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.
Lower bound found for volatility swap in SABR model.
Improved bounds for Black-Scholes volatility lead to faster root-finding.
Sharp bounds on weak convergence rate for rough volatility models.
In this note, Black--Scholes implied volatility is expressed in terms of various optimisation problems. From these representations, upper and lower bounds are derived which hold uniformly across moneyness and call price. Various symmetries of the Black--Scholes formula are exploited to derive new bounds from old. These…
In this paper we derive an easily computed approximation to European basket call prices for a local volatility jump-diffusion model. We apply the asymptotic expansion method to find the approximate value of the lower bound of European basket call prices. If the local volatility function is time independent then there i…
We show that in a large class of stochastic volatility models with additional skew-functions (local-stochastic volatility models) the tails of the cumulative distribution of the log-returns behave as exp(-c|y|), where c is a positive constant depending on time and on model parameters. We obtain this estimate proving a …
New formulation tackles arbitrage in volatile markets using eigenvalue bounds.
The paper reviews recent statistical methods for financial markets, focusing on jumps, volatility, and microstructure noise.
ThiopheneIV is a new solver for implied volatility with proven monotonicity.
The aim of this paper is to study the fast computation of the lower and upper bounds on the value function for utility maximization under the Heston stochastic volatility model with general utility functions. It is well known there is a closed form solution of the HJB equation for power utility due to its homothetic pr…
Researchers develop optimal methods to estimate rough volatility parameters.
Asymptotic analysis of short-maturity options on realized variance in local-stochastic volatility models.
Currency volatility shocks predict lower excess returns, and buying weak transmitters outperforms selling strong ones.
Study finds adding more information to robust option pricing does not improve bounds.
In the paper, we characterize the asymptotic behavior of the implied volatility of a basket call option at large and small strikes in a variety of settings with increasing generality. First, we obtain an asymptotic formula with an error bound for the left wing of the implied volatility, under the assumption that the dy…
Novel method uses Bayesian filters and PCRLB for state estimation of option prices.
Study improves weak error estimates for rough volatility models.
HyFi cryptocurrencies backed by institutions show lower price risk than fully decentralized ones.
Adaptive Heston model calibration using PCRLB and switching filters.
Explicit robust hedging strategies for convex or concave payoffs under a continuous semimartingale model with uncertainty and small transaction costs are constructed. In an asymptotic sense, the upper and lower bounds of the cumulative volatility enable us to super-hedge convex and concave payoffs respectively. The ide…
Maker-taker fees can prevent algorithmic cooperation in market making, but not always.
The study forecasts portfolio volatility using cointegrated asset dynamics.
We study the Heston-Cox-Ingersoll-Ross++ stochastic-local volatility model in the context of foreign exchange markets and propose a Monte Carlo simulation scheme which combines the full truncation Euler scheme for the stochastic volatility component and the stochastic domestic and foreign short interest rates with the …
Adapts Monte Carlo method to price π-options related to maximum drawdown.
The paper analyzes short maturity Asian options using large deviations theory.
Derivatives on the Chicago Board Options Exchange volatility index (VIX) have gained significant popularity over the last decade. The pricing of VIX derivatives involves evaluating the square root of the expected realised variance which cannot be computed by direct Monte Carlo methods. Least squares Monte Carlo methods…
In this paper, we propose the uncertain volatility models with stochastic bounds. Like the regular uncertain volatility models, we know only that the true model lies in a family of progressively measurable and bounded processes, but instead of using two deterministic bounds, the uncertain volatility fluctuates between …
Paper introduces CSIE for estimating stock market volatility.
Study confirms rough volatility in financial data, independent of microstructure noise.
Paper uses ML for high-dimensional option pricing under uncertain volatility model.
DSVM model predicts financial market volatility with better accuracy.
New method estimates convergence bounds for nonlinear Markov chains.
The paper examines sizing strategies for algorithmic trading in volatile markets.
We present a detailed study on the mean first-passage time of volatility processes. We analyze the theoretical expressions based on the most common stochastic volatility models along with empirical results extracted from daily data of major financial indices. We find in all these data sets a very similar behavior that …
Sophisticated volatility models outperform naive portfolio strategies.
When trading incurs proportional costs, leverage can scale an asset's return only up to a maximum multiple, which is sensitive to its volatility and liquidity. In a model with one safe and one risky asset, with constant investment opportunities and proportional costs, we find strategies that maximize long term returns …
Volatility modelling has become a significant area of research within Financial Mathematics. Wiener process driven stochastic volatility models have become popular due their consistency with theoretical arguments and empirical observations. However such models lack the ability to take into account long term and fundame…
Motivated by marginals-mimicking results for Itô processes via SDEs and by their applications to volatility modeling in finance, we discuss the weak convergence of the law of a hypoelliptic diffusions conditioned to belong to a target affine subspace at final time, namely if $X_{\cdot}=(Y_\cd…
We discuss - in what is intended to be a pedagogical fashion - a criterion, which is a lower bound on a certain ratio, for when a stock (or a similar instrument) is not a good investment in the long term, which can happen even if the expected return is positive. The root cause is that prices are positive and have skewe…
We study specific nonlinear transformations of the Black-Scholes implied volatility to show remarkable properties of the volatility surface. Model-free bounds on the implied volatility skew are given. Pricing formulas for the European options which are written in terms of the implied volatility are given. In particular…
Study uses CSIE to estimate portfolio volatility relative to market.
The study extends SPT to account for real-world transaction costs, improving portfolio performance.
We consider an SPDE description of a large portfolio limit model where the underlying asset prices evolve according to certain stochastic volatility models with default upon hitting a lower barrier. The asset prices and their volatilities are correlated via systemic Brownian motions, and the resulting SPDE is defined o…
We present a detailed analysis of \emph{observable} moments based parameter estimators for the Heston SDEs jointly driving the rate of returns and the squared volatilities . Since volatilities are not directly observable, our parameter estimators are constructed from empirical moments of realized volatilitie…
We discuss the possibility of obtaining model-free bounds on volatility derivatives, given present market data in the form of a calibrated local volatility model. A counter-example to a wide-spread conjecture is given.
In order to understand the origin of stock price jumps, we cross-correlate high-frequency time series of stock returns with different news feeds. We find that neither idiosyncratic news nor market wide news can explain the frequency and amplitude of price jumps. We find that the volatility patterns around jumps and aro…
We use a continuous version of the standard deviation premium principle for pricing in incomplete equity markets by assuming that the investor issuing an unhedgeable derivative security requires compensation for this risk in the form of a pre-specified instantaneous Sharpe ratio. First, we apply our method to price opt…
Our model predicts stock market intervals using chaotic fusion and graph convolutional networks.