scholarly journals An Optimal Model for Water Resources Risk Hedging Based on Water Option Trading

Water ◽  
2018 ◽  
Vol 10 (8) ◽  
pp. 1026 ◽  
Author(s):  
Haibin Yan ◽  
Ping-An Zhong ◽  
Juan Chen ◽  
Bin Xu ◽  
Yenan Wu ◽  
...  
Keyword(s):  
Trading Strategy ◽  
Water Transfer ◽  
Water Shortages ◽  
Long Distance ◽  
Option Trading ◽  
Risk Hedging ◽  
Water Users ◽  
Proposed Model ◽  
Trading Model ◽  
Expected Revenue

The uncertainty of forecasted runoffs brings risks of water shortages to water users in the intake area of long-distance water transfer projects, and the uncertainty of spot market prices may cause them to buy water at high prices. In order to hedge these risks, this paper proposes a risk hedging model for decision-making in water option trading from the viewpoint of water users. With the objective of maximizing the expected revenue of water users, the proposed model was solved by an analytical method and an optimal water option strategy was obtained for the users. The proposed model is applied to an intake area of an inter-basin water transfer project in China. The results show that the proposed water option trading model can provide water users with an optimal option strategy. The optimal options trading strategy can effectively reduce the risk caused by the uncertainties of forecasted runoffs and water prices. We also explored the influence of the uncertainty degree of the forecasted runoffs and water price on the option trading strategy. The results show that the expected revenue of water users increases as the variances of the errors of forecasted runoffs and water prices increase.

Hierarchical Concept-Driven Language Model

2021 ◽  
Vol 15 (6) ◽  
pp. 1-22
Author(s):  
Yashen Wang ◽  
Huanhuan Zhang ◽  
Zhirun Liu ◽  
Qiang Zhou
Keyword(s):  
Language Model ◽  
Generation Process ◽  
Data Generation ◽  
Modeling Framework ◽  
Long Distance ◽  
Short Text ◽  
Proposed Model ◽  
Scalable Inference ◽  
End To End ◽  
Hidden Layer

For guiding natural language generation, many semantic-driven methods have been proposed. While clearly improving the performance of the end-to-end training task, these existing semantic-driven methods still have clear limitations: for example, (i) they only utilize shallow semantic signals (e.g., from topic models) with only a single stochastic hidden layer in their data generation process, which suffer easily from noise (especially adapted for short-text etc.) and lack of interpretation; (ii) they ignore the sentence order and document context, as they treat each document as a bag of sentences, and fail to capture the long-distance dependencies and global semantic meaning of a document. To overcome these problems, we propose a novel semantic-driven language modeling framework, which is a method to learn a Hierarchical Language Model and a Recurrent Conceptualization-enhanced Gamma Belief Network, simultaneously. For scalable inference, we develop the auto-encoding Variational Recurrent Inference, allowing efficient end-to-end training and simultaneously capturing global semantics from a text corpus. Especially, this article introduces concept information derived from high-quality lexical knowledge graph Probase, which leverages strong interpretability and anti-nose capability for the proposed model. Moreover, the proposed model captures not only intra-sentence word dependencies, but also temporal transitions between sentences and inter-sentence concept dependence. Experiments conducted on several NLP tasks validate the superiority of the proposed approach, which could effectively infer meaningful hierarchical concept structure of document and hierarchical multi-scale structures of sequences, even compared with latest state-of-the-art Transformer-based models.

scholarly journals Allocation and Scheduling of Handling Resources in the Railway Container Terminal Based on Crossing Crane Area

2021 ◽  
Vol 13 (3) ◽  
pp. 1190
Author(s):  
Gang Ren ◽  
Xiaohan Wang ◽  
Jiaxin Cai ◽  
Shujuan Guo
Keyword(s):  
Programming Model ◽  
Container Terminal ◽  
Simultaneous Optimization ◽  
Mixed Integer ◽  
Gantry Crane ◽  
Optimization Scheme ◽  
Long Distance ◽  
Proposed Model ◽  
Hybrid Heuristic Algorithm ◽  
Searching Ability

The integrated allocation and scheduling of handling resources are crucial problems in the railway container terminal (RCT). We investigate the integrated optimization problem for handling resources of the crane area, dual-gantry crane (GC), and internal trucks (ITs). A creative handling scheme is proposed to reduce the long-distance, full-loaded movement of GCs by making use of the advantages of ITs. Based on this scheme, we propose a flexible crossing crane area to balance the workload of dual-GC. Decomposing the integrated problem into four sub-problems, a multi-objective mixed-integer programming model (MIP) is developed. By analyzing the characteristic of the integrated problem, a three-layer hybrid heuristic algorithm (TLHHA) incorporating heuristic rule (HR), elite co-evolution genetic algorithm (ECEGA), greedy rule (GR), and simulated annealing (SA) is designed for solving the problem. Numerical experiments were conducted to verify the effectiveness of the proposed model and algorithm. The results show that the proposed algorithm has excellent searching ability, and the simultaneous optimization scheme could ensure the requirements for efficiency, effectiveness, and energy-saving, as well as the balance rate of dual-GC.

