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0111 · Feb 202519922001200920172026
2 results for macro-sentiment

Crypto simulations show HODL strategy loads risk onto most investors, with macro-sentiment affecting returns.

problem Understanding real risk-return trade-offs and factors affecting crypto returns.
method Two independent analyses: 480 million Monte Carlo simulations and Bayesian multi-horizon local projection framework.
result HODL strategy exposes most investors to extreme downside risk, and macro-sentiment conditions are dominant indicators for future outcomes.

Cryptocurrency forecasting model considers macro, sentiment, and technical indicators.

problem High price volatility in cryptocurrency markets.
method Dual-prediction mechanism incorporating macroeconomic fluctuations, technical indicators, and individual cryptocurrency price changes.
result The proposed model outperforms ten comparison methods in short-term cryptocurrency forecasting.