加密货币收益的因子模型

FinPlanRN: Other Investments (Topic) Pub Date : 2021-10-10 DOI:10.2139/ssrn.3935934

Daniele Bianchi, M. Babiak

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引用次数: 6

摘要

我们通过仪器主成分分析(IPCA)的视角，研究了大量加密货币对的每日实现回报和风险溢价的动态(见Kelly et al. 2019)。我们表明，具有三个潜在因素和时变因素负载的模型显着优于具有可观察风险因素的基准模型:总(预测)R

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A Factor Model for Cryptocurrency Returns

We investigate the dynamics of daily realised returns and risk premiums for a large cross-section of cryptocurrency pairs through the lens of an Instrumented Principal Component Analysis (IPCA) (see Kelly et al. 2019). We show that a model with three latent factors and time-varying factor loadings significantly outperforms a benchmark model with observable risk factors: the total (predictive) R

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FinPlanRN: Other Investments (Topic)

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