Pub Date : 2018-11-30DOI: 10.1080/0013791X.2019.1636439
L. Roebers, A. Selvi, Juan C. Vera
Abstract We introduce a solution scheme for portfolio optimization problems with cardinality constraints. Typical portfolio optimization problems are extensions of the classical Markowitz mean–variance portfolio optimization model. We solve such types of problems using a method similar to column generation. In this scheme, the original problem is restricted to a subset of the assets resulting in a master convex quadratic problem. Then the dual information of the master problem is used in a subproblem to propose more assets to consider. We also consider other extensions to the Markowitz model to diversify the portfolio selection within given intervals for active weights.
{"title":"Using column generation to solve extensions to the Markowitz model","authors":"L. Roebers, A. Selvi, Juan C. Vera","doi":"10.1080/0013791X.2019.1636439","DOIUrl":"https://doi.org/10.1080/0013791X.2019.1636439","url":null,"abstract":"Abstract We introduce a solution scheme for portfolio optimization problems with cardinality constraints. Typical portfolio optimization problems are extensions of the classical Markowitz mean–variance portfolio optimization model. We solve such types of problems using a method similar to column generation. In this scheme, the original problem is restricted to a subset of the assets resulting in a master convex quadratic problem. Then the dual information of the master problem is used in a subproblem to propose more assets to consider. We also consider other extensions to the Markowitz model to diversify the portfolio selection within given intervals for active weights.","PeriodicalId":49210,"journal":{"name":"Engineering Economist","volume":"64 1","pages":"275 - 288"},"PeriodicalIF":1.2,"publicationDate":"2018-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/0013791X.2019.1636439","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48255860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-10-02DOI: 10.1080/0013791x.2018.1537550
{"title":"Call for Wellington Award nominations","authors":"","doi":"10.1080/0013791x.2018.1537550","DOIUrl":"https://doi.org/10.1080/0013791x.2018.1537550","url":null,"abstract":"","PeriodicalId":49210,"journal":{"name":"Engineering Economist","volume":"63 1","pages":"382 - 382"},"PeriodicalIF":1.2,"publicationDate":"2018-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/0013791x.2018.1537550","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45193558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-07-09DOI: 10.1080/0013791X.2018.1468945
H. Sarper, P. Chacon, M. Demirtaş, Igor Melnykov, Gökçe Palak, Jane M. Fraser
ABSTRACT This article revisits a classic two-period engineering economy problem known as the oil pump problem and adds randomness to its cash flows one at a time. Conditional cumulative probability density functions of the internal and unconditional cumulative probability density functions of the external rates of return are reported. The analytical results are verified with Monte Carlo simulation. A procedure is proposed to assess project desirability by using the probability of project acceptance as the output. The cumulative distribution functions of both rates are used in numerical examples to illustrate how project desirability or acceptance probabilities can be calculated. It is shown that the distribution of the external rate of return yields the same probability of acceptance as the distribution of the internal rate of return. This article provides an up-to-date and exhaustive review of the literature on the distribution of the rate of return in stochastic investment problems. The review also shows that the oil pump problem is still popular and widely discussed.
