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Articoli di riviste sul tema "Asset-based model"

Autore: Grafiati

Pubblicato: 4 giugno 2021

Ultima modifica: 20 febbraio 2023

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1

Gomes, Luiz Flavio Autran Monteiro, Luís Alberto Duncan Rangel, and Gisele Dos Santos. "An AHP-based asset allocation model." International Journal of Business and Systems Research 10, no. 1 (2016): 78. http://dx.doi.org/10.1504/ijbsr.2016.073693.

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2

Kampert, David, Ulrich Epple, and Martin Mertens. "Model-Based Management of Asset Information." Softwaretechnik-Trends 32, no. 2 (May 2012): 84–85. http://dx.doi.org/10.1007/bf03323492.

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3

Qin, Jie. "Regret-based capital asset pricing model." Journal of Banking & Finance 114 (May 2020): 105784. http://dx.doi.org/10.1016/j.jbankfin.2020.105784.

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4

McLean, Robert A. "LAPM: A Liquidity-Based Asset Pricing Model." CFA Digest 32, no. 2 (May 2002): 69–70. http://dx.doi.org/10.2469/dig.v32.n2.1078.

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5

Duffie, Darrell, and William Zame. "The Consumption-Based Capital Asset Pricing Model." Econometrica 57, no. 6 (November 1989): 1279. http://dx.doi.org/10.2307/1913708.

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6

Holmström, Bengt, and Jean Tirole. "LAPM: A Liquidity-Based Asset Pricing Model." Journal of Finance 56, no. 5 (October 2001): 1837–67. http://dx.doi.org/10.1111/0022-1082.00391.

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7

Arroyo, Cristino R. "TESTING A PRODUCTION-BASED ASSET-PRICING MODEL." Economic Inquiry 34, no. 2 (April 1996): 357–77. http://dx.doi.org/10.1111/j.1465-7295.1996.tb01382.x.

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8

North, Reiner. "Fuzzy-Logic-Based Asset Allocation." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 27, no. 03 (May 29, 2019): 483–512. http://dx.doi.org/10.1142/s0218488519500223.

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This paper provides an introduction to how, on the basis of concepts from fuzzy logic, a model of asset allocation can be constructed which can represent and aggregate all the relevant quantitative and qualitative features of an investment plan realistically and in this way attains comparatively good recommendations like an expert. All calculation steps are carried out in a transparent and reproducible manner. In order to clarify the approach and the advantages of the procedure, a pilot model is developed. This supports the advisor with the asset allocation, by first analysing the features of the investment goal and the market expectations and then evaluating the merits of several investment strategies as well as displaying the steps towards their evaluation in a comprehensible manner. Based on case studies, the results of the pilot model are compared with known good recommendations from an investigation of Stiftung Warentest on the quality of advice in banks.

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9

Delikouras, Stefanos, and Alexandros Kostakis. "A Single-Factor Consumption-Based Asset Pricing Model." Journal of Financial and Quantitative Analysis 54, no. 2 (September 14, 2018): 789–827. http://dx.doi.org/10.1017/s0022109018000819.

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We propose a single-factor asset pricing model based on an indicator function of consumption growth being less than its endogenous certainty equivalent. This certainty equivalent is derived from generalized disappointment-aversion preferences, and it is located approximately 1 standard deviation below the conditional mean of consumption growth. Our single-factor model can explain the cross section of expected returns for size, value, reversal, profitability, and investment portfolios at least as well as the Fama–French multifactor models. Our results show strong empirical support for asymmetric preferences and question the effectiveness of the smooth utility framework, which is traditionally used in consumption-based asset pricing.

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Yan, Yu, and Yiming Wang. "Asset Pricing Model Based on Fractional Brownian Motion." Fractal and Fractional 6, no. 2 (February 11, 2022): 99. http://dx.doi.org/10.3390/fractalfract6020099.

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This paper introduces one unique price motion process with fractional Brownian motion. We introduce the imaginary number into the agent’s subjective probability for the reason of convergence; further, the result similar to Ito Lemma is proved. As an application, this result is applied to Merton’s dynamic asset pricing framework. We find that the four order moment of fractional Brownian motion is entered into the agent’s decision-making. The decomposition of variance of economic indexes supports the possibility of the complex number in price movement.

