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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.

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48 results for investment opinion

Optimal investment strategy with expert opinions in uncertain conditions.

problem Optimizing wealth in a model with unobservable drift and costly expert opinions.
method Embedding into a full information problem, using viscosity solutions and stochastic Perron's method.
result Constructing optimal trading and expert opinion strategies under sufficient regularity conditions.

Study optimal investment with herd behavior using rational decision decomposition.

problem Optimal investment problem considering herd behavior between two agents.
method Introduce average deviation term, use variational method, rational decision decomposition, investment opinion.
result Quantitative analysis of herd behavior impact on investment decisions.

The Chain-of-Decision approach improves forecasting of financial professionals' trading decisions.

problem Challenges in forecasting professionals' behaviors, especially in trading decisions.
method Integrates an opinion-generator-in-the-loop to provide subjective analysis based on news items.
result Promising improvements in the proposed tasks' performance.

ChatGPT improves financial reasoning, overcoming biases in gold investment.

problem Improving financial reasoning and overcoming biases in investment decisions.
method Applied advanced prompt engineering and semantic news information to enhance LLMs' performance.
result ChatGPT with CoT prompt provides more explainable predictions and higher investment returns.

Investigates optimal consumption and investment using alternative data sources.

problem Optimal consumption and investment decisions under hidden economic regimes.
method Develops a novel duality theory for a jump-diffusion process with alternative data.
result Provides conditions for using control approach based on dynamic programming.

The availability of data on digital traces is growing to unprecedented sizes, but inferring actionable knowledge from large-scale data is far from being trivial. This is especially important for computational finance, where digital traces of human behavior offer a great potential to drive trading strategies. We contrib…

2015-06-04abs ↗pdf ↗

In an increasingly polarized world, demagogues who reduce complexity down to simple arguments based on emotion are gaining in popularity. Are opinions and online discussions falling into demagoguery? In this work, we aim to provide computational tools to investigate this question and, by doing so, explore the nature an…

2018-02-19abs ↗pdf ↗

The paper introduces a method to incorporate expert opinion on observable quantities into statistical models.

problem Tackling the challenge of integrating expert knowledge on observable quantities into statistical models.
method The approach involves updating a prior belief using a loss function that reflects expert opinion on observable quantities.
result The method allows for a flexible specification of expert opinion and is straightforward to implement.

This paper introduces a new market-based carbon risk measure for portfolio optimization.

problem The challenge of measuring and managing carbon risk in investment portfolios.
method Develops a market-based carbon risk measure and applies it to minimum variance portfolio construction.
result Market-based carbon risk measures can complement fundamental-based approaches in portfolio optimization.

A classification of companies into sectors of the economy is important for macroeconomic analysis and for investments into the sector-specific financial indices and exchange traded funds (ETFs). Major industrial classification systems and financial indices have historically been based on expert opinion and developed ma…

2015-03-20abs ↗pdf ↗

Opinions and beliefs determine the evolution of social systems. This is of particular interest in finance, as the increasing complexity of financial systems is coupled with information overload. Opinion formation, therefore, is not always the result of optimal information processing. On the contrary, agents are bounded…

2014-08-01abs ↗pdf ↗

Crowd opinions in microblogs can predict event outcomes, matching with expert opinions.

problem Utilizing crowd wisdom for event outcome prediction in microblogs.
method Multi-label sentiment classification of tweets to gauge crowd opinion and compare with expert predictions.
result Crowd opinions in microblogs often match with expert opinions, especially in non-debate events.

The paper develops a method for inferring second opinions from experts using counterfactual inference.

problem Designing efficient decision support systems for second opinions.
method Set invariant Gumbel-Max structural causal model for multiclass classification.
result The proposed model can infer second opinions more accurately than non-causal models.

