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-…
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48 results for “asset price processes”
The paper uses deep learning to detect asset price bubbles in tech stocks.
problem Detecting financial asset price bubbles using deep learning.
method Deep learning techniques applied to call option prices for financial asset bubbles detection.
result The proposed deep learning algorithm provides a theoretical foundation for positive and continuous stochastic asset price processes.
Introduces new financial models using subordinated processes.
problem Modeling asset returns with behavioral finance considerations.
method Introduces multiple internally embedded financial time-clocks, subordinated to Brownian motion, with a behavioral subordinator.
result New log-price process with multiple embedded subordinations, requiring estimation of new parameters.
Study uses deep learning to predict asset prices, finds complex target processes lead to meaningless predictions.
problem Complexity of successful price prediction models hinders understanding.
method Deep learning models for high-frequency price prediction, focusing on volatility and directional prediction.
result Inadequately defined target price process renders predictions meaningless.
Numerical Method for Highly Non-linear Mean-reverting Asset Price Model with CEV-type Processq-fin.RM
New numerical method for non-linear asset price model with CEV volatility.
problem Describing stochastic volatility in asset price dynamics.
method Proposes a mean-reverting theta-rho model with CEV volatility, constructs a truncated EM method.
result Truncated EM solutions can evaluate path-dependent financial products.
Pricing of European basket call option with n-assets and a bond is discussed in this paper, where all prices of n-assets and the bond are driven by Exponential Ornstein-Uhlenbeck processes. The close-form of European basket option pricing formula is derived. Utilizing with 1-order differential approximate numerical sol…
Lévy-Ito Models in Financeq-fin.MF
Models for financial assets with jumps and Brownian motion.
problem Understanding asset prices with jumps and their returns.
method Lévy-Ito models with Brownian motion and Poisson measure.
result Excess return rates calculated for risky assets.
A new method for pricing exchange options under stochastic volatility and jumps.
problem Pricing European and American exchange options with stochastic volatility and jumps.
method Equivalent martingale measure, numeraire choice, integral transforms, Kolmogorov backward equation, integral equations.
result Reduced exchange option pricing to a one-dimensional problem of a call option.
Sequential processing biases asset allocation in artificial stock markets.
problem Systematic bias in asset allocation due to sequential processing of order books.
method Examined the impact of sequential versus parallel clearing mechanisms on multi-asset price dynamics.
result Sequential processing introduces a significant bias affecting the allocation of traders' capital.
A financial market model where agents trade using realistic combinations of buy-and-hold strategies is considered. Minimal assumptions are made on the discounted asset-price process - in particular, the semimartingale property is not assumed. Via a natural market viability assumption, namely, absence of arbitrages of t…
Distributions of assets returns exhibit a slight skewness. In this note we show that our model of endogenous price formation \cite{Reimann2006} creates an asymmetric return distribution if the price dynamics are a process in which consecutive trading periods are dependent from each other in the sense that opening price…
Proves FTAP in markets with or without transaction costs.
problem Applying FTAP to markets with transaction costs.
method Proof based on strict no-arbitrage condition, no concatenation or boundedness properties required.
result FTAP proven for both frictionless and markets with transaction costs.
Backward stochastic difference equations on lattices with application to market equilibrium analysismath.PR
Study BSΔE on lattices for asset price analysis.
problem Optimal investment and market equilibrium analysis in asset price models.
method Backward stochastic difference equations on lattices.
result Applications to optimal investment and market equilibrium analysis.
A heat kernel approach is proposed for the development of a general, flexible, and mathematically tractable asset pricing framework in finite time. The pricing kernel, giving rise to the price system in an incomplete market, is modelled by weighted heat kernels which are driven by multivariate Markov processes and whic…
Investigates price dynamics of two assets with and without bubbles, deriving conditions for equilibrium prices.
problem Understanding price dynamics and bubbles in multi-asset markets.
method Derives sufficient and necessary conditions for average equilibrium price dynamics in a two-asset model.
result Assets with positive average dividends display hump-shaped bubbles, while those with constant fundamental values show misvaluation effects.
We derive behavioral finance option pricing formulas consistent with the rational dynamic asset pricing theory. In the existing behavioral finance option pricing formulas, the price process of the representative agent is not a semimartingale, which leads to arbitrage opportunities for the option seller. In the literatu…
Study determines Lévy exponent from derivative prices.
problem Determine Lévy exponent in asset pricing models.
method Analyzes power-payoff derivatives to infer Lévy exponent structure.
result Lévy exponent can be determined from derivative prices.
