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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.

168,878 papers · 148 categories

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78156234312 · Jun 202019922001200920172026
48 results for short rate explosion

We propose a randomised version of the Heston model-a widely used stochastic volatility model in mathematical finance-assuming that the starting point of the variance process is a random variable. In such a system, we study the small-and large-time behaviours of the implied volatility, and show that the proposed random…

2016-08-25abs ↗pdf ↗

Bayesian model improves categorization of explosions from sparse data.

problem Challenges in categorizing explosions from limited data.
method Bayesian update to Event Categorization Matrix model with Bayesian Decision Theory.
result Consistent gains in overall accuracy and lower false negative rates.

At present, there is an explosion of practical interest in the pricing of interest rate (IR) derivatives. Textbook pricing methods do not take into account the leptokurticity of the underlying IR process. In this paper, such a leptokurtic behaviour is illustrated using LIBOR data, and a possible martingale pricing sche…

2004-01-23abs ↗pdf ↗

Study on VIX options pricing in SABR model, showing infinite prices due to volatility explosion.

problem Infinite VIX futures and call prices due to volatility explosion in SABR model.
method Analyzing SABR model, showing vtv_t as unique solution to diffusion process, proving explosion using Feller test, proposing capped volatility process.
result VIX futures and call prices are infinite for any maturity due to volatility explosion, but capped volatility process mitigates this issue.

In the LIBOR market model, forward interest rates are log-normal under their respective forward measures. This note shows that their distributions under the other forward measures of the tenor structure have approximately log-normal tails.

2010-08-12abs ↗pdf ↗

We consider an interest rate model with log-normally distributed rates in the terminal measure in discrete time. Such models are used in financial practice as parametric versions of the Markov functional model, or as approximations to the log-normal Libor market model. We show that the model has two distinct regimes, a…

2011-04-02abs ↗pdf ↗

We show that the moment explosion time in the rough Heston model [El Euch, Rosenbaum 2016, arxiv:1609.02108] is finite if and only if it is finite for the classical Heston model. Upper and lower bounds for the explosion time are established, as well as an algorithm to compute the explosion time (under some restrictions…

2018-01-29abs ↗pdf ↗

Early training phase affects deep neural network optimization and generalization.

problem The choice of learning rate influences generalization in deep learning models.
method Showed that SGD implicitly penalizes the trace of the Fisher Information Matrix (FIM) from the start of training, and explicitly penalizing the trace of FIM improves generalization.
result Catastrophic Fisher explosion (large trace of FIM early in training) is linked to poor generalization.

We present a plausible micro-founded model for the previously postulated power law finite time singular form of the crash hazard rate in the Johansen-Ledoit-Sornette model of rational expectation bubbles. The model is based on a percolation picture of the network of traders and the concept that clusters of connected tr…

2016-01-28abs ↗pdf ↗

Study on martingale property and moment explosions in signature volatility models.

problem Analyzing the martingale property and moment explosions in signature volatility models.
method Fine analysis of the explosion time of a signature stochastic differential equation.
result The price process is a true martingale if and only if the order of the linear form is odd and a correlation parameter is negative.

The paper extends Merton model to price equity warrants under subdiffusive fractional Brownian motion of the short rate.

problem Equity warrant pricing under subdiffusive fractional Brownian motion of the short rate.
method The paper applies subdiffusive mechanism to analyze equity warrant in a fractional Brownian motion environment, deriving a pricing formula for equity warrant.
result The paper provides a pricing formula for equity warrants under subdiffusive fractional Brownian motion model of the short rate.

Classical (Itô diffusions) stochastic volatility models are not able to capture the steepness of small-maturity implied volatility smiles. Jumps, in particular exponential Lévy and affine models, which exhibit small-maturity exploding smiles, have historically been proposed to remedy this (see \cite{Tank} for an overvi…

2015-03-27abs ↗pdf ↗

New models for short rates show longer periods at higher rates.

problem Modeling longer periods of higher interest rates.
method Developed a class of time-homogeneous one-factor Markov diffusion models with specific boundary conditions.
result Explicit expressions for bond prices and transition densities in new probability measure.

