Study risk-averse insider's behavior in dynamic signal asset pricing.
problem Analyzing risk-averse insider's dynamic signal in asset pricing.
method Employing a weak conditioning methodology to construct a Schrödinger bridge, deriving necessary conditions for equilibrium.
result Derive explicit closed-form solutions for important cases.
Study on Kyle-Back model with risk aversion and non-Gaussian beliefs.
problem Existence of equilibrium in Kyle's insider trading model.
method Forward-backward system coupled via optimal transport constraint, stochastic representation, well-posedness of solutions.
result Existence and properties of equilibrium for small risk aversion parameter.
Informed traders strategically reveal noisier signals, making prices less responsive to public information.
problem How informed traders strategically reveal signals impacts market prices and utility.
method Modeling a market with an informed trader, an uninformed trader, and liquidity providers, proving equilibrium existence.
result In equilibrium, the insider strategically reveals a noisier signal, making prices less responsive to public information.
A model for insider trading with past price dependencies.
problem Modeling insider trading with past price information.
method Functional Itô calculus for path-dependent price functions.
result Existence of equilibrium conditions for insider trading.
Within the well-known framework of financial portfolio optimization, we analyze the existing relationships between the condition of arbitrage and the utility maximization in presence of \emph{insider information}. We assume that, since the initial time, the information flow is altered by adding the knowledge of an addi…
Extends Kyle model to multiple traders with different time-preference coefficients.
problem Existence and convergence of discrete-time Kyle models with multiple insiders.
method Extends Basak and Cuoco's model to include traders with different time-preference coefficients.
result Parameter restrictions ensure the existence of a Radner equilibrium and long-term survival of traders.
Kyle (1985) builds a pioneering and influential model, in which an insider with long-lived private information submits an optimal order in each period given the market maker's pricing rule. An inconsistency exists to some extent in the sense that the ``constant pricing rule " actually assumes an adaptive expected price…
Study dynamic equilibrium with insider and general uninformed agent preferences.
problem Analyzing asymmetric information and general utility functions in a continuous-time economy.
method Introducing a new method to prove existence of a partial communication equilibrium (PCE) for agents with general utility functions.
result Identify the equilibrium price in the small and large risk aversion limits for agents with power utility.
Forward hedging reshapes incentive provision in firms.
problem How does forward hedging affect incentive provision in firms?
method We consider a CARA framework to jointly characterize optimal production, compensation, and static hedging in equilibrium.
result Delegation and external hedging are partial substitutes, and delegation can increase firm value even when the agent is more risk averse.
We analyze and quantify, in a financial market with parameter uncertainty and for a Constant Relative Risk Aversion investor, the utility effects of two different boundedly rational (i.e., sub-optimal) investment strategies (namely, myopic and unconditional strategies) and compare them between each other and with the u…
Modeling insider trading with transaction costs and fair pricing.
problem Maximizing profits for an informed trader in a market with transaction costs and fair pricing.
method Single auction model and continuous time analogue, analyzing equilibrium behavior with polynomial and differential equations.
result Equilibrium trading strategy and pricing rules are affected by transaction costs, revealing an information gap.
A continuous-path semimartingale market model with wealth processes discounted by a riskless asset is considered. The numeraire portfolio is the unique strictly positive wealth process that, when used as a benchmark to denominate all other wealth, makes all wealth processes local martingales. It is assumed that the num…
MVPI framework optimizes risk in reinforcement learning, improving performance in robot simulations.
problem Optimizing risk in reinforcement learning control problems.
method Mean-Variance Policy Iteration (MVPI) framework for risk-averse control in MDPs.
result Risk-averse TD3 outperforms previous methods in robot simulation tasks.
Different models of capital exchange among economic agents have been proposed recently trying to explain the emergence of Pareto's wealth power law distribution. One important factor to be considered is the existence of risk aversion. In this paper we study a model where agents posses different levels of risk aversion,…
A new algorithm avoids worst-case outcomes in risky contexts.
problem Risk-averse behavior in contextual bandits is challenging.
method Developed a first risk-averse contextual bandit algorithm with online regret guarantees.
result First algorithm with an online regret guarantee for risk-averse contextual bandits.