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11

Jarrow, Robert A., Philip Protter, and Alexandre F. Roch. "A liquidity-based model for asset price bubbles." Quantitative Finance 12, no. 9 (September 2012): 1339–49. http://dx.doi.org/10.1080/14697688.2011.620976.

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12

Djordjevic, Marija. "Consumption-based macroeconomic models of asset pricing theory." Ekonomski anali 61, no. 211 (2016): 7–28. http://dx.doi.org/10.2298/eka1611007d.

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The family of consumptionbased asset pricing models yields a stochastic discount factor proportional to the marginal rate of intertemporal substitution of consumption. In examining the empirical performance of this class of models, several puzzles are discovered. In this literature review we present the canonical model, the corresponding empirical tests, and different extensions to this model that propose a resolution of these puzzles.

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13

Ayub, Usman, Samaila Kausar, Umara Noreen, Muhammad Zakaria, and Imran Abbas Jadoon. "Downside Risk-Based Six-Factor Capital Asset Pricing Model (CAPM): A New Paradigm in Asset Pricing." Sustainability 12, no. 17 (August 20, 2020): 6756. http://dx.doi.org/10.3390/su12176756.

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The importance of downside risk cannot be denied. In this study, we have replaced beta in the five-factor model of using downside beta and have added a momentum factor to suggest a new six-factor downside beta capital asset pricing model (CAPM). Two models are tested—a beta- and momentum-based six-factor model and a downside-beta- (proxy of downside risk) and momentum-based six-factor model. Beta and downside beta are highly correlated; therefore, portfolios are double-sorted to disentangle the correlation. Factor loadings, i.e., size, value, momentum, profitability, and investment, are constructed. The standard methodologies are applied. Data for sample stocks from different non-financial sectors listed in the Pakistan Stock Exchange (PSX) are taken from January 2000 to December 2018. The PSX-100 index and three-month T-bills are taken as proxies for market and risk-free returns. The study uses three subsamples for robustness—period of very high volatility, period of stability, and period of stability and growth with volatility. The results show that the value factor is redundant in both models. The momentum factor is rejected in the beta-based six-factor model only. The beta-based six-factor model shows very low R2 in periods of highly volatility. The R2 is high for the other periods. In contrast, the downside beta six-factor model captures the downside trend of the market in an effective manner with a relatively high R2. The risk–return relationship is stronger for the downside beta model. These reasons lead us to believe that, overall, the downside beta six-factor model is a better option for investors as compared to the beta-based six-factor model in the area of asset pricing models.

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14

Martino, A. Martino, and Giovanni W. Puopolo. "Factors-based Asset Pricing Models: a literature review." International Journal of Finance 7, no. 4 (September 19, 2022): 37–53. http://dx.doi.org/10.47941/ijf.1034.

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In this paper we provide a literature review of the main factors-based asset pricing models, focusing in particular on factors related to firm characteristics. After presenting the Capital Asset Pricing Model, we describe first the most important empirical evidence that led to the well-known Fama-French three-factors model. Next, we highlight the most widely used multi-factors pricing models based on momentum, liquidity, investment and profitability, also outside the U.S. Finally, we discuss the ability of firm characteristics to predict the behavior of future stock returns.

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15

BRODY, DORJE C., LANE P. HUGHSTON, and ANDREA MACRINA. "INFORMATION-BASED ASSET PRICING." International Journal of Theoretical and Applied Finance 11, no. 01 (February 2008): 107–42. http://dx.doi.org/10.1142/s0219024908004749.

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A new framework for asset price dynamics is introduced in which the concept of noisy information about future cash flows is used to derive the corresponding price processes. In this framework an asset is defined by its cash-flow structure. Each cash flow is modelled by a random variable that can be expressed as a function of a collection of independent random variables called market factors. With each such "X-factor" we associate a market information process, the values of which we assume are accessible to market participants. Each information process consists of a sum of two terms; one contains true information about the value of the associated market factor, and the other represents "noise". The noise term is modelled by an independent Brownian bridge that spans the interval from the present to the time at which the value of the factor is revealed. The market filtration is assumed to be that generated by the aggregate of the independent information processes. The price of an asset is given by the expectation of the discounted cash flows in the risk-neutral measure, conditional on the information provided by the market filtration. In the case where the cash flows are the dividend payments associated with equities, an explicit model is obtained for the share-price process. Dividend growth is taken into account by introducing appropriate structure on the market factors. The prices of options on dividend-paying assets are derived. Remarkably, the resulting formula for the price of a European-style call option is of the Black–Scholes–Merton type. We consider the case where the rate at which information is revealed to the market is constant, and the case where the information rate varies in time. Option pricing formulae are obtained for both cases. The information-based framework generates a natural explanation for the origin of stochastic volatility in financial markets, without the need for specifying on an ad hoc basis the dynamics of the volatility.

