A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
Generative AI predicts economic activity from corporate transcripts.
Current economic theories miss most of economic dynamics.
Survey finds LLMs match human economic expectations closely.
We provide an economic interpretation of the practice consisting in incorporating risk measures as constraints in a classic expected return maximization problem. For what we call the infimum of expectations class of risk measures, we show that if the decision maker (DM) maximizes the expectation of a random return unde…
Investor expectations shifted pessimistically during the 2020 stock market crash and recovery.
We are in the middle of a complex debate as to whether Economics is really a proper natural science. The 'Discussion & Debate' issue of this Euro. Phys. J. Special Topic volume is: 'Can economics be a Physical Science?' I discuss some aspects here.
New axioms justify ES without NRC, linking it to mean-ES portfolio selection.
Paper formalizes Simon's satisficing through FFSD, proving its equivalence to expected utility theory.
This paper attempts to provide a decision-theoretic foundation for the measurement of economic tail risk, which is not only closely related to utility theory but also relevant to statistical model uncertainty. The main result is that the only risk measures that satisfy a set of economic axioms for the Choquet expected …
Paper proposes a new estimator for nested expectations with faster convergence.
We consider an infinite dimensional optimization problem motivated by mathematical economics. Within the celebrated "Arbitrage Pricing Model", we use probabilistic and functional analytic techniques to show the existence of optimal strategies for investors who maximize their expected utility.
Solves ambiguity in incomplete markets by minimizing price measure entropy.
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…
Economics tool predicts failure times in reliability systems.
Introduces a new price measure and a second-order economic theory for volatility forecasting.
More than thirty years ago, Charnes, Cooper and Schinnar (1976) established an enlightening contact between economic production functions (EPFs) -- a cornerstone of neoclassical economics -- and information theory, showing how a generalization of the Cobb-Douglas production function encodes homogeneous functions. As ex…
In the same way as the Hilbert Program was a response to the foundational crisis of mathematics, this article tries to formulate a research program for the socio-economic sciences. The aim of this contribution is to stimulate research in order to close serious knowledge gaps in mainstream economics that the recent fina…
We study the effects of introducing information inefficiency in a model for a random linear economy with a representative consumer. This is done by considering statistical, instead of classical, economic general equilibria. Employing two different approaches we show that inefficiency increases the consumption set of a …
Bayesian hierarchical models are increasing popular in economics. When using hierarchical models, it is useful not only to calculate posterior expectations, but also to measure the robustness of these expectations to reasonable alternative prior choices. We use variational Bayes and linear response methods to provide f…
Economic factors significantly influence stock returns, as shown by attribution analysis.
In all empirical-network studies, the observed properties of economic networks are informative only if compared with a well-defined null model that can quantitatively predict the behavior of such properties in constrained graphs. However, predictions of the available null-model methods can be derived analytically only …
Understanding cities is central to addressing major global challenges from climate and health to economic resilience. Although increasingly perceived as fundamental socio-economic units, the detailed fabric of urban economic activities is only now accessible to comprehensive analyses with the availability of large data…
Study shows climate change can cause a 'run on fossil fuels' affecting prices and production.
Paper introduces a new method for calibrating ESGs to both historical and forward-looking data.
Study improves stock return prediction by switching between economic states, outperforming traditional methods.
Study shows time-varying stock returns across economic states.
Although not a formal pricing consideration, gap risk or hedging errors are the norm of derivatives businesses. Starting with the gap risk during a margin period of risk of a repurchase agreement (repo), this article extends the Black-Scholes-Merton option pricing framework by introducing a reserve capital approach to …
Optimizes treatment allocation using covariates for better outcomes.
Optimal intervention in economic networks modeled as influence maximization, with hard computational problems.
This paper explores data science applications in economics using a taxonomy of models and hybrid models showing higher accuracy.
Peru's abundant natural resources and friendly trade policies has made the country a major economic player in both South America and the global community. Consequently, exports are playing an increasingly important role in Peru's national economy. Indeed, growing from 13.1% as of 1994, exports now contribute approximat…
The paper gives picture of enrichment to economic and financial system analysis using agent-based models as a form of advanced study for financial economic data post-statistical-data analysis and micro-simulation analysis. Theoretical exploration is carried out by using comparisons of some usual financial economy syste…
In economics literature, it is accepted that all people are rational and they try to maximize their utilities as possible as they can. In addition, economic theories are formed with the assumptions not suitable to real life. For instance, indifference curves are drawn with the assumptions that there are two goods, peop…
Open AI models affect bond yields differently than closed ones.
The paper finds stocks with higher dynamic network risk have lower returns.
GPR ensemble method predicts stock returns efficiently.
This work explains crises in markets without external news using bounded rational agents.
LLMs can predict CFO responses to economic surveys
Framework for optimizing search engine rankings using observational data.
Formalizes vNM utility theorem using Lean 4, proving existence and uniqueness.
The relationship between expectation and price is commonly established with two principles: no-arbitrage, which asserts that both maps are positive; and equivalence, which asserts that the maps share the same null events. Constructed from the Arrow-Debreu securities, classical and quantum models of economics are then d…
ECNNs improve stock market predictions by correcting errors from previous steps.
At what level should government or companies support research? This complex multi-faceted question encompasses such qualitative bonus as satisfying natural human curiosity, the quest for knowledge and the impact on education and culture, but one of its most scrutinized component reduces to the assessment of economic pe…
New methods improve uncertainty in machine learning predictions for asset returns.
The sharp decline in Ireland's economic performance in recent years has coincided with a recent fall in asylum applications. Simultaneously countries such as Switzerland are seeing increases in asylum numbers with evidence for greater numbers of Nigerian applicants, a group that have for some time been the largest nati…
In this paper, we investigate risk minimization problem of derivatives based on non-tradable underlyings by means of dynamic g-expectations which are slight different from conditional g-expectations. In this framework, inspired by [1] and [16], we introduce risk indifference price, marginal risk price and derivative he…
How do we assign value to economic transactions? To answer this question, we must consider whether the value of objects is inherent, is a product of social interaction, or involves other mechanisms. Economic theory predicts that there is an optimal price for any market transaction, and can be observed during auctions o…
Study preferences over uncertain time payments, finds growth-optimality better than expected utility theory.