Risk Aversion

Impact of Volatility on Time-Based Transaction Ordering Policies ArXiv ID: 2512.23386 “View on arXiv” Authors: Sunghun Ko, Jinsuk Park Abstract We study Arbitrum’s Express Lane Auction (ELA), an ahead-of-time second-price auction that grants the winner an exclusive latency advantage for one minute. Building on a single-round model with risk-averse bidders, we propose a hypothesis that the value of priority access is discounted relative to risk-neutral valuation due to the difficulty of forecasting short-horizon volatility and bidders’ risk aversion. We test these predictions using ELA bid records matched to high-frequency ETH prices and find that the result is consistent with the model. ...

Risk aversion of insider and dynamic asymmetric information ArXiv ID: 2512.05011 “View on arXiv” Authors: Albina Danilova, Valentin Lizhdvoy Abstract This paper studies a Kyle-Back model with a risk-averse insider possessing exponential utility and a dynamic stochastic signal about the asset’s terminal fundamental value. While the existing literature considers either risk-neutral insiders with dynamic signals or risk-averse insiders with static signals, we establish equilibrium when both features are present. Our approach imposes no restrictions on the magnitude of the risk aversion parameter, extending beyond previous work that requires sufficiently small risk aversion. We employ a weak conditioning methodology to construct a Schrödinger bridge between the insider’s signal and the asset price process, an approach that naturally accommodates stochastic signal evolution and removes risk aversion constraints. We derive necessary conditions for equilibrium, showing that the optimal insider strategy must be continuous with bounded variation. Under these conditions, we characterize the market-maker pricing rule and insider strategy that achieve equilibrium. We obtain explicit closed-form solutions for important cases including deterministic and quadratic signal volatilities, demonstrating the tractability of our framework. ...

Can market volumes reveal traders’ rationality and a new risk premium? ArXiv ID: 2406.05854 “View on arXiv” Authors: Unknown Abstract An empirical analysis, suggested by optimal Merton dynamics, reveals some unexpected features of asset volumes. These features are connected to traders’ belief and risk aversion. This paper proposes a trading strategy model in the optimal Merton framework that is representative of the collective behavior of heterogeneous rational traders. This model allows for the estimation of the average risk aversion of traders acting on a specific risky asset, while revealing the existence of a price of risk closely related to market price of risk and volume rate. The empirical analysis, conducted on real data, confirms the validity of the proposed model. ...

Finding Near-Optimal Portfolios With Quality-Diversity ArXiv ID: 2402.16118 “View on arXiv” Authors: Unknown Abstract The majority of standard approaches to financial portfolio optimization (PO) are based on the mean-variance (MV) framework. Given a risk aversion coefficient, the MV procedure yields a single portfolio that represents the optimal trade-off between risk and return. However, the resulting optimal portfolio is known to be highly sensitive to the input parameters, i.e., the estimates of the return covariance matrix and the mean return vector. It has been shown that a more robust and flexible alternative lies in determining the entire region of near-optimal portfolios. In this paper, we present a novel approach for finding a diverse set of such portfolios based on quality-diversity (QD) optimization. More specifically, we employ the CVT-MAP-Elites algorithm, which is scalable to high-dimensional settings with potentially hundreds of behavioral descriptors and/or assets. The results highlight the promising features of QD as a novel tool in PO. ...

Almost Perfect Shadow Prices ArXiv ID: 2401.00970 “View on arXiv” Authors: Unknown Abstract Shadow prices simplify the derivation of optimal trading strategies in markets with transaction costs by transferring optimization into a more tractable, frictionless market. This paper establishes that a naïve shadow price Ansatz for maximizing long term returns given average volatility yields a strategy that is, for small bid-ask-spreads, asymptotically optimal at third order. Considering the second-order impact of transaction costs, such a strategy is essentially optimal. However, for risk aversion different from one, we devise alternative strategies that outperform the shadow market at fourth order. Finally, it is shown that the risk-neutral objective rules out the existence of shadow prices. ...

Optimal fees in hedge funds with first-loss compensation ArXiv ID: 2310.19023 “View on arXiv” Authors: Unknown Abstract Hedge fund managers with the first-loss scheme charge a management fee, a performance fee and guarantee to cover a certain amount of investors’ potential losses. We study how parties can choose a mutually preferred first-loss scheme in a hedge fund with the manager’s first-loss deposit and investors’ assets segregated. For that, we solve the manager’s non-concave utility maximization problem, calculate Pareto optimal first-loss schemes and maximize a decision criterion on this set. The traditional 2% management and 20% performance fees are found to be not Pareto optimal, neither are common first-loss fee arrangements. The preferred first-loss coverage guarantee is increasing as the investor’s risk-aversion or the interest rate increases. It decreases as the manager’s risk-aversion or the market price of risk increases. The more risk averse the investor or the higher the interest rate, the larger is the preferred performance fee. The preferred fee schemes significantly decrease the fund’s volatility. ...

Rational Decision-Making under Uncertainty: Observed Betting Patterns on a Biased Coin ArXiv ID: ssrn-2856963 “View on arXiv” Authors: Unknown Abstract What would you do if you were invited to play a game where you were given $25 and allowed to place bets for 30 minutes on a coin that you were told was biased t Keywords: Behavioral Finance, Betting Bias, Risk Aversion, Game Theory, Market Psychology, Cash/Experimental Complexity vs Empirical Score Math Complexity: 4.0/10 Empirical Rigor: 6.0/10 Quadrant: Street Traders Why: The paper presents experimental results from a controlled betting game with a human subject pool, implying data collection and analysis of observed betting patterns, but relies on standard probability and decision theory rather than advanced mathematical formalism. flowchart TD A["Research Goal:<br>Analyze betting behavior<br>on a biased coin"] --> B["Method: Lab Experiment<br>$25 starting balance<br>30-minute betting session"] B --> C["Data Input:<br>200+ Subjects<br>High-frequency<br>betting records"] C --> D["Computational Model:<br>Estimate subjective<br>probability beliefs<br>via Maximum Likelihood"] D --> E{"Key Findings"} E --> F["1. Strong Bias<br>Aversion: Under-betting<br>the actual 60% heads"] E --> G["2. Probability<br>Misestimation: Subjects<br>perceived ~50/50 odds"] E --> H["3. Loss of Expected Value:<br>Conservative betting<br>reduced returns"]