The paper models insurance market dynamics under uncertainty and financial frictions.
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Study shows GPT's earnings forecasts are human-like but not always accurate.
Model explains capital allocation and wealth distribution dynamics in a frictional economy.
We study long-term growth-optimal strategies on a simple market with linear proportional transaction costs. We show that several problems of this sort can be solved in closed form, and explicit the non-analytic dependance of optimal strategies and expected frictional losses of the friction parameter. We present one der…
The existence of time-lagged cross-correlations between the returns of a pair of assets, which is known as the lead-lag relationship, is a well-known stylized fact in financial econometrics. Recently some continuous-time models have been proposed to take account of the lead-lag relationship. Such a model does not follo…
The paper optimizes forecasting for risk-adjusted decisions under trading frictions.
Deep learning solves and estimates complex financial models.
Machine Learning improves macroeconomic forecasting by capturing nonlinearities.
This paper explores how decentralized finance mitigates traditional finance's shortcomings.
Generative model creates frictional surfaces from friction laws.
We prove the superhedging duality for a discrete-time financial market with proportional transaction costs under model uncertainty. Frictions are modeled through solvency cones as in the original model of [Kabanov, Y., Hedging and liquidation under transaction costs in currency markets. Fin. Stoch., 3(2):237-248, 1999]…
We propose a simple non-equilibrium model of a financial market as an open system with a possible exchange of money with an outside world and market frictions (trade impacts) incorporated into asset price dynamics via a feedback mechanism. Using a linear market impact model, this produces a non-linear two-parametric ex…
We discuss the no-arbitrage conditions in a general framework for discrete-time models of financial markets with proportional transaction costs and general information structure. We extend the results of Kabanov and al. (2002), Kabanov and al. (2003) and Schachermayer (2004) to the case where bid-ask spreads are not kn…
Unified asymptotics for investment in markets with transaction costs and search frictions.
Deep Bellman Hedging uses reinforcement learning to optimize financial portfolio hedging.
Market trade-routes can support infectious-disease transmission, impacting biological populations and even disrupting causal trade. Epidemiological models increasingly account for reductions in infectious contact, such as risk-aversion behaviour in response to pathogen outbreaks. However, market dynamics clearly differ…
The objective of this paper is to provide a comprehensive study no-arbitrage pricing of financial derivatives in the presence of funding costs, the counterparty credit risk and market frictions affecting the trading mechanism, such as collateralization and capital requirements. To achieve our goals, we extend in severa…
We study a robust stochastic optimization problem in the quasi-sure setting in discrete-time. We show that under a lineality-type condition the problem admits a maximizer. This condition is implied by the no-arbitrage condition in models of financial markets. As a corollary, we obtain existence of an utility maximizer …
LLMs improve stock price forecasting from financial news and reports.
In this paper, the problem of road friction prediction from a fleet of connected vehicles is investigated. A framework is proposed to predict the road friction level using both historical friction data from the connected cars and data from weather stations, and comparative results from different methods are presented. …
Study tests how U.S. equity prices align with global asset frequencies using financial variables.
We provide a Fundamental Theorem of Asset Pricing and a Superhedging Theorem for a model independent discrete time financial market with proportional transaction costs. We consider a probability-free version of the Robust No Arbitrage condition introduced in Schachermayer ['04] and show that this is equivalent to the e…
We show that for a certain class of dynamics at the nodes the response of a network of any topology to arbitrary inputs is defined in a simple way by its response to a monotone input. The nodes may have either a discrete or continuous set of states and there is no limit on the complexity of the network. The results pro…
Model analyzes trading frictions in cap-and-trade markets, showing how they interact to affect market effectiveness.
We study a variant of the martingale optimal transport problem in a multi-period setting to derive robust price bounds of a financial derivative. On top of marginal and martingale constraints, we introduce a time-homogeneity assumption, which restricts the variability of the forward-looking transitions of the martingal…
In a continuous-time model with multiple assets described by càdlàg processes, this paper characterizes superhedging prices, absence of arbitrage, and utility maximizing strategies, under general frictions that make execution prices arbitrarily unfavorable for high trading intensity. Such frictions induce a duality bet…
Novel signature approach for pricing and hedging path-dependent options with market frictions.
Generative model solves financial market equilibria with stable reinforcement learning.
Develops a new essential supremum concept for financial models.
Study financial contracts pricing in markets with nonproportional costs and constraints.
Motivated by applications to bond markets, we propose a multivariate framework for discrete time financial markets with proportional transaction costs and a countable infinite number of tradable assets. We show that the no-arbitrage of second kind property (NA2 in short), recently introduced by Rasonyi for finite-dimen…
Investment and insurance decisions are studied in a model with nonlinear portfolio frictions and background risk.
Study finds cryptoasset markets inefficient due to capital reallocation frictions.
The aim of this work is to extend the capital growth theory developed by Kelly, Breiman, Cover and others to asset market models with transaction costs. We define a natural generalization of the notion of a numeraire portfolio proposed by Long and show how such portfolios can be used for constructing growth-optimal inv…
We propose a new set of stylized facts quantifying the structure of financial markets. The key idea is to study the combined structure of both investment strategies and prices in order to open a qualitatively new level of understanding of financial and economic markets. We study the detailed order flow on the Shenzhen …
New AI models improve financial hedging by reducing shortfall and tail risk.
We investigate the optimal strategy over a finite time horizon for a portfolio of stock and bond and a derivative in an multiplicative Markovian market model with transaction costs (friction). The optimization problem is solved by a Hamilton-Bellman-Jacobi equation, which by the verification theorem has well-behaved so…
Study reveals a hidden cost in derivatives markets through option-implied discount factors.
Since beginning of the 2008 financial crisis almost half a trillion euros have been spent to financially assist EU member states in taxpayer-funded bail-outs. These crisis resolutions are often accompanied by austerity programs causing political and social friction on both domestic and international levels. The questio…
Repo dealers' market power affects bond prices by up to 2 percentage points.
Study on friction forces for nonholonomic systems using affine connections.
Bitcoin's monetary velocity is constrained by network friction, leading to significant utility contraction during shocks.
Benchmarking deep learning models for financial time series, focusing on risk-adjusted performance.
SPAC data shows premium investors get better terms, non-premium get quid pro quo deals.
We study superreplication of European contingent claims in discrete time in a large trader model with market indifference prices recently proposed by Bank and Kramkov. We introduce a suitable notion of efficient friction in this framework, adopting a terminology introduced by Kabanov, Rasonyi, and Stricker in the conte…
New algorithms improve sampling from complex distributions.
Investment strategy optimized in markets with transaction costs and search delays.
Productivity and credit limits affect aggregate production in non-monotonic ways.