Volatilities and correlations rise with trend strength via quadratic polynomials, refining mean-reversion models and supporting lattice gas modeling of markets near criticality.
Licença de uso do Banco Central do Brasil
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
verdicts
UNVERDICTED 4representative citing papers
A literature survey finds no peer-reviewed Bitcoin price models beat the naive baseline at medium horizons and proposes methodological improvements including walk-forward testing and Diebold-Mariano tests.
Cost-aware execution filters enable selected machine learning strategies, particularly long-only XGBoost, to achieve over 65% annualized returns and Sharpe ratios above 1 in hourly BTC trading despite 10bp costs.
Empirical panel regressions on 142 Brazilian firms find the market differentiates high from low long-term accounting performers but shows weaker separation between high and medium performers.
citing papers explorer
-
Trends, Volatility, Correlations, and Critical Phenomena in Financial Markets
Volatilities and correlations rise with trend strength via quadratic polynomials, refining mean-reversion models and supporting lattice gas modeling of markets near criticality.
-
Bitcoin Price Prediction: Peer-Reviewed Evidence and Social Media Discourse
A literature survey finds no peer-reviewed Bitcoin price models beat the naive baseline at medium horizons and proposes methodological improvements including walk-forward testing and Diebold-Mariano tests.
-
Machine Learning-Based Bitcoin Trading Under Transaction Costs: Evidence From Walk-Forward Forecasting
Cost-aware execution filters enable selected machine learning strategies, particularly long-only XGBoost, to achieve over 65% annualized returns and Sharpe ratios above 1 in hourly BTC trading despite 10bp costs.