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This paper investigates an infinite horizon, discounted, consumption-portfolio problem in a market with one bond, one liquid risky asset, and one illiquid risky asset with proportional transaction costs. We consider an agent with liquidity preference, modeled by a Cobb-Douglas utility function that includes the liquid wealth. We analyze the properties of the value function and divide the solvency region into three re…
We propose a static equilibrium model for limit order book where profit-maximizing investors receive an information signal regarding the liquidation value of the asset and execute via a competitive dealer with random initial inventory, who trades against a competitive limit order book populated by liquidity suppliers. We show that an equilibrium exists for bounded signal distributions, obtain closed form solutions fo…
We consider a stochastic volatility asset price model in which the volatility is the absolute value of a continuous Gaussian process with arbitrary prescribed mean and covariance. By exhibiting a Karhunen-Loève expansion for the integrated variance, and using sharp estimates of the density of a general second-chaos variable, we derive asymptotics for the asset price density for large or small values of the variable, …
In this paper, we investigate the Merton portfolio management problem in the context of non-exponential discounting. This gives rise to time-inconsistency of the decision-maker. If the decision-maker at time t=0 can commit his/her successors, he/she can choose the policy that is optimal from his/her point of view, and constrain the others to abide by it, although they do not see it as optimal for them. If there is no…
An Oracle result is not yet a protocol payout, a redeemable position is not yet collateral in a holder's account, and a redemption event is not a complete measure of economic entitlement. This companion paper develops an event-sourced framework for Polymarket conditions from preparation through protocol finality and observed holder realization. The empirical design uses three Conditional Tokens Framework event famili…
The computation of Black-Scholes implied volatility is a fundamental task in quantitative finance, underpinning option valuation, model calibration and risk management. Although implied volatility is routinely used in practice, the inversion of the Black-Scholes pricing formula remains a challenging numerical problem, particularly in asymptotic regimes corresponding to extreme option prices, strikes or maturities, wh…
We study optimal portfolio and consumption in a regime-switching multi-name credit market with default contagion. Defaults generate portfolio losses and alter the intensities of surviving securities. Under Cobb--Douglas utility, homogeneity reduces the HJB equation to a recursive ODE system indexed by the default states. Solving it backward from the all-default state, we establish existence and uniqueness of positive…
This paper develops an autonomous framework for systematic factor investing via agentic AI. Rather than relying on sequential manual prompts, our approach operationalizes the model as a self-directed engine that endogenously formulates interpretable trading signals. To mitigate data snooping biases, this closed-loop system imposes strict empirical discipline through out-of-sample validation and economic rationale req…
In this paper, we study an intertemporal utility maximization problem in which an investor chooses consumption and portfolio strategies in the presence of a stochastic factor and a no-borrowing constraint. In the spirit of the Kim-Omberg model, the stochastic factor represents the expected excess return of the risky asset. It is perfectly negatively correlated with shocks to the risky asset, and follows an Ornstein-U…
We develop a transparent and fully auditable LLM-based pipeline for macro-financial stress testing, combining structured prompting with optional retrieval of country fundamentals and news. The system generates machine-readable macroeconomic scenarios for the G7, which cover GDP growth, inflation, and policy rates, and are translated into portfolio losses through a factor-based mapping that enables Value-at-Risk and E…
Large language models show promise for financial decision-making, yet deploying them as autonomous trading agents raises fundamental challenges: how to adapt instructions when rewards arrive late and obscured by market noise, how to synthesize heterogeneous information streams into coherent decisions, and how to bridge the gap between model outputs and executable market actions. We present ATLAS (Adaptive Trading wit…
The proliferation of Large Language Models (LLMs) is challenged by hallucinations, critical failure modes where models generate non-factual, nonsensical or unfaithful text. This paper introduces Semantic Divergence Metrics (SDM), a novel lightweight framework for detecting Faithfulness Hallucinations -- events of severe deviations of LLMs responses from input contexts. We focus on a specific implementation of these L…
Investment herding, a phenomenon where households mimic the decisions of others rather than relying on their own analysis, has significant effects on financial markets and household behavior. Excessive investment herding may reduce investments and lead to a depletion of household consumption, which is called the crowding-out effect. While existing research has qualitatively examined the impact of investment herding o…
We investigate the asymptotic behaviour of the Bachelier implied volatility tails, extending the large-strike results established for the Black-Scholes implied volatility. Exploiting the theory of regular variation, we derive explicit expressions for the Bachelier implied volatility in the wings of the smile, directly linking them to the tail decay of the underlying returns' distribution. Furthermore, we establish a …
We argue that the Declarative Self-improving Python (DSPy) optimizers are a way to align the large language model (LLM) prompts and their evaluations to the human annotations. We present a comparative analysis of five teleprompter algorithms, namely, Cooperative Prompt Optimization (COPRO), Multi-Stage Instruction Prompt Optimization (MIPRO), BootstrapFewShot, BootstrapFewShot with Optuna, and K-Nearest Neighbor Few …
In this paper, we study large losses arising from defaults of a credit portfolio. We assume that the portfolio dependence structure is modelled by the Archimedean copula family as opposed to the widely used Gaussian copula. The resulting model is new, and it has the capability of capturing extremal dependence among obligors. We first derive sharp asymptotics for the tail probability of portfolio losses and the expect…
We derive the short-maturity asymptotics for European and VIX option prices in local-stochastic volatility models where the volatility follows a continuous-path Markov process. Both out-of-the-money (OTM) and at-the-money (ATM) asymptotics are considered. Using large deviations theory methods, the asymptotics for the OTM options are expressed as a two-dimensional variational problem, which is reduced to an extremal p…
We focus on a behavioral model, that has been recently proposed in the literature, whose rational can be traced back to the Half-Full/Half-Empty glass metaphor. More precisely, we generalize the Half-Full/Half-Empty approach to the context of positive and negative lotteries and give financial and behavioral interpretations of the Half-Full/Half-Empty parameters. We develop a portfolio selection model based on the Hal…
Chain-of-thought prompting asks the model to emit intermediate reasoning steps before the answer, which reliably lifts arithmetic, symbolic, and multi-hop tasks.