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16

Chen, Long, Xiang Xie, Qiuchen Lu, Ajith Kumar Parlikad, Michael Pitt, and Jian Yang. "Gemini Principles-Based Digital Twin Maturity Model for Asset Management." Sustainability 13, no. 15 (July 23, 2021): 8224. http://dx.doi.org/10.3390/su13158224.

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Various maturity models have been developed for understanding the diffusion and implementation of new technologies/approaches. However, we find that existing maturity models fail to understand the implementation of emerging digital twin technique comprehensively and quantitatively. This research aims to develop an innovative maturity model for measuring digital twin maturity for asset management. This model is established based on Gemini Principles to form a systematic view of digital twin development and implementation. Within this maturity model, three main dimensions consisting of nine sub-dimensions have been defined firstly, which were further articulated by 27 rubrics. Then, a questionnaire survey with 40 experts involved is designed and conducted to examine these rubrics. This model is finally illustrated and validated by two case studies in Shanghai and Cambridge. The results show that the digital twin maturity model is effective to qualitatively evaluate and compare the maturity of digital twin implementation at the project level. It can also initiate the roadmap for improving the performance of digital twin supported asset management.

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17

Liu, Yutong, and Peiyi Song. "An Intelligent Digital Media Asset Management Model Based on Business Ecosystem." Computational Intelligence and Neuroscience 2022 (May 13, 2022): 1–14. http://dx.doi.org/10.1155/2022/1190538.

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In the context of media convergence, it is of great significance to study and discuss the intelligent digital media asset management model and build a digital media asset management ecosystem model to carry out effective digital media asset management for media organizations and promote the value creation of digital media content assets. Based on the business ecosystem, this study adopts a system dynamics approach to construct a system dynamics model through theoretical research and simulation analysis. By studying the positioning of intelligent digital media asset management and service patterns, the basic framework of digital media asset management ecosystems is proposed. To explore the interaction between different factors, the system dynamics model of value creation in digital media asset management ecosystems is built in this paper. This study provides new insights for media organizations on building an intelligent digital media asset management model and promoting the development and utilization of media content resources.

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18

Modgil, Puneet, and M. Syamala Devi. "Ontology-Based Research Asset Management Model for Academic Environment." SRELS Journal of Information Management 57, no. 1 (February 29, 2020): 17. http://dx.doi.org/10.17821/srels/2020/v57i1/146800.

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19

Grossman, S. J., A. Melino, and R. J. Shiller. "Estimating the Continuous-Time Consumption-Based Asset-Pricing Model." Journal of Business & Economic Statistics 5, no. 3 (July 1987): 315. http://dx.doi.org/10.2307/1391605.

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20

Pruna, Radu T., Maria Polukarov, and Nicholas R. Jennings. "Loss aversion in an agent-based asset pricing model." Quantitative Finance 20, no. 2 (November 1, 2019): 275–90. http://dx.doi.org/10.1080/14697688.2019.1655784.

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21

Ren, Haiying, and Siwei Li. "A Heterogeneous Agent-based Asset Pricing Model and Simulation." International Journal of Engineering and Manufacturing 2, no. 4 (August 29, 2012): 9–18. http://dx.doi.org/10.5815/ijem.2012.04.02.

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22

Grossman, S. J., A. Melino, and R. J. Shiller. "Estimating the Continuous-Time Consumption-Based Asset-Pricing Model." Journal of Business & Economic Statistics 5, no. 3 (July 1987): 315–27. http://dx.doi.org/10.1080/07350015.1987.10509594.

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23

Ikamari, Cynthia, Philip Ngare, and Patrick Weke. "Multi-asset option pricing using an information-based model." Scientific African 10 (November 2020): e00564. http://dx.doi.org/10.1016/j.sciaf.2020.e00564.

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24

Evans, Paul, and Iftekhar Hasan. "The consumption-based capital asset pricing model: International evidence." Journal of Multinational Financial Management 8, no. 1 (January 1998): 1–21. http://dx.doi.org/10.1016/s1042-444x(98)00014-0.

