arXiv · arXiv · 2020
We propose the Hawkes flocking model that assesses systemic risk in high-frequency processes at the two perspectives -- endogeneity and interactivity. We examine the futures markets of WTI crude oil and gasoline for the past decade, and perform a comparative analysis with conditional value-at-risk as a benchmark measure. In terms of high-frequency structure, we derive the empirical findings. The endogenous systemic r…
Hyun Jin Jang, Kiseop Lee, Kyungsub Lee
arXiv · arXiv · 2025
Climate change is a major threat to the future of humanity, and its impacts are being intensified by excess man-made greenhouse gas emissions. One method governments can employ to control these emissions is to provide firms with emission limits and penalize any excess emissions above the limit. Excess emissions may also be offset by firms who choose to invest in carbon reducing and capturing projects. These projects …
Liam Welsh, Udit Grover, Sebastian Jaimungal
arXiv · arXiv · 2024
We investigate the impact of several critical events associated with the Russo Ukrainian war, started officially on 24 February 2022 with the Russian invasion of Ukraine, on ten European electricity markets, two natural gas markets (the European reference trading hub TTF and N.Y. NGNMX market) and how these markets interact to each other and with USDRUB exchange rate, a financial market. We analyze the reactions of t…
Panayotis G. Papaioannou, George P. Papaioannou, George Evangelidis, George Gavalakis
arXiv · arXiv · 2024
This paper is devoted to the price-storage dynamics in natural gas markets. A novel stochastic path-dependent volatility model is introduced with path-dependence in both price volatility and storage increments. Model calibrations are conducted for both the price and storage dynamics. Further, we discuss the pricing problem of discrete-time swing options using the dynamic programming principle, and a deep learning-bas…
Jinniao Qiu, Antony Ware, Yang Yang
arXiv · arXiv · 2024
One approach to reducing greenhouse gas (GHG) emissions is to incentivize carbon capturing and carbon reducing projects while simultaneously penalising excess GHG output. In this work, we present a novel market framework and characterise the optimal behaviour of GHG offset credit (OC) market participants in both single-player and two-player settings. The single player setting is posed as an optimal stopping and contr…
Liam Welsh, Sebastian Jaimungal
arXiv · arXiv · 2023
Deep Reinforcement Learning (Deep RL) has been explored for a number of applications in finance and stock trading. In this paper, we present a practical implementation of Deep RL for trading natural gas futures contracts. The Sharpe Ratio obtained exceeds benchmarks given by trend following and mean reversion strategies as well as results reported in literature. Moreover, we propose a simple but effective ensemble le…
Yuanrong Wang, Yinsen Miao, Alexander CY Wong, Nikita P Granger, Christian Michler
arXiv · arXiv · 2022
This paper examines the relationship between the price of the Dubai crude oil and the price of the US natural gas using an updated monthly dataset from 1992 to 2018, incorporating the latter events in the energy markets. After employing a variety of unit root and cointegration tests, the long-run relationship is examined via the autoregressive distributed lag (ARDL) cointegration technique, along with the Toda-Yamamo…
Stavros Stavroyiannis
arXiv · arXiv · 2020
Hydraulic fracturing stimulates fracture swarm in reservoir formation though pressurized injection fluid. However restricted by the availability of formation data, the variability embraced by reservoir keeps uncertain, driving unstable gas recovery along with low resource efficiency, being responsible for resource scarcity, contaminated water, and injection-induced earthquake. Resource efficiency is qualified though …
Cheng Cheng
arXiv · arXiv · 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 · 2019
Using the United Nations COMTRADE database we apply the reduced Google matrix (REGOMAX) algorithm to analyze the multiproduct world trade in years 2004-2016. Our approach allows to determine the trade balance sensitivity of a group of countries to a specific product price increase from a specific exporting country taking into account all direct and indirect trade pathways via all world countries exchanging 61 UN COMT…
Célestin Coquidé, Leonardo Ermann, José Lages, D. L. Shepelyansky
arXiv · arXiv · 2018
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, following supply and demand shocks. Such energy price uncertainty attracts many market participants…
Hayette Gatfaoui
arXiv · arXiv · 2009
This paper considers ideal gas-like models of trading markets, where each agent is identified as a gas molecule that interacts with others trading in elastic or money-conservative collisions. Traditionally, these models introduce different rules of random selection and exchange between pair agents. Unlike these traditional models, this work introduces a chaotic procedure able of breaking the pairing symmetry of agent…
C. Pellicer-Lostao, R. Lopez-Ruiz
arXiv · arXiv · 2024
We study liquidity on decentralized exchanges (DEXs), identifying factors at the platform, blockchain, token pair, and liquidity pool levels with predictive power for market depth metrics. We introduce the v2 counterfactual spread metric, a novel criterion which assesses the degree of liquidity concentration in pools using the ``concentrated liquidity'' mechanism, allowing us to decompose the effect of a factor on ma…
Brian Z. Zhu, Dingyue Liu, Xin Wan, Gordon Liao, Ciamac C. Moallemi
arXiv · arXiv · 2023
Constant product markets with concentrated liquidity (CL) are the most popular type of automated market makers. In this paper, we characterise the continuous-time wealth dynamics of strategic LPs who dynamically adjust their range of liquidity provision in CL pools. Their wealth results from fee income, the value of their holdings in the pool, and rebalancing costs. Next, we derive a self-financing and closed-form op…
Álvaro Cartea, Fayçal Drissi, Marcello Monga
arXiv · arXiv · 2023
We investigate how liquidity providers (LPs) choose between high- and low-fee trading venues, in the face of a fixed common gas cost. Analyzing Uniswap data, we find that high-fee pools attract 58% of liquidity supply yet execute only 21% of volume. Large LPs dominate low-fee pools, frequently adjusting out-of-range positions in response to informed order flow. In contrast, small LPs converge to high-fee pools, accep…
Alfred Lehar, Christine Parlour, Marius Zoican
arXiv · arXiv · 2023
Liquidity providers (LPs) on decentralized exchanges (DEXs) can protect themselves from adverse selection risk by updating their positions more frequently. However, repositioning is costly, because LPs have to pay gas fees for each update. We analyze the causal relation between repositioning and liquidity concentration around the market price, using the entry of blockchain scaling solutions, Arbitrum and Polygon, as …
Basile Caparros, Amit Chaudhary, Olga Klein
arXiv · arXiv · 2022
Uniswap is a Constant Product Market Maker built around liquidity pools, where pairs of tokens are exchanged subject to a fee that is proportional to the size of transactions. At the time of writing, there exist more than 6,000 pools associated with Uniswap v3, implying that empirical investigations on the full ecosystem can easily become computationally expensive. Thus, we propose a systematic workflow to extract an…
Deborah Miori, Mihai Cucuringu
arXiv · arXiv · 2026
Decentralized exchanges record trading and liquidity provision on public blockchains, but empirical analysis requires interpreting these records and linking them to execution metadata. dexamine is a Python package that parses Uniswap v2 and v3 events on Ethereum. It converts transaction receipt logs into observations of trades and liquidity changes, with token quantities, pool state, transaction order, and gas inform…
Magnus Hansson