从标普500期权估计波动率缩放贴现因子
文章 arXiv papers · 作者: Kenichiro Shiraya et al.
总结
本文构建了一个由时变波动率缩放的随机贴现因子(SDF),并利用标普500期权价格隐含的信息进行估计。其目的是还原市场参与者的前瞻性预期,同时降低观测噪声的影响。估计出的SDF呈非单调形态:虚值程度较浅的看跌期权一侧出现隆起,且期限越长,形状越明显地呈现W形。结果表明,期限会影响中央隆起的强度。
作者解释称,市场风险价格恒定的随机波动率可以解释这一形态。他们还利用估计出的SDF推导股权溢价,并报告称其样本外预测表现优于包括马丁界限在内的现有基准。文档没有提供样本期、具体实施选择,或预测增益的幅度及统计显著性,因此这份摘要有助于理解所提方法,但不足以独立评估其稳健性。
核心观点
- 所提出的SDF利用时变波动率缩放期权隐含信息。
- 其估计形态呈非单调特征,虚值程度较浅的看跌期权一侧有隆起,期限越长越接近W形。
- 在市场风险价格恒定的条件下,随机波动率为观测到的形态提供了一种理论解释。
- 据报告,由此推导的股权溢价样本外预测表现优于马丁界限等基准。
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# Estimating the Stochastic Discount Factor from Option Prices and Predicting the Equity Premium # Estimating the Stochastic Discount Factor from Option Prices and Predicting the Equity Premium This paper proposes a stochastic discount factor (SDF) scaled by time-varying volatility. By utilizing prices and market data implied solely from S\&P 500 options, the proposed framework recovers a stable, non-monotonic SDF that captures the pure forward-looking expectations of market participants while mitigating observation noise. Our empirical analysis reveals that the SDF exhibits a distinctive hump on the shallow put side, which transitions into a more clearly defined W-shape as the time to maturity increases, identifying maturity as a key factor influencing the intensity of the central hump. We show that this structural feature can be theoretically rationalized by stochastic volatility dynamics under a constant market price of risk. The equity premium derived from the time-varying volatility scaled SDF demonstrates superior out-of-sample predictive performance relative to existing benchmarks, such as the Martin bounds.
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