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arXiv research

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.

168,742 papers · 148 categories

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48 results for investment sizing

Significant differences in the evolution of firm size distribution for various industries in the United States have been revealed and documented. For theoretical considerations, this finding puts major constraints on the modelling of firm growth. For practical purposes, the observed differences create a solid basis for…

2009-03-02abs ↗pdf ↗

Paper proposes optimal investment and reinsurance strategies considering financial and insurance risks dependence.

problem Optimal investment and reinsurance strategies under dependent financial and insurance risks.
method Stochastic control approach to maximize expected exponential utility of terminal wealth.
result Minimal dependence between financial and insurance risks significantly impacts investment and reinsurance strategies.

Investment disputes increase stock volatility, especially for companies with negative outcomes.

problem Investment disputes affect stock market volatility and investor uncertainty.
method Analysis of abnormal share fluctuations and various explanatory variables.
result Investment disputes lead to increased stock volatility, particularly for companies with negative outcomes.

We study an optimal investment control problem for an insurance company. The surplus process follows the Cramer-Lundberg process with perturbation of a Brownian motion. The company can invest its surplus into a risk free asset and a Black-Scholes risky asset. The optimization objective is to minimize the probability of…

2015-02-08abs ↗pdf ↗

We first estimate the average growth of a company's annual income and its variance by using both real company data and a numerical model which we already introduced a couple of years ago. Investment strategies expecting for income growth is evaluated based on the numerical model. Our numerical simulation suggests the p…

2003-03-17abs ↗pdf ↗

This study examines representation bias in open-source Qwen models for investment decisions.

problem Representation bias in financial applications of large language models.
method Balanced round-robin prompting over 150 U.S. equities, constrained decoding, token-logit aggregation.
result Firm size and valuation increase model confidence, while risk factors decrease it.

Investment strategy depends on many factors for venture capital funds.

problem Finding the optimal portfolio size for venture capital funds.
method Analyzes various factors affecting fund returns and optimal portfolio size, starting with basic assumptions and increasing complexity.
result Investment strategy depends on many factors, not a one-size-fits-all formula.

In this paper, we discuss the Cramér-Lundberg model with investments, where the price of the invested risk asset follows a geometric Brownian motion with drift aa and volatility σ>0.σ> 0. By assuming there is a cap on the claim sizes, we prove that the probability of ruin has at least an algebraic decay rate if $2a/σ^2 …

2010-02-27abs ↗pdf ↗

Investment tool predicts higher returns for Madrid real estate units.

problem Determining which real estate units have higher returns to investment in Madrid.
method Data collection from Idealista.com, descriptive statistics, return index, machine learning algorithms.
result Introduction of machine learning algorithms for rental real estate price prediction.

The paper analyzes how contagion affects the survival probability of investment groups in microfinance.

problem The impact of contagion on the survival probability of investment groups in microfinance.
method A probabilistic approach to compute group survival probability with and without contagion effects.
result In homogeneous groups, including more members increases the probability of eventual default to 1.

Study shows institutional investments significantly impact cryptocurrency market evolution.

problem Limited understanding of institutional investments' role in cryptocurrency market evolution.
method Quantitative analysis of 1324 cryptocurrencies' investments from 2014-2022.
result Institutional investments correlate with cryptocurrency market capitalization.

An algorithm was recently introduced by INTECH for the purposes of estimating the trading-profit contribution of systematic rebalancing to the relative return of rules-based investment strategies. We apply this methodology to analyze the size factor through the use of equal-weighted portfolios. These strategies combine…

2016-01-28abs ↗pdf ↗

We introduce a general decision tree framework to value an option to invest/divest in a project, focusing on the model risk inherent in the assumptions made by standard real option valuation methods. We examine how real option values depend on the dynamics of project value and investment costs, the frequency of exercis…

2018-09-04abs ↗pdf ↗

Enhanced financial forecasting using supervised autoencoders with noise augmentation and triple labeling.

problem Improving investment strategy performance on noisy financial data.
method Supervised autoencoders with noise augmentation and triple barrier labeling.
result Supervised autoencoders with balanced noise augmentation and bottleneck size significantly boost strategy effectiveness.

Study examines Indian equity mutual funds' investment style and risk-shifting.

problem Understanding how Indian equity mutual funds' investment styles affect their returns.
method Estimating size and style beta coefficients, identifying breakpoints, analyzing investment styles, and assessing risk-shifting intensity.
result Funds can enhance returns by shifting to high-return styles like Small Value and Small Blend.

In this paper we propose a novel application of Gaussian processes (GPs) to financial asset allocation. Our approach is deeply rooted in Stochastic Portfolio Theory (SPT), a stochastic analysis framework introduced by Robert Fernholz that aims at flexibly analysing the performance of certain investment strategies in st…

2016-05-09abs ↗pdf ↗

Deep learning predicts uncertainty to optimize Eurodollar futures trading.

problem Optimizing investment size in high-frequency Eurodollar futures trading.
method Deep learning models to estimate prediction uncertainty, scaling investment size.
result Clear outperformance with Sharpe ratio metric compared to alternative strategies.