Error estimates for discrete approximations of game options with multivariate diffusion asset pricesmath.PR
Study provides error estimates for approximating game options with diffusion asset prices.
problem Approximating fair prices of game options with diffusion asset prices.
method Error estimates for discrete approximations of diffusion processes, applied to game options.
result Effective tool for computing fair prices of game options in multi-asset markets.
In this paper we propose a general derivative pricing framework which employs decoupled time-changed (DTC) Lévy processes to model the underlying asset of contingent claims. A DTC Lévy process is a generalized time-changed Lévy process whose continuous and pure jump parts are allowed to follow separate random time scal…
Option Pricing with Mixed Levy Subordinated Price Process and Implied Probability Weighting Functionq-fin.MF
The paper integrates behavioral finance into asset pricing using subordinated models.
problem Modeling asset returns considering investor behavior and psychological factors.
method Employing subordination to incorporate investor behavior in dynamic asset pricing theory, introducing a mixed Levy subordinated model.
result Option traders overweight the probability of big losses compared to spot traders, showing diminishing sensitivity.
Researchers calculate the price of a perpetual put option in Lévy models.
problem Calculating the price of a perpetual American put option in Lévy models.
method Derive the explicit price using geometric spectrally negative Lévy processes and optimal threshold.
result The optimal exercise time is the first epoch when the asset price drops below an optimal threshold.
This paper proposes to model asset price dynamics with a mixture of diffusion processes where the instantaneous volatility of the underlying diffusion process contains a random vector. The marginal probability distributions of the proposed process can match exactly the risk-neutral distributions implied by both spot va…
Exponential Lévy processes have been used for modelling financial derivatives because of their ability to exhibit many empirical features of markets. Using their multidimensional analogue, a general analytic pricing formula is obtained, allowing for the direct valuation of multi-asset options on $n \in \z^+$ risky asse…
New models explain multidimensional rough volatility from microscopic price dynamics.
problem Designing new rough stochastic volatility models for multi-asset scenarios.
method Using Hawkes processes to model microstructural interactions and investigate scaling limits.
result Multivariate rough volatility models arise naturally from microscopic price dynamics.
Adversarial deep hedging learns to hedge without specifying asset price models.
problem Lack of effective underlying asset models for deep hedging.
method Adversarial learning framework where a hedger and a generator compete to improve hedging performance.
result Adversarial deep hedging achieves competitive performance without explicit asset process modeling.
Information-Based Asset Pricingq-fin.PR
A new framework for asset price dynamics is introduced in which the concept of noisy information about future cash flows is used to derive the price processes. In this framework an asset is defined by its cash-flow structure. Each cash flow is modelled by a random variable that can be expressed as a function of a colle…
Paper analyzes arbitrage in uncertain markets, providing quantitative asset pricing.
problem Dealing with model uncertainty in markets that allow small arbitrage.
method Quantitative analysis of arbitrage, focusing on asset price processes close to martingales.
result Quantitative version of the Fundamental Theorem of Asset Pricing and Super-Replication Theorem.
Since exchange economy considerably varies in the market assets, asset prices have become an attractive research area for investigating and modeling ambiguous and uncertain information in today markets. This paper proposes a new generative uncertainty mechanism based on the Bayesian Inference and Correntropy (BIC) tech…
This paper extends Black-Scholes model for illiquid markets with jumps.
problem Pricing derivative securities in markets with jumps and illiquidity.
method Generalizes Frey-Stremme model for Levy process with jumps, derives nonlinear PDE, proposes numerical scheme.
result Shows influence of large traders and jump intensity on option prices.
The paper models asset pricing with agents having different beliefs and examines the effects of liquidity constraints.
problem Asset pricing with heterogeneous beliefs and illiquidity.
method A tractable model with quadratic costs on inventories and trading rates, characterized by a system of linear parabolic equations.
result The equilibrium price is influenced by holding and liquidity costs, and the asymptotics for small costs provide insights.
This paper develops a pricing model for data assets from the buyer's perspective.
problem Insufficient research on pricing data assets from the buyer's perspective.
method Develops a pricing model based on the informational value of data assets from the buyer's perspective, using an implicit function derived from value functions in investment-consumption problems under ambiguity markets.
result Derives general expressions and explicit pricing formulas for data assets under various conditions.
