Hasil untuk "q-fin.TR"

Y. Shao, Zhengting Gan, E. Epifanovsky et al.

A summary of the technical advances that are incorporated in the fourth major release of the Q-Chem quantum chemistry program is provided, covering approximately the last seven years. These include developments in density functional theory methods and algorithms, nuclear magnetic resonance (NMR) property evaluation, coupled cluster and perturbation theories, methods for electronically excited and open-shell species, tools for treating extended environments, algorithms for walking on potential surfaces, analysis tools, energy and electron transfer modelling, parallel computing capabilities, and graphical user interfaces. In addition, a selection of example case studies that illustrate these capabilities is given. These include extensive benchmarks of the comparative accuracy of modern density functionals for bonded and non-bonded interactions, tests of attenuated second order Møller–Plesset (MP2) methods for intermolecular interactions, a variety of parallel performance benchmarks, and tests of the accuracy of implicit solvation models. Some specific chemical examples include calculations on the strongly correlated Cr2 dimer, exploring zeolite-catalysed ethane dehydrogenation, energy decomposition analysis of a charged ter-molecular complex arising from glycerol photoionisation, and natural transition orbitals for a Frenkel exciton state in a nine-unit model of a self-assembling nanotube.

Anderson Cs, E. Heeley, Y. Huang et al.

G. B. D. C. K. S. H. A. H. H. Y. A. C. B. S. B. L. C. Aad Abbott Abbott Abeling Abidi Aboulhorma Abramow, G. Aad, B. Abbott et al.

The standard model of particle physics1–4 describes the known fundamental particles and forces that make up our Universe, with the exception of gravity. One of the central features of the standard model is a field that permeates all of space and interacts with fundamental particles5–9. The quantum excitation of this field, known as the Higgs field, manifests itself as the Higgs boson, the only fundamental particle with no spin. In 2012, a particle with properties consistent with the Higgs boson of the standard model was observed by the ATLAS and CMS experiments at the Large Hadron Collider at CERN10,11. Since then, more than 30 times as many Higgs bosons have been recorded by the ATLAS experiment, enabling much more precise measurements and new tests of the theory. Here, on the basis of this larger dataset, we combine an unprecedented number of production and decay processes of the Higgs boson to scrutinize its interactions with elementary particles. Interactions with gluons, photons, and W and Z bosons—the carriers of the strong, electromagnetic and weak forces—are studied in detail. Interactions with three third-generation matter particles (bottom (b) and top (t) quarks, and tau leptons (τ)) are well measured and indications of interactions with a second-generation particle (muons, μ) are emerging. These tests reveal that the Higgs boson discovered ten years ago is remarkably consistent with the predictions of the theory and provide stringent constraints on many models of new phenomena beyond the standard model. Ten years after the discovery of the Higgs boson, the ATLAS experiment at CERN probes its kinematic properties with a significantly larger dataset from 2015–2018 and provides further insights on its interaction with other known particles.

Daniel I. Kaufer, Jeffrey L. Cummings, Jeffrey L. Cummings et al.

U. Bhawandeep, V. Khachatryan, A. Sirunyan et al.

The CMS trigger system must reduce an input data rate from the LHC bunch-crossing frequency of 40 MHz to a rate which will be written to permanent storage. A detailed study has recently been made of the performance of this system. This paper presents key elements of the results obtained and gives details of a draft “trigger table” for the Level-1 Trigger and the High-Level Trigger selection at a “start-up” luminosity of 2× 1033 cm – 2s – 1. High efficiencies for most physics objects are attainable with a selection that remains inclusive and avoids detailed topological or other requirements on the event.

A. Heister, S. Schael, R. Barate et al.

Jin Zhang, Hongling Zou, Q. Qing et al.

