SlideVaR balances risk and prudence by considering variable investor attitudes.
problem Finding a risk measure that reflects variable investor attitudes and market changes.
method Introducing SlideVaR, a new risk measure that considers risk-tail regions and sub-additivity.
result SlideVaR outperforms traditional measures in markets with frequent state changes.
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…
New concept of attitude towards probability introduced in risk sharing problems.
problem Risk sharing problems and attitudes towards probability.
method Generalized definition of probability premium, local approximation, rank-dependent utility model, dual theory.
result Attitude towards probability can be first-order or second-order, depending on the model.
Examines optimal risk sharing with realistic risk attitudes, finding risk seeking in certain subdomains.
problem Optimal risk sharing with empirically realistic risk attitudes.
method Allows for risk-seeking agents, generalizes expected utility, and uses counter-monotonic improvement theorem.
result First empirical results on optimal risk sharing with realistic risk attitudes.
Optimal risk sharing found for heterogeneous risk attitudes using distortion risk measures.
problem Risk sharing in economies with diverse risk attitudes.
method Modeling preferences with distortion risk measures, using comonotonic and counter-monotonic principles.
result Optimal risk sharing strategies identified based on risk attitudes, reducing the n-agent problem to a two-agent formulation. 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.
Study analyzes gambling behavior and risk attitudes using blockchain data.
problem Lack of real-life gambling data for validating predictions and experimental findings.
method Collects and analyzes betting data from a decentralized application on the Ethereum Blockchain.
result Empirical examples of gambling systems and insights into risk preferences.
Empirical evidence supports new financial market definitions.
problem Investor risk attitudes in financial markets.
method Developed a new method to analyze risk attitudes.
result Risk-averse behavior in equity investors, risk-loving behavior in risk-free asset investors.
Solves equity premium puzzle with time-varying variables.
problem Equity premium puzzle.
method Consumption Capital Asset Pricing Model with time-varying subjective time discount factors.
result Calculated coefficient of relative risk aversion (CRRA) is around 4.40.
We provide foundations for decisions in face of unlikely events by extending the standard framework of Savage to include preferences indexed by a family of events. We derive a subjective lexicographic expected utility representation which allows for infinitely many lexicographically ordered levels of events and for eve…
A new insurance and reinsurance pricing scheme based on realized loss.
problem Determining fair and risk-adjusted insurance premiums.
method Performance-based variable premium scheme with random initial premium adjusted based on realized loss.
result The variable premium scheme reduces reinsurer's total risk exposure compared to expected-value premium.
Little is known about how different types of advertising affect brand attitudes. We investigate the relationships between three brand attitude variables (perceived quality, perceived value and recent satisfaction) and three types of advertising (national traditional, local traditional and digital). The data represent t…
Solves the equity premium puzzle without calibrated values.
problem Equity premium puzzle in finance.
method Derived new model from 4 different equations, found subjective time discount factor and coefficient of relative risk aversion.
result Calculated values and risk attitude determination align with empirical literature.
In decision under risk, the primal moments of mean and variance play a central role to define the local index of absolute risk aversion. In this paper, we show that in canonical non-EU models dual moments have to be used instead of, or on par with, their primal counterparts to obtain an equivalent index of absolute ris…
Model-free preference under ambiguity defined and applied.
problem Understanding and quantifying ambiguity aversion and prudence.
method Introduces a new model-free definition of ambiguity attitudes and applies it in various contexts.
result New definition of ambiguity prudence equivalent to specific mathematical functions.
In this paper I show how reliable estimates of the Value of a Statistical Life (VSL) can be obtained using cross sectional data using Garen's instrumental variable (IV) approach. The increase in the range confidence intervals due to the IV setup can be reduced by a factor of 3 by using a proxy to risk attitude. In orde…
This study proves new financial market theorems breaking standard risk definitions.
problem Breaking standard risk definitions in financial markets.
method Presenting proofs for new financial market theorems.
result New definitions are richer and broader than standard ones considering shape.
Researchers quantify risk exposure and sensitivities in financial markets under model uncertainty.
problem Optimizing investment and pricing under model uncertainty in financial markets.
method Distributionally robust optimization, Wasserstein ball, first-order sensitivity analysis.
result Sensitivities of value function, investment policy, and marginal prices to model uncertainty can be non-monotonic.