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25

He, Zhongzhi (Lawrence), and Lawrence Kryzanowski. "A reformulated asset pricing model based on contrarian strategies." Studies in Economics and Finance 23, no. 3 (October 2006): 185–201. http://dx.doi.org/10.1108/10867370610711039.

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26

Pruna, Radu T., Maria Polukarov, and Nicholas R. Jennings. "Avoiding regret in an agent-based asset pricing model." Finance Research Letters 24 (March 2018): 273–77. http://dx.doi.org/10.1016/j.frl.2017.09.014.

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27

Wheatley, Simon. "Some tests of the consumption-based asset pricing model." Journal of Monetary Economics 22, no. 2 (September 1988): 193–215. http://dx.doi.org/10.1016/0304-3932(88)90019-0.

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28

Sahuc, Jean-Guillaume. "The ECB’s asset purchase programme: A model-based evaluation." Economics Letters 145 (August 2016): 136–40. http://dx.doi.org/10.1016/j.econlet.2016.06.009.

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29

Panov, Vladimir, and Evgenii Samarin. "Multivariate asset‐pricing model based on subordinated stable processes." Applied Stochastic Models in Business and Industry 35, no. 4 (March 21, 2019): 1060–76. http://dx.doi.org/10.1002/asmb.2446.

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30

Salem, Dalia, and Emad Elwakil. "Expert-based approach to rank critical asset assessment factors for healthcare facilities." Facilities 39, no. 9/10 (January 25, 2021): 615–34. http://dx.doi.org/10.1108/f-05-2020-0060.

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Purpose This research’s main objective is to develop an expert-based approach to rank critical asset assessment factors for health-care facilities. This approach will improve the asset management of health-care buildings. This paper aims to study and prioritize the relative importance of asset criticality factors. Design/methodology/approach The research methodology begins with a comprehensive literature review of state-of-the-art health-care facilities management, asset management tools, critical asset assessment and approaches to model techniques. Then, using the expert-based opinion and the collected data through the analytical hierarchy process approach to developing the asset assessment model contains physical, environmental, general safety and revenue loss assessment models. Findings Results showed that the general safety factors and the sub-factors of life safety and physical safety contributed to asset condition assessment. Practical implications The proposed critical asset assessment ranking will benefit health-care facility organizations by assessing their asset performance according to capital renewal needs. Originality/value This study offers a novel conceptual framework to understand and determine rank critical asset assessment factors for health-care facilities.

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Nasir, A. A. M., S. Azri, U. Ujang, and Z. Majid. "CONCEPTUAL MODEL OF 3D ASSET MANAGEMENT BASED ON MYSPATA TO SUPPORT SMART CITY APPLICATION IN MALAYSIA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIV-4/W3-2020 (November 23, 2020): 313–22. http://dx.doi.org/10.5194/isprs-archives-xliv-4-w3-2020-313-2020.

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Abstract. Urbanization is the access to modernization and development around the world. Nowadays, with the current technology development, smart cities are seen as a new approach in urban management and development. 3D asset management is one of the components to support the idea of smart city. 3D asset management is important to assist the monitoring and maintenance of asset in smart city by enabling visualization of 3D models, locating and query in real-time based. In Malaysia, the government is looking seriously at the issues of asset management and maintenance. This is happened because asset management in present day is already moving towards the revolution of smart city but still considered as time consuming and open to human errors as the asset managers or authorities still considering on paper-dependent and manual inspection practise. In the past few years, Malaysia has developing an electronic-based asset management, MySPATA that is made prior to the inefficiency on the asset management system. MySPATA has been introduced as electronic based asset management solution for immovable assets that belong to various department and ministries. However, the creation of MySPATA is considered as bland and time-consuming as its application only storing and displaying asset information. Thus, the implementation of 3D asset management is required for a better and effective management. In this paper, we proposed the conceptual model of 3D asset management by incorporating with the new CityGML standard. The proposed 3D asset management is based on MySPATA module. CityGML plays an important role in demonstrating the 3D asset management for modelling, string and exchanging city models in the international standard. So, the 3D asset management is developed based on MySPATA module that integrated with new CityGML concept. Therefore, with this new approach and concept, the managing of assets will lead for better management and maintenance.

