Hinz, J, Tarnopolskaya, T & Yee, J 2020, 'Efficient algorithms of pathwise dynamic programming for decision optimization in mining operations', Annals of Operations Research, pp. 1-33.View/Download from: Publisher's site
© 2018 Springer Science+Business Media, LLC, part of Springer Nature Complexity and uncertainty associated with commodity resource valuation and extraction requires stochastic control methods suitable for high dimensional states. Recent progress in duality and trajectory-wise techniques has introduced a variety of fresh ideas to this field with surprising results. This paper presents a concept which implements this promising development and illustrates it on a selection of traditional commodity extraction problems. We describe efficient algorithms for obtaining approximate solutions along with a diagnostic technique, which provides a quantitative measure for solution performance in terms of the distance between the approximate and the optimal control policy. All quantitative tools are efficiently implemented and are publicly available within a user friendly package in the statistical language R, which can help practitioners in a broad range of decision optimization problems.
© 2017 Elsevier B.V. The increased market penetration of renewable energy sources and the rapid development of electric battery storage technologies yield a potential for reducing electricity price volatility while maintaining stability of the power grid. This work presents an algorithmic approach to control battery levels and forward positions to optimally manage power output fluctuations caused by intermittent renewable energy generation. This paper will also explore the effect of battery technology on the firm's optimal trading behaviour in the electricity spot market.
This paper examines discrete-time optimal control problems arising in the context of optimal asset liquidation using recently published algorithms and code. We address these questions within a realistic framework, assuming that the order placement decisions must be adapted dynamically. Furthermore, we show how a duality-based technique can be used to assess the quality of our numerical solution.
Hinz, J & Yee, J 2017, 'Stochastic switching for partially observable dynamics and optimal asset allocation', International Journal of Control, vol. 90, no. 3, pp. 553-565.View/Download from: UTS OPUS or Publisher's site
© 2016 Informa UK Limited, trading as Taylor & Francis Group. In industrial applications, optimal control problems frequently appear in the context of decision-making under incomplete information. In such framework, decisions must be adapted dynamically to account for possible regime changes of the underlying dynamics. Using stochastic filtering theory, Markovian evolution can be modelled in terms of latent variables, which naturally leads to high-dimensional state space, making practical solutions to these control problems notoriously challenging. In our approach, we utilise a specific structure of this problem class to present a solution in terms of simple, reliable, and fast algorithms. The algorithms presented in this paper have already been implemented in an R package.
Hinz, J 2016, 'Using Convex Switching Techniques for Partially Observable Decision Processes', IEEE TRANSACTIONS ON AUTOMATIC CONTROL, vol. 61, no. 9, pp. 2727-2732.View/Download from: Publisher's site
Hinz, J & Yap, N 2016, 'Algorithms for optimal control of stochastic switching systems', Theory of Probability & Its Applications, vol. 60, no. 4, pp. 770-800.View/Download from: UTS OPUS or Publisher's site
Optimal control problems of switching type with linear state dynamics are ubiquitous in applications of stochastic optimization. For high-dimensional problems of this type, solutions which utilize some convexity related properties are useful. For such problems, we present novel algorithmic solutions which require minimal assumptions while demonstrating remarkable computational efficiency. Furthermore, we devise procedures of the primal-dual kind to assess the distance to optimality of these approximate solutions.
© 2016 Australian Mathematical Society. Optimal control problems of stochastic switching type appear frequently when making decisions under uncertainty and are notoriously challenging from a computational viewpoint. Although numerous approaches have been suggested in the literature to tackle them, typical real-world applications are inherently high dimensional and usually drive common algorithms to their computational limits. Furthermore, even when numerical approximations of the optimal strategy are obtained, practitioners must apply time-consuming and unreliable Monte Carlo simulations to assess their quality. In this paper, we show how one can overcome both difficulties for a specific class of discrete-time stochastic control problems. A simple and efficient algorithm which yields approximate numerical solutions is presented and methods to perform diagnostics are provided.
