Equilibrium strategies in random-demand procurement auctions with sunk costs

We address an auction model which captures basic features of balancing markets for electricity. The existence and uniqueness of equilibrium are examined and a method for explicit calculation of bid strategies is presente

Valuing virtual production capacities on flow commodities

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 contract writers try to hedge themselves by appropriate physical assets, for instance, using storage utilities, through transmission and/or production capacities. However, the correct valuation of such contacts and their physical counterparts is still under lively debate. In this approach, an axiomatic setting to discuss price dynamics for flow commodity contracts is suggested. By means of a minimal set of reasonable assumptions we suggest a framework where the standard change-of-numeraire transformation converts a flow commodity market into a market consisting of zero bonds and some additional risky asset. Utilizing this structure, we apply the toolkit of interest rate theory to price the availability of production capacity on a flow commodit

Hypergroup Actions and Wavelets

This is the proceedings of the 2nd Japanese-German Symposium on Infinite Dimensional Harmonic Analysis held from September 20th to September 24th 1999 at the Department of Mathematics of Kyoto University.この論文集は, 1999年9月20日から9月24日の日程で京都大学理学研究科数学教室において開催された第2回日独セミナー「無限次元調和解祈」の成果をもとに編集されたものである.編集 : ハーバート・ハイヤー, 平井 武, 尾畑 信明Editors: Herbert Heyer, Takeshi Hirai, Nobuaki Obata #enIn analogy to wavelet transforms, we use group-like structures in order to introduce a class of integral transformations. We consider them in the context of Hilbert spaces and study their inversion

An application of high-dimensional statistics to predictive modeling of grade variability

The economic viability of a mining project depends on its efficient exploration, which requires a prediction of worthwhile ore in a mine deposit. In this work, we apply the so-called LASSO methodology to estimate mineral concentration within unexplored areas. Our methodology outperforms traditional techniques not only in terms of logical consistency, but potentially also in costs reduction. Our approach is illustrated by a full source code listing and a detailed discussion of the advantages and limitations of our approach. © 2020 by the authors. Licensee MDPI, Basel, Switzerland

risk aversion in modeling of cap and trade mechanism and optimal design of emission markets

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 how the architecture of an environmental market can be optimized under the realistic assumption of risk-aversion and which approximations must be met therefore

Properly designed emissions trading schemes do work!

Emissions trading markets have been touted as the most efficient mechanism to achieve environmental goals at least cost. Whether in the form of voluntary markets or in a mandatory framework like in the first phase of the European Union (EU) Emission Trading Scheme (ETS), the regulator sets a cap on the emissions which can occur without penalty, and provides emissions allowances accordingly. The recipients are free to use these emission certificates to cover their emissions, or to sell them to the firms which are expected to emit more than what they can cover with their original allocations. As observed in most existing programs, cap-and-trade systems can fail to reach their emission targets as too generous an allocation of pollution permits serves as a disincentive for emissions reductions and deflates pollution prices. Moreover, the implementation of the first phase of the EU-ETS has been widely criticized on one more sensitive account: providing significant (some went as far as calling them obscene) windfall profits for power producers. Here we weight on this debate with the results of a rigorous quantitative modeling undertaking, providing insight into what went wrong in the first phase of the EU-ETS, and proposing alternative reduction schemes with provable advantages. Using market equilibrium models and numerical tools, we demonstrate that properly designed market-based pollution reduction mechanisms can reach pre-assigned emissions targets at low reduction cost and windfall profits, while being flexible enough to promote clean technologies. In the present article, we illustrate our claims with the results of a hypothetical cap-and-trade scheme for the Japanese electricity market

A martingale method of portfolio optimization for unobservable mean rate of return

In the Black-Scholes type financial market, the risky asset S 1 ( ) is supposed to satisfy dS 1 ( t ) = S 1 ( t )( b ( t ) dt + Sigma ( t ) dW ( t ) where W ( ) is a Brownian motion. The processes b ( ), Sigma ( ) are progressively measurable with respect to the filtration generated by W ( ). They are known as the mean rate of return and the volatility respectively. A portfolio is described by a progressively measurable processes Pi1 ( ), where Pi1 ( t ) gives the amount invested in the risky asset at the time t. Typically, the optimal portfolio Pi1 ( ) (that, which maximizes the expected utility), depends at the time t, among other quantities, on b ( t ) meaning that the mean rate of return shall be known in order to follow the optimal trading strategy. However, in a real-world market, no direct observation of this quantity is possible since the available information comes from the behavior of the stock prices which gives a noisy observation of b ( ). In the present work, we consider the optimal portfolio selection which uses only the observation of stock prices