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32

Liu, Yanyu. "Broad Asset Portfolio Designed Based on the Mean-Variance Model." BCP Business & Management 26 (September 19, 2022): 714–23. http://dx.doi.org/10.54691/bcpbm.v26i.2031.

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Contemporarily, broad asset class allocation has gradually become an ideal investment strategy for investors and institutions. This paper constructs the optimal asset class allocation and portfolio design with python based on the mean-variance model, using stocks, gold, crude oil, bonds, futures, foreign exchange, funds, commodities, digital currencies and treasury bonds as the main underlying assets. To compare the asset allocation portfolios constructed by different approaches (the equally weighted investment model, the minimum variance model and the maximum Sharpe ratio model), the comparative analysis is implemented in terms of five indicators, including the annualised return, annualised volatility, Sharpe ratio, maximum drawdown and return-to-drawdown ratio. After the comparison, the advantages of the maximum Sharpe ratio model are demonstrated. According to the results, the mean-variance model, as a risk management model from the investor’s perspective, is consistent with the investment logic of investors and financial institutions that it outperforms the traditional minimum variance model and equally weighted model in terms of profitability and risk control. Therefore, the mean-variance model has certain theoretical guidance for broad asset class allocation. Overall, these results shed light on portfolio designed for investments.

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Hanachor, M. E., and E. N. Wordu. "DEVELOPING A MODEL FOR PROMOTING ASSET BASED COMMUNITY DEVELOPMENT (ABCD) IN NIGERIA." International Journal of Research -GRANTHAALAYAH 9, no. 4 (May 8, 2021): 522–28. http://dx.doi.org/10.29121/granthaalayah.v9.i4.2021.3881.

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Asset based community development (ABCD) is a shift and direct contrast to the conversional need-based community development (NBD). It focuses on community asset as useful tool to stir up the development of a community. It is concerned with what is available in the community that could be used to development as against dependence on outsiders or expert for development. The different types of asset in communities were enumerated. The benefits and criticisms against the approach were also highlighted. A model to guide the application of the approach was designed. The paper is of the view that every development intervention in the nation should have its root on asset-based development approach.

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Zhang, Mingyuan. "Time Series Artificial Neural Network based Classification Model for Asset Trading Strategy." Highlights in Business, Economics and Management 1 (November 28, 2022): 214–33. http://dx.doi.org/10.54097/hbem.v1i.2565.

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Best daily trading strategy is meaningful to investors to obtain the maximum return. Financial market plays a key role in the social development. Sufficient funds are of great significance to promote the development of all sectors of society. From the perspective of investors, their purpose is to obtain the maximum income through investing assets in the market. At the same time, the benefit of investors can attract more investors and funds. However, there are huge risks in investment in financial markets. This is mainly because the changes of assets' prices are very complex, and traders cannot predict the changes of assets' prices. Therefore, it is of great significance for investors to determine the trading behavior according to the historical data of asset's price. Aiming at the problem of asset investment strategy, we study from three aspects: asset value accounting, optimal investment strategy and investment decision prediction. A novel method is proposed to represent trading action based on asset state, which represents the current asset state through a 0-1 variable. Then, the change of state indicates the occurrence of transaction. Based on this variable, we propose an evaluation model of the total value of the asset on every day. By maximizing the value of the combination, we establish an optimization model and the Genetic Algorithm (GA) is used to search the best investment combination. Using the prior information of the price, we first solve the combination of asset states of the investor corresponding to the best trading strategy. Then, taking the sequence of states as the supervision information, an Artificial Neural Network (ANN) based classification model for asset state prediction is established. The historical data of Bitcoin daily price is used to predict the asset state on the current day, to realize the decision-making of daily trading strategy. Extensive experiments have been conducted, and the experimental results verify our model can effectively find potential pattern for asset investment and achieve good profits based on the predict investment decisions.

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Kruttli, Mathias S. "From Which Consumption-Based Asset Pricing Models Can Investors Profit? Evidence from Model-Based Priors." Finance and Economics Discussion Series 2016, no. 27 (April 2016): 1–51. http://dx.doi.org/10.17016/feds.2016.027.

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36

Korbel, Jakob J., Umar H. Siddiq, and Rüdiger Zarnekow. "Towards Virtual 3D Asset Price Prediction Based on Machine Learning." Journal of Theoretical and Applied Electronic Commerce Research 17, no. 3 (July 7, 2022): 924–48. http://dx.doi.org/10.3390/jtaer17030048.

