the Valencian Region (Spain)." Data 3, no. 4: 47.

Journal article
Published: 10 October 2018 in Sustainability
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Macroeconomic indicators regarding employment have been gradually improved by southern European countries during recent years. However, the labour market still seems to be highly polarized across regions and some groups are persistently excluded from jobs recovery. This paper analyses the effectiveness of active labour market initiatives in the Valencian region, one of the worst-affected areas regarding unemployment in Spain. By using a large official database from the Valencian government, results of the probit model show that participating on active labour market initiatives have a positive impact on the probability of exiting unemployment, even after controlling for age, level of education and gender of candidates. The research also reveals that people aged 55 and older and females constitute the most vulnerable groups. Regarding women, only those with higher education increase their probability of finding a job.

ACS Style

Francisco Guijarro. Economic Recovery and Effectiveness of Active Labour Market Initiatives for the Unemployed in Spain: A Gender Perspective of the Valencian Region. Sustainability 2018, 10, 3623 .

AMA Style

Francisco Guijarro. Economic Recovery and Effectiveness of Active Labour Market Initiatives for the Unemployed in Spain: A Gender Perspective of the Valencian Region. Sustainability. 2018; 10 (10):3623.

Chicago/Turabian Style

Francisco Guijarro. 2018. "Economic Recovery and Effectiveness of Active Labour Market Initiatives for the Unemployed in Spain: A Gender Perspective of the Valencian Region." Sustainability 10, no. 10: 3623.

Journal article
Published: 04 September 2018 in Sustainability
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The 17 Sustainable Development Goals (SDGs) adopted by the United Nations are at the center of the global political agenda to eradicate extreme poverty, achieve universal education, promote gender equality and ensure environmental sustainability between others. These goals are organised in 169 indicators, which give an accurate perspective on the main dimensions related with country sustainable development. To gain insight into the relative position of involved countries, it is necessary to develop a composite index that summarises the global progress in the achievement of these goals, but considering possible conflicts and trade-offs between individual SDGs. The objective of this paper is to introduce a Goal Programming model to calculate a composite SDG index, capable of overcoming some of the limitations of celebrated approaches such as arithmetic and geometric averages. The proposed model balances between two extreme solutions: one which calculates a consensus index that reflects the majority trend of the SDGs, and another one which biases the estimated index towards those SDGs that show the most discrepancy with the rest. The model is applied on the EU-28 countries, and shows that the best performing countries regarding the sustainable development are Austria and Luxembourg, while Greece and Romania remain as the worst performers.

ACS Style

Francisco Guijarro; Juan A. Poyatos. Designing a Sustainable Development Goal Index through a Goal Programming Model: The Case of EU-28 Countries. Sustainability 2018, 10, 3167 .

AMA Style

Francisco Guijarro, Juan A. Poyatos. Designing a Sustainable Development Goal Index through a Goal Programming Model: The Case of EU-28 Countries. Sustainability. 2018; 10 (9):3167.

Chicago/Turabian Style

Francisco Guijarro; Juan A. Poyatos. 2018. "Designing a Sustainable Development Goal Index through a Goal Programming Model: The Case of EU-28 Countries." Sustainability 10, no. 9: 3167.

Journal article
Published: 12 January 2018 in Journal of the Operational Research Society
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This paper proposes a new measure to find the cardinality constrained frontier in the mean–variance portfolio optimization problem. In previous research, assets belonging to the cardinality constrained portfolio change according to the desired level of expected return, so that the cardinality constraint can actually be violated if the fund manager wants to satisfy clients with different return requirements. We introduce a perceptual approach in the mean–variance cardinality constrained portfolio optimization problem by considering a novel similarity measure, which compares the cardinality constrained frontier with the unconstrained mean–variance frontier. We assume that the closer the cardinality constrained frontier to the mean–variance frontier, the more appealing it is for the decision maker. This makes the assets included in the portfolio invariant to any specific level of return, through focusing not on the optimal portfolio but on the optimal frontier.

ACS Style

Francisco Guijarro. A similarity measure for the cardinality constrained frontier in the mean–variance optimization model. Journal of the Operational Research Society 2018, 69, 928 -945.

AMA Style

Francisco Guijarro. A similarity measure for the cardinality constrained frontier in the mean–variance optimization model. Journal of the Operational Research Society. 2018; 69 (6):928-945.

Chicago/Turabian Style

Francisco Guijarro. 2018. "A similarity measure for the cardinality constrained frontier in the mean–variance optimization model." Journal of the Operational Research Society 69, no. 6: 928-945.