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Bulgarian Health System Cost Assessment Methods Application for the Decision 'Make or Buy' 保加利亚卫生系统成本评估方法在“做还是买”决策中的应用
ERN: Other Econometrics: Econometric & Statistical Methods - Special Topics (Topic) Pub Date : 2020-01-20 DOI: 10.18769/ijasos.616022
V. Terziev, Stoyanka Petkova-Georgieva
{"title":"Bulgarian Health System Cost Assessment Methods Application for the Decision 'Make or Buy'","authors":"V. Terziev, Stoyanka Petkova-Georgieva","doi":"10.18769/ijasos.616022","DOIUrl":"https://doi.org/10.18769/ijasos.616022","url":null,"abstract":"The application of cost assessment methods for the decision “make or buy” is very useful for the private enterprises and this can be traced by the published scientific experimental evidences about the future benefits. The subject, focused of the present research is to investigate whether it is appropriate for the Bulgarian health system cost assessment methods to be used. Most of the Bulgarian hospitals are not private and this is a challenge for the health mangers to lead the hospital on profit even if the financing is a mixed public-private and the regulatory issues do not allow them to take the decision “make or buy” on their own. The most important analyzed result is the impact of the decision “make or buy” on different kinds of costs that are common at the hospital activities. The present publication consists with the results from the first part of the conducted research.","PeriodicalId":239853,"journal":{"name":"ERN: Other Econometrics: Econometric & Statistical Methods - Special Topics (Topic)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115948844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Uncertainty Measures from Partially Rounded Probabilistic Forecast Surveys 部分四舍五入概率预测调查的不确定性度量
ERN: Other Econometrics: Econometric & Statistical Methods - Special Topics (Topic) Pub Date : 2020-01-13 DOI: 10.2139/ssrn.3522499
A. Glas, Matthias Hartmann
{"title":"Uncertainty Measures from Partially Rounded Probabilistic Forecast Surveys","authors":"A. Glas, Matthias Hartmann","doi":"10.2139/ssrn.3522499","DOIUrl":"https://doi.org/10.2139/ssrn.3522499","url":null,"abstract":"Although survey‐based point predictions have been found to outperform successful forecasting models, corresponding variance forecasts are frequently diagnosed as heavily distorted. Professional forecasters who report inconspicuously low ex ante variances often produce squared forecast errors that are much larger on average. In this paper, we document the novel stylized fact that this variance misalignment is related to the rounding behavior of survey participants. Rounding may reflect the fact that some survey participants employ a rather judgmental approach to forecasting as opposed to using a formal model. We use the distinct numerical accuracies of panelists' reported probabilities as a way to propose several alternative and easily implementable corrections that (i) can be carried out in real time, that is, before outcomes are observed, and (ii) deliver a significantly improved match between ex ante and ex post forecast uncertainty. According to our estimates, uncertainty about inflation, output growth and unemployment in the U.S. and the Euro area is higher after correcting for the rounding effect. The increase in the share of nonrounded responses in recent years also helps to understand the trajectory of survey‐based average uncertainty during the years since the financial and sovereign debt crisis.","PeriodicalId":239853,"journal":{"name":"ERN: Other Econometrics: Econometric & Statistical Methods - Special Topics (Topic)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127131709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Can Machines 'Learn' Finance? 机器能“学习”金融吗?
ERN: Other Econometrics: Econometric & Statistical Methods - Special Topics (Topic) Pub Date : 2020-01-10 DOI: 10.2139/ssrn.3624052
Ronen Israel, B. Kelly, T. Moskowitz
{"title":"Can Machines 'Learn' Finance?","authors":"Ronen Israel, B. Kelly, T. Moskowitz","doi":"10.2139/ssrn.3624052","DOIUrl":"https://doi.org/10.2139/ssrn.3624052","url":null,"abstract":"Machine learning for asset management faces a unique set of challenges that differ markedly from other domains where machine learning has excelled. Understanding these differences is critical for developing impactful approaches and realistic expectations for machine learning in asset management. We discuss a variety of beneficial use cases and potential pitfalls, and emphasize the importance of economic theory and human expertise for achieving success through financial machine learning.","PeriodicalId":239853,"journal":{"name":"ERN: Other Econometrics: Econometric & Statistical Methods - Special Topics (Topic)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121995781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 24
Predicting Educational Loan Defaults: Application of Artificial Intelligence Models 预测教育贷款违约:人工智能模型的应用
ERN: Other Econometrics: Econometric & Statistical Methods - Special Topics (Topic) Pub Date : 2019-12-20 DOI: 10.2139/ssrn.3510012
M. Jayadev, Neel Shah, R. Vadlamani