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Although 3D models are today indispensable in various industries, the adequate pricing of 3D models traded on online platforms, i.e., virtual 3D assets, remains vague. This study identifies relevant price determinants of virtual 3D assets through the analysis of a dataset containing the characteristics of 135.384 3D models. Machine learning algorithms were applied to derive a virtual 3D asset price prediction tool based on the analysis results. The evaluation revealed that the random forest regression model is the most promising model to predict virtual 3D asset prices. Furthermore, the findings imply that the geometry and number of material files, as well as the quality of textures, are the most relevant price determinants, whereas animations and file formats play a minor role. However, the analysis also showed that the pricing behavior is still substantially influenced by the subjective assessment of virtual 3D asset creators.

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Cavalieri, Salvatore, and Marco Giuseppe Salafia. "A Model for Predictive Maintenance Based on Asset Administration Shell." Sensors 20, no. 21 (October 23, 2020): 6028. http://dx.doi.org/10.3390/s20216028.

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Maintenance is one of the most important aspects in industrial and production environments. Predictive maintenance is an approach that aims to schedule maintenance tasks based on historical data in order to avoid machine failures and reduce the costs due to unnecessary maintenance actions. Approaches for the implementation of a maintenance solution often differ depending on the kind of data to be analyzed and on the techniques and models adopted for the failure forecasts and for maintenance decision-making. Nowadays, Industry 4.0 introduces a flexible and adaptable manufacturing concept to satisfy a market requiring an increasing demand for customization. The adoption of vendor-specific solutions for predictive maintenance and the heterogeneity of technologies adopted in the brownfield for the condition monitoring of machinery reduce the flexibility and interoperability required by Industry 4.0. In this paper a novel approach for the definition of a generic and technology-independent model for predictive maintenance is presented. Such model leverages on the concept of the Reference Architecture Model for Industry (RAMI) 4.0 Asset Administration Shell, as a means to achieve interoperability between different devices and to implement generic functionalities for predictive maintenance.

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Ma, Haoran. "Research on Financial Asset Allocation Based on Mathematical Programming Model." Frontiers in Business, Economics and Management 6, no. 2 (November 16, 2022): 106–9. http://dx.doi.org/10.54097/fbem.v6i2.2818.

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With the increase of the total amount of family finance and the continuous enrichment of the types of family financial assets, the awareness of family financial management is increasingly strengthened, and people's understanding of family financial assets and their choice behavior begin to change. Financial asset investment has been deeply involved in people's social business activities, especially commercial banks, investment institutions, foundations, etc., which must participate in the investment and management of valuable financial assets at home and abroad. If investors want to reduce the risk of assets without losing profits, they need to diversify their investments and allocate assets effectively. For specific family financial products, some situations often occur in the process of combination, for example, the specific share of insurance assets is gradually increasing, while the share of cash and savings deposits is gradually decreasing. In this paper, the dominant principle of investment strategy is established, and the mathematical programming model of financial asset allocation is established. On this basis, the method of selecting the optimal financial asset portfolio is put forward.

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Passath, Theresa, Cornelia Huber, Linus Kohl, Hubert Biedermann, and Fazel Ansari. "A Knowledge-Based Digital Lifecycle-Oriented Asset Optimisation." Tehnički glasnik 15, no. 2 (June 9, 2021): 226–334. http://dx.doi.org/10.31803/tg-20210504111400.

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The digitalisation of the value chain promotes sophisticated virtual product models known as digital twins (DT) in all asset-life-cycle (ALC) phases. These models. however, fail on representing the entire phases of asset-life-cycle (ALC), and do not allow continuous life-cycle-costing (LCC). Hence, energy efficiency and resource optimisation across the entire circular value chain is neglected. This paper demonstrates how ALC optimisation can be achieved by incorporating all product life-cycle phases through the use of a RAMS²-toolbox and the generation of a knowledge-based DT. The benefits of the developed model are demonstrated in a simulation, considering RAMS2 (Reliability, Availability, Maintainability, Safety and Sustainability) and the linking of heterogeneous data, with the help of a dynamic Bayesian network (DBN).

