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.
The study finds no evidence of stochastic arbitrage opportunities in S&P 500 index options.
We propose a simple stochastic model of market behavior. Dividing market participants into two groups: trend-followers and fundamentalists, we derive the general form of a stochastic equation of market dynamics. The model has two characteristic time scales: the time of changes of market environment and the characterist…
The study models mortgage prepayment risk using stochastic housing market activity.
The paper analyzes arbitrage theory in a fluctuating market of stochastic dimension.
Investor optimizes worst-case portfolio in uncertain markets.
The paper explores arbitrage opportunities in derivative markets under specific conditions.
Study market-to-book ratios using Stochastic Portfolio Theory.
Study finds optimal retirement timing in uncertain wage scenarios.
Stock price change in financial market occurs through transactions in analogy with diffusion in stochastic physical systems. The analysis of price changes in real markets shows that long-range correlations of price fluctuations largely depend on the number of transactions. We introduce the multiplicative stochastic mod…
In this paper, we employ the Heston stochastic volatility model to describe the stock's volatility and apply the model to derive and analyze the optimal trading strategies for dealers in a security market. We also extend our study to option market making for options written on stocks in the presence of stochastic volat…
Study BSΔE on lattices for asset price analysis.
FinFlowRL learns from experts to optimize financial control in changing markets.
Novel method uses PDifMPs to price American options more accurately.
Optimal market making strategy for electronic markets with persistent order flows.
We present a nonlinear stochastic differential equation (SDE) which mimics the probability density function (PDF) of the return and the power spectrum of the absolute return in financial markets. Absolute return as a measure of market volatility is considered in the proposed model as a long-range memory stochastic vari…
We develop a general term structure framework taking stochastic discontinuities explicitly into account. Stochastic discontinuities are a key feature in interest rate markets, as for example the jumps of the term structures in correspondence to monetary policy meetings of the ECB show. We provide a general analysis of …
Proposes a virtual bidding strategy for electricity markets using stochastic control.
This paper deals with an optimal position management problem for a market maker who has to face uncertain customer order flows in an illiquid market, where the market maker's continuous trading incurs a stochastic linear price impact. Although the execution timing is uncertain, the market maker can also ask its OTC cou…
DSVM model predicts financial market volatility with better accuracy.
Paper models Bitcoin market dynamics using 1+1D field theory.
Develops a stochastic approach to financial market delays.
We analyze a market impact game between 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…
Study forward investment performance in semimartingale markets with stochastic factors.
Enhances swaption modeling with rough stochastic volatility.
Optimizes portfolios with constraints and stochastic factors, deriving explicit solutions.
Study the hedging of cryptocurrency options in a volatile market.
Study optimizes market making in Chinese stock market with stochastic control and scenario analysis.
Model strategic interactions between market makers and traders to optimize execution.
The mathematical model of a linear system with the short memory about own stochastic behavior is proposed. It is assumed that the system is under a continual influence of independent stochastic impulses. In a short memory approximation the expression of the stochastic process is found. An application of the model propo…
We introduce a theory of stochastic integration with respect to a family of semimartingales depending on a continuous parameter, as a mathematical background to the theory of bond markets. We apply our results to the problem of super-replication and utility maximization from terminal wealth in a bond market. Finally, w…
We introduce solvable stochastic dealer models, which can reproduce basic empirical laws of financial markets such as the power law of price change. Starting from the simplest model that is almost equivalent to a Poisson random noise generator, the model becomes fairly realistic by adding only two effects, the self-mod…
Paper uses RL to optimize bid-ask spreads for diverse options.
FinFlowRL combines imitation and reinforcement learning for better financial control.
The paper models battery valuation in intraday electricity markets, incorporating liquidity costs.
This papers addresses the stock option pricing problem in a continuous time market model where there are two stochastic tradable assets, and one of them is selected as a numéraire. It is shown that the presence of arbitrarily small stochastic deviations in the evolution of the numéraire process causes significant chang…
The paper extends macroscopic market making to stochastic games, revealing properties and solving equations.
We derive properties of the cdf of random variables defined as saddle-type points of real valued continuous stochastic processes. This facilitates the derivation of the first-order asymptotic properties of tests for stochastic spanning given some stochastic dominance relation. We define the concept of Markowitz stochas…
Modeling market makers' quoting strategies to understand price impact.
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…
Using agent-based modelling, empirical evidence and physical ideas, such as the energy function and the fact that the phase space must have twice the dimension of the configuration space, we argue that the stochastic differential equations which describe the motion of financial prices with respect to real world probabi…
This paper optimizes portfolio management in incomplete markets with stochastic factors, considering periodic wealth evaluations.
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…
We extend Kirman's model by introducing variable event time scale. The proposed flexible time scale is equivalent to the variable trading activity observed in financial markets. Stochastic version of the extended Kirman's agent based model is compared to the non-linear stochastic models of long-range memory in financia…
Optimizes trading in markets with unpredictable price impacts.
Paper introduces a new volatility model for natural gas markets and discusses swing option pricing.
We combine geometric data analysis and stochastic modeling to describe the collective dynamics of complex systems. As an example we apply this approach to financial data and focus on the non-stationarity of the market correlation structure. We identify the dominating variable and extract its explicit stochastic model. …
Since they were authorized by the U.S. Security and Exchange Commission in 1998, electronic exchanges have boomed, and by 2010 high frequency trading accounted for over 70% of equity trades in the US. Such markets are thought to increase liquidity because of the presence of market makers, who are willing to trade as co…
Hybrid model simulates market dynamics using neural stochastic background traders.