{"title":"Distribution of the internal and external rates of return in a partially stochastic oil pump problem","authors":"H. Sarper, P. Chacon, M. Demirtaş, Igor Melnykov, Gökçe Palak, Jane M. Fraser","doi":"10.1080/0013791X.2018.1468945","DOIUrl":"https://doi.org/10.1080/0013791X.2018.1468945","url":null,"abstract":"ABSTRACT This article revisits a classic two-period engineering economy problem known as the oil pump problem and adds randomness to its cash flows one at a time. Conditional cumulative probability density functions of the internal and unconditional cumulative probability density functions of the external rates of return are reported. The analytical results are verified with Monte Carlo simulation. A procedure is proposed to assess project desirability by using the probability of project acceptance as the output. The cumulative distribution functions of both rates are used in numerical examples to illustrate how project desirability or acceptance probabilities can be calculated. It is shown that the distribution of the external rate of return yields the same probability of acceptance as the distribution of the internal rate of return. This article provides an up-to-date and exhaustive review of the literature on the distribution of the rate of return in stochastic investment problems. The review also shows that the oil pump problem is still popular and widely discussed.","PeriodicalId":49210,"journal":{"name":"Engineering Economist","volume":"63 1","pages":"343 - 362"},"PeriodicalIF":1.2,"publicationDate":"2018-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/0013791X.2018.1468945","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43666975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-11DOI: 10.1080/0013791X.2018.1461287
Youngmin Kim, D. Enke
ABSTRACT A challenge to developing data-driven approaches in finance and trading is the limited availability of data because periods of instability, such as during financial market crises, are relatively rare. This study applies a stability-oriented approach (SOA) based on statistical tests to compare data for the current period to a past set of data for a stable period, providing higher reliability due to a more abundant source of data. Based on an SOA, this study uses an artificial neural network (ANN), which is one of the commonly applied machine learning algorithms, for simultaneously forecasting the volatility and classifying the level of market stability. In addition, this study develops a dynamic target volatility strategy for asset allocation using an ANN to enhance the ability of a target volatility strategy that is established for automatically allocating capital between a risky asset and a risk-free cash position. In order to examine the impact of the proposed strategy, the results are compared to the buy-and-hold strategy, the static asset allocation strategy, and the conventional target volatility strategy using different volatility forecasting methodologies. An empirical case study of the proposed strategy is simulated in both the Korean and U.S. stock markets.
{"title":"A dynamic target volatility strategy for asset allocation using artificial neural networks","authors":"Youngmin Kim, D. Enke","doi":"10.1080/0013791X.2018.1461287","DOIUrl":"https://doi.org/10.1080/0013791X.2018.1461287","url":null,"abstract":"ABSTRACT A challenge to developing data-driven approaches in finance and trading is the limited availability of data because periods of instability, such as during financial market crises, are relatively rare. This study applies a stability-oriented approach (SOA) based on statistical tests to compare data for the current period to a past set of data for a stable period, providing higher reliability due to a more abundant source of data. Based on an SOA, this study uses an artificial neural network (ANN), which is one of the commonly applied machine learning algorithms, for simultaneously forecasting the volatility and classifying the level of market stability. In addition, this study develops a dynamic target volatility strategy for asset allocation using an ANN to enhance the ability of a target volatility strategy that is established for automatically allocating capital between a risky asset and a risk-free cash position. In order to examine the impact of the proposed strategy, the results are compared to the buy-and-hold strategy, the static asset allocation strategy, and the conventional target volatility strategy using different volatility forecasting methodologies. An empirical case study of the proposed strategy is simulated in both the Korean and U.S. stock markets.","PeriodicalId":49210,"journal":{"name":"Engineering Economist","volume":"63 1","pages":"273 - 290"},"PeriodicalIF":1.2,"publicationDate":"2018-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/0013791X.2018.1461287","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43852899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-11DOI: 10.1080/0013791X.2018.1467990
M. Sharifi, R. Kwon
ABSTRACT This article considers a principal agent model for structuring a performance-based contract in the presence of fixed cost and cost-plus contracts. A scenario-based bilevel programming approach is considered to determine the values of key contract parameters. Additionally, the risk of cost uncertainty is considered in the model in the form of conditional value at risk (CVaR). The incorporation of risk of cost uncertainty can mitigate the impact of extreme events in the tail of the customer's total cost distribution. The numerical results find that at higher risk aversion levels, the customer is willing to pay more to the supplier and at the same time accept a smaller percentage of the shared cost between the supplier and the customer, which indicates the shift of the risk to the supplier. Although the customer is paying more in higher risk aversion levels, less cost is incurred in cases of realization of extreme events compared to the lower risk aversion levels. At lower risk aversion levels, the customer sets a smaller value of incentives for the supplier.