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40

Gao, Xi-Rong, Jian Yang, and Wen-xuan Dong. "An Improved Real Option Pricing Model of Internet Asset." International Journal of Asian Business and Information Management 9, no. 2 (April 2018): 15–28. http://dx.doi.org/10.4018/ijabim.2018040102.

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This article shows that against the neglect on Internet asset value in traditional financial accounting theory and practice, the authors proposed an improved real option model for assessing Internet asset value based on Metcalfe's law and adaptive expectation hypothesis, and used it to assess the Internet asset value of Tencent company. The results showed that the improved real option model can accurately assess the value of Internet asset, and the assessment result was extremely consistent with the result assessed by efficient market theory algorithm. The results also showed that Internet asset value played a predominate role in Internet enterprise overall value, and both the initial revenue growth and estimated time had a significant positive effect on Internet asset value, and long-term industry operation cost coefficient and short-term corporate operation cost coefficient had a significant negative effect on Internet asset value. The results indicated that cutting the cost or increasing the network users could promote the value of Internet asset.

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41

Susanti, Neneng, and Deden Novan Setiawan Nugraha. "THE COMPARISON OF APPLICATION OF STOCK RETURN EVALUATION IN RECORDED COMPANIES IN LQ 45 FOR THE 2012-2016 PERIOD." Journal of Economic Empowerment Strategy (JEES) 2, no. 1 (February 28, 2019): 1. http://dx.doi.org/10.30740/j.v2i1.30.

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The purpose of this study is not only to compare the Capital Asset Price Model, Arbitration Price Theory, Three Factor Price Model, Three Factor Price Model, and Five Factor Price Model to study the Capital Asset Price Model, Price Arbitration Price Theory, Three Factor Price Model, Four Factors Pricing Model and Five Factors Pricing Model for excess returns and for determining the best asset pricing model in terms of the ability to explain estimates of excess returns. This research includes explanatory research (explanatory research), namely looking at the relationship between research variables and testing hypotheses that have been formulated previously. This study examines the effect of variables in the asset pricing model and compares the asset pricing models in explaining excess returns. Based on the results of the research that has been carried out the best model that can be used in assessing the asset pricing model is the five Price Model Factors, this is evidenced by the value of R2 or R Square of 89.4%, the value is greater than the value of R2 or R Square Capital Asset Pricing Model, Arbitration Price Theory, Three Price Factor Models, and Four Price Factor Models, which were 34.7%, 55.2%, 77.2% and 79% respectively.

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42

Susanti, Neneng, and Deden Novan Setiawan Nugraha. "THE COMPARISON OF APPLICATION OF STOCK RETURN EVALUATION IN RECORDED COMPANIES IN LQ 45 FOR THE 2012-2016 PERIOD." Journal of Economic Empowerment Strategy (JEES) 2, no. 1 (February 28, 2019): 1. http://dx.doi.org/10.30740/jees.v2i1.30.

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Abstract (sommario):

The purpose of this study is not only to compare the Capital Asset Price Model, Arbitration Price Theory, Three Factor Price Model, Three Factor Price Model, and Five Factor Price Model to study the Capital Asset Price Model, Price Arbitration Price Theory, Three Factor Price Model, Four Factors Pricing Model and Five Factors Pricing Model for excess returns and for determining the best asset pricing model in terms of the ability to explain estimates of excess returns. This research includes explanatory research (explanatory research), namely looking at the relationship between research variables and testing hypotheses that have been formulated previously. This study examines the effect of variables in the asset pricing model and compares the asset pricing models in explaining excess returns. Based on the results of the research that has been carried out the best model that can be used in assessing the asset pricing model is the five Price Model Factors, this is evidenced by the value of R2 or R Square of 89.4%, the value is greater than the value of R2 or R Square Capital Asset Pricing Model, Arbitration Price Theory, Three Price Factor Models, and Four Price Factor Models, which were 34.7%, 55.2%, 77.2% and 79% respectively.

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Wang, Jian, Xinqi Shen, Mei Li, Quanbo Lu, and Yixiao Yue. "Asset Administration Shell-Based Workshop Transportation System Design." Digital Technologies Research and Applications 2, no. 1 (December 1, 2022): 1. http://dx.doi.org/10.54963/dtra.v2i1.73.