{"title":"Predicting Educational Loan Defaults: Application of Artificial Intelligence Models","authors":"M. Jayadev, Neel Shah, R. Vadlamani","doi":"10.2139/ssrn.3510012","DOIUrl":"https://doi.org/10.2139/ssrn.3510012","url":null,"abstract":"We show that Educational loans is a case for application of artificial intelligence models to predict potential defaulters with a reasonable accuracy. Ensemble models tend to perform better than simple artificial techniques and statistical models and that the performance can be improved significantly by model stacking. We argue here that a stacked model created using a few sparsely correlated base models is likely to be the best model for predicting Educational loan defaults given that the interaction between diverse features would create non-linearities that are impossible to model using a single model, there is little a priori knowledge of the distribution of educational loan defaults and the relationships between various factors that govern the distribution. It is evident that collateral-free loans have a considerably higher rate of default with moral hazard problem as compared to the loans with collateral. Students qualifying from well rated educational institutions are prone to strategic default or wilful default. Considering the impact of macroeconomic conditions greatly improve the classification accuracies.","PeriodicalId":239853,"journal":{"name":"ERN: Other Econometrics: Econometric & Statistical Methods - Special Topics (Topic)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125594246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Do ‘Complex’ Financial Models Really Lead to Complex Dynamics? Agent-Based Models and Multifractality “复杂”的金融模型真的会导致复杂的动态吗?基于agent的模型和多重分形
ERN: Other Econometrics: Econometric & Statistical Methods - Special Topics (Topic) Pub Date : 2019-12-15 DOI: 10.2139/ssrn.3426341
J. Kukacka, L. Kristoufek
{"title":"Do ‘Complex’ Financial Models Really Lead to Complex Dynamics? Agent-Based Models and Multifractality","authors":"J. Kukacka, L. Kristoufek","doi":"10.2139/ssrn.3426341","DOIUrl":"https://doi.org/10.2139/ssrn.3426341","url":null,"abstract":"Agent-based models are usually claimed to generate complex dynamics; however, the link to such complexity has not been subject to rigorous examination. This paper studies this link between the complexity of financial time series—measured by their multifractal properties—and the design of various small-scale agent-based frameworks used to model the heterogeneity of financial markets. Nine popular models are analyzed, and while some of the models do not generate interesting multifractal patterns, we observe the strongest tendency towards multifractal behavior for the Bornholdt Ising model, the discrete choice-based models by Gaunersdorfer & Hommes and Schmitt & Westerhoff, and the transition probabilities-based framework by Franke & Westerhoff. Complexity is thus not an automatic feature of the time series generated by any agent-based model but generated only by models with specific properties. In addition, because multifractality is considered a financial stylized fact, its presence can be used as a new means to validate such models.","PeriodicalId":239853,"journal":{"name":"ERN: Other Econometrics: Econometric & Statistical Methods - Special Topics (Topic)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125618774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 42
The Equivalent Constant-Elasticity-of-Variance (CEV) Volatility of the Stochastic-Alpha-Beta-Rho (SABR) Model 随机- α - β - rho (SABR)模型的等效恒定弹性方差(CEV)波动率
ERN: Other Econometrics: Econometric & Statistical Methods - Special Topics (Topic) Pub Date : 2019-11-29 DOI: 10.2139/ssrn.3495464
Jaehyuk Choi, Lixin Wu
{"title":"The Equivalent Constant-Elasticity-of-Variance (CEV) Volatility of the Stochastic-Alpha-Beta-Rho (SABR) Model","authors":"Jaehyuk Choi, Lixin Wu","doi":"10.2139/ssrn.3495464","DOIUrl":"https://doi.org/10.2139/ssrn.3495464","url":null,"abstract":"This study presents new analytic approximations of the stochastic-alpha-beta-rho (SABR) model. Unlike existing studies that focus on the equivalent Black-Scholes (BS) volatility, we instead derive the equivalent volatility under the constant-elasticity-of-variance (CEV) model, which is the limit of the SABR model when the volatility of volatility approaches 0. Numerical examples demonstrate the accuracy of the CEV volatility approximation for a wide range of parameters. Moreover, in our approach, arbitrage occurs at a lower strike price than in existing BS-based approximations.","PeriodicalId":239853,"journal":{"name":"ERN: Other Econometrics: Econometric & Statistical Methods - Special Topics (Topic)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130271897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
A Comparison among Reinforcement Learning Algorithms in Financial Trading Systems 金融交易系统中强化学习算法的比较
ERN: Other Econometrics: Econometric & Statistical Methods - Special Topics (Topic) Pub Date : 2019-11-20 DOI: 10.2139/ssrn.3522712
M. Corazza, G. Fasano, R. Gusso, R. Pesenti
