New method separates model and non-model risks for more practical asset pricing.
problem Asset pricing under model-uncertainty.
method Binary model-risks and constraints over preferences; unique model-risk pricing formula.
result Unique model-risk pricing formula with dynamically conserved constant.
Paper proposes equal risk pricing for financial derivatives using convex risk measures.
problem Equal risk pricing and hedging in financial derivatives with convex risk measures.
method Established that the problem reduces to solving independently hedging problems for writer and buyer with zero initial capital. Provided dynamic programming equations for European and American options under Markovian decompositions of convex risk measures.
result Equal risk pricing leads to more similar and smaller risks for both writer and buyer compared to other pricing methods.
Introduces an unobservable intrinsic electricity price to link storage theory with risk premium.
problem Connecting storage theory with risk premium in electricity markets.
method Introduces an unobservable intrinsic electricity price and derives prices for various contracts.
result Finds an overall negative risk premium in empirical analysis.
This review classifies electricity price models for risk management.
problem Choosing suitable models for risk management in electricity markets.
method Classification of models based on their ability to represent price behavior.
result Helps users select appropriate models for risk management.
The paper studies risk-based prices in financial markets under volatility uncertainty.
problem Risk-based indifference prices in financial markets under volatility uncertainty.
method Asymptotic analysis of risk-based prices in discrete-time financial markets.
result Risk-based prices form a strongly continuous convex monotone semigroup.
Unified Bayesian framework for CAT bond pricing.
problem Uncertainty in catastrophe occurrences and interest rates in CAT bond markets.
method Bayesian framework based on uncertainty quantification of catastrophes and interest rates.
result Unified asset pricing approach with informative expected risk premia.
Paper proposes an analytical pricing model for puttable bonds with credit risk.
problem Analytical pricing of puttable bonds with credit risk.
method Developed a 2-factor structural PDE model and derived analytical pricing formula under specific conditions.
result Derived analytical pricing formula for puttable bonds with credit risk.
The paper examines variable annuities pricing and risk management using the Black-Scholes model and identifies key risk drivers.
problem Model risk in pricing and managing variable annuities using the Black-Scholes model.
method Derives a model-free decomposition of variable annuity prices and investigates hedging strategies.
result The spot price risk can always be eliminated by the BS-based hedging strategy, but there is gradual slippage and instantaneous leakage.
The paper extends the market price of risk for electricity swap contracts, incorporating jump risk.
problem Pricing electricity swap contracts with consideration of jump risk.
method Introducing a Merton type model with jumps and transferring to the physical measure, comparing arithmetic and geometric averaging.
result A decomposition of swap's market price of risk into classical and market price of risk components.
New financial model revises risk measure under NA condition.
problem Revising classical financial mathematics with coherent risk measure on L0. method Developed a new version of the fundamental theorem of asset pricing and provided dual representations.
result Set of risk-hedging prices is closed under NA condition.
Analyzes how rough volatility affects stock pricing and risk premium.
problem Impact of non-deterministic volatility risk on stock pricing.
method Rough volatility model under historical measure, analysis of stochastic volatility risk.
result Impact of non-deterministic volatility risk on pricing is significant.
New model explains option pricing with time-varying volatility risk aversion.
problem Time variations in the shape of the pricing kernel.
method Introduced a pricing kernel with time-varying volatility risk aversion combined with Heston-Nandi GARCH model.
result Variance risk ratio (VRR) emerges as a key variable in option pricing.
The paper defines and implements risk-indifference pricing for American-style contingent claims.
problem Pricing American-style contingent claims under uncertainty.
method Indifference pricing using convex risk measures and stochastic volatility models, with numerical solutions via deep learning.
result Characterization of indifference prices via Backward Stochastic Differential Equations (BSDEs).
Model for hedging price and quantity risks in electricity markets.
problem Hedging risks for energy retailers in a regulated electricity market.
method Closed-form solution for optimal portfolio using financial instruments based on price and weather indexes.
result Closed-form solution for mean-var model in discrete setting without distributional assumptions.
Paper proposes a risk-averse approach to energy storage price arbitrage using conformal uncertainty quantification.
problem Inherent volatility and uncertainty of real-time electricity prices create financial risks for storage arbitrage.
method Two-layer prediction model with conformal uncertainty quantification for high coverage of real-time price uncertainty.
result The framework achieves good profit margins with minimal losses, demonstrating effectiveness in real-time market.
