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Search Minerva’s current Findings using transparent hybrid retrieval. Results remain strictly inside the configured corpus.

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Results for “computer-Science”

30 findings

73match

Finding 33331 source

The study concludes that integrating Sentiment Analysis with Technical Analysis enhances stock market predictions. Potential applications include more accurate financial forecasting and investment strategies. Future research could explore additional data sources and further refine the models.

LexicalMeaningQualityGraph

Matched: computer, science

63match

Finding 68201 source

The study concludes that AI-powered financial advisers democratize wealth management and optimize investment strategies. Future research should focus on improving transparency and user experience. Potential applications include personalized investment services and enhanced financial decision-making tools.

LexicalMeaningQualityGraph

Matched: computer, science

59match

Finding 63141 source

The results suggest that GWO is a promising tool for optimizing trading strategy parameters, leading to higher returns. Potential applications include algorithmic trading and financial market analysis. Future research could explore other indicators and broader datasets.

LexicalMeaningQualityGraph

Matched: computer, science

57match

Finding 41611 source

Marcos Lpez de Prados paper redefines financial engineering as a mature discipline, stressing its unique role in solving real-world investment problems beyond traditional mathematics, statistics, or computer science approaches.

LexicalMeaningQualityGraph

Matched: computer, science

56match

Finding 21361 source

The research outlines a framework integrating network science, deep learning, and Explainable AI, introducing novel graph modeling of transactional data with crucial indicators like high volumes and node degree metrics.

LexicalMeaningQualityGraph

Matched: computer, science

54match

Finding 64641 source

The research highlights the importance of contextual features in improving PEAD prediction models. Potential applications include enhancing trading strategies and financial analysis. Future research could explore further refinement of textual features and their integration with contextual data.

LexicalMeaningQualityGraph

Matched: computer, science

54match

Finding 31981 source

Utilizing a novel Mamba-based state space model, the paper transforms Bitcoin price prediction by addressing non-linear dynamics and regime shifts. Its originality integrates forecasting with practical trading algorithms, while its novelty adapts techniques from NLP and computer vision, rendering it a compelling contribution to academic research and quantitative finance applications.

LexicalMeaningQualityGraph

Matched: computer, science

53match

Finding 79361 source

Researchers unveil an open-source economic index tracking AI adoption and capability across jobs, revealing highest uptake in finance, computer science, and the arts, but surprisingly low use in legal services.

LexicalMeaningQualityGraph

Matched: computer, science

51match

Finding 49221 source

The study unveils a framework that fuses neural networks with reinforcement learning, significantly improving forecasting and risk management for trading and portfolio optimization, but necessitates further scalability and efficiency evaluations.

LexicalMeaningQualityGraph

Matched: computer, science

51match

Finding 76161 source

The research introduced metrics including Rank Graduation Accuracy, Robustness, and Fairness for quantitative insights, yet challenges such as high false positions and limited external factors persist, emphasizing balanced, interpretable AI.

LexicalMeaningQualityGraph

Matched: computer, science

51match

Finding 76141 source

Deep learning models including GRU, LSTM, RNN, and CNN remarkably outperform classical logistic regression and SVM, generating superior IBM stock forecasts and trading strategies using twenty years of historical data.

LexicalMeaningQualityGraph

Matched: computer, science

50match

Finding 49211 source

Using one-minute data from 2015 to 2022, the hybrid model lowers error metrics like $$MAPE$$, $$MSE$$, and $$RMSE$$ by decomposing signals into intrinsic mode functions, capturing short- and long-term trends.

LexicalMeaningQualityGraph

Matched: computer, science

50match

Finding 79481 source

Study reveals dynamic price discovery in decentralized finance as $36%$ of total $27%$ drop occurs before public announcements, indicating market participants with advanced processing act prior to common knowledge readily.

LexicalMeaningQualityGraph

Matched: computer, science

50match

Finding 79501 source

Paper distinguishes between raw public information and common knowledge, while acknowledging rigorous methodology with limitations such as 49 hack events and dependency on social media channels, impacting market regulation implications.

LexicalMeaningQualityGraph

Matched: computer, science

50match

Finding 48181 source

Combining feature extraction, asset correlation, and penalty constraints in a multi-period framework using the Bellman equation and Markov decision processes, the method outperforms traditional strategies while managing risk despite volatility.