scholarly journals Options trading strategy based on ARIMA forecasting

2020 ◽  
Vol 4 (2) ◽  
pp. 111-127
Author(s):  
Pierre Rostan ◽  
Alexandra Rostan ◽  
Mohammad Nurunnabi
Keyword(s):  
Composite Index ◽  
Garch Model ◽  
Trading Strategy ◽  
Credit Crisis ◽  
Strike Price ◽  
Index Options ◽  
Content Type ◽  
Option Trading ◽  
Auto Regressive ◽  
Options Trading

Purpose The purpose of this paper is to illustrate a profitable and original index options trading strategy. Design/methodology/approach The methodology is based on auto regressive integrated moving average (ARIMA) forecasting of the S&P 500 index and the strategy is tested on a large database of S&P 500 Composite index options and benchmarked to the generalized auto regressive conditional heteroscedastic (GARCH) model. The forecasts validate a set of criteria as follows: the first criterion checks if the forecasted index is greater or lower than the option strike price and the second criterion if the option premium is underpriced or overpriced. A buy or sell and hold strategy is finally implemented. Findings The paper demonstrates the valuable contribution of this option trading strategy when trading call and put index options. It especially demonstrates that the ARIMA forecasting method is a valid method for forecasting the S&P 500 Composite index and is superior to the GARCH model in the context of an application to index options trading. Originality/value The strategy was applied in the aftermath of the 2008 credit crisis over 60 months when the volatility index (VIX) was experiencing a downtrend. The strategy was successful with puts and calls traded on the USA market. The strategy may have a different outcome in a different economic and regional context.

scholarly journals Stop Plan of Express and Local Train for Regional Rail Transit Line

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Qin Luo ◽  
Yufei Hou ◽  
Wei Li ◽  
Xiongfei Zhang
Keyword(s):  
Energy Consumption ◽  
Travel Time ◽  
Programming Model ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Long Distance ◽  
Passenger Travel ◽  
Urban Rail ◽  
Proposed Model ◽  
Rail Line

The urban rail transit line operating in the express and local train mode can solve the problem of disequilibrium passenger flow and space and meet the rapid arrival demand of long-distance passengers. In this paper, the Logit model is used to analyze the behavior of passengers choosing trains by considering the sensitivity of travel time and travel distance. Then, based on the composition of passenger travel time, an integer programming model for train stop scheme, aimed at minimizing the total passenger travel time, is proposed. Finally, combined with a certain regional rail line in Shenzhen, the plan is solved by genetic algorithm and evaluated through the time benefit, carrying capacity, and energy consumption efficiency. The simulation result shows that although the capacity is reduced by 6 trains, the optimized travel time per person is 10.34 min, and the energy consumption is saved by about 16%, which proves that the proposed model is efficient and feasible.

scholarly journals Interbasin water transfer in a changing world: A new conceptual model

2021 ◽  
pp. 030913332110650
Author(s):  
Edward Rollason ◽  
Pammi Sinha ◽  
Louise J Bracken
Keyword(s):  
Water Scarcity ◽  
Conceptual Models ◽  
Management Strategies ◽  
Temporal Distribution ◽  
Water Transfer ◽  
Decision Makers ◽  
Global Issue ◽  
Proposed Model ◽  
Interbasin Water Transfer ◽  
Water Scarce

Water scarcity is a global issue, affecting in excess of four billion people. Interbasin Water Transfer (IBWT) is an established method for increasing water supply by transferring excess water from one catchment to another, water-scarce catchment. The implementation of IBWT peaked in the 1980s and was accompanied by a robust academic debate of its impacts. A recent resurgence in the popularity of IBWT, and particularly the promotion of mega-scale schemes, warrants revisiting this technology. This paper provides an updated review, building on previously published work, but also incorporates learning from schemes developed since the 1980s. We examine the spatial and temporal distribution of schemes and their drivers, review the arguments for and against the implementation of IBWT schemes and examine conceptual models for assessing IBWT schemes. Our analysis suggests that IBWT is growing in popularity as a supply-side solution for water scarcity and is likely to represent a key tool for water managers into the future. However, we argue that IBWT cannot continue to be delivered through current approaches, which prioritise water-centric policies and practices at the expense of social and environmental concerns. We critically examine the Socio-Ecological Systems and Water-Energy-Food (WEF) Nexus models as new conceptual models for conceptualising and assessing IBWT. We conclude that neither model offers a comprehensive solution. Instead, we propose an enhanced WEF model (eWEF) to facilitate a more holistic assessment of how these mega-scale engineering interventions are integrated into water management strategies. The proposed model will help water managers, decision-makers, IBWT funders and communities create more sustainable IBWT schemes.