A. Sirunyan, A. Tumasyan, W. Adam et al.

This work summarizes and puts in an overall perspective studies done within the compact muon solenoid (CMS) concerning the discovery potential for squarks and gluinos, sleptons, charginos and neutralinos, supersymmetric (SUSY) dark matter, lightest Higgs, sparticle mass determination methods and the detector design optimization in view of SUSY searches. It represents the status of our understanding of these subjects as of summer 1997. As a benchmark we used the minimal supergravity-inspired supersymmetric standard model (mSUGRA) with a stable lightest supersymmetric particle (LSP). Discovery of supersymmetry at the large hadron collider should be relatively straightforward. It may occur through the observation of large excesses of events in missing ET plus jets, or with one or more isolated leptons. An excess of trilepton events or isolated dileptons with missing ET, exhibiting a characteristic signature in the l+l− invariant mass distribution, could also be the first manifestation of SUSY production. Squarks and gluinos can be discovered for masses in excess of 2 TeV. Charginos and neutralinos can be discovered from an excess of events in dilepton or trilepton final states. Inclusive searches can give early indications from their copious production in squark and gluino cascade decays. Indirect evidence for sleptons can also be obtained from inclusive dilepton studies. Isolation requirements and a jet veto would allow detection of both the direct chargino/neutralino production and the directly produced sleptons. Squark and gluino production may also represent a copious source of Higgs bosons through cascade decays. The lightest SUSY Higgs h → b may be reconstructed with a signal/background ratio of order 1 thanks to hard cuts on ETmiss justified by escaping LSPs. The LSP of SUSY models with conserved R-parity represents a very good candidate for cosmological dark matter. The region of parameter space where this is true is well covered by our searches, at least for tanβ = 2. If supersymmetry exists at the electroweak scale, it could hardly escape detection in CMS and the study of supersymmetry will form a central part of our physics program.

A. Sirunyan, A. Tumasyan, W. Adam et al.

New sets of CMS underlying-event parameters (“tunes”) are presented for the pythia8 event generator. These tunes use the NNPDF3.1 parton distribution functions (PDFs) at leading (LO), next-to-leading (NLO), or next-to-next-to-leading (NNLO) orders in perturbative quantum chromodynamics, and the strong coupling evolution at LO or NLO. Measurements of charged-particle multiplicity and transverse momentum densities at various hadron collision energies are fit simultaneously to determine the parameters of the tunes. Comparisons of the predictions of the new tunes are provided for observables sensitive to the event shapes at LEP, global underlying event, soft multiparton interactions, and double-parton scattering contributions. In addition, comparisons are made for observables measured in various specific processes, such as multijet, Drell–Yan, and top quark-antiquark pair production including jet substructure observables. The simulation of the underlying event provided by the new tunes is interfaced to a higher-order matrix-element calculation. For the first time, predictions from pythia8 obtained with tunes based on NLO or NNLO PDFs are shown to reliably describe minimum-bias and underlying-event data with a similar level of agreement to predictions from tunes using LO PDF sets.

M. Ablikim, M. Achasov, P. Adlarson et al.

There has recently been a dramatic renewal of interest in hadron spectroscopy and charm physics. This renaissance has been driven in part by the discovery of a plethora of charmonium-like XYZ states at BESIII and B factories, and the observation of an intriguing proton-antiproton threshold enhancement and the possibly related X(1835) meson state at BESIII, as well as the threshold measurements of charm mesons and charm baryons. We present a detailed survey of the important topics in tau-charm physics and hadron physics that can be further explored at BESIII during the remaining operation period of BEPCII. This survey will help in the optimization of the data-taking plan over the coming years, and provides physics motivation for the possible upgrade of BEPCII to higher luminosity.

G. Ambrosi, Q. An, R. Asfandiyarov et al.

High-energy cosmic-ray electrons and positrons (CREs), which lose energy quickly during their propagation, provide a probe of Galactic high-energy processes and may enable the observation of phenomena such as dark-matter particle annihilation or decay. The CRE spectrum has been measured directly up to approximately 2 teraelectronvolts in previous balloon- or space-borne experiments, and indirectly up to approximately 5 teraelectronvolts using ground-based Cherenkov γ-ray telescope arrays. Evidence for a spectral break in the teraelectronvolt energy range has been provided by indirect measurements, although the results were qualified by sizeable systematic uncertainties. Here we report a direct measurement of CREs in the energy range 25 gigaelectronvolts to 4.6 teraelectronvolts by the Dark Matter Particle Explorer (DAMPE) with unprecedentedly high energy resolution and low background. The largest part of the spectrum can be well fitted by a ‘smoothly broken power-law’ model rather than a single power-law model. The direct detection of a spectral break at about 0.9 teraelectronvolts confirms the evidence found by previous indirect measurements, clarifies the behaviour of the CRE spectrum at energies above 1 teraelectronvolt and sheds light on the physical origin of the sub-teraelectronvolt CREs.

M. Morris, J. Teevan, Katrina Panovich

P. Bolton, Hui Chen, Neng Wang

Julius Graf, Thibaut Mastrolia

In this work, we investigate the market-making problem on a trading session in which a continuous phase on a limit order book is followed by a closing auction. Whereas standard optimal market-making models typically rely on terminal inventory penalties to manage end-of-day risk, ignoring the significant liquidity events available in closing auctions, we propose a Deep Q-Learning framework that explicitly incorporates this mechanism. We introduce a market-making framework designed to explicitly anticipate the closing auction, continuously refining the projected clearing price as the trading session evolves. We develop a generative stochastic market model to simulate the trading session and to emulate the market. Our theoretical model and Deep Q-Learning method is applied on the generator in two settings: (1) when the mid price follows a rough Heston model with generative data from this stochastic model; and (2) when the mid price corresponds to historical data of assets from the S&P 500 index and the performance of our algorithm is compared with classical benchmarks from optimal market making.