{"title":"A Comparison among Reinforcement Learning Algorithms in Financial Trading Systems","authors":"M. Corazza, G. Fasano, R. Gusso, R. Pesenti","doi":"10.2139/ssrn.3522712","DOIUrl":"https://doi.org/10.2139/ssrn.3522712","url":null,"abstract":"In this work we analyze and implement different Reinforcement Learning (RL) algorithms in financial trading system applications. RL-based algorithms applied to financial systems aim to find an optimal policy, that is an optimal mapping between the variables describing the state of the system and the actions available to an agent, by interacting with the system itself in order to maximize a cumulative return. In this contribution we compare the results obtained considering different on-policy (SARSA) and off-policy (Q-Learning, Greedy-GQ) RL algorithms applied to daily trading in the Italian stock market. We consider both computational issues related to the implementation of the algorithms, and issues originating from practical application to real stock markets, in an effort to improve previous results while keeping a simple and understandable structure of the used models.","PeriodicalId":239853,"journal":{"name":"ERN: Other Econometrics: Econometric & Statistical Methods - Special Topics (Topic)","volume":"238 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123039345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Application of Anti-Windup Phenomenon for an Estimator Design in A Multivariable System 反卷绕现象在多变量系统估计器设计中的应用
ERN: Other Econometrics: Econometric & Statistical Methods - Special Topics (Topic) Pub Date : 2019-11-19 DOI: 10.2139/ssrn.3489698
Piyali Das, R. Mehta, O. P. Roy
{"title":"Application of Anti-Windup Phenomenon for an Estimator Design in A Multivariable System","authors":"Piyali Das, R. Mehta, O. P. Roy","doi":"10.2139/ssrn.3489698","DOIUrl":"https://doi.org/10.2139/ssrn.3489698","url":null,"abstract":"Using an anti-windup property an illustrative example of multivariable system is provided here in this study. An estimator has been designed using the logic anti-windup, where proportional integral control law is applied to perform the analysis. Controlling a single input single output system is very simple but for a multivariable system controlling becomes complex. The estimator is activating the observer and using parameters unknown states of the plant estimated. Now using this control logic unwanted external disturbances also was mitigated using the anti-windup state observer based controller (AWC).","PeriodicalId":239853,"journal":{"name":"ERN: Other Econometrics: Econometric & Statistical Methods - Special Topics (Topic)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123424177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
The Macroeconomy and the Cross-Section of International Equity Index Returns: A Machine Learning Approach 宏观经济和国际股票指数回报的横截面:一种机器学习方法
ERN: Other Econometrics: Econometric & Statistical Methods - Special Topics (Topic) Pub Date : 2019-11-13 DOI: 10.2139/ssrn.3480042
Andreea Popescu
{"title":"The Macroeconomy and the Cross-Section of International Equity Index Returns: A Machine Learning Approach","authors":"Andreea Popescu","doi":"10.2139/ssrn.3480042","DOIUrl":"https://doi.org/10.2139/ssrn.3480042","url":null,"abstract":"The paper evaluates the out-of-sample predictive potential of machine learning methods in the cross-section of international equity index returns using firm fundamentals and macroeconomic predictors. The relatively small number of equity indices in the cross-section compared to the multitude of predictive signals, makes this an ideal setting to examine return predictability using machine learning techniques. I find that macroeconomic signals seem to substantially improve out-of-sample performance, especially when non-linear features are incorporated via neural networks. The performance of a long-short country bet based on forecasted returns cannot be explained by standard definitions of risk.","PeriodicalId":239853,"journal":{"name":"ERN: Other Econometrics: Econometric & Statistical Methods - Special Topics (Topic)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128490476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Combination Portfolio: A Cocktail Therapy for Training Portfolio Selection 组合投资组合:培训投资组合选择的鸡尾酒疗法
ERN: Other Econometrics: Econometric & Statistical Methods - Special Topics (Topic) Pub Date : 2019-10-25 DOI: 10.2139/ssrn.3448896
Tsungwu Ho
{"title":"Combination Portfolio: A Cocktail Therapy for Training Portfolio Selection","authors":"Tsungwu Ho","doi":"10.2139/ssrn.3448896","DOIUrl":"https://doi.org/10.2139/ssrn.3448896","url":null,"abstract":"The quantitative practice of portfolio selection aims to select the in-sample optimal portfolio that is robust out of sample. However, at each estimation period, the conventional method is selection by solving a given objective function, without a learning mechanism, or training. \u0000 \u0000This paper designs a method to train portfolio selection. Each optimal portfolio is a combination of three basic elements: strategy, covariance matrix, and risk type; therefore, like the cocktail therapy, we propose a selection method by first augmenting the combination to 250 optimal portfolios at each estimation period, and then we propose a score to select the best portfolio to hold in the next period. In the machine learning literature, combining multiple models together in some way has proven to be useful. Such combinations of models are sometimes called committees. We show that the combination portfolio exhibits superior performance and robustness, and the alternative way to train portfolio selection is useful.","PeriodicalId":239853,"journal":{"name":"ERN: Other Econometrics: Econometric & Statistical Methods - Special Topics (Topic)","volume":"194 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120898433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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