15秒到Alpha:商业地产证券的高频风险定价

A. Christopoulos, J. Barratt
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摘要

本文介绍了一种适用于CMBX的日频率和日内频率的简化形式风险分解估计的推广方法。我们估计了违约、流动性、流动性过剩和利率波动在每日和日内频率上的风险分区。我们的新估计技术将以前模拟的风险分区与使用主成分和OLS方法的当前市场数据相结合。我们发现流动性和过剩流动性风险分区在解释历史上(2007年11月至2019年4月)和20天预测中的每日有效买卖价差方面具有重要意义。在2019年4月至2021年4月期间,我们将模型从每日频率扩展到日内频率,以15秒的间隔估计日内频率。在Covid期间,我们在横截面中发现了风险分割波动的常规模式,并在自动交易策略中利用相关且更频繁交易的REIT部门的这些见解。在我们的54个多头/空头日内交易策略中,96%表现出显著的阿尔法,63%产生了0.73%至48.74%之间的异常累积收益。这些结果支持商业房地产证券在更高频率上进行风险划分的定价风险。
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15 Seconds to Alpha: Higher frequency risk pricing for commercial real estate securities
This paper introduces a generalizable method to estimate reduced form risk decompositions at daily and intraday frequencies applied to CMBX. We estimate partitions for the risks of default, liquidity, excess liquidity, and interest rate volatility at daily and intraday frequencies. Our new estimation technique combines previously simulated risk partitions with current market data using principal components and OLS methods. We find liquidity and excess liquidity risk partitions are significant in explaining daily effective bid-ask spreads historically, from 11/2007-4/2019, and in 20-day forecasts. During the Covid pandemic, we extend the model from daily to intraday frequency, estimating intraday in 15 second intervals over the period 4/2020-4/2021. During Covid, we find regular patterns of risk partition volatility in the cross-section and exploit those insights in the related, and more frequently traded, REIT sector in automated trading strategies. In our 54 long/short day trading strategies, 96% showed significant alphas, and 63% produced abnormal cumulative returns between 0.73% and 48.74%. These results support pricing risk with risk partitioning at higher frequencies for commercial real estate securities.
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