Mandatory emission trading schemes are being established around the world. Participants of such market schemes are always exposed to risks. This leads to the creation of an accompanying market for emission-linked derivatives. To evaluate the fair prices
T he existence of mandatory emission trading schemes in Europe and the United States, and the increased liquidity of trading on futures contracts on CO2 emissions allowances, led naturally to the next step in the development of these markets: These futures contracts are now used as underliers for a vibrant derivative market. In this paper, we give a rigorous analysis of a simple risk-neutral reduced-form model for allowance futures prices, demonstrate its calibration to historical data, and show how to price European call options written on these contracts.
This paper is concerned with the mathematical analysis of emissions markets. We review the existing quantitative analyses on the subject and introduce some of the mathematical challenges posed by the implementation of the new phase of the European Union
The introduction of marketable pollution rights is considered as an appropriate way to combat environmental problems on a global scale. According to theoretical arguments, a properly designed emission trading system should help reaching pollution reduction at low social costs. Nowadays, environmental markets are being established around the world. Their practice provides a stress test for the underlying economic theory and raises a lively discussion about advantages and shortcomings of emission trading. In this work, we highlight some core principles underlying quantitative understanding of emission markets and elaborate on mathematical problems and applications, arising in this context. © 2010 Vieweg+Teubner und Deutsche Mathematiker-Vereinigung.
Unlike derivatives of ?nancial contracts, commodity options exhibit distinct particularities owing to physical aspects of the underlying. An adaptation of no-arbitrage pricing to this kind of derivative turns out to be a stress test, challenging the martingale-based models with diverse technical and technological constraints, with storability and short selling restrictions, and sometimes with the lack of an e?cient dynamic hedging. In this work, we study the e?ect of storability on risk neutral commodity price modeling and suggest a model class where arbitrage is excluded for both commodity futures trading and simultaneous dynamical management of the commodity stock. The proposed framework is based on key results from interest rate theory.
Tackling climate change is at the top of many agendas. In this context, emission trading schemes are considered as promising tools. The regulatory framework for an emission trading scheme introduces a market for emission allowances and creates a need for risk management by appropriate financial contracts. In this work, we address logical principles underlying their valuation.
Carmona, R, Fehr, M & Hinz, J 2009, 'Optimal stochastic control and carbon price formation', SIAM Journal on Control and Optimization, vol. 48, no. 4, pp. 2168-2190.View/Download from: UTS OPUS or Publisher's site
To meet the targets of the Kyoto Protocol, the European Union established the European Emission Trading Scheme, a mandatory market for carbon emission allowances. This regulatory framework has introduced a market for emission allowances and created a var
Doege, J, Fehr, M, Hinz, J, Luthi, H & Wilhelm, M 2009, 'Risk management in power markets: The Hedging value of production flexibility', European Journal Of Operational Research, vol. 199, no. 3, pp. 936-943.View/Download from: UTS OPUS or Publisher's site
Since the 1990s power markets are being restructured worldwide and nowadays electrical power is traded as a commodity. The liberalization and with it the uncertainty in gas, fuel and electrical power prices requires an effective management of production
Hinz, J 2007, 'Review of "Weather Derivative Valuation: The Meteorological, Statistical, Financial and Mathematical Foundations.", by S. Jewson, A. Brix, and C. Ziehmann', Journal of the American Statistical Association, vol. 102, no. 477, pp. 380-380.
Hinz, J 2006, 'Equilibrium strategies in random-demand procurement auctions with sunk costs', IMA Journal of Management Mathematics, vol. 17, no. 1, pp. 61-81.
As a result of storability restrictions, the price risk management of flow commodities (such as natural gas, oil, and electrical power) is by no means a trivial matter.To protect price spikes, consumers purchase diverse swing-type contracts, whereas cont
Hinz, J & Wilhelm, M 2006, 'Pricing flow commodity derivatives using fixed income market techniques', International Journal of Theoretical and Applied Finance, vol. 9, no. 8, pp. 1299-1321.
Hinz, J 2003, 'Modelling day-ahead electricity prices', Applied Mathematical Finance, vol. 10, no. 2, pp. 149-161.
Hinz, J 2003, 'Optimizing a portfolio of power-producing plants', Bernoulli journal, vol. 9, no. 4, pp. 659-669.
