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arXiv research

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.

168,657 papers · 148 categories

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110220329439 · Jun 202019922001200920172026
48 results for Market parameters

Study improves queue length estimation from connected vehicles by filtering parameters.

problem Large errors in estimated queue lengths at low market penetration rates.
method Used Kalman and Particle filters as multilevel real-time estimators.
result Filters reduce estimation errors and improve accuracy within 15 minutes.

Price fluctuations in financial markets can be characterized by Lévy's stable distribution, which is supported by the generalized central limit system. When the stable parameters were estimated from four different stock markets in long term, they similarly indicated an unique value. On the other hand, when analyzed in …

2017-09-19abs ↗pdf ↗

Investigates optimal consumption and investment strategies in non-Markovian markets with unbounded parameters.

problem Optimal consumption and investment strategies in non-Markovian markets with unbounded parameters.
method Martingale optimal principle and quadratic BSDEs with exponential moment.
result Establishes optimal strategies for consumption and investment.

Unified theory explains market impact using a simplified supply-demand parameter.

problem Understanding the market impact of metaorders and excess volatility.
method Coarse-grained approach with a single parameter ρ to model supply-demand equilibrium and market impact.
result Establishes a connection between excess volatility and order-driven markets through the square-root law.

We consider a market with fractional Brownian motion with stochastic integrals generated by the Riemann sums. We found that this market is arbitrage free if admissible strategies that are using observations with an arbitrarily small delay. Moreover, we found that this approach eliminates the discontinuity of the stocha…

2015-09-22abs ↗pdf ↗

Investment strategies in financial markets can lead to instability due to market impacts.

problem Market impacts make it impossible for investors to accurately optimize their strategies.
method Built an agent-based model with technical analysis strategy agents to investigate optimization instability.
result Investment strategies' parameters never converged but continued to change, leading to unstable market price evolution.

Model financial markets using information theory with a single parameter.

problem Capture the complexity of financial markets with a simple model.
method Derive an idealized model based on four information-theoretic assumptions, minimizing surprisal and divergence.
result The model uses squared radial Ornstein-Uhlenbeck processes for state variables and their sums.

The paper examines utility maximization in markets with hidden Gaussian drift, finding restrictions on model parameters.

problem Utility maximization problems in markets with hidden Gaussian drift mean-reverting processes.
method Derives sufficient conditions for bounded maximum expected utility of terminal wealth for models with full and partial information.
result Restrictions on model parameters for bounded maximum expected utility.

Optimized portfolio management with dynamic market regimes using RL and OC learning.

problem Mean-Variance portfolio optimization in a regime-switching market.
method Reinforcement learning (RL) with Orthogonality Condition (OC) learning for regime-switching market dynamics.
result OC learning outperforms TD learning in simulated and real market scenarios, leading to better portfolio performance.

Study Nash equilibrium in mean field portfolio games with random market parameters.

problem Modeling wealth and relative performance in competitive financial markets.
method Martingale optimality principle approach to characterize Nash equilibrium in mean field FBSDE.
result Unique Nash equilibrium found under weak interaction assumption and market parameters independence.

Prediction problems in finance go beyond estimating the unknown parameters of a model (e.g. of expected returns). This is because such a model would have to include parameters governing the market participants' propensity to change their opinions on the validity of that model. This leads to a well--known circular situa…

2019-06-07abs ↗pdf ↗

New MMM captures hierarchical marketing effects and sign restrictions.

problem Measuring effectiveness of marketing activities with hierarchical structure and sign constraints.
method Proposes a constrained maximum likelihood approach using Hamiltonian Monte Carlo algorithm.
result Demonstrates superior performance on real datasets compared to multi-stage methods.

The study assesses how financial markets' efficiency changed during the COVID-19 crisis.

problem The impact of COVID-19 on financial market efficiency.
method Dynamic estimation method for Hurst exponent and memory parameter using alpha-stable distribution and dependence structure.
result Financial markets' efficiency varied during the COVID-19 crisis, with some indices showing less impact than others.

