scholarly journals Large-Scale Portfolio Allocation Under Transaction Costs and Model Uncertainty

2017 ◽  
Author(s):  
Nikolaus Hautsch ◽  
Stefan Voigt
Keyword(s):  
Transaction Costs ◽  
Model Uncertainty ◽  
Large Scale ◽  
Portfolio Allocation

Agricultural Co-operatives

2017 ◽  
Author(s):  
Samira Nuhanovic-Ribic ◽  
Ermanno C. Tortia ◽  
Vladislav Valentinov
Keyword(s):  
Developing Countries ◽  
Transaction Costs ◽  
Vertical Integration ◽  
Large Scale ◽  
Scale Production ◽  
Economic Literature ◽  
Economic Independence ◽  
Large Scale Production ◽  
Entrepreneurial Action

Over the last decades, agricultural co-operatives grew substantially in most developed and developing countries, often reaching dominant market positions. We inquire into the economic mechanism behind this growth, by elaborating on the relation between co-operative identity and co-operative benefits. We highlight the ability of agricultural co-operatives to co-ordinate large-scale production, to monitor work contributions and product quality, and to ensure economic independence of farmer members. Following the two principal streams in the economic literature, we distinguish between the conceptions of agricultural co-operatives as units of vertical integration and as firms characterized by common governance of collective entrepreneurial action and ability to reduce transaction costs and economic risk. We describe the financial and governance limitations of agricultural co-operatives while taking account of new co-operative models presenting institutional tools introduced to overcome these limitations. We conclude by suggesting directions for enhancing the role of co-operatives in agricultural and rural development.

scholarly journals Utility Maximization with Proportional Transaction Costs Under Model Uncertainty

2020 ◽  
Vol 45 (4) ◽  
pp. 1210-1236 ◽  
Author(s):  
Shuoqing Deng ◽  
Xiaolu Tan ◽  
Xiang Yu
Keyword(s):  
Dynamic Programming ◽  
Transaction Costs ◽  
Model Uncertainty ◽  
Utility Maximization ◽  
Exponential Utility ◽  
Market Condition ◽  
Maximization Problem ◽  
Proportional Transaction Costs ◽  
Utility Indifference ◽  
Basic Features

We consider a discrete time financial market with proportional transaction costs under model uncertainty and study a numéraire-based semistatic utility maximization problem with an exponential utility preference. The randomization techniques recently developed in Bouchard, Deng, and Tan [Bouchard B, Deng S, Tan X (2019) Super-replication with proportional transaction cost under model uncertainty. Math. Finance 29(3):837–860.], allow us to transform the original problem into a frictionless counterpart on an enlarged space. By suggesting a different dynamic programming argument than in Bartl [Bartl D (2019) Exponential utility maximization under model uncertainty for unbounded endowments. Ann. Appl. Probab. 29(1):577–612.], we are able to prove the existence of the optimal strategy and the convex duality theorem in our context with transaction costs. In the frictionless framework, this alternative dynamic programming argument also allows us to generalize the main results in Bartl [Bartl D (2019) Exponential utility maximization under model uncertainty for unbounded endowments. Ann. Appl. Probab. 29(1):577–612.] to a weaker market condition. Moreover, as an application of the duality representation, some basic features of utility indifference prices are investigated in our robust setting with transaction costs.

Practical Method for Damage Evaluation Based on Point Estimate Considering Uncertainty of Structural Properties

2015 ◽  
Vol 802 ◽  
pp. 255-260
Author(s):  
Kahori Iiyama ◽  
Masataka Hoso ◽  
Takanori Ishida ◽  
Kohei Fujita ◽  
Yoshihiro Yamazaki ◽  
...  
Keyword(s):  
Structural Properties ◽  
Model Uncertainty ◽  
Structural Damage ◽  
Large Scale ◽  
Practical Method ◽  
Point Estimate ◽  
Damage Evaluation ◽  
Building Structures ◽  
Large Scale Simulation ◽  
Seismic Simulation