Optimizes risk-neutral probabilities for derivative pricing.
problem Deriving bounds on derivative values under multiple risk-neutral scenarios.
method Convex optimization over the set of risk-neutral probability distributions.
result Tractable finite-dimensional optimization problems for pricing.
Study optimal liquidation under high risk aversion and small price impact.
problem Optimal liquidation of options under high risk aversion and linear price impact.
method Analyzes Bachelier model with linear price impact, computes utility indifference prices, and finds asymptotically optimal portfolios.
result Establishes a scaling limit for vanishing price impact and computes corresponding utility indifference prices.
Study utility indifference pricing in a Bachelier model with small linear price impact.
problem Utility indifference pricing in a model with linear price impact.
method Analyzes the Bachelier model with exponential utility indifference prices for vanilla European options.
result Computes the scaling limit of utility indifference prices for a vanishing price impact inversely proportional to risk aversion.
This paper studies the valuation of European contingent claims with short selling bans under the equal risk pricing (ERP) framework proposed in Guo and Zhu (2017) where analytical pricing formulae were derived in the case of monotonic payoffs under risk-neutral measures. We establish a unified framework for this new pr…
Risk hedging can reduce operational costs by adjusting prices and production levels in response to asset price movements.
problem How risk hedging impacts operational decisions in response to asset price movements.
method Developed and solved a risk-management model integrating risk hedging into a price-setting newsvendor problem.
result Hedging generally reduces optimal price and VPQ, but may increase VPQ under certain conditions.
Generative model uses DDPMs for risk-neutral derivative pricing.
problem Derivative pricing using arbitrage-free models.
method Developed a framework using DDPMs to generate risk-neutral asset price dynamics.
result Empirically validated the method for both European and path-dependent derivatives.
This essay quantifies convexities in incomplete markets using entropy, adjusting prices for risk and incompleteness.
problem Quantifying convexities in incomplete markets and adjusting prices for risk and incompleteness.
method Using entropy, the essay quantifies convexities and adjusts prices for risk and incompleteness in incomplete markets.
result A new price principle derived from a log-martingale condition is introduced, matching risk aversion and adjusting for market incompleteness and default risk.
Deep RL solves dynamic risk pricing for complex financial models.
problem Dynamic risk measures in financial derivatives pricing.
method Deterministic actor-critic deep reinforcement learning (ACRL) for time-consistent expectile risk.
result High-quality hedging policies and prices for complex financial instruments.
This study measures price risk aversion using indirect utility functions in a lab experiment.
problem Measuring risk aversion with uncertain prices in experimental economics.
method Using indirect utility functions and a multiple price list method in a lab experiment.
result Price risk aversion is statistically greater than payoff risk aversion.
This paper improves financial derivative pricing by incorporating multiple hedging instruments.
problem Valuation of financial derivatives with multiple hedging instruments.
method Deep hedging algorithm and reinforcement learning to solve global hedging problems.
result Including options as hedging instruments can significantly decrease equal risk prices and market incompleteness.
The paper models and prices cyber insurance risks, distinguishing idiosyncratic, systematic, and systemic risks.
problem Modeling and pricing cyber insurance policies, especially for systemic risks.
method Distinguishes three types of cyber risks and proposes methods for their valuation.
result Complex methods are needed for systemic cyber risks, including risk-neutral valuation and monetary risk measures.
This paper investigates how two important sources of risk -- market tail risk and extreme market volatility risk -- are priced into the cross-section of asset returns across various investment horizons. To identify such risks, we propose a quantile spectral beta representation of risk based on the decomposition of cova…
New method uses non-translation invariant risk measures for fair financial derivative pricing.
problem Inequalities in financial derivative pricing under traditional risk measures.
method Deep reinforcement learning with modified deep hedging algorithm.
result Effective pricing of financial derivatives without price inflation.
New volatility model for option pricing with time-varying risk premium.
problem Volatility risk premium is time-varying and not well captured by existing models.
method Combines Markov switching with Realized GARCH framework to derive a state-dependent pricing kernel.
result The model reduces option pricing errors by 15% or more compared to competing models.
Paper introduces benchmark-neutral pricing for long-term contracts.
problem High prices of long-term contracts under risk-neutral pricing.
method Uses growth optimal portfolio as numeraire and new pricing measure.
result Identifies minimal possible prices for contingent claims.
Introduces an asymmetric model for measuring market risk.
problem Existing models are symmetric and do not account for asymmetric risk.
method Develops an asymmetric capital asset pricing model that considers position-dependent market risk.
result Long positions in Apple stock have lower volatility than the market, contrary to the standard model.