We study the risk criterion for investments based on the drawdown from the maximal value of the capital in the past. Depending on investor's risk attitude, thus his risk exposure, we find that the distribution of these drawdowns follows a general power law. In particular, if the risk exposure is Kelly-optimal, the expo…
Optimal insurance contracts are designed to screen risk preferences and risk types under asymmetric information.
problem Designing optimal insurance contracts under asymmetric information and risk types.
method Constructing a menu of contracts that maximizes mean-variance utilities, subject to truth-telling constraints.
result Equilibrium contracts exhibit nonlinear pricing with decreasing risk loadings, inducing self-selection.
This paper solves robust utility maximization with unknown claim dependencies.
problem Investor optimizes utility in the presence of an intractable contingent claim.
method Quantile optimization approach, transforming dynamic problem into static concave optimization.
result Optimal payoffs depend on ambiguity attitude, market conditions, and claim characteristics.
Paper tackles optimal policy learning with observational data in multi-action scenarios.
problem Optimal policy learning in multi-action settings with observational data.
method Review of estimation approaches, analysis of risk preference, discussion of potential failures.
result Average regret of a policy with multi-valued treatment is contingent on the decision-maker's attitude towards risk.
LLMs can simulate human investment attitudes based on personality traits.
problem Investigating how LLMs mimic human investment behaviors.
method Simulated investment task using LLM personas with specific Big Five personality profiles.
result LLMs can produce meaningful behavioural differences in investment tasks that align with human traits.
This paper introduces a method to incorporate risk sensitivity in RL using quadratic variation penalties.
problem Risk-sensitive reinforcement learning under entropy regularization.
method Equivalent martingale property and quadratic variation penalty for value process.
result The proposed method improves finite-sample performance in linear-quadratic control problems.
A key issue in the estimation of energy hedges is the hedgers' attitude towards risk which is encapsulated in the form of the hedgers' utility function. However, the literature typically uses only one form of utility function such as the quadratic when estimating hedges. This paper addresses this issue by estimating an…
ANFIS system improves satellite attitude estimation and control.
problem Improving accuracy of satellite attitude estimation and control.
method Adaptive neuro-fuzzy integrated (ANFIS) model for satellite attitude estimation and control.
result ANFIS controller outperforms optimal PID controller in time and smoothness.
Study optimal stopping for group with diverse discount rates using an attitude function.
problem Optimal stopping for a group with diverse discount rates under an aggregation preference.
method Develop iterative approach using consistent planning for time-consistent equilibria.
result Characterize all time-consistent mild equilibria as fixed points of an operator.
Neural networks outperform conventional filters in inertial sensor-based attitude estimation.
problem Limited accuracy in inertial sensor-based attitude estimation due to dynamic and static motion.
method Investigated neural networks versus conventional filters for improving accuracy.
result Neural networks outperform conventional filters only with domain-specific optimizations.
A sliding surface stabilizes rigid body attitude control.
problem Stabilizing rigid body attitude control robustly.
method Proposed sliding surface as Lie subgroup, designed sliding-mode controller.
result Closed-loop system is robust against disturbances and unwinding.
Paper proposes a deep learning method for better IMU gyroscope data.
problem Improving accuracy of IMU gyroscope data for robot orientation estimation.
method Dilated convolution neural network, proper loss function, key points identification.
result Algorithm outperforms state-of-the-art on unseen test sequences.
This paper analyzes a game between insurer and reinsurer under ambiguity and risk aversion, optimizing reinsurance and investment strategies.
problem Optimizing reinsurance and investment strategies in a game between insurer and reinsurer under ambiguity and risk aversion.
method Stackelberg game, α-maxmin mean-variance criterion, Heston's stochastic volatility, Hamilton-Jacobi-Bellman equations, Riccati differential equations. result Excess-of-loss reinsurance is optimal for the insurer, and the equilibrium strategies are determined by specific equations.
Most people are risk-averse (risk-seeking) when they expect to gain (lose). Based on a generalization of ``expected utility theory'' which takes this into account, we introduce an automaton mimicking the dynamics of economic operations. Each operator is characterized by a parameter q which gauges people's attitude unde…
Paper introduces EnDKF for more accurate pose tracking.
problem Accurate pose tracking with directional uncertainty.
method EnDKF integrates unit-quaternion attitude representation for better directional uncertainty capture.
result Significant reduction in error compared to traditional methods.
We present a novel methodology for predicting future outcomes that uses small numbers of individuals participating in an imperfect information market. By determining their risk attitudes and performing a nonlinear aggregation of their predictions, we are able to assess the probability of the future outcome of an uncert…
This paper solves a financial portfolio selection problem in incomplete markets.
problem Portfolio selection in incomplete financial markets with ambiguity.
method Constructing an efficient frontier, simplifying the problem, introducing a new distorted Legendre transformation, and proving the bipolar relation and distorted duality theorem.
result The existence and uniqueness of optimal strategies are shown for different utility functions under specific conditions.