{"title":"Performance-based contract design under cost uncertainty: A scenario-based bilevel programming approach","authors":"M. Sharifi, R. Kwon","doi":"10.1080/0013791X.2018.1467990","DOIUrl":"https://doi.org/10.1080/0013791X.2018.1467990","url":null,"abstract":"ABSTRACT This article considers a principal agent model for structuring a performance-based contract in the presence of fixed cost and cost-plus contracts. A scenario-based bilevel programming approach is considered to determine the values of key contract parameters. Additionally, the risk of cost uncertainty is considered in the model in the form of conditional value at risk (CVaR). The incorporation of risk of cost uncertainty can mitigate the impact of extreme events in the tail of the customer's total cost distribution. The numerical results find that at higher risk aversion levels, the customer is willing to pay more to the supplier and at the same time accept a smaller percentage of the shared cost between the supplier and the customer, which indicates the shift of the risk to the supplier. Although the customer is paying more in higher risk aversion levels, less cost is incurred in cases of realization of extreme events compared to the lower risk aversion levels. At lower risk aversion levels, the customer sets a smaller value of incentives for the supplier.","PeriodicalId":49210,"journal":{"name":"Engineering Economist","volume":"63 1","pages":"291 - 318"},"PeriodicalIF":1.2,"publicationDate":"2018-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/0013791X.2018.1467990","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43901631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-05-31DOI: 10.1080/0013791X.2018.1465619
T. Boucher
Abstract In this article, we study the use of the international standard for measuring the generosity of research and development tax subsidies, the B-index, as a predictor of the effectiveness of a subsidy. We find a close relationship, with some modifications of the B-index required. We demonstrate how a synthesis of the B-index and a structural model of a firm's wealth-maximizing behavior can be used to evaluate policy proposals regarding modifications to the research and development tax credit.
{"title":"On the generosity and effectiveness of the research and development tax credit","authors":"T. Boucher","doi":"10.1080/0013791X.2018.1465619","DOIUrl":"https://doi.org/10.1080/0013791X.2018.1465619","url":null,"abstract":"Abstract In this article, we study the use of the international standard for measuring the generosity of research and development tax subsidies, the B-index, as a predictor of the effectiveness of a subsidy. We find a close relationship, with some modifications of the B-index required. We demonstrate how a synthesis of the B-index and a structural model of a firm's wealth-maximizing behavior can be used to evaluate policy proposals regarding modifications to the research and development tax credit.","PeriodicalId":49210,"journal":{"name":"Engineering Economist","volume":"63 1","pages":"319 - 342"},"PeriodicalIF":1.2,"publicationDate":"2018-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/0013791X.2018.1465619","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43102014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-05-31DOI: 10.1080/0013791X.2018.1456596
Francisco Salas-Molina, J. Rodríguez-Aguilar, D. Plà-Santamaria
ABSTRACT Cash management models are usually based on a set of bounds that complicate the selection of the optimal policies due to nonlinearity. We here propose to linearize cash management models to guarantee optimality through linear-quadratic multiobjective compromise programming models. We illustrate our approach through a reformulation of the suboptimal state-of-the-art Gormley-Meade’s model to achieve optimality. Furthermore, we introduce a much simpler formulation that we call the boundless model that also provides optimal solutions without using bounds. Results from a sensitivity analysis using real data sets from 54 different companies show that our boundless model is highly robust to cash flow prediction errors.
{"title":"Boundless multiobjective models for cash management","authors":"Francisco Salas-Molina, J. Rodríguez-Aguilar, D. Plà-Santamaria","doi":"10.1080/0013791X.2018.1456596","DOIUrl":"https://doi.org/10.1080/0013791X.2018.1456596","url":null,"abstract":"ABSTRACT Cash management models are usually based on a set of bounds that complicate the selection of the optimal policies due to nonlinearity. We here propose to linearize cash management models to guarantee optimality through linear-quadratic multiobjective compromise programming models. We illustrate our approach through a reformulation of the suboptimal state-of-the-art Gormley-Meade’s model to achieve optimality. Furthermore, we introduce a much simpler formulation that we call the boundless model that also provides optimal solutions without using bounds. Results from a sensitivity analysis using real data sets from 54 different companies show that our boundless model is highly robust to cash flow prediction errors.","PeriodicalId":49210,"journal":{"name":"Engineering Economist","volume":"63 1","pages":"363 - 381"},"PeriodicalIF":1.2,"publicationDate":"2018-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/0013791X.2018.1456596","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48207437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-06DOI: 10.1080/0013791X.2017.1414342
Miguel Rodríguez García, Pablo Domínguez Caamaño, José Antonio Comesaña Benavides, J. C. Prado-Prado
ABSTRACT Owner operator truck drivers have been dealing with a long-standing problem: compensation per distance. Owner operators who get paid according to these criteria get a fixed payment per distance traveled regardless of how long it takes to actually cover the distance. This means that there are numerous situations that truck drivers are working; yet they might be unpaid because the truck is not moving. To compensate for the unfairness of the pay rate models, owner operators have continuously increased their working hours. In addition, many studies have confirmed that a fair payment is among the most important factors that truck drivers take into consideration when deciding to leave a company. Consequently, an unfair pay rate, along with the hard labor conditions truck drivers suffer from, inevitably leads to high turnover rates. For all these reasons, our study aims at developing a fair, financially sustainable pay rate for owner operators that will help companies ensure a stable and highly experienced workforce by making sure that owner operators can cover the real expenses of their working activity. Finally, in order to prove that our pay rate was of practical use, we test the model on one of the largest Spanish agro-food companies.
