Decomposes portfolio returns into drift and asset price distribution changes.
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Efficient method for pricing multi-asset options with local volatility.
Study robust hedging and valuation under combined uncertainty about asset price drifts and volatilities.
We investigate the relation between the fair price for European-style vanilla options and the distribution of short-term returns on the underlying asset ignoring transaction and other costs. We compute the risk-neutral probability density conditional on the total variance of the asset's returns when the option expires.…
We study a problem of finding an optimal stopping strategy to liquidate an asset with unknown drift. Taking a Bayesian approach, we model the initial beliefs of an individual about the drift parameter by allowing an arbitrary probability distribution to characterise the uncertainty about the drift parameter. Filtering …
Develops a method to estimate the shadow riskless rate from empirical data.
Study shows price bubbles can exist even with heterogeneous beliefs.
A new stochastic volatility model with quadratic drift prevents moment explosions and preserves stock price martingale property.
In this paper we present a new multi-asset pricing model, which is built upon newly developed families of solvable multi-parameter single-asset diffusions with a nonlinear smile-shaped volatility and an affine drift. Our multi-asset pricing model arises by employing copula methods. In particular, all discounted single-…
Study provides error estimates for approximating game options with diffusion asset prices.
The existence of the pricing kernel is shown to imply the existence of an ambient information process that generates market filtration. This information process consists of a signal component concerning the value of the random variable X that can be interpreted as the timing of future cash demand, and an independent no…
This paper formulates a model of utility for a continuous time framework that captures the decision-maker's concern with ambiguity about both volatility and drift. Corresponding extensions of some basic results in asset pricing theory are presented. First, we derive arbitrage-free pricing rules based on hedging argumen…
Bayesian investor learns unknown asset drift, trades mean-variance optimal portfolio, but policy is robust to observation model distortion.
The paper optimizes portfolios using MACD signals derived from price history.
We consider a general class of continuous asset price models where the drift and the volatility functions, as well as the driving Brownian motions, change at a random time . Under minimal assumptions on the random time and on the driving Brownian motions, we study the behavior of the model in all the filtrations whi…
Paper separates financial time series into fast and slow components.
Two models incorporate market microstructure noise into asset pricing and option valuation.
The target of this paper is to consider model the risky asset price on the financial market under the Knightian uncertainty, and pricing the ask and bid prices of the uncertain risk. We use the nonlinear analysis tool, i.e., G-frame work [26], to construct the model of the risky asset price and bid-ask pricing for the …
Develops a model for bid and ask prices using stochastic control.
Financial contracts with options that allow the holder to extend the contract maturity by paying an additional fixed amount found many applications in finance. Closed-form solutions for the price of these options have appeared in the literature for the case when the contract underlying asset follows a geometric Brownia…
Finite difference approximations to multi-asset American put option price are considered. The assets are modelled as a multi-dimensional diffusion process with variable drift and volatility. Approximation error of order one quarter with respect to the time discretisation parameter and one half with respect to the space…
Extends option pricing framework without risk-free asset using Levy jumps.
Study a financial market with singular drift and no arbitrage, considering jumps and delays.
New model describes asset price dynamics during economic bubbles.
Investment strategy in uncertain markets improved by learning and risk-ambiguity preferences.
Optimal B-robust estimate is constructed for multidimensional parameter in drift coefficient of diffusion type process with small noise. Optimal mean-variance robust (optimal V -robust) trading strategy is find to hedge in mean-variance sense the contingent claim in incomplete financial market with arbitrary informatio…
Study optimizes financial strategies in markets with uncertain drift.
The paper examines utility maximization in markets with hidden Gaussian drift, finding restrictions on model parameters.
In common finance literature, Black-Scholes partial differential equation of option pricing is usually derived with no-arbitrage principle. Considering an asset market, Merton applied the Hamilton-Jacobi-Bellman techniques of his continuous-time consumption-portfolio problem, deriving general equilibrium relationships …
Study on hedging and valuation of basis risk in incomplete markets with partial information.
This paper analyzes microstructure dynamics in coupled markets using CFMMs.
Study optimal asset liquidation under uncertain drift and volatility changes.
Study solves DREs for trading strategies using signals and past prices.
We study time consistent dynamic pricing mechanisms of European contingent claims under uncertainty by using G framework introduced by Peng ([24]). We consider a financial market consisting of a riskless asset and a risky stock with price process modelled by a geometric generalized G-Brownian motion, which features the…
Stability of the utility maximization problem with random endowment and indifference prices is studied for a sequence of financial markets in an incomplete Brownian setting. Our novelty lies in the nonequivalence of markets, in which the volatility of asset prices (as well as the drift) varies. Degeneracies arise from …
Novel method uses PDifMPs to price American options more accurately.
Most models for barrier pricing are designed to let a market maker tune the model-implied covariance between moves in the asset spot price and moves in the implied volatility skew. This is often implemented with a local volatility/stochastic volatility mixture model, where the mixture parameter tunes that covariance. T…
Improved growth strategies by incorporating stochastic factors in asset returns.
We study hedging and pricing of unattainable contingent claims in a non-Markovian regime-switching financial model. Our financial market consists of a bank account and a risky asset whose dynamics are driven by a Brownian motion and a multivariate counting process with stochastic intensities. The interest rate, drift, …
We consider a class of assets whose risk-neutral pricing dynamics are described by an exponential Lévy-type process subject to default. The class of processes we consider features locally-dependent drift, diffusion and default-intensity as well as a locally-dependent Lévy measure. Using techniques from regular perturba…
Framework monitors insurance pricing models for drift and recalibration.
Study analyzes market equilibrium returns with price impact and transaction costs.
In the paper "On Truncated Variation of Brownian Motion with Drift" (Bull. Pol. Acad. Sci. Math. 56 (2008), no.4, 267 - 281) we defined truncated variation of Brownian motion with drift, where is a standard Brownian motion. Truncated variation differs from regular variation by neglect…
In this paper we discuss the optimal liquidation over a finite time horizon until the exit time. The drift and diffusion terms of the asset price are general functions depending on all variables including control and market regime. There is also a local nonlinear transaction cost associated to the liquidation. The mode…
Investors' strategic trading affects asset prices, modeled as a game.
The paper optimizes investment strategies with constraints for life-cycle models.
In quantitative finance, we often model asset prices as semimartingales, with drift, diffusion and jump components. The jump activity index measures the strength of the jumps at high frequencies, and is of interest both in model selection and fitting, and in volatility estimation. In this paper, we give a novel estimat…
Modeling financial bubbles in banking networks affects systemic risk.