CLIP jointly trains an image encoder and a text encoder so matched image–caption pairs are close in a shared space, enabling zero-shot visual classification by text prompts.
In-context learning is when a frozen language model improves at a task from examples placed in the prompt, without weight updates.
Prompt injection is an attack that inserts instructions into retrieved or user-supplied text so the model obeys the attacker instead of the developer’s system policy.
Household Savings Rate — Aggregate saving that supports or constrains future consumption and risk asset demand.
Retail Sales Growth — Nominal and real consumption momentum, critical for growth and inflation nowcasts.
Unemployment Rate — Labor slack measure tied to wage pressure, consumption resilience, and recession rule signals.
A hostile takeover is an attempt to buy control against the target board’s recommendation — a bid to shareholders, not a negotiated merger.
A mutual fund is an open-end vehicle that deals at end-of-day NAV — no intra-day book, and redemptions can force sales.
Bernie Madoff’s 2008 confession revealed a decades-long Ponzi whose redemption run arrived when the GFC made people ask for cash — fraud that needed a crash to be discovered, not a crash caused by the fraud.
The Panic of 1792 was the first US securities-market crash, after a leveraged attempt to corner federal debt, and the first Treasury-led lender-of-last-resort operation under Hamilton.
A municipal bond is debt of a US state, city, or related authority — often tax-exempt, with credit that is not a Treasury.
The central limit theorem says that sums of many independent, finite-variance shocks look Gaussian — which is why so many models start with a normal, and why they fail when those assumptions fail.
The efficient frontier is the set of mean-variance-optimal portfolios — maximum expected return for each volatility, given the inputs.
Modern portfolio theory is Markowitz mean-variance optimization — diversify covariances, not just names, to get more return per unit of variance.
The central limit theorem says that sums of many independent, finite-variance shocks look Gaussian — which is why so many models start with a normal, and why they fail when those assumptions fail.
Chain-of-thought prompting asks the model to emit intermediate reasoning steps before the answer, which reliably lifts arithmetic, symbolic, and multi-hop tasks.
CLIP jointly trains an image encoder and a text encoder so matched image–caption pairs are close in a shared space, enabling zero-shot visual classification by text prompts.
A hostile takeover is an attempt to buy control against the target board’s recommendation — a bid to shareholders, not a negotiated merger.
Household Savings Rate — Aggregate saving that supports or constrains future consumption and risk asset demand.
In-context learning is when a frozen language model improves at a task from examples placed in the prompt, without weight updates.
Bernie Madoff’s 2008 confession revealed a decades-long Ponzi whose redemption run arrived when the GFC made people ask for cash — fraud that needed a crash to be discovered, not a crash caused by the fraud.
A municipal bond is debt of a US state, city, or related authority — often tax-exempt, with credit that is not a Treasury.
A mutual fund is an open-end vehicle that deals at end-of-day NAV — no intra-day book, and redemptions can force sales.
The Panic of 1792 was the first US securities-market crash, after a leveraged attempt to corner federal debt, and the first Treasury-led lender-of-last-resort operation under Hamilton.
Prompt injection is an attack that inserts instructions into retrieved or user-supplied text so the model obeys the attacker instead of the developer’s system policy.
Retail Sales Growth — Nominal and real consumption momentum, critical for growth and inflation nowcasts.
Unemployment Rate — Labor slack measure tied to wage pressure, consumption resilience, and recession rule signals.