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.
New simulation shows trading algorithms' performance varies with parallelism.
New method finds better arbitrage opportunities in AMMs.
A new trading model combines GARCH and PPO for better stock trading profits.
Developed scalable ABM for complex financial markets.
Paper uses agent-based simulation to identify investor types in financial markets.
KineticSim accelerates financial market simulations 3406x over CPU.
We implement a master-slave parallel genetic algorithm (PGA) with a bespoke log-likelihood fitness function to identify emergent clusters within price evolutions. We use graphics processing units (GPUs) to implement a PGA and visualise the results using disjoint minimal spanning trees (MSTs). We demonstrate that our GP…
Sequential processing biases asset allocation in artificial stock markets.
AI model predicts stock prices using social media data and hybrid neural networks.
Prediction markets show considerable promise for developing flexible mechanisms for machine learning. Here, machine learning markets for multivariate systems are defined, and a utility-based framework is established for their analysis. This differs from the usual approach of defining static betting functions. It is sho…
Efficiently calibrates SABR/LIBOR models to real market caplets and swaptions data.
The present paper analyses the formal parallelism existing between the laws of thermodynamics and some economic principles. Based on previous works, we shall show how the existence in Economics of principles analogous to those in thermodynamics involves the occurrence of economic events that remind of well-known phenom…
Research predicts money market volume based on capital market and bank rates ratio.
The thermodynamics of markets is analyzed, revealing parallels with thermodynamic laws.
Paper improves financial trading models using GPU parallelism.
Geometric arbitrage theory reformulates a generic asset model possibly allowing for arbitrage by packaging all asset and their forward dynamics into a stochastic principal fibre bundle, with a connection whose parallel transport encodes discounting and portfolio rebalancing, and whose curvature measures, in this geomet…
Study on price fluctuations in NFT market, showing heavy-tailed distributions and long-range memory.
Study shows market quality improves with larger orders, not smaller tick sizes or higher trading frequencies.
A microscopic model is established for financial Brownian motion from the direct observation of the dynamics of high-frequency traders (HFTs) in a foreign exchange market. Furthermore, a theoretical framework parallel to molecular kinetic theory is developed for the systematic description of the financial market from m…
KineticSim: A lightweight, high-performance execution engine for real-time market simulators
This paper examines Bitcoin's price predictability, finding inefficiencies under certain conditions.
There are no solid arguments to sustain that digital currencies are the future of online payments or the disruptive technology that some of its former participants declared when used to face critiques. This paper aims to solve the cryptocurrency puzzle from a behavioral finance perspective by finding the parallelism be…
We propose the development of a prediction market for forecasting prices for "toxic assets" to be transferred from Irish banks to the National Asset Management Agency (NAMA). Such a market allows market participants to assume a stake in a security whose value is tied to a future event. We propose that securities are cr…
A surprising image of the stock market arises if the price time series of all Dow Jones Industrial Average stock components are represented in one chart at once. The chart evolves into a braid representation of the stock market by taking into account only the crossing of stocks and fixing a convention defining overcros…
The relativistic quantum mechanic approach is used to develop a stock market dynamics. The relativistic is conceptional here as the meaning of big external volatility or volatility shock on a financial market. We used a differential geometry approach with the parallel transport of the prices to obtain a direct shift of…
Optimal fees protect passive LPs in AMMs under varying market conditions.
Copulas model cross-product effects in intraday power markets.
Stylized facts can be regarded as constraints for any modeling attempt of price dynamics on a financial market, in that an empirically reasonable model has to reproduce these stylized facts at least qualitatively. The dynamics of market prices is modeled on a macro-level as the result of the dynamic coupling of two dyn…
We empirically study the trading activity in the electronic on-book segment and in the dealership off-book segment of the London Stock Exchange, investigating separately the trading of active market members and of other market participants which are non-members. We find that (i) the volume distribution of off-book tran…
Proposes a framework to adjust quotes for informational risk in markets with informed traders and price-revealing quotes.
Model uses statistical physics principles to predict financial market volatility and returns.
In addressing the question of the time scales characteristic for the market formation, we analyze high frequency tick-by-tick data from the NYSE and from the German market. By using returns on various time scales ranging from seconds or minutes up to two days, we compare magnitude of the largest eigenvalue of the corre…
The study examines cryptocurrency market activity, revealing multifractal inter-transaction times and challenging traditional statistical models.
Neural HMM with AGA captures multi-scale dynamics in financial markets.
Detailed study of multifractal characteristics of the financial time series of asset values and of its returns is performed using a collection of the high frequency Deutsche Aktienindex data. The tail index (), the Renyi exponents based on the box counting algorithm for the graph () and the generalized Hurst ex…
We review the nature of some well-known phenomena such as volatility smiles, convexity adjustments and parallel derivative markets. We propose that the market is incomplete and postulate the existence of intrinsic risks in every contingent claim as a basis for understanding these phenomena. In a continuous time framewo…
All DeFi markets are essentially CFMMs with increasing invariants.
ContestTrade uses competitive teams to improve LLM trading performance.
This paper uses neural networks to predict stock prices more accurately.
GPU computing has become popular in computational finance and many financial institutions are moving their CPU based applications to the GPU platform. Since most Monte Carlo algorithms are embarrassingly parallel, they benefit greatly from parallel implementations, and consequently Monte Carlo has become a focal point …
In the area of traditional physics the atomic nucleus belongs to the most complex systems. It involves essentially all elements that characterize complexity including the most distinctive one whose essence is a permanent coexistence of coherent patterns and of randomness. From a more interdisciplinary perspective, thes…
Recent technological development has enabled researchers to study social phenomena scientifically in detail and financial markets has particularly attracted physicists since the Brownian motion has played the key role as in physics. In our previous report (arXiv:1703.06739; to appear in Phys. Rev. Lett.), we have prese…
Quantum algorithms accelerate financial risk computation.
Modeling horse race betting odds with Ornstein-Uhlenbeck process.
Graph-based approach predicts stock trends using dynamic multi-relational graphs.
New types of machine learning hardware in development and entering the market hold the promise of revolutionizing deep learning in a manner as profound as GPUs. However, existing software frameworks and training algorithms for deep learning have yet to evolve to fully leverage the capability of the new wave of silicon.…
We give a brief introduction to the Gauge Theory of Arbitrage. Treating a calculation of Net Present Values (NPV) and currencies exchanges as a parallel transport in some fibre bundle, we give geometrical interpretation of the interest rate, exchange rates and prices of securities as a proper connection components. Thi…
MoE-F combines LLMs online for better time-series prediction.