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.
Optimizes sparse mean-reverting portfolios for higher returns.
The paper values perpetual callable American volatility options using a mean-reverting volatility model.
Modified model prevents volatility from approaching zero.
Optimal timing strategy for mean-reverting price spreads.
Mean-reverting assets are one of the holy grails of financial markets: if such assets existed, they would provide trivially profitable investment strategies for any investor able to trade them, thanks to the knowledge that such assets oscillate predictably around their long term mean. The modus operandi of cointegratio…
Solves optimal control for trading multiple mean-reverting assets.
This paper considers the mean-reverting portfolio design problem arising from statistical arbitrage in the financial markets. The problem is formulated by optimizing a criterion characterizing the mean-reversion strength of the portfolio and taking into consideration the variance of the portfolio and an investment budg…
This paper considers the mean-reverting portfolio design problem arising from statistical arbitrage in the financial markets. We first propose a general problem formulation aimed at finding a portfolio of underlying component assets by optimizing a mean-reversion criterion characterizing the mean-reversion strength, ta…
New GP kernels avoid mean reversion without losing smoothness.
The paper models exchange rate risk premium using mean-reverting dynamics.
Recent empirical studies suggest that the volatilities associated with financial time series exhibit short-range correlations. This entails that the volatility process is very rough and its autocorrelation exhibits sharp decay at the origin. Another classic stylistic feature often assumed for the volatility is that it …
The paper studies efficient simulation methods for financial firm values under fast mean-reverting volatility.
A Monte Carlo method for pairs trading on mean-reverting spreads with Lévy processes.
The log-periodic power law (LPPL) is a model of asset prices during endogenous bubbles. A major open issue is to verify the presence of LPPL in price sequences and to estimate the LPPL parameters. Estimation is complicated by the fact that daily LPPL returns are typically orders of magnitude smaller than measured price…
Investors benefit from long horizons in a market with mean-reverting equity returns.
Trading styles affect long-run variance of asset prices, increasing under trend-following and decreasing under mean-reverting.
The paper solves complex swing option pricing equations with numerical methods.
Paper presents fast methods for pricing energy derivatives using mean-reverting jump-diffusion models.
In this paper we want to exploit further the semi-discrete method appeared in Halidias and Stamatiou (2015). We are interested in the numerical solution of mean reverting CEV processes that appear in financial mathematics models and are described as non negative solutions of certain stochastic differential equations wi…
Study approximates weak error for specific stochastic models with rough and Gaussian mean-reverting volatility.
New numerical method for non-linear asset price model with CEV volatility.
Two new models improve option valuation for negative or mean reverting futures markets.
The present paper introduces a jump-diffusion extension of the classical diffusion default intensity model by means of subordination in the sense of Bochner. We start from the bi-variate process of a diffusion state variable driving default intensity and a default indicator process and time change it wi…
Investors can achieve optimal risk-reward trade-offs with bonds and stocks under mean-reverting stock returns.
Study on market data relaxation and correlations in mean-reverting models.
The paper derives closed-form approximations for mean-reverting SABR models and calibrates them to equity volatilities.
We study an optimization-based approach to con- struct a mean-reverting portfolio of assets. Our objectives are threefold: (1) design a portfolio that is well-represented by an Ornstein-Uhlenbeck process with parameters estimated by maximum likelihood, (2) select portfolios with desirable characteristics of high mean r…
Optimal control models for limit order trading often assume that the underlying asset price is a Brownian motion since they deal with relatively short time scales. The resulting optimal bid and ask limit order prices tend to track the underlying price as one might expect. This is indeed the case with the model of Avell…
A one-factor asset pricing model with an Ornstein--Uhlenbeck process as its state variable is studied under partial information: the mean-reverting level and the mean-reverting speed parameters are modeled as hidden/unobservable stochastic variables. No-arbitrage pricing formulas for derivative securities written on a …
Optimizes trading returns using Hurst exponent and Q-learning.
Modeling horse race betting odds with Ornstein-Uhlenbeck process.
Paper proposes a new method for finding sparse mean reverting portfolios efficiently.
We introduce a class of randomly time-changed fast mean-reverting stochastic volatility models and, using spectral theory and singular perturbation techniques, we derive an approximation for the prices of European options in this setting. Three examples of random time-changes are provided and the implied volatility sur…
We introduce a mean-reverting SDE whose solution is naturally defined on the space of correlation matrices. This SDE can be seen as an extension of the well-known Wright-Fisher diffusion. We provide conditions that ensure weak and strong uniqueness of the SDE, and describe its ergodic limit. We also shed light on a use…
A large class of trading strategies focus on opportunities offered by the yield curve. In particular, a set of yield curve trading strategies are based on the view that the yield curve mean-reverts. Based on these strategies' positive performance, a multiple pairs trading strategy on major currency pairs was implemente…
Study on large portfolio losses with correlated volatility processes converging to a stochastic PDE.
Using spectral decomposition techniques and singular perturbation theory, we develop a systematic method to approximate the prices of a variety of options in a fast mean-reverting stochastic volatility setting. Four examples are provided in order to demonstrate the versatility of our method. These include: European opt…
Optimal control problem for firm cash flow with dividend and capital injection strategies.
Gaussian Processes enhance financial forecasting by predicting mean-reverting time series with probability distributions.
We investigate a generalized stochastic model with the property known as mean reversion, that is, the tendency to relax towards a historical reference level. Besides this property, the dynamics is driven by multiplicative and additive Wiener processes. While the former is modulated by the internal behavior of the syste…
Optimizes trading large volumes of volatile assets with fast mean-reverting volatility.
We propose a multi-scale stochastic volatility model in which a fast mean-reverting factor of volatility is built on top of the Heston stochastic volatility model. A singular pertubative expansion is then used to obtain an approximation for European option prices. The resulting pricing formulas are semi-analytic, in th…
We first investigate the evolution of opening and closing auctions volumes of US equities along the years. We then report dynamical properties of pre-auction periods: the indicative match price is strongly mean-reverting because the imbalance is; the final auction price reacts to a single auction order placement or can…
In this note, we derive the characteristic function expansion for logarithm of the underlying asset price in corrected Heston model as proposed by Fouque and Lorig.
The paper finds optimal levels for traders in mean-reverting markets.
A new model for short rates using pure-jump processes.
The paper analyzes a five-factor capital market model and facilitates exact simulation.
We study several optimal stopping problems that arise from trading a mean-reverting price spread over a finite horizon. Modeling the spread by the Ornstein-Uhlenbeck process, we analyze three different trading strategies: (i) the long-short strategy; (ii) the short-long strategy, and (iii) the chooser strategy, i.e. th…