Study risk-sensitive reinforcement learning with entropic risk measures and generative models.
problem Risk-sensitive reinforcement learning in discounted MDPs with recursive entropic risk measures.
method Introduced Model-Based ERM Q-Value Iteration (MB-RS-QVI) and derived PAC bounds on sample complexity for value and policy learning. result PAC bounds show exponential dependence on ∣β∣/(1−γ), with tight bounds in S and A. New framework learns complex AI attitudes from heterogeneous data.
problem Heterogeneous ordinal structure in AI attitudes, poorly captured by existing methods.
method Monotone Gaussian score embedding, BNP complexity discovery, confirmatory fixed-K estimation.
result Reduced holdout MSE by 25.8% over single-graph baseline.
New axioms justify ES without NRC, linking it to mean-ES portfolio selection.
problem Economic axioms for portfolio risk assessment and mean-ES portfolio selection.
method Introducing concentration aversion as an alternative to NRC, establishing axiomatic foundations.
result Concentration aversion uniquely characterizes the family of ES and provides new formulas.
New approach for optimal stopping under model ambiguity, considering agent's attitude towards ambiguity.
problem Optimal stopping under model ambiguity and varying levels of ambiguity aversion.
method Introduces a time-inconsistent stopping problem with an α-maxmin nonlinear expectation and seeks subgame perfect equilibrium policies through fixed-point iterations. result Equilibrium stopping policies can be obtained through fixed-point iteration and vary based on an agent's ambiguity attitude.
Study examines perceptions and attitudes about breast cancer on Twitter.
problem Understanding public perceptions and attitudes towards breast cancer on social media.
method Identified and collected tweets, used topic modeling and sentiment analysis.
result Identified themes and quantified users' perceptions and emotions about breast cancer.
New text as data techniques offer a great promise: the ability to inductively discover measures that are useful for testing social science theories of interest from large collections of text. We introduce a conceptual framework for making causal inferences with discovered measures as a treatment or outcome. Our framewo…
Study optimal portfolios for many players in a market model with random coefficients.
problem Optimal portfolio selection for many players under relative performance criteria in a market model with random coefficients.
method Game theory and stochastic optimal control, focusing on CARA and CRRA risk preferences, and extending to continuum of players.
result Existence of forward Nash equilibrium and mean field equilibrium for the n-agent game and corresponding mean field stochastic optimal control problem.
Experiment shows cognitive biases impact human-AI collaboration, highlighting the need for diverse evaluator samples.
problem Cognitive biases affect human-AI collaboration, leading to suboptimal outcomes.
method Randomized experiment with 2,784 participants, manipulating AI suggestion quality, task burden, and financial incentives.
result Individual attitudes toward AI are the strongest predictor of performance, influencing accuracy and overcorrection.
A new model selects low-carbon mutual funds considering ESG criteria, risk, and investor preferences.
problem Aligning financial investments with a low-carbon economy.
method Tri-criterion portfolio selection model using a preference-based multi-objective genetic algorithm (ev-MOGA).
result The model successfully incorporates carbon risk exposure and loss-adverse attitudes into portfolio construction.
New framework shifts bandit algorithms from expected reward to preference metrics, optimizing mixtures of arms.
problem Traditional bandit algorithms focus on expected rewards, ignoring variability and risk.
method Introduces preference metrics (PMs) and designs algorithms to optimize mixtures of arms.
result Optimal policy selects mixtures of arms based on specific weights, not a single best arm.
In this paper we present an interacting-agent model of stock markets. We describe a stock market through an Ising-like model in order to formulate the tendency of traders getting to be influenced by the other traders' investment attitudes [1], and formulate the traders' decision-making regarding investment as the maxim…
Study incentive efficiency in monopoly insurance markets with hidden information.
problem Maximizing social welfare in a monopoly insurance market with hidden agent types.
method Maximizes social welfare function subject to incentive compatibility and individual rationality constraints.
result Optimal menus of contracts depend on the level of social welfare weight and agent risk attitudes.
Study nonconcave portfolio choice with smooth ambiguity and Bayesian learning.
problem Nonconcave portfolio choice under smooth ambiguity and Bayesian learning.
method Developed a general framework for dynamic, non-concave asset allocation.
result Dynamic consistency achieved through a robust representation.