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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.

168,657 papers · 148 categories

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54108161215 · Jun 202019922001200920172026
48 results for current profitability

Study optimal portfolio selection using average and current profitability of risky assets.

problem Continuous-time mean-variance portfolio selection in time-varying financial markets.
method Introduced AP and CP indexes; estimated AP and CP using second-order variation of an auxiliary wealth process.
result Estimations of AP and CP are more accurate than traditional MLE.

In a dual risk model, the premiums are considered as the costs and the claims are regarded as the profits. The surplus can be interpreted as the wealth of a venture capital, whose profits depend on research and development. In most of the existing literature of dual risk models, the profits follow the compound Poisson …

2015-10-13abs ↗pdf ↗

Study examines impact of capital structure on Indian auto companies' profitability.

problem Understanding the impact of capital structure on profitability of Indian auto companies.
method Used fixed and random effect models with 10 years of data from 17 companies.
result Optimal capital structure improves company performance and maintains capital adequacy.

Fair market valuations ignore future worker profits in employee-owned firms.

problem Ignoring future worker profits in fair market valuations for employee-owned firms.
method Analyzing property rights and residual claimants in employee-owned firms.
result Fair market valuations are inappropriate for employee-owned firms.

The basic financial purpose of a firm is to maximize its value. An inventory management system should also contribute to realization of this basic aim. Many current asset management models currently found in financial management literature were constructed with the assumption of book profit maximization as basic aim. H…

2013-01-16abs ↗pdf ↗

LARA forecasts financial asset trends by refining noisy labels and extracting profitable samples.

problem Low signal-to-noise ratio and stochastic nature of financial data lead to poor predictions.
method LARA combines LA-Attention and RA-Labeling to refine and extract profitable samples.
result LARA significantly outperforms existing methods on Qlib platform.

Study on liquidity providers' performance in decentralized exchanges.

problem Unclear profitability of liquidity providers in decentralized exchanges.
method Reconstructing LP PnL dynamics from on-chain events, introducing a new metric.
result Only about one out of six LPs avoids losses, suggesting open questions about LP participation motives.

Current auto loans converge to super-prime credit despite remaining underwater.

problem Inefficient consumer behavior in auto loans leading to suboptimal credit risk.
method Large-sample statistical hypothesis test on transition matrix between risk bands.
result All current risk bands converge to super-prime credit, despite remaining underwater.

The study compares profitability of conventional and Islamic banks in Bangladesh.

problem Evaluating profitability of commercial banks in Bangladesh.
method Examined bank-specific, industry-specific, and banking system factors on profitability.
result Islamic banks consistently outperform conventional banks in profitability.

The profitability of CPMMs is significantly impacted by mint and burn fees.

problem Understanding the profitability of decentralized exchanges.
method Formalized liquidity providers' profitability conditions, studied the effect of mint and burn fees, and compiled a large data set from Uniswap V2 transactions.
result The profitability of liquidity provision is severely affected by mint and burn costs.

Fossil power firms have recently profited more than renewables, but this may be a temporary phenomenon.

problem The profitability gap between renewable and fossil power firms in Europe.
method Machine-learning clustering and Bayesian model averaging.
result Renewable power firms are becoming more profitable, while fossil power firms are becoming less so.

Developing an Agent-Based Model to Mitigate Adverse Selection in Uniswap v3 Liquidity Providers

problem Adverse selection in Uniswap v3 liquidity providers
method Agent-Based Model incorporating blockchain microstructure and volatility dynamics
result Dynamic fee schedules improve hedged Profit and Loss for liquidity providers

Real time bidding (RTB) enables demand side platforms (bidders) to scale ad campaigns across multiple publishers affiliated to an RTB ad exchange. While driving multiple campaigns for mobile app install ads via RTB, the bidder typically has to: (i) maintain each campaign's efficiency (i.e., meet advertiser's target cos…

2018-11-11abs ↗pdf ↗

This paper proposes a two-stage scoring approach to help lenders decide their fund allocations in the peer-to-peer (P2P) lending market. The existing scoring approaches focus on only either probability of default (PD) prediction, known as credit scoring, or profitability prediction, known as profit scoring, to identify…

2018-10-05abs ↗pdf ↗

A new framework integrates credit scoring into profit scoring for better P2P lending investments.

problem Maximizing profit while minimizing risk in P2P lending investments.
method Two-stage framework using Light Gradient Boosting Machine (lightGBM) to integrate credit scoring into profit scoring.
result The proposed framework identifies more profitable loans and provides better investment guidance.

Study shows adding similar investors can either increase or decrease profits, depending on their strategy.

problem Investors argue conflictingly about the impact of adding similar investors on their profits.
method Built an agent-based financial market model with additional agents and investigated their earnings.
result Adding similar fundamental agents stabilizes market prices and decreases profits, while adding similar technical agents makes prices unstable and increases profits.