A new measure quantifies how risk-averse different risk measures are.
problem Measuring the degree of risk aversion among different risk measures.
method Two axioms: normalization and linearity. Two formulas for the functional.
result Quantifies the degree of risk aversion among spectral risk measures.
Robo-advisors estimate clients' risk aversion using interactive questionnaires.
problem Estimating risk aversion of non-expert clients using adaptive questionnaires.
method Model risk aversion with cost functions and spectral risk measures. Use inverse reinforcement learning to design questions maximizing distinguishing power.
result Designing questions by maximizing distinguishing power achieves satisfactory accuracy in learning risk aversion with fewer than 50 questions.
Risk aversion is a key element of utility maximizing hedge strategies; however, it has typically been assigned an arbitrary value in the literature. This paper instead applies a GARCH-in-Mean (GARCH-M) model to estimate a time-varying measure of risk aversion that is based on the observed risk preferences of energy hed…
Modeling informed trading with risk-averse market makers.
problem Understanding informed trading and its impact on market liquidity and risk premia.
method Connections between optimal transport theory and Kyle's model, including new characterizations of profits and duality.
result Liquidity is lower, assets exhibit short-term reversals, and risk premia depend on market maker inventories, which are mean reverting.
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…
Investigates how diversification preferences relate to risk attitudes.
problem Connecting diversification preferences to risk attitudes.
method Analyzes diversification preferences for various pairs of risks under different conditions.
result Diversification preferences for certain pairs of risks imply specific levels of risk aversion.
New insights into risk aversion for complex decision models.
problem Understanding risk aversion in non-monotone decision models.
method Characterization of probabilistic risk aversion for generalized rank-dependent functions.
result Probabilistic risk aversion is determined by the distortion function, which is convex or scaled quantile-spread mixtures.
Unified formula for optimal portfolio under piecewise hyperbolic risk aversion.
problem Optimizing portfolios with piecewise hyperbolic risk aversion utilities.
method Derive a unified closed-form formula for the optimal portfolio.
result Unified formula reflects risk aversion behaviors and risk-taking behaviors.
Investigates a Kyle model with imperfect information and risk aversion.
problem Tackles a Kyle model with imperfect information and risk-averse informed traders.
method Solves an optimal transport problem and a filtering problem under specific measures.
result Constructs an equilibrium for the Gaussian Kyle model with imperfect information and risk aversion.
Deep Hedging learns optimal strategies for various risk levels.
problem Finding optimal hedging policies for diverse risk aversions.
method Continuous Reinforcement Learning with actor-critic algorithm.
result Demonstrated effectiveness in a stochastic volatility model.
Risk-averse reinforcement learning optimizes option hedging.
problem Optimizing option hedging under risk aversion and realistic market conditions.
method Applied Trust Region Volatility Optimization (TRVO) to a vanilla option hedging environment.
result The derived hedging strategy outperforms Black & Scholes and is robust to market variations.
New methods reduce bias in estimating optimality gaps for risk-averse stochastic programs.
problem Optimality gap estimation bias in risk-averse stochastic programs.
method Two independent samples, each estimating a different component of the optimality gap.
result Our method reduces bias in estimating optimality gaps for risk-averse problems.
Paper develops NPG for risk-averse RL with ECRMs, proving global convergence.
problem Ensuring reliable performance in stochastic RL problems with risk-averse policies.
method Developed natural policy gradient updates for ECRMs-based RL problems, proving global optimality and iteration complexity.
result Global convergence of risk-averse NPG algorithm with ECRMs.
Stochastic domains often involve risk-averse decision makers. While recent work has focused on how to model risk in Markov decision processes using risk measures, it has not addressed the problem of solving large risk-averse formulations. In this paper, we propose and analyze a new method for solving large risk-averse …
New MFG model for MV portfolio management with peer-based risk aversion.
problem Time-inconsistent mean-variance portfolio management with peer-based risk aversion.
method Mean-field game, smooth regularization, fixed-point arguments, convergence analysis.
result Existence of mean-field equilibrium in time-inconsistent MFG.
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.