Online reviews have become a vital source of information in purchasing a service (product). Opinion spammers manipulate reviews, affecting the overall perception of the service. A key challenge in detecting opinion spam is obtaining ground truth. Though there exists a large set of reviews online, only a few of them hav…

2019-03-19abs ↗pdf ↗

The kind of realized mission inflows the sensitivity to risk. Among other factors, the risk results from decision about liquid assets investment level and liquid assets financing. The higher the risk exposure, the higher the level of liquid assets. If the specific risk exposure is smaller, the more aggressive could be …

2013-01-16abs ↗pdf ↗

We reformulate the Cont-Bouchaud model of financial markets in terms of classical "super-spins" where the spin value is a measure of the number of individual traders represented by a portfolio manager of an investment agency. We then extend this simplified model by switching on interactions among the super-spins to mod…

1998-10-14abs ↗pdf ↗

SINN combines social science and deep learning for predicting opinion dynamics.

problem Predicting opinion dynamics in social networks using traditional models requires extensive calibration with real data.
method SINN integrates theoretical models and social media data using physics-informed neural networks (PINNs) and matrix factorization.
result SINN outperforms six baseline methods in predicting opinion dynamics on real-world and synthetic datasets.

Well-defined formal definitions for sentiment and opinion are extended to incorporate the necessary elements to provide a formal quantitative definition of reputation. This definition takes the form of a time-based index, in which each element is a function of a collection of opinions mined during a given time period. …

2017-05-28abs ↗pdf ↗

Study shows social reinforcement learning can lead to persistent but metastable polarization.

problem Understanding the persistence and dynamics of opinion polarization.
method Simulation and mathematical analysis of a reinforcement learning model of opinion dynamics.
result Polarization observed in the model is metastable and will eventually lead to consensus.

We propose a simple model for the behaviour of longterm investors on a stock market, consisting of three particles, which represent the current price of the stock and the opinion of the buyers, respectively sellers, about the right trading price. As time evolves, both groups of traders update their opinions with respec…

2008-03-25abs ↗pdf ↗

Georgia's pension reform affects individual welfare.

problem Optimizing pension systems to ensure old age welfare and reduce budgetary pressure.
method Historical analysis, comparative international experience, and assessment of investment potential.
result Challenges and potential improvements of the mandatory funded pension system.

Unsupervised summarization generates novel reviews reflecting consensus opinions.

problem Creating summaries that reflect subjective information in multiple documents.
method Generative model with hierarchical variational autoencoder, pointer-generator mechanism.
result Model produces fluent and coherent summaries reflecting common opinions.

Modeling financial market dynamics with noise and fundamentalist agents.

problem Understanding opinion formation and market behavior in financial markets.
method Agent-based model with Erdös-Rényi random graph structure, incorporating anxiety parameter.
result Model accurately reproduces key market features like fat-tailed returns and volatility clustering.

The proliferation of fake news and filter bubbles makes it increasingly difficult to form an unbiased, balanced opinion towards a topic. To ameliorate this, we propose 360° Stance Detection, a tool that aggregates news with multiple perspectives on a topic. It presents them on a spectrum ranging from support to opposit…

2018-04-03abs ↗pdf ↗

Behavioral finance has become an increasingly important subfield of finance. However the main parts of behavioral finance, prospect theory included, understand financial markets through individual investment behavior. Behavioral finance thereby ignores any interaction between participants. We introduce a socio-financia…

2014-10-09abs ↗pdf ↗

Donald Trump was lagging behind in nearly all opinion polls leading up to the 2016 US presidential election, but he surprisingly won the election. This raises the following important questions: 1) why most opinion polls were not accurate in 2016? and 2) how to improve the accuracies of opinion polls? In this paper, we …

2018-12-31abs ↗pdf ↗

An increasing number of people are using online social networking services (SNSs), and a significant amount of information related to experiences in consumption is shared in this new media form. Text mining is an emerging technique for mining useful information from the web. We aim at discovering in particular tweets s…

2016-03-24abs ↗pdf ↗

In the spirit of behavioral finance, we study the process of opinion formation among investors using a variant of the 2D Voter Model with a tunable social temperature. Further, a feedback acting on the temperature is introduced, such that social temperature reacts to market imbalances and thus becomes time dependent. I…

2012-12-19abs ↗pdf ↗