Dynamics of the major USA market indices DJIA, S&P, Nasdaq, and NYSE is analyzed from the point of view of the random walking problem with two-step correlations of the market moves. The parameters characterizing the stochastic dynamics are determined empirically from the historical quotes for the daily, weekly, and mon…

2001-12-16abs ↗pdf ↗

New model explains market dynamics with phase transitions and non-linear interactions.

problem Understanding complex multi-asset market dynamics with phase transitions.
method Developed a Multi-Asset Non-Equilibrium Skew (MANES) model based on Langevin dynamics and McKean-Vlasov equation.
result The model accurately predicts market returns and phase transitions in both benign and distressed markets.

Paper introduces Market-adaptive Ratio for better portfolio management.

problem Traditional risk-adjusted ratios fail to account for bull and bear markets.
method Integrates ρρ parameter and uses reinforcement learning to adjust portfolio allocations dynamically.
result Market-adaptive Ratio outperforms traditional ratios in bull and bear markets.

A first-order model for a stock market assigns to each stock a return parameter and a variance parameter that depend only on the rank of the stock. A second-order model assigns these parameters based on both the rank and the name of the stock. First- and second-order models exhibit stability properties that make them a…

2013-02-15abs ↗pdf ↗

We analyze a market impact game between nn risk averse agents who compete for liquidity in a market impact model with permanent price impact and additional slippage. Most market parameters, including volatility and drift, are allowed to vary stochastically. Our first main result characterizes the Nash equilibrium in t…

2019-12-19abs ↗pdf ↗

A novel SVR parameter optimization method using GSA outperforms other meta-heuristics in stock market forecasting.

problem Optimizing SVR parameters for reliable regression performance on small sample sizes.
method Golden Sine Algorithm (GSA) for parameter tuning of SVR.
result The GSA-based SVR outperforms eleven other meta-heuristics in terms of accuracy and computing time.

We analyze a negative-parameter variant of the diversity-weighted portfolio studied by Fernholz, Karatzas, and Kardaras (Finance Stoch 9(1):1-27, 2005), which invests in each company a fraction of wealth inversely proportional to the company's market weight (the ratio of its capitalization to that of the entire market)…

2015-04-04abs ↗pdf ↗

Paper establishes MLE consistency for market microstructure models.

problem Estimating parameters in partially observed diffusion models.
method Tractable sufficient condition for MLE consistency based on stationary distribution.
result Maximum likelihood estimators are consistent for market microstructure parameters.

Extended model ensures long-term survival of traders in limited stock market participation.

problem Limited stock market participation and survival of traders over long periods.
method Extended Basak and Cuoco (1998) model with different time-preference coefficients.
result Parameter restrictions ensure long-term survival of traders.

Paper proposes method to calibrate market simulator for various scenarios.

problem Calibrate market simulator to represent different market conditions.
method Two-step method using GAN with self-attention to train discriminator and optimize simulator parameters.
result Demonstrates effectiveness of method in capturing various market scenarios.

Estimates boundaries for acceptable bilateral gamma risk in financial markets.

problem Determining the compensation needed for risky future cash flows to be considered acceptable.
method Statistical inference from market prices and derivatives, using prospect theory.
result Upper and lower boundaries for bilateral gamma risk are estimated and tested against market data.

The study identifies core and satellite segments in the cryptocurrency market.

problem Identifying similar cryptocurrencies for strategic asset allocation.
method Segmentation of the cryptocurrency market using image / pattern recognition methods.
result Core and satellite segments identified in the cryptocurrency market.

In this paper, we present a simple stock market model (the market game) which incorporates, as ab initio dynamics delayed majority dynamics, according to which agents (with heterogeneous strategies and price expectations) are rewarded if their actions at time t are the actions of the majority of agents at time t+1. We …

2003-11-26abs ↗pdf ↗

We consider arbitrage free valuation of European options in Black-Scholes and Merton markets, where the general structure of the market is known, however the specific parameters are not known. In order to reflect this subjective uncertainty of a market participant, we follow a Bayesian approach to option pricing. Here …

2016-02-15abs ↗pdf ↗

We develop a trinomial tree model for pricing perpetual derivatives and European options.

problem Pricing perpetual derivatives and European options in a market with two risky assets and a perpetual derivative of one of them.
method We introduce a recombining trinomial tree model, consider a market with two risky assets and a perpetual derivative, and use a replicating portfolio to price options and generate relationships between risk-neutral and real-world parameters.
result We develop implied parameter surfaces for real-world parameters in the model using historical data.