The Conditional Distribution of Excess Returns: An Empirical Analysis
The Conditional Distribution of Excess Returns: An Empirical Analysis
复制标题
DOI：
10.1080/01621459.1995.10476537
复制
发表时间：
1994-11
期刊：
影响因子：
--
通讯作者：
Silverio Foresi;Franco Peracchi
中科院分区：
文献类型：
--
作者：
Silverio Foresi;Franco Peracchi
摘要在这篇文章中，我们描述了累积分布函数的超额收益的条件下，一个广泛的预测，总结了经济状况。我们通过估计响应变量值网格上的条件logit模型序列来做到这一点。我们的方法揭示了更高阶的多维结构，不能只通过建模的前两个时刻的分布。我们比较了两种建模方法：一种是基于传统的线性logit模型，另一种是基于加性logit模型。第二种方法避免了完全非参数方法的“维数灾难”问题，同时保留了可解释性和让数据确定响应变量和预测变量之间关系的形状的能力。我们发现，加性logit更适合，并揭示了数据的方面，仍然未检测到的线性logit。加性模型在样本外预测和投资组合选择中仍保持其优越性。
Abstract In this article we describe the cumulative distribution function of excess returns conditional on a broad set of predictors that summarize the state of the economy. We do so by estimating a sequence of conditional logit models over a grid of values of the response variable. Our method uncovers higher-order multidimensional structure that cannot be found by modeling only the first two moments of the distribution. We compare two approaches to modeling: one based on a conventional linear logit model and the other based on an additive logit. The second approach avoids the “curse of dimensionality” problem of fully nonparametric methods while retaining both interpretability and the ability to let the data determine the shape of the relationship between the response variable and the predictors. We find that the additive logit fits better and reveals aspects of the data that remain undetected by the linear logit. The additive model retains its superiority even in out-of-sample prediction and portfolio s...