Method calibrates local volatility and stochastic short rate models for equity-rate dynamics.

problem Joint calibration of local volatility and stochastic short rate models.
method Iterative approach using semimartingale optimal transport.
result Demonstrated performance on market data using European SPX options and cap interest rate options.

We enhance short-rate models to control implied volatility analytically.

problem Controlling implied volatility in short-rate models.
method Randomized Affine Diffusion (RAnD) method applied to Heath-Jarrow-Morton framework.
result Randomized short-rate models improve calibration and control implied volatility shapes.

It is well known that the Cox-Ingersoll-Ross (CIR) stochastic model to study the term structure of interest rates, as introduced in 1985, is inadequate for modelling the current market environment with negative short interest rates. Moreover, the diffusion term in the rate dynamics goes to zero when short rates are sma…

2018-06-10abs ↗pdf ↗

In the context of multi-curve modeling we consider a two-curve setup, with one curve for discounting (OIS swap curve) and one for generating future cash flows (LIBOR for a give tenor). Within this context we present an approach for the clean-valuation pricing of FRAs and CAPs (linear and nonlinear derivatives) with one…

2014-01-21abs ↗pdf ↗

We study convexity and monotonicity properties for prices of bonds and bond options when the short rate is modeled by a diffusion process. We provide conditions under which convexity of the price in the short rate is guaranteed. Under these conditions the price is decreasing in the drift and increasing in the volatilit…

2007-02-15abs ↗pdf ↗

We extend Dupire's formula for stochastic interest rates and local volatility.

problem Deriving formulas for stochastic interest rates and local volatility.
method Generalizations of Dupire's formula for stochastic drift and local volatility.
result Validated the limits of the generalized Dupire formulae for specific cases.

We consider a short rate model, driven by a stochastic process on the cone of positive semidefinite matrices. We derive sufficient conditions ensuring that the model replicates normal, inverse or humped yield curves.

2012-03-25abs ↗pdf ↗

We introduce Dirac processes, using Dirac delta functions, for short-rate-type pricing of financial derivatives. Dirac processes add spikes to the existing building blocks of diffusions and jumps. Dirac processes are Generalized Processes, which have not been used directly before because the dollar value of non-Real nu…

2015-04-17abs ↗pdf ↗

Stochastic gradient methods are dominant in nonconvex optimization especially for deep models but have low asymptotical convergence due to the fixed smoothness. To address this problem, we propose a simple yet effective method for improving stochastic gradient methods named predictive local smoothness (PLS). First, we …

2018-05-23abs ↗pdf ↗

Noise injection before gradient steps helps in regularization for neural networks.

problem Improving generalization in overparametrized neural networks.
method Injecting small noise perturbations before computing gradient steps, especially in layer-wise fashion.
result Small noise perturbations can explicitly regularize neural networks without variance explosion.

We discuss a simple extension of the Ho and Lee model with generic time-dependent drift in which: 1) we compute bond prices analytically; 2) the yield curve is sensible and the asymptotic yield is positive; and 3) our analytical solution provides a clean and simple way of separating volatility from the drift in the sho…

2015-02-21abs ↗pdf ↗

We consider the stochastic volatility model dSt=σtStdWt,dσt=ωσtdZtdS_t = σ_t S_t dW_t,dσ_t = ωσ_t dZ_t, with (Wt,Zt)(W_t,Z_t) uncorrelated standard Brownian motions. This is a special case of the Hull-White and the β=1β=1 (log-normal) SABR model, which are widely used in financial practice. We study the properties of this model, discretized in …

2017-07-04abs ↗pdf ↗

RNN beats Lee-Carter in forecasting mortality rates.

problem Forecasting mortality rates across different demographics.
method Long Short-Term Memory (LSTM) recurrent neural network trained on multiple countries, ages, and sexes.
result RNN model outperforms the Lee-Carter model in mortality rate forecasting.