A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
Paper introduces a new volatility model for natural gas markets and discusses swing option pricing.
The study finds a long-term relationship between Dubai crude oil and US natural gas prices.
The paper models natural gas futures prices and volatility, using Monte Carlo and reinforcement learning.
The study models and forecasts natural gas prices using skewed, heavy-tailed distributions.
In this work we analyse a stochastic control problem for the valuation of a natural gas power station while taking into account operating characteristics. Both electricity and gas spot price processes exhibit mean-reverting spikes and Markov regime-switches. The Levy regime-switching model incorporates the effects of d…
We study historical calibration of one- and two-factor models that are known to describe relatively well the dynamics of energy underlyings such as spot and index natural gas or oil prices at different physical locations or regional power prices. We take into account uneven frequency of data due to weekends, holidays, …
This paper focuses on the valuation and hedging of gas storage facilities, using a spot-based valuation framework coupled with a financial hedging strategy implemented with futures contracts. The first novelty consist in proposing a model that unifies the dynamics of the futures curve and the spot price, which accounts…
How does dynamic price information flow among Northern European electricity spot prices and prices of major electricity generation fuel sources? We use time series models combined with new advances in causal inference to answer these questions. Applying our methods to weekly Nordic and German electricity prices, and oi…
We price weather-contingent options by use of Monte Carlo simulations. After calibrating the models to fit quoted prices, we analyze bid-ask spreads in terms of correlations across markets. Results are presented for a double-trigger Weather vs. Natural Gas call option.
Energy markets are strategic to governments and economic development. Several commodities compete as substitutable energy sources and energy diversifiers. Such competition reduces the energy vulnerability of countries as well as portfolios' risk exposure. Vulnerability results mainly from price trends and fluctuations,…
In this article we present a continuous time model for natural gas and crude oil future prices. Its main feature is the possibility to link both energies in the long term and in the short term. For each energy, the future returns are represented as the sum of volatility functions driven by motions. Under the risk neutr…
One important effect of price shocks in the United States has been increased political attention paid to the structure and performance of oil and natural gas markets, along with some governmental support for energy conservation. This paper describes how price changes helped lead the emergence of a political agenda acco…
We describe an agent-based simulation of a fictional (but feasible) information trading business. The Gas Price Information Trader (GPIT) buys information about real-time gas prices in a metropolitan area from drivers and resells the information to drivers who need to refuel their vehicles. Our simulation uses real wor…
Introduces GA-P/E, a growth-adjusted stock valuation measure.
Study compares Bitcoin, gold, and gas price complexity using multifractal and multiscale entropy methods.
The recent liberalization of the electricity and gas markets has resulted in the growth of energy exchanges and modelling problems. In this paper, we modelize jointly gas and electricity spot prices using a mean-reverting model which fits the correlations structures for the two commodities. The dynamics are based on Or…
Modeling gas fee competition in decentralized exchanges to optimize arbitrage profits.
This paper analyzes Ethereum's gas fees and their derivatives, providing a comprehensive model.
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, a…
This study introduces a new GAS blending ensemble model for Bitcoin price prediction.
Paper introduces MN-DAG for modeling evolving causal relationships in multivariate time series.
Study analyzes European energy markets' reactions to 2022 events using Bayesian methods.
Model forecasts natural gas consumption with Fourier series and feedback.
Model predicts volatility and dependencies in EUA and energy prices.
The recently announced Energy Union by the European Commission is the most recent step in a series of developments aiming at integrating the EU's gas markets to increase social welfare (SW) and security of gas supply. Based on a spatial partial equilibrium model, we analyze the changes in consumption, prices, and SW up…
Deep RL strategy improves natural gas trading performance.
Paper models uncertainty in electricity and gas markets to assess its impact.
The paper examines how cheaper and faster chains affect Uniswap v3 liquidity and profitability.
Blockchain scaling reduces gas fees, allowing more frequent liquidity updates and concentration.
Study examines value relevance of oil and gas reserve disclosures in London Stock Exchange.
Swing options on the gas market are american style option where daily quantities exercices are constrained and global quantities exerciced each year constrained too. The option holder has to decide each day how much he consumes of the quantities satisfying the constraints and tries to use a strategy in order to maximiz…
Optimizes routing in decentralized exchanges with gas fees.
The prediction of the gas production from mature gas wells, due to their complex end-of-life behavior, is challenging and crucial for operational decision making. In this paper, we apply a modified deep LSTM model for prediction of the gas flow rates in mature gas wells, including the uncertainties in input parameters.…
Study simulates Variance Gamma processes for energy derivatives pricing.
Deep reinforcement learning boosts commodities trading performance.
Study improves carbon price forecasting using quantile regression and feature selection.
Conversion of corn to ethanol in the US since 2005 has been a major cause of global food price increases during that time and has been shown to be ineffective in achieving US energy independence and reducing environmental impact. We make three key statements to enhance understanding and communication about ethanol prod…
Let and be natural vector bundles defined over the category $\Cal Mf_m^+$ of smooth oriented --dimensional manifolds and orientation preserving local diffeomorphisms, with . Let be an object of $\Cal Mf_m^+$ which is connected. We give a complete classification of all separately con…
This paper introduces an information-based model for the pricing of storable commodities such as crude oil and natural gas. The model uses the concept of market information about future supply and demand as a basis for valuation. Physical ownership of a commodity is taken to provide a stream of convenience dividends eq…
Deep learning optimizes gas storage operations.
In this paper we treat a gas storage valuation problem as a Markov Decision Process. As opposed to existing literature we model the gas price process as a regime-switching model. Such a model has shown to fit market data quite well in Chen and Forsyth (2010). Before we apply a numerical algorithm to solve the problem, …
Paper uses neural networks to predict NOx emissions from gas turbines.
Empirical analysis of financial market trends and reversions across various time scales.
Study examines trading costs on Uniswap, finding adversarial slippage is significant for large trades and certain assets.
GA-MSSR optimizes forex trading rules for higher returns and reduced risk.
We consider the crossed product by of the adiabatic groupoid associated with any Lie groupoid . We construct an explicit Morita equivalence between the exact sequence of order 0 pseudodifferential operators on and (a restriction of) the natural exact sequence associated with . As an imp…
This paper considers the ideal gas-like model of trading markets, where each individual is identified as a gas molecule that interacts with others trading in elastic or money-conservative collisions. Traditionally this model introduces different rules of random selection and exchange between pair agents. Real economic …
VB approach for dynamic network models improves efficiency and accuracy.