Model predicts stationary equilibrium in investment decisions of firms in fluctuating markets.

problem Investment decisions in fluctuating markets with varying volatility and commodity prices.
method Mean-field model with Gaussian productivity shocks and two-state Markov chain for macroeconomic events.
result Existence, uniqueness, and characterization of stationary mean-field equilibrium with barrier-type investment strategy.

LLMs show biases in investment analysis, leading to unreliable recommendations.

problem LLMs face conflicts between pre-trained knowledge and real-time market data, leading to biases in investment analysis.
method Experimental framework to investigate emergent behaviors in LLMs, analyzing sector, size, and momentum biases.
result Distinct, model-specific biases observed, including a tendency to prefer technology stocks, large-cap stocks, and contrarian strategies.

The present study introduce the human capital component to the Fama and French five-factor model proposing an equilibrium six-factor asset pricing model. The study employs an aggregate of four sets of portfolios mimicking size and industry with varying dimensions. The first set consists of three set of six portfolios e…

2018-09-21abs ↗pdf ↗

An investor with constant relative risk aversion trades a safe and several risky assets with constant investment opportunities. For a small fixed transaction cost, levied on each trade regardless of its size, we explicitly determine the leading-order corrections to the frictionless value function and optimal policy.

2013-06-12abs ↗pdf ↗

Quantum computer optimizes investment portfolios, outperforming traditional methods.

problem Minimizing risk while meeting return and budget constraints in investment portfolios.
method Used D-Wave quantum annealer and hybrid solvers to solve Portfolio Optimization problem.
result D-Wave quantum solution performs close to traditional commercial solvers for tested problem sizes.

Prompted by a recent experiment by Victor Haghani and Richard Dewey, this note generalises the Kelly strategy (optimal for simple investment games with log utility) to a large class of practical utility functions and including the effect of extraneous wealth. A counterintuitive result is proved : for any continuous, co…

2016-11-28abs ↗pdf ↗

Building on similarities between earthquakes and extreme financial events, we use a self-organized criticality-generating model to study herding and avalanche dynamics in financial markets. We consider a community of interacting investors, distributed on a small-world network, who bet on the bullish (increasing) or bea…

2013-09-14abs ↗pdf ↗

SCS identifies a range of plausible equally weighted portfolios, quantifying selection uncertainty.

problem Uncertainty in selecting the best equally weighted portfolio subset.
method Introduces Selection Confidence Set (SCS) for EWPs, covering plausible portfolios with high probability.
result SCS quantifies selection uncertainty and covers the unknown optimal selection with high probability.

Investor skill levels affect optimal portfolio size, study shows.

problem Optimal portfolio size for different skill levels of investors.
method Mathematical methods to study annual and continuous portfolio diversification, regression analysis.
result Strong investors should hold concentrated portfolios, poor investors should hold diversified portfolios.

Study uses machine learning and PolyModel to improve hedge fund performance.

problem Improving hedge fund investment performance with machine learning.
method Integration of machine learning techniques, PolyModel feature selection, and analysis of fund size.
result Machine learning enhances cumulative returns but increases annual volatility.

Enhanced financial forecasting with supervised autoencoders for S&P 500 and cryptocurrencies.

problem Improving investment strategy performance in financial markets.
method Supervised autoencoders with noise augmentation and triple barrier labeling.
result Supervised autoencoders with balanced parameters significantly boost strategy effectiveness.

Behavioral theories posit that investor sentiment exhibits predictive power for stock returns, whereas there is little study have investigated the relationship between the time horizon of the predictive effect of investor sentiment and the firm characteristics. To this end, by using a Granger causality analysis in the …

2018-03-08abs ↗pdf ↗

In this paper the utility optimization problem for a general insurance model is studied. The reserve process of the insurance company is described by a stochastic differential equation driven by a Brownian motion and a Poisson random measure, representing the randomness from the financial market and the insurance claim…

2009-08-31abs ↗pdf ↗

An interbank market lets participants pool the risk arising from the combination of illiquid investments and random withdrawals by depositors. But it also creates the potential for one bank's failure to trigger off avalanches of further failures. We simulate a model of interbank lending to study the interplay of these …

2001-04-04abs ↗pdf ↗

We apply the Zipf power law to financial time series of WIG20 index daily changes (open-close). Thanks to the mapping of time series signal into the sequence of 2k+1 'spin-like' states, where k=0, 1/2, 1, 3/2, ..., we are able to describe any time series increments, with almost arbitrary accuracy, as the one of such 's…

2011-07-17abs ↗pdf ↗

Investing is a compression problem, maximizing growth by minimizing divergence.

problem Maximizing long-term wealth and minimizing risk of ruin in investing.
method Decomposes investing into three terms: money, entropy, and divergence. Uses Kelly Criterion and universal portfolio theory.
result Investing can be seen as a compression problem, with optimal strategies minimizing divergence.