Study examines downsizing impact on Indian construction firms' profitability.

problem Impact of downsizing layoffs on construction firms' profitability in India.
method Used Co-integration test, OLS, and VAR models on secondary data of 15 companies.
result Employee Expenses and Number of Employees have significant impact on profitability.

Expands robust profit opportunities to include distributional uncertainty.

problem Distributional uncertainty in financial markets.
method Formulates infinite dimensional primal problems, simplifies to finite dimensional dual problems using Wasserstein distance.
result Distributional uncertainty can enhance robustness of profit opportunities.

A common assumption of political economy is that profit rates across firms or sectors tend to uniformity, and often models are formulated in which this tendency is assumed to have been realised. But in reality this tendency is never realised and the distribution of firm profits is not degenerate but skewed to the right…

2004-07-27abs ↗pdf ↗

Study increasing profits in a flexible financial market model.

problem Characterize increasing profits in a 1D diffusion market with interest rates.
method Characterize increasing profits using an auxiliary deterministic signed measure and a canonical trading strategy.
result Existence and characterization of increasing profits in terms of νν and θθ.

We investigate the structure of the profit landscape obtained from the most basic, fluctuation based, trading strategy applied for the daily stock price data. The strategy is parameterized by only two variables, p and q. Stocks are sold and bought if the log return is bigger than p and less than -q, respectively. Repet…

2012-05-02abs ↗pdf ↗

The paper defines fair profit sharing ratios in Islamic PL contracts.

problem Determining fair profit sharing ratios in Islamic PL contracts.
method Introduces cc-fair profit sharing ratios and uses econometrics models to compute or approximate them.
result Elucidates the relation between profit sharing ratios and economic factors.

Study shows how financial report sentiment impacts bank profitability.

problem Understanding causal effects of financial report sentiment on bank profitability.
method Causal forest machine learning methodology, FinancialBERT sentiment scores, SHAP analysis, comprehensive dataset.
result Statistically significant causal associations between balance sheet and expense management variables and profitability.

Optimizes liquidity provision intervals for profitable AMM participation.

problem Financial losses from poor liquidity provision intervals and reallocation costs.
method Developed a tractable stochastic optimization problem.
result Computes optimal liquidity provision intervals for profitable liquidity concentration.

Proposes a framework to reconcile policy learning and profit maximization in CATE estimation.

problem Aligning CATE estimation with profit maximization for optimal customer treatment decisions.
method Optimizes a novel objective function that concentrates learning capacity near the decision boundary, ensuring consistency with the original profit function.
result Consistent CATE estimates can be recovered from existing profit-maximization pipelines, allowing firms to navigate the trade-off between accuracy and profit.

Study examines the impact of employment benefit costs on firm profitability.

problem Impact of employment benefit costs on firm profitability.
method Panel data regression analysis using E-Views.
result There is a significant positive relationship between employment benefit costs and firm profitability.

It has been assumed that arbitrage profits are not possible in efficient markets, because future prices are not predictable. Here we show that predictability alone is not a sufficient measure of market efficiency. We instead propose to measure inefficiencies of markets in terms of the maximal profit an ideal trader can…

2004-03-24abs ↗pdf ↗

The paper limits the profitability of technical trading rules and finds they are not better than random trading.

problem The profitability of technical trading rules in stock markets is controversial.
method Proves the upper bound of cumulative return and investigates the profitability of technical trading rules using bootstrap methodology.
result Technical trading rules are not better than random trading and less profitable than the market.

BESS shows potential in European markets for frequency support, but not for energy arbitrage.

problem Lack of profitability for BESS in energy arbitrage in most European markets.
method Proposed a general payoff model for BESS operation and calculated utilization factors for common applications.
result BESS shows higher potential in providing frequency support services, especially in Central Western and Northern Europe.

Study improves trading decisions by predicting profit and loss outcomes.

problem Inconsistent profitability of machine learning forecasts in financial markets.
method Developed a novel algorithm for forecasting profit and loss outcomes, integrating with market trend predictions.
result Significantly improved performance of trading strategies, including traditional and algorithmic trading.

Study upper hedging prices for contingent claims in models with various types of arbitrage.

problem Valuation of contingent claims in market models with different types of arbitrage.
method Analysis of market models with increasing profit, strong arbitrage, and arbitrage of the first kind.
result Option prices are reduced when increasing profit is present, and corporate stock price processes can be derived from issuance and repurchase plans.

Study finds WACC negatively impacts firm profitability in Bangladesh's food industry.

problem Determining the impact of Weighted Average Cost of Capital (WACC) on firm profitability.
method Fixed Effects Panel Regression Model using 12 food and allied industry companies from 2005-2019.
result WACC negatively correlates with firm profitability (ROA), significant relationship.

Customer retention campaigns increasingly rely on predictive models to detect potential churners in a vast customer base. From the perspective of machine learning, the task of predicting customer churn can be presented as a binary classification problem. Using data on historic behavior, classification algorithms are bu…

2017-12-21abs ↗pdf ↗