In usual stochastic volatility models, the process driving the volatility of the asset price evolves according to an autonomous one-dimensional stochastic differential equation. We assume that the coefficients of this equation are smooth. Using Itô's formula, we get rid, in the asset price dynamics, of the stochastic i…
Paper establishes robust asset pricing theorems under uncertainty.
problem Tackles asset pricing in uncertain discrete time settings.
method Introduces a new topological framework for spaces and functional analysis.
result Equivalence of robust no arbitrage condition and robust pricing system existence.
The paper calculates option prices for assets with stochastic volatility using FFT.
problem Calculating option prices for assets with stochastic volatility.
method Assumed normal asset dynamics with stochastic volatility following CIR process. Used FFT for evaluation and compared with Monte Carlo simulation.
result Comparison of FFT and Monte Carlo results for option pricing.
The Kalman filter and Heston model are used to estimate asset prices and trading performance.
problem Estimating asset prices using stochastic models.
method Kalman filter applied to mean-reverting processes and Heston model with method of moments.
result The Kalman filter and Heston model provide effective methods for estimating asset prices and trading performance.
Integrates ESG factors into Bachelier's model for asset pricing.
problem Incorporating ESG factors into classical finance models.
method Defines ESG price process and integrates into Bachelier's model.
result Enables option pricing valuation with ESG factors.
Bayesian model improves asset price forecasting using realized volatility.
problem Improving asset price forecasting accuracy.
method Integrates dynamic gamma process with DLMs for price and realized volatility.
result Significant improvements in asset price forecasting compared to standard models.
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 …
A new framework for asset pricing based on modelling the information available to market participants is presented. Each asset is characterised by the cash flows it generates. Each cash flow is expressed as a function of one or more independent random variables called market factors or "X-factors". Each X-factor is ass…
Extended fundamental theorem of asset pricing with transaction costs.
problem Modeling arbitrage in models with both fixed and proportional transaction costs.
method Introducing a family of measures and an adapted process to extend the fundamental theorem.
result Equivalence between lack of arbitrage and existence of specific probability measures.
New model for electricity pricing captures mean reversion and jumps.
problem Capturing mean reversion and jumps in electricity market prices.
method Exponential functional of a jump Lévy process, partial integro-differential equation (PIDE), finite differences method.
result European option value is the unique viscosity solution of a PIDE.
The study addresses overlooked data-generating processes in time-series asset pricing.
problem The literature on time-series asset pricing overlooks the data-generating processes for factors expressed in return differences.
method The study proposes a new definition of returns and compound returns for factors, and uses OLS with net returns for single-index models.
result OLS with net returns for single-index models leads to inflated alphas, exaggerated t-values, and overestimated Sharpe ratios.
Develops European power option pricing under correlated interest rate and asset processes.
problem Pricing European power options under correlated interest rate and asset processes.
method Martingale method and Girsannov transform.
result Derives European power option pricing formulae under two market assumptions.
New pricing model uses variance-gamma process for financial assets.
problem Traditional pricing models need improvement for complex financial assets.
method Developed a new class of models based on variance-gamma process.
result The new model can price a variety of financial assets effectively.
We derive the price of a spread option based on two assets which follow a bivariate volatility modulated Volterra process dynamics. Such a price dynamics is particularly relevant in energy markets, modelling for example the spot price of power and gas. Volatility modulated Volterra processes are in general not semimart…
It is well documented that a model for the underlying asset price process that seeks to capture the behaviour of the market prices of vanilla options needs to exhibit both diffusion and jump features. In this paper we assume that the asset price process is Markov with cadlag paths and propose a scheme for computing…
Gaussian stochastic volatility models: Scaling regimes, large deviations, and moment explosionsq-fin.MF
Study on Gaussian models reveals moment explosions under certain volatility conditions.
problem Understanding the behavior of asset price processes in Gaussian stochastic volatility models.
method Established large and moderate deviation principles, analyzed exit probabilities, and proved moment explosion results.
result If volatility grows faster than linearly, all moments of order greater than one are infinite for asset price processes.
We provide a critical analysis of the proof of the fundamental theorem of asset pricing given in the paper "Arbitrage and approximate arbitrage: the fundamental theorem of asset pricing" by B. Wong and C.C. Heyde (Stochastics, 2010) in the context of incomplete Itô-process models. We show that their approach can only w…