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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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1223 · Apr 201819922001200920172026
48 results for IOC reforms

Bangladesh's banking sector improved through financial reforms, but challenges remain.

problem Weak asset quality, inadequate provisioning, and negative capitalization of state-owned banks.
method Two phases of reforms: private ownership promotion and gradual deregulation.
result Significant improvements in asset quality and capitalization, but challenges persist.

Convex neural networks enforce convex constraints on weights and activations, improving generalization.

problem Improving generalization and reducing overfitting in neural networks.
method Enforce convex constraints on weights and activations, using non-negative weights and non-decreasing convex activation functions.
result Convex neural networks self-regularize, outperforming base architectures and achieving similar performance to convolutional architectures.

We study the gap between the state pension provided by the Italian pension system pre-Dini reform and post-Dini reform. The goal is to fill the gap between the old and the new pension by joining a defined contribution pension scheme and adopting an optimal investment strategy that is target-based. We find that it is po…

2018-04-15abs ↗pdf ↗

Mamba outperforms Reformer in minute-level stock prediction using LLM sentiment scores.

problem Improving minute-level stock market prediction accuracy in volatile markets.
method Combining sentiment scores from top LLMs with stock price data, training Mamba and Reformer models.
result Mamba achieved lower error rates across all tested LLMs, especially with LLaMA 3.3--70B.

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.

This review examines TDFs in Chile's pension reform, recommending dynamic glide paths and diversified benchmarks.

problem Chile's pension system needs to adapt to modern investment strategies.
method Comprehensive review of TDFs, highlighting challenges and opportunities for Chilean regulators and fund managers.
result Dynamic glide paths and diversified benchmarks are recommended for better retirement outcomes.

Cost-benefit analysis often assumes accurate estimates, but this study finds significant inaccuracies.

problem Inaccurate cost and benefit estimates in public investments.
method Largest dataset of public investments, statistical analysis of cost overruns and benefit shortfalls.
result Significant inaccuracies in cost and benefit estimates of public investments.

Italy and the Eurozone are heading in the year 2012 into a financial depression of unprecedented magnitude, with a forthcoming multitude of often contradictory public economic and financial stability emergency interventions whose ultimate endogenous and exogenous effects on public and private health spending and on the…

2012-07-26abs ↗pdf ↗

Study assesses the impact of Basel III reforms on Bangladeshi banks.

problem Impact of Basel III liquidity and capital requirements on Bangladeshi banks.
method Panel data analysis with fixed effects, including macroeconomic variables.
result Higher capital and liquidity requirements negatively affect banks' profitability but positively impact interest rates and private sector lending.

Paper details how to smoothly transition from EONIA to ESTR without significant financial impact.

problem Transition from EONIA to ESTR impacts financial instruments, especially OTC derivatives.
method Detailed analysis of how clean discounting approach based on ESTR affects pricing of OIS, IRS, and XVAs.
result The transition to EONIA-free pricing framework is safe and consistent, ensuring complete elimination of EONIA.

The UNKNOT problem solved using natural language processing and machine learning.

problem Determining if a knot is the unknot.
method Braid word representation, binary classification, Reformer and shared-QK Transformer networks, reinforcement learning, Markov moves, braid relations.
result Reformer and shared-QK Transformer networks outperform fully-connected networks in predicting the unknot.

Haircutting non-cash collateral has become a key element of the post-crisis reform of the shadow banking system and OTC derivatives markets. This article develops a parametric haircut model by expanding haircut definitions beyond the traditional value-at-risk measure and employing a double-exponential jump-diffusion mo…

2017-08-25abs ↗pdf ↗

Model shows disclosure reduces trading costs in oligopolistic markets.

problem Reducing trading costs in oligopolistic markets with imperfect competition.
method Developed a multi-period Kyle-type model with mandatory disclosure and imperfect competition, proving existence and uniqueness of a linear equilibrium.
result Disclosure lowers trading costs by reducing price impact, and its marginal benefit is larger when competition is weak.

Ethereum block builders can earn up to $14M/month by reordering transactions, harming users.

problem Block builders can exploit transaction reordering to earn significant profits, harming users.
method Estimation of MEV payments and analysis of reordering effects.
result Block builders can earn up to $14M/month by reordering transactions, skewing the distribution.

Over-the-counter markets are at the center of the postcrisis global reform of the financial system. We show how the size and structure of such markets can undergo rapid and extensive changes when participants engage in portfolio compression, a post-trade netting technology. Tightly-knit and concentrated trading structu…

2017-05-19abs ↗pdf ↗

We report an empirical study of the Ibovespa index of the Sao Paulo Stock Exchange in which we detect the existence of long-range correlations. To analyze our data we introduce a rescaled variant of the usual Detrended Fluctuation Analysis that allows us to obtain the Hurst exponent through a one-parameter fitting. We …

2003-02-17abs ↗pdf ↗

Over the past decade, the stellar growth of Indian economy has been challenged by persistently high levels of inflation, particularly in food prices. The primary reason behind this stubborn food inflation is mismatch in supply-demand, as domestic agricultural production has failed to keep up with rising demand owing to…

2017-01-30abs ↗pdf ↗

Study shows GDP and CPI predict CCC funding, highlighting need for economic forecasting.

problem Challenges in aligning CCC funding with DEI initiatives.
method Quantitative correlational design, analyzing 30 years of economic data.
result Strong positive correlation between GDP growth and CCC funding levels, and between CPI and funding levels.

Multi-label learning studies the problem where an instance is associated with a set of labels. By treating single-label learning problem as one task, the multi-label learning problem can be casted as solving multiple related tasks simultaneously. In this paper, we propose a novel Multi-task Gradient Descent (MGD) algor…

2019-11-18abs ↗pdf ↗

Study analyzes profitability and efficiency of Chinese banks, finding state-owned banks superior.

problem Analyzing efficiency and profitability of Chinese banks over time.
method Used Data envelopment analysis (Super-SBM-UND-VRS based DEA) model considering non-performing loans as undesired output.
result State-owned banks and Rural/City Commercial Banks have better profitability super-efficiency than Joint-stock Banks.

Barcelona evaluates major events for economic and social impact.

problem Evaluating the economic and social impact of major events in Barcelona.
method Analyzes the economic and social dimensions of Barcelona's major events from 1888 to 2004.
result Develops a rational argument for communicating the economic benefits of major events.

EMDLOT predicts bond defaults better than traditional methods.

problem Lack of interpretability and irregular temporal dependencies in financial data.
method Integrates time-series and textual data, uses Time-Aware LSTM, soft clustering, and multi-level attention.
result EMDLOT outperforms traditional and deep learning benchmarks in recall, F1-score, and mAP.

This work models overnight rates with jumps and discontinuities, extending classical short-rate models.

problem Capturing the jump behavior and discontinuities in overnight rates for accurate modeling.
method Developed a term structure modeling framework based on overnight rates, accommodating stochastic discontinuities.
result Simple specifications can capture the jump behavior of overnight rates, and explicit valuation formulas are provided.

This paper takes stock of megaproject management, an emerging and hugely costly field of study. First, it answers the question of how large megaprojects are by measuring them in the units mega, giga, and tera, concluding we are presently entering a new "tera era" of trillion-dollar projects. Second, total global megapr…

2014-08-29abs ↗pdf ↗

PSQRNN model forecasts electricity consumption in China by integrating neural networks and quantile regression.

problem Electricity forecasting in China due to regional economic, social, and natural conditions.
method PSQRNN combines neural networks and semiparametric quantile regression to model electricity consumption.
result PSQRNN model outperforms traditional methods in forecasting electricity consumption in China.