E. Seo, L. Cho, Y. Estrin et al.

Darren Shannon, Jin Gong, Barry Sheehan

Public announcement dates are used in the green bond literature to measure equity market reactions to upcoming green bond issues. We find a sizeable number of green bond announcements were pre-dated by anonymous information leakages on the Bloomberg Terminal. From a candidate set of 2,036 'Bloomberg News' and 'Bloomberg First Word' headlines gathered between 2016 and 2022, we identify 259 instances of green bond-related information being released before being publicly announced by the issuing firm. These pre-announcement leaks significantly alter the equity trading dynamics of the issuing firms over intraday and daily event windows. Significant negative abnormal returns and increased trading volumes are observed following news leaks about upcoming green bond issues. These negative investor reactions are concentrated amongst financial firms, and leaks that arrive pre-market or early in market trading. We find equity price movements following news leaks can be explained to a greater degree than following public announcements. Sectoral differences are also observed in the key drivers behind investor reactions to green bond leaks by non-financials (Tobin's Q and free cash flow) and financials (ROA). Our results suggest that information leakages have a strong impact on market behaviour, and should be accounted for in green bond literature. Our findings also have broader ramifications for financial literature going forward. Privileged access to financially material information, courtesy of the ubiquitous use of Bloomberg Terminals by professional investors, highlights the need for event studies to consider wider sets of communication channels to confirm the date at which information first becomes available.

Zhaofeng Zhang

The report goes through the main steps of replicating and improving the article "Adaptive Liquidity Provision in Uniswap V3 with Deep Reinforcement Learning." The replication part includes how to obtain data from the Uniswap Subgraph, details of the implementation, and comments on the results. After the replication, I propose a new structure based on the original model, which combines Mamba with DDQN and a new reward function. In this new structure, I clean the data again and introduce two new baselines for comparison. As a result, although the model has not yet been applied to all datasets, it shows stronger theoretical support than the original model and performs better in some tests.

Tomas Espana, Yadh Hafsi, Fabrizio Lillo et al.

We investigate the use of Reinforcement Learning for the optimal execution of meta-orders, where the objective is to execute incrementally large orders while minimizing implementation shortfall and market impact over an extended period of time. Departing from traditional parametric approaches to price dynamics and impact modeling, we adopt a model-free, data-driven framework. Since policy optimization requires counterfactual feedback that historical data cannot provide, we employ the Queue-Reactive Model to generate realistic and tractable limit order book simulations that encompass transient price impact, and nonlinear and dynamic order flow responses. Methodologically, we train a Double Deep Q-Network agent on a state space comprising time, inventory, price, and depth variables, and evaluate its performance against established benchmarks. Numerical simulation results show that the agent learns a policy that is both strategic and tactical, adapting effectively to order book conditions and outperforming standard approaches across multiple training configurations. These findings provide strong evidence that model-free Reinforcement Learning can yield adaptive and robust solutions to the optimal execution problem.

Di Zhang

Triangular arbitrage is a profitable trading strategy in financial markets that exploits discrepancies in currency exchange rates. Traditional methods for detecting triangular arbitrage opportunities, such as exhaustive search algorithms and linear programming solvers, often suffer from high computational complexity and may miss potential opportunities in dynamic markets. In this paper, we propose a novel approach to triangular arbitrage detection using Graph Neural Networks (GNNs). By representing the currency exchange network as a graph, we leverage the powerful representation and learning capabilities of GNNs to identify profitable arbitrage opportunities more efficiently. Specifically, we formulate the triangular arbitrage problem as a graph-based optimization task and design a GNN architecture that captures the complex relationships between currencies and exchange rates. We introduce a relaxed loss function to enable more flexible learning and integrate Deep Q-Learning principles to optimize the expected returns. Our experiments on a synthetic dataset demonstrate that the proposed GNN-based method achieves a higher average yield with significantly reduced computational time compared to traditional methods. This work highlights the potential of using GNNs for solving optimization problems in finance and provides a promising approach for real-time arbitrage detection in dynamic financial markets.

C. Kelstrup, Dorte B. Bekker-Jensen, T. Arrey et al.