Discussion on the Harm and Protection of Water Hammer of Cavities Collapsing during Long Distance Water Transfer Project

2013 ◽  
Vol 777 ◽  
pp. 407-411
Author(s):  
Li Zhao ◽  
Yu Dong Lu
Keyword(s):  
Water Hammer ◽  
Water Transfer ◽  
Constant Speed ◽  
Long Distance ◽  
Hydraulic Impact ◽  
Tube Explosion ◽  
Valve Effect ◽  
Air Valve ◽  
Pipeline Pressure

In long distance water transfer project, the pipeline pressure caused by the change of hydraulic impact on pipeline is the most dangerous, which cavities hammer boost up to the general water several times, the tube explosion phenomenon is most caused by water hammer of cavities collapsing. After long-term practice, two-way surge tower and constant speed buffer air valve effect remarkable on water hammer of cavities collapsing.

scholarly journals Optimizing the Pairs-Trading Strategy Using Deep Reinforcement Learning with Trading and Stop-Loss Boundaries

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-20 ◽  
Author(s):  
Taewook Kim ◽  
Ha Young Kim
Keyword(s):  
Reinforcement Learning ◽  
Trading Strategy ◽  
Trading Strategies ◽  
Cointegration Test ◽  
Optimum Level ◽  
Pairs Trading ◽  
Proposed Model ◽  
The Mean ◽  
Stop Loss ◽  
The Given

Many researchers have tried to optimize pairs trading as the numbers of opportunities for arbitrage profit have gradually decreased. Pairs trading is a market-neutral strategy; it profits if the given condition is satisfied within a given trading window, and if not, there is a risk of loss. In this study, we propose an optimized pairs-trading strategy using deep reinforcement learning—particularly with the deep Q-network—utilizing various trading and stop-loss boundaries. More specifically, if spreads hit trading thresholds and reverse to the mean, the agent receives a positive reward. However, if spreads hit stop-loss thresholds or fail to reverse to the mean after hitting the trading thresholds, the agent receives a negative reward. The agent is trained to select the optimum level of discretized trading and stop-loss boundaries given a spread to maximize the expected sum of discounted future profits. Pairs are selected from stocks on the S&P 500 Index using a cointegration test. We compared our proposed method with traditional pairs-trading strategies which use constant trading and stop-loss boundaries. We find that our proposed model is trained well and outperforms traditional pairs-trading strategies.

scholarly journals Developing a framework for water right allocation in inter-basin water transfer systems under uncertainty: The Solakan–Rafsanjan water transfer experience

2020 ◽  
Vol 20 (7) ◽  
pp. 2658-2681
Author(s):  
Ali Sahebzadeh ◽  
Reza Kerachian ◽  
Hamidreza Mohabbat ◽  
Saeed Ashrafi
Keyword(s):  
Water Allocation ◽  
Value At Risk ◽  
Information Aggregation ◽  
Water Transfer ◽  
Weighted Averaging ◽  
Low Flow ◽  
Conditional Value At Risk ◽  
Essential Information ◽  
Water Users ◽  
Basin Water

Abstract In this article, a methodology is presented for water allocation to demands in new inter-basin water transfer projects. In this methodology, by proposing some criteria such as universality, equity, enforceability, adaptivity, and exclusivity, a new scheme is developed in order to determine the share of water users. For taking the available water uncertainty into account, the concept of conditional value at risk (CVaR) is used, in which the goal is to minimize an indicator of loss in low flow conditions. Also, in order to estimate the relative weights of criteria, a novel method is introduced. This method is founded on two essential information aggregation operators, namely, hybrid weighted averaging (HWA) and ordered weighted averaging (OWA). The significant property of this method is that the weighting process is done by considering the relative weights of experts and the viewpoint of the analyzer jointly. The results of the CVaR-based model are compared with those obtained from a long-term water allocation optimization model with monthly time steps. The performance of the proposed methodology is evaluated using available data from the Solakan–Rafsanjan water transfer project.

Water quality model parameter identification of an open channel in a long distance water transfer project based on finite difference, difference evolution and Monte Carlo

2013 ◽  
Vol 69 (3) ◽  
pp. 587-594 ◽  
Author(s):  
Dongguo Shao ◽  
Haidong Yang ◽  
Yi Xiao ◽  
Biyu Liu
Keyword(s):  
Water Quality ◽  
Open Channel ◽  
Differential Evolution Algorithm ◽  
Water Transfer ◽  
Water Quality Model ◽  
Model Parameters ◽  
Quality Model ◽  
Long Distance ◽  
Mcmc Simulation ◽  
Evolution Algorithm

A new method is proposed based on the finite difference method (FDM), differential evolution algorithm and Markov Chain Monte Carlo (MCMC) simulation to identify water quality model parameters of an open channel in a long distance water transfer project. Firstly, this parameter identification problem is considered as a Bayesian estimation problem and the forward numerical model is solved by FDM, and the posterior probability density function of the parameters is deduced. Then these parameters are estimated using a sampling method with differential evolution algorithm and MCMC simulation. Finally this proposed method is compared with FDM–MCMC by a twin experiment. The results show that the proposed method can be used to identify water quality model parameters of an open channel in a long distance water transfer project under different scenarios better with fewer iterations, higher reliability and anti-noise capability compared with FDM–MCMC. Therefore, it provides a new idea and method to solve the traceability problem in sudden water pollution accidents.

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