Elliott, RJ & Hinz, J 2002, 'Portfolio optimization, hidden Markov models, and technical analysis of P&F-charts', International Journal of Theoretical and Applied Finance, vol. 5, no. 4, pp. 385-399.
Hinz, J 1997, 'An application of wavelet analysis to pricing and hedging derivative securities', Probability and Mathematical Statistics, vol. 19, pp. 43-53.
Falbo, P & Hinz, J 2016, 'Risk Aversion in Modeling of Cap-and-Trade Mechanism and Optimal Design of Emission Markets' in Benth, E..F. & Di Nunno, G. (eds), Stochastics of Environmental and Financial Economics, Springer, Germany, pp. 265-284.View/Download from: Publisher's site
According to theoretical arguments, a properly designed emission trading system should help reaching pollution reduction at low social burden based on the theoretical work of environmental economists, cap-and-trade systems are put into operations all over the world. However, the practice from emissions trading yields a real stress test for the underlying theory and reveals a number of its weak points. This paper aims to fill the gap between general welfare concepts underlying understanding of liberalized market and specific issues of real-world emission market operation. In our work, we present a novel technique to analyze emission market equilibrium in order to address diverse questions in the setting of risk-averse market players. Our contribution significantly upgrades all existing models in this field, which neglect risk-aversion aspects at the cost of having a wide range of singularities in their conclusions, now resolved in our approach. Furthermore, we show both how the architecture of an environmental market can be optimized under the realistic assumption of risk-aversion.
Hinz, J & Yee, J 2016, 'Algorithmic Solutions for Optimal Switching Problems', IEEE CPS, 2016 Second International Symposium on Stochastic Models in Reliability Engineering, Life Science and Operations Management (SMRLO), IEEE, Beer Sheva, Israel, pp. 586-590.View/Download from: UTS OPUS or Publisher's site
In practice, optimal control problems of stochastic switching are notoriously challenging from a computational viewpoint, since typical real-world applications are high dimensional. In this approach, we suggest an algorithmic solution which is based on some convexity assumptions frequently fulfilled in applications. Furthermore, we show how the quality of numerical solution can be assessed. An efficient implementation of our algorithms is discussed.
Hinz, J & Yee, J. 2016, 'Solving Control Problems with Linear State Dynamics - A Practical User Guide', In Proceedings of the Second International Symposium on Stochastic Models in Reliability Engineering, Life Science and Operations Management (SMRLO’16),, 2016 Second International Symposium on Stochastic Models in Reliability Engineering, Life Science and Operations Management (SMRLO), IEEE CPS, Beer Sheva, Israel, pp. 591-596.View/Download from: UTS OPUS or Publisher's site
Hinz, J, Falbo, P & Pelizzari, C 2015, 'Risk-Averse Equilibrium Modeling and Social Optimality of Cap-and-Trade Mechanisms', Stochastic Models, Statistics and Their Applications, Workshop on Stochastic Models, Statistics and Their Applications, Springer, Wrocław, Poland, pp. 261-269.View/Download from: Publisher's site
We present and explore a link between social optimality and risk-neutral dynamics satisfied in the equilibrium of emission markets. Our contribution addresses market modeling in the setting of risk-averse market players and goes beyond all existing models in this field, which neglect risk-aversion aspects at the cost of having a wide range of singularities.
Hinz, J, Yee, J & Tarnopolskaya, T 2015, 'On the valuation of natural resource investments using optimal stochastic switching', 21st International Congress on Modelling and Simulation, International Congress on Modelling and Simulation, MODELLING & SIMULATION SOC AUSTRALIA & NEW ZEALAND INC, Brisbane, pp. 1070-1076.
Hinz, J & Novikov, A 2009, 'On fair pricing of emission-related derivatives', Research Paper Series, Quantitative Finance Research Centre, University of Technology, Sydney.View/Download from: UTS OPUS
Research Paper Number: 257 Abstract: The climate rescue is on the top of many agendas. In thisc ontext, emission trading schemes are considered as promising tools. The regulatory framework of an emission trading scheme introduces a market for emission allowances and creates need for risk management by appropriate financial contracts. In this work, we address logical principles underlying their valuation.