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…
Proposes a method to solve deep neural networks' local minimum problem.
problem Local minimum problem in deep neural networks training.
method Transforms cross-entropy loss into risk-averse error criterion, adjusts RSI, and uses convexity region.
result Trained deep learning machine is expected to be inside a global minimum's attraction basin.
Proposes a new risk measurement method for risk-averse stochastic optimization.
problem Risk-averse stochastic optimization problems.
method Develops a risk measure based on argmin and minimum concepts.
result Guarantees the existence of solutions for the proposed problem.
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.
New model considers wealth and time affecting risk aversion in portfolio selection.
problem Optimal investment strategy and consumption process depend on wealth and future income balance.
method Proposed a new mean-variance-utility framework with time and state-dependent risk aversion, solved using game theory.
result Equilibrium investment and consumption policies derived, aligning with investor behavior.
This paper solves optimal consumption-investment choices with wealth-driven risk aversion using neural networks.
problem Optimal consumption-investment choices under wealth-driven risk aversion.
method Neural network LSTM trained on jump-diffusion model data to optimize investment rate and consumption.
result Neural network approach shows promising results in solving the investment problem.
Spectral risk measures are attractive risk measures as they allow the user to obtain risk measures that reflect their risk-aversion functions. To date there has been very little guidance on the choice of risk-aversion functions underlying spectral risk measures. This paper addresses this issue by examining two popular …
The geometric Lévy model (GLM) is a natural generalisation of the geometric Brownian motion model (GBM) used in the derivation of the Black-Scholes formula. The theory of such models simplifies considerably if one takes a pricing kernel approach. In one dimension, once the underlying Lévy process has been specified, th…
In this paper the fractional trading ansatz of money management is reconsidered with special attention to chance and risk parts in the goal function of the related optimization problem. By changing the goal function with due regards to other risk measures like current drawdowns, the optimal fraction solutions reflect t…
Study shows Skorokhod insider outperforms forward insider in logarithmic utility maximization.
problem Maximizing logarithmic utility for an insider with different anticipating techniques.
method Comparison of Russo-Vallois forward and Skorokhod integrals.
result Skorokhod insider outperforms forward insider in logarithmic utility maximization.
The paper characterizes equilibrium strategies under random risk aversion, showing unique solutions based on risk aversion distribution.
problem Characterizing equilibrium strategies in a continuous-time portfolio selection problem under random risk aversion.
method Provided a complete characterization of all deterministic equilibrium strategies in closed form, analyzing the structure of the solution based on the distribution of random risk aversion.
result The equilibrium is unique (if exists) when the expectation of random risk aversion is finite, but infinite expectation leads to either infinitely many equilibria or a unique trivial one.
Develops optimal uncertainty quantification for risk-averse decision makers.
problem Quantifying prediction uncertainty for risk-sensitive domains.
method Decision-theoretic foundations connecting uncertainty quantification with risk-averse decision-making.
result Risk-Averse Calibration (RAC) algorithm provides optimal prediction sets for risk-averse decision makers.
Paper robustifies reinforcement learning with risk-averse methods.
problem Making predictions robust to changes in system dynamics or rewards.
method Approximates Robust Reinforcement Learning using Φ-divergence and Risk-Averse formulation. result Classical Reinforcement Learning can be robustified using standard deviation penalization.
Network analysis detects insider trading by flagging coordinated trades.
problem Detecting insider trading due to limited labelled data.
method Data-driven network approach using SEC trade data.
result Algorithm identifies insider trading clusters with high accuracy.
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.
This paper unifies risk-averse Thompson sampling for continuous risk functionals.
problem Designing and analyzing risk-averse Thompson sampling algorithms for continuous risk functionals.
method Developed analytical toolkits to prove asymptotically optimal regret bounds for various risk measures.
result Proved asymptotic optimality of ρ-MTS for Bernoulli distributions and a class of risk measures. The study reveals traders' risk aversion and a new risk premium from market volumes.
problem Understanding traders' rationality and risk aversion from market volumes.
method Optimal Merton dynamics model to estimate average risk aversion and price of risk.
result Validation of the proposed trading strategy model on real data.