LexicalMeaningQualityGraph

Matched: computer, science

50match

Finding 76151 source

A GRU-based strategy achieved highest profits, lower drawdowns, while the study presented an eight-step methodology and SAFE framework for evaluating sustainability, accuracy, fairness, and explainability, setting benchmarks in risk-managed trading.

LexicalMeaningQualityGraph

Matched: computer, science

50match

Finding 49201 source

A novel hybrid model combining Variational Mode Decomposition, Artificial Neural Networks, Long Short-Term Memory, Gated Recurrent Units, and an innovative Q-learning ensemble improves volatility predictions compared to traditional forecasting methods.

LexicalMeaningQualityGraph

Matched: computer, science

50match

Finding 38281 source

Despite increased computational complexity and a focus on univariate forecasting, the innovative TDA-enhanced model outperformed traditional approaches, delivering insights and opening new avenues for reinforcement learning and high-frequency trading applications.

LexicalMeaningQualityGraph

Matched: computer, science

50match

Finding 48191 source

Extensive tests on indices S&P100, DJIA, and S&P/TSX, using portfolio value, Sharpe ratio, and maximum drawdown metrics, validate the strategy, though heavy reliance on hyperparameter tuning creates real-world deployment challenges.

LexicalMeaningQualityGraph

Matched: computer, science

50match

Finding 79491 source

Innovative approach incorporates a high-frequency event study with precise on-chain and social media timing, alongside a strategic three-period theoretical model including information processing costs, representing a novel empirical design effectively.

LexicalMeaningQualityGraph

Matched: computer, science

50match

Finding 21351 source

Graph Neural Networks, notably Graph Attention Networks, revolutionize fraud detection by capturing hidden transactional relationships and achieving a 91% recall compared to conventional models 72% accuracy in identifying fraudulent schemes.

LexicalMeaningQualityGraph

Matched: computer, science

50match

Finding 38271 source

Using a novel sliding window approach to extract multi-scale geometric features and nonlinear dependencies, the study rigorously compares TDA-augmented models with alternative techniques, validated by Friedman and Holm statistical tests.

LexicalMeaningQualityGraph

Matched: computer, science

50match

Finding 48171 source

New portfolio management strategy combines deep reinforcement learning with convolutional neural networks and WaveNet to capture dynamic asset patterns and relationships, delivering superior returns despite transaction costs and variable risks.

LexicalMeaningQualityGraph

Matched: computer, science

50match

Finding 50581 source

Surprisingly, the proposed model outperforms traditional methods and beats the market index in US stocks, offering enhanced risk management through improved Mean-Variance and Conditional Value at Risk portfolio optimization strategies.

LexicalMeaningQualityGraph

Matched: computer, science

50match

Finding 47271 source

The study introduces an innovative graph-based framework for factor models that ingeniously integrates bond features like credit rating and country, significantly improving interpretability and robustness in credit spread decompositions, remarkably.

LexicalMeaningQualityGraph

Matched: computer, science

50match

Finding 22691 source

The study employs comprehensive Z-score normalization, simulation evaluations on 2018-2023 historical data, and rigorous comparisons with established models, highlighting significant improvements using MAPE values as low as $$0.6187$$ and $$0.6667$$.

LexicalMeaningQualityGraph

Matched: computer, science

50match

Finding 47281 source

Surprisingly, both the Graph Factor Model and Credit Factor Model outperform traditional PCA, autoencoders, and Instrumented PCA by capturing more variance and handling missing data better than conventional techniques, effectively.

LexicalMeaningQualityGraph

Matched: computer, science

50match

Finding 20571 source

Researchers reveal the unexpected power of the total liabilities-to-operating costs ratio; this metric, when combined with return on equity, current ratio, operating cash flow, and equity multiplier, predicts financial misreporting.

LexicalMeaningQualityGraph

Matched: computer, science

50match

Finding 47291 source

Rigorous testing on corporate bond returns reveals that domain-informed sparsity enables clear economic interpretations, yet reliance on factor correlations may reduce independence, presenting a trade-off between interpretability and performance, notably.

LexicalMeaningQualityGraph

Matched: computer, science

50match

Finding 28461 source

Employing short to medium lookback periods between 5 and 30 days, the strategy yields attractive Sharpe ratios and limited drawdowns, outperforming passive Bitcoin holding by controlling momentum and risk effectively.

LexicalMeaningQualityGraph

Matched: computer, science