Study proposes a machine learning method to predict stock price crashes based on investor sentiment.
problem Predicting stock price crashes due to investor sentiment.
method Minimum covariance determinant methodology and cross-sectional regression analysis.
result The proposed method effectively captures stock price crash risk and is robust across different firm sizes.
Develops framework for valuing and assessing risk of renewable PPAs.
problem Valuation and risk assessment of non-standard renewable PPAs.
method Formalizes payoff structures, derives fair contract prices, proposes market risk-assessment methodology.
result Fair prices and risk profiles vary across technologies and contractual structures.
Solves ambiguity in incomplete markets by minimizing price measure entropy.
problem Ambiguity in pricing incomplete markets.
method Minimizes the entropy of the price measure from the economic measure, subject to mark-to-market constraints.
result Resolves ambiguity and provides a consistent pricing measure.
Catastrophe risk is a major threat faced by individuals, companies, and entire economies. Catastrophe (CAT) bonds have emerged as a method to offset this risk and a corresponding literature has developed that attempts to provide a market-consistent pricing methodology for these and other long-dated, insurance-type cont…
The paper bounds payoffs and option prices in discrete models.
problem Measuring risk in discrete models and incomplete markets.
method Analytical and simulated bounds for payoff functions and option prices.
result Analytical and simulated bounds for European and American options.
The standard asset pricing models (the CCAPM and the Epstein-Zin non-expected utility model) counterintuitively predict that equilibrium asset prices can rise if the representative agent's risk aversion increases. If the income effect, which implies enhanced saving as a result of an increase in risk aversion, dominates…
Deep learning method for fair derivative pricing.
problem Fair pricing of financial derivatives with hedging.
method Deep reinforcement learning, modified equal risk pricing framework.
result Derivative prices are arbitrage-free and more tractable.
We propose a probabilistic framework for pricing derivatives, which acknowledges that information and beliefs are subjective. Market prices can be translated into implied probabilities. In particular, futures imply returns for these implied probability distributions. We argue that volatility is not risk, but uncertaint…
A statistical decision problem is hidden in the core of option pricing. A simple form for the price C of a European call option is obtained via the minimum Bayes risk, R_B, of a 2-parameter estimation problem, thus justifying calling C Bayes (B-)price. The result provides new insight in option pricing, among others obt…
Study financial contracts pricing in markets with nonproportional costs and constraints.
problem Financial contract pricing in markets with nonproportional transaction costs and portfolio constraints.
method Direct and dual characterization of market-consistent prices with acceptable risk thresholds.
result Extension of the Fundamental Theorem of Asset Pricing to include good deals and scalable good deals.
This paper deals with applications of coherent risk measures to pricing in incomplete markets. Namely, we study the No Good Deals pricing technique based on coherent risk. Two forms of this technique are presented: one defines a good deal as a trade with negative risk; the other one defines a good deal as a trade with …
Paper uses machine learning to uncover nonlinear dynamics in CAT bond pricing.
problem Traditional linear models miss nonlinear relationships in CAT bond pricing.
method Advanced machine learning techniques applied to CAT bond transaction records.
result Machine learning enhances CAT bond pricing accuracy and reveals complex risk interactions.
Is the elasticity of intertemporal substitution (EIS) more or less than one? This question can be answered by confronting theoretical results of asset pricing models with investor behaviour during episodes of stock market panic. If we consider these episodes as periods of high risk aversion, then lower asset prices are…
This paper presents an optimal allocation problem in a financial market with one risk-free and one risky asset, when the market is driven by a stochastic market price of risk. We solve the problem in continuous time, for an investor with a Constant Relative Risk Aversion (CRRA) utility, under two scenarios: when the ma…
Unified framework for ESG-inclusive portfolio optimization and pricing.
problem Incorporating ESG ratings into dynamic asset pricing theory.
method Introducing ESG-valued return as a linear transformation of financial and ESG scores, preserving traditional risk aversion with an ESG affinity parameter.
result Developed a more complex portfolio optimization problem in a space governed by reward, risk, and ESG score.
When investors have heterogeneous attitudes towards risk, it is reasonable to assume that each investor has a pricing kernel, and that these individual pricing kernels are aggregated to form a market pricing kernel. The various investors are then buyers or sellers depending on how their individual pricing kernels compa…
A simple spin system is constructed to simulate dynamics of asset prices and studied numerically. The outcome for the distribution of prices is shown to depend both on the dimension of the system and the introduction of price into the link measure. For dimensions below 2, the associated risk is high and the price distr…