{"title":"Designing a fair, financially sustainable pay rate for owner-operator truck drivers. Modeling and case study","authors":"Miguel Rodríguez García, Pablo Domínguez Caamaño, José Antonio Comesaña Benavides, J. C. Prado-Prado","doi":"10.1080/0013791X.2017.1414342","DOIUrl":"https://doi.org/10.1080/0013791X.2017.1414342","url":null,"abstract":"ABSTRACT Owner operator truck drivers have been dealing with a long-standing problem: compensation per distance. Owner operators who get paid according to these criteria get a fixed payment per distance traveled regardless of how long it takes to actually cover the distance. This means that there are numerous situations that truck drivers are working; yet they might be unpaid because the truck is not moving. To compensate for the unfairness of the pay rate models, owner operators have continuously increased their working hours. In addition, many studies have confirmed that a fair payment is among the most important factors that truck drivers take into consideration when deciding to leave a company. Consequently, an unfair pay rate, along with the hard labor conditions truck drivers suffer from, inevitably leads to high turnover rates. For all these reasons, our study aims at developing a fair, financially sustainable pay rate for owner operators that will help companies ensure a stable and highly experienced workforce by making sure that owner operators can cover the real expenses of their working activity. Finally, in order to prove that our pay rate was of practical use, we test the model on one of the largest Spanish agro-food companies.","PeriodicalId":49210,"journal":{"name":"Engineering Economist","volume":"63 1","pages":"250 - 272"},"PeriodicalIF":1.2,"publicationDate":"2018-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/0013791X.2017.1414342","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45104561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-01-05DOI: 10.1080/0013791X.2017.1413150
Mathieu Sauvageau, M. Kumral
ABSTRACT Mining projects are subject to multiple sources of market uncertainties such as metal price, exchange rates, and their volatilities. Assessing a mining project's exposure to market risk usually requires Monte Carlo simulations to capture a range of probable outcomes. The probability of a major loss is extracted from the probability density function of simulated prices at a given time into the future. This article proposes an approach to calibrate the stochastic process to be used in Monte Carlo simulations. The simulations are then used for measuring the cash flow at risk of a mining project. To assess the performance of the proposed approach, a case study is conducted on a mining project. The results show that the calibration approach is robust and apt at fitting various stochastic processes to historical observations.
{"title":"Cash flow at risk valuation of mining project using Monte Carlo simulations with stochastic processes calibrated on historical data","authors":"Mathieu Sauvageau, M. Kumral","doi":"10.1080/0013791X.2017.1413150","DOIUrl":"https://doi.org/10.1080/0013791X.2017.1413150","url":null,"abstract":"ABSTRACT Mining projects are subject to multiple sources of market uncertainties such as metal price, exchange rates, and their volatilities. Assessing a mining project's exposure to market risk usually requires Monte Carlo simulations to capture a range of probable outcomes. The probability of a major loss is extracted from the probability density function of simulated prices at a given time into the future. This article proposes an approach to calibrate the stochastic process to be used in Monte Carlo simulations. The simulations are then used for measuring the cash flow at risk of a mining project. To assess the performance of the proposed approach, a case study is conducted on a mining project. The results show that the calibration approach is robust and apt at fitting various stochastic processes to historical observations.","PeriodicalId":49210,"journal":{"name":"Engineering Economist","volume":"63 1","pages":"171 - 187"},"PeriodicalIF":1.2,"publicationDate":"2018-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/0013791X.2017.1413150","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47692822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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