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In view of the lack of unified data architecture and model of workshop transportation system components, this paper proposes the concept of the workshop transportation system functional unit based on asset administration shell (AAS). The designed workshop transportation system can solve the problem of unified modelling for different types of equipment, and realize the rapid construction and adjustment of the system. Meanwhile, the system has been applied in the specific workshop transportation system and enables well application results. In the functional unit of workshop transportation system, automatic markup language (AML) is applied. This paper constructs the AAS model based on the industrial 4.0 reference architecture model (RAMI4.0), and introduces the workshop transportation system AAS model and its realistic mapping as an example. The workshop transportation system functional unit AAS model based on the RAMI4.0 provides an effective solution for the standardization and integration of workshop transportation system components, which is no requirement to develop specific data conversion tools for this purpose. All transportation equipment with AAS can achieve information exchange and interoperability. It is conducive for the rapid implementation of workshop transportation system engineering and provides a guide for the establishment of intelligent workshop. Thereby, the proposed methodology demonstrates the flexibility and interoperability of AAS in smart manufacturing.

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Mezquita, Yeray, Blaž Podgorelec, Ana Belén Gil-González, and Juan Manuel Corchado. "Blockchain-Based Supply Chain Systems, Interoperability Model in a Pharmaceutical Case Study." Sensors 23, no. 4 (February 9, 2023): 1962. http://dx.doi.org/10.3390/s23041962.

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Abstract (sommario):

The main purpose of supply chain systems based on blockchain technology is to take advantage of technology innovations to ensure that a tracked asset's audit trail is immutable. However, the challenge lies in tracking the asset among different blockchain-based supply chain systems. The model proposed in this paper has been designed to overcome the identified challenges. Specifically, the proposed model enables: (1) the asset to be tracked among different blockchain-based supply-chain systems; (2) the tracked asset’s supply chain to be cryptographically verified; (3) a tracked asset to be defined in a standardized format; and (4) a tracked asset to be described with several different standardized formats. Thus, the model provides a great advantage in terms of interoperability between different blockchain-driven supply chains over other models in the literature, which will need to replicate the information in each blockchain platform they operate with, while giving flexibility to the platforms that make use of it and maintain the scalability of those logistic platforms. This work aims to examine the application of the proposed model from an operational point of view, in a scenario within the pharmaceutical sector.

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Kang, Tae Soo, and Hyunduk Suh. "Asset-based Reserve Requirements in a Dynamic Stochastic General Equilibrium Model." Asian Economic Papers 16, no. 2 (June 2017): 216–42. http://dx.doi.org/10.1162/asep_a_00539.

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We discuss the macroeconomic effects of asset-based reserve requirements (ABRR) in a dynamic stochastic general equilibrium model. In contrast to the conventional reserve requirement system, ABRR impose reserve requirements on financial institutions’ asset holdings. The policy can be used for macro prudential purposes to reduce pro-cyclicality of financial institutions. Using a financial friction New Keynesian model based on Meh and Moran ( 2010 ), we show that ABRR can be a more effective instrument in the presence of sector-specific shocks than the Basel-III type countercyclical capital buffer. The reason is that the former policy can adjust the asset return of the specific sector hit by the shock, whereas the latter does not have such sector-specific treatment.

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Sutanta, E., EK Nurnawati, C. Iswahyudi, and RA Kumalasanti. "The Model Prototype of WebGIS-based for Organizational Asset Management." Journal of Physics: Conference Series 1823, no. 1 (March 1, 2021): 012032. http://dx.doi.org/10.1088/1742-6596/1823/1/012032.

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47

Penman, Stephen, and Julie Zhu. "An accounting-based asset pricing model and a fundamental factor." Journal of Accounting and Economics 73, no. 2-3 (April 2022): 101476. http://dx.doi.org/10.1016/j.jacceco.2021.101476.

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48

Wallace, Neil. "A model of the liquidity structure based on asset indivisibility." Journal of Monetary Economics 45, no. 1 (February 2000): 55–68. http://dx.doi.org/10.1016/s0304-3932(99)00048-3.

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49

Berkowitz, Jeremy. "Generalized spectral estimation of the consumption-based asset pricing model." Journal of Econometrics 104, no. 2 (September 2001): 269–88. http://dx.doi.org/10.1016/s0304-4076(01)00081-1.

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Wang, W., and W. Zhang. "An asset residual life prediction model based on expert judgments." European Journal of Operational Research 188, no. 2 (July 2008): 496–505. http://dx.doi.org/10.1016/j.ejor.2007.03.044.

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