arXiv · arXiv q-fin · 2023
In this paper, we extend the market price of risk for delivery periods (MPDP) of electricity swap contracts by introducing a dimension for jump risk. As introduced by Kemper et al. (2022), the MPDP arises through the use of geometric averaging while pricing electricity swaps in a geometric framework. We adjust the work by Kemper et al. (2022) in two directions: First, we examine a Merton type model taking jumps into …
Annika Kemper, Maren Diane Schmeck
arXiv · arXiv q-fin · 2020
In electricity markets, futures contracts typically function as a swap since they deliver the underlying over a period of time. In this paper, we introduce a market price for the delivery periods of electricity swaps, thereby opening an arbitrage-free pricing framework for derivatives based on these contracts. Furthermore, we use a weighted geometric averaging of an artificial geometric futures price over the corresp…
Annika Kemper, Maren D. Schmeck, Anna Kh. Balci
arXiv · arXiv · 2019
We propose a multi-factor polynomial framework to model and hedge long-term electricity contracts with delivery period. This framework has several advantages: the computation of forwards, risk premium and correlation between different forwards are fully explicit, and the model can be calibrated to observed electricity forward curves easily and well. Electricity markets suffer from non-storability and poor medium- to …
Xi Kleisinger-Yu, Vlatka Komaric, Martin Larsson, Markus Regez
arXiv · arXiv · 2008
We study superhedging of contingent claims with physical delivery in a discrete-time market model with convex transaction costs. Our model extends Kabanov's currency market model by allowing for nonlinear illiquidity effects. We show that an appropriate generalization of Schachermayer's robust no arbitrage condition implies that the set of claims hedgeable with zero cost is closed in probability. Combined with classi…
Teemu Pennanen, Irina Penner
arXiv · arXiv q-fin · 2024
In this paper, we propose a complete modelling framework to value several batteries in the electricity intraday market at the trading session scale. The model consists of a stochastic model for the 24 mid-prices (one price per delivery hour) combined with a deterministic model for the liquidity costs (representing the cost of going deeper in the order book). A stochastic optimisation framework based on dynamic progra…
Enzo Cognéville, Thomas Deschatre, Xavier Warin
arXiv · arXiv q-fin · 2020
We develop a tractable equilibrium model for price formation in intraday electricity markets in the presence of intermittent renewable generation. Using stochastic control theory, we identify the optimal strategies of agents with market impact and exhibit the Nash equilibrium in closed form for a finite number of agents as well as in the asymptotic framework of mean field games. Our model reproduces the empirical fea…
Olivier Féron, Peter Tankov, Laura Tinsi
arXiv · arXiv q-fin · 2026
Commodity futures are shaped by harvest cycles, weather shocks, storage conditions, and seasonal demand, but it remains unclear whether recurring patterns yield robust out-of-sample trading profits. Existing research documents return seasonality in commodity futures as well as more complex seasonal structure, while leaving less evidence on how alternative seasonal models compare under common implementation constraint…
Ralph Kosch, Robin Forsberg
arXiv · arXiv q-fin · 2026
The rapid growth of weather-dependent renewable generation increases price volatility and imbalance penalty risk in power markets, creating the need for advanced quantitative trading strategies. We develop a data-driven continuous-time stochastic optimal control framework for intraday electricity trading using stochastic differential equations with drift terms ensuring mean reversion to deterministic forecast traject…
Chiheb Ben Hammouda, Michael Samet, Raul Tempone
arXiv · arXiv q-fin · 2023
Intraday electricity markets play an increasingly important role in balancing the intermittent generation of renewable energy resources, which creates a need for accurate probabilistic price forecasts. However, research to date has focused on univariate approaches, while in many European intraday electricity markets all delivery periods are traded in parallel. Thus, the dependency structure between different traded p…
Simon Hirsch, Florian Ziel
arXiv · arXiv q-fin · 2021
Machine learning techniques are playing more and more important roles in finance market investment. However, finance quantitative modeling with conventional supervised learning approaches has a number of limitations. The development of deep reinforcement learning techniques is partially addressing these issues. Unfortunately, the steep learning curve and the difficulty in quick modeling and agile development are impe…
Zechu Li, Xiao-Yang Liu, Jiahao Zheng, Zhaoran Wang, Anwar Walid
arXiv · arXiv q-fin · 2019
Financial markets for Liquified Natural Gas (LNG) are an important and rapidly-growing segment of commodities markets. Like other commodities markets, there is an inherent spatial structure to LNG markets, with different price dynamics for different points of delivery hubs. Certain hubs support highly liquid markets, allowing efficient and robust price discovery, while others are highly illiquid, limiting the effecti…
Michael Weylandt, Yu Han, Katherine B. Ensor
arXiv · arXiv q-fin · 2018
In the seminal paper on optimal execution of portfolio transactions, Almgren and Chriss (2001) define the optimal trading strategy to liquidate a fixed volume of a single security under price uncertainty. Yet there exist situations, such as in the power market, in which the volume to be traded can only be estimated and becomes more accurate when approaching a specified delivery time. During the course of execution, a…
Julien Vaes, Raphael Hauser
arXiv · arXiv · 2017
This paper provides a general framework for modeling financial contagion in a system with obligations in multiple illiquid assets (e.g., currencies). In so doing, we develop a multi-layered financial network that extends the single network of Eisenberg and Noe (2001). In particular, we develop a financial contagion model with fire sales that allows institutions to both buy and sell assets to cover their liabilities i…
Zachary Feinstein
arXiv · arXiv · 2017
We propose a hedging approach for general contingent claims when liquidity is a concern and trading is subject to transaction cost. Multiple assets with different liquidity levels are available for hedging. Our risk criterion targets a tradeoff between minimizing the risk against fluctuations in the stock price and incurring low liquidity costs. Following Çetin U., Jarrow R.A., and Protter P. (2004) we work in an arb…
Panagiotis Christodoulou, Nils Detering, Thilo Meyer-Brandis