This study introduces a practical method for evaluating structural damage based on a large-scale simulation targeting expansive areas, like whole cities. In such a seismic simulation that deals with numerous building structures, it is desirable to estimate the damage based on a stochastic evaluation considering the uncertainty of structural properties. This is because an accurate modeling of numerous building structures, according to each designed value, would require a great deal of time. However, a damage evaluation considering the model uncertainty generally involves numerous calculations and is inadequate for such a large-scale simulation. Therefore, we propose a method using the point estimate technique which can estimate the probability of damage under model uncertainty from a small number of calculations. The applicability and usefulness of the proposed method is evaluated by comparing it to the method based on a Monte Carlo simulation.

scholarly journals Evaluation of the MODIS LAI/FPAR Algorithm Based on 3D-RTM Simulations: A Case Study of Grassland

2020 ◽  
Vol 12 (20) ◽  
pp. 3391
Author(s):  
Jiabin Pu ◽  
Kai Yan ◽  
Guohuan Zhou ◽  
Yongqiao Lei ◽  
Yingxin Zhu ◽  
...  
Keyword(s):  
Model Uncertainty ◽  
Large Scale ◽  
Near Infrared ◽  
Evaluation Method ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Scale Dependency ◽  
Area Index ◽  
Input Uncertainty

Uncertainty assessment of the moderate resolution imaging spectroradiometer (MODIS) leaf area index (LAI) and the fraction of photosynthetically active radiation absorbed by vegetation (FPAR) retrieval algorithm can provide a scientific basis for the usage and improvement of this widely-used product. Previous evaluations generally depended on the intercomparison with other datasets as well as direct validation using ground measurements, which mix the uncertainties from the model, inputs, and assessment method. In this study, we adopted the evaluation method based on three-dimensional radiative transfer model (3D RTM) simulations, which helps to separate model uncertainty and other factors. We used the well-validated 3D RTM LESS (large-scale remote sensing data and image simulation framework) for a grassland scene simulation and calculated bidirectional reflectance factors (BRFs) as inputs for the LAI/FPAR retrieval. The dependency between LAI/FPAR truth and model estimation serves as the algorithm uncertainty indicator. This paper analyzed the LAI/FPAR uncertainty caused by inherent model uncertainty, input uncertainty (BRF and biome classification), clumping effect, and scale dependency. We found that the uncertainties of different algorithm paths vary greatly (−6.61% and +84.85% bias for main and backup algorithm, respectively) and the “hotspot” geometry results in greatest retrieval uncertainty. For the input uncertainty, the BRF of the near-infrared (NIR) band has greater impacts than that of the red band, and the biome misclassification also leads to nonnegligible LAI/FPAR bias. Moreover, the clumping effect leads to a significant LAI underestimation (−0.846 and −0.525 LAI difference for two clumping types), but the scale dependency (pixel size ranges from 100 m to 1000 m) has little impact on LAI/FPAR uncertainty. Overall, this study provides a new perspective on the evaluation of LAI/FPAR retrieval algorithms.

scholarly journals Model Uncertainty for Displacement Prediction for Laterally Loaded Piles on Granular Fill

2020 ◽  
Vol 10 (2) ◽  
pp. 613 ◽  
Author(s):  
Manuel Bueno Aguado ◽  
Félix Escolano Sánchez ◽  
Eugenio Sanz Pérez
Keyword(s):  
Model Uncertainty ◽  
Large Scale ◽  
Site Investigation ◽  
Laterally Loaded Piles ◽  
Relevant Issue ◽  
Displacement Prediction ◽  
Laterally Loaded Pile ◽  
Granular Fill ◽  
Laterally Loaded ◽  
Real Scale

Engineers are often concerned with the capability of a particular mathematical model to simulate a real-scale phenomenon. Model uncertainty is a relevant issue in order to assess the safety factor of a particular structure. In this paper, large-scale laterally loaded pile outputs are compared to predictions using well-known formulations. In this way, an insight on model uncertainty is presented. Both p-y method proposed by the API, and the horizontal reaction modulus proposed in many codes are used to predict displacement. Both are correlated to the site investigation. In this way, engineers are provided with a critical view of the available prediction methods to assess laterally loaded pile behaviour.

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