More on Stock Selection Strategy: Alpha Hunting, Risk Adjustment, and Nonparametric Diagnostics

Lingjie Ma
Additional contact information
Lingjie Ma: University of Illinois at Chicago

Chapter Chapter 5 in Quantitative Investing, 2020, pp 181-227 from Springer

Abstract: Abstract In the previous chapter, we introduced a general procedure and multi-factor framework for alpha construction of stock selection strategies. In this chapter, we continue to explore stock selection strategy with more advanced topics. In particular, we focus on alpha (new factor) hunting, risk adjustment, and nonparametric diagnostics. Regarding new alpha discovery, we present the guidance of IPARE. From a methodological perspective, we introduce the weighted least squares (WLS) method, which provides a tool to integrate risk into a multi-factor alpha model. We then introduce nonparametric approaches as a complement to parametric analysis. In the industry insights section, we provide a nonparametric diagnostics package used in the industry to investigate a new factor. The last section on R programming shows how to refine plots with parameters.

Date: 2020
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-47202-3_5

Ordering information: This item can be ordered from
http://www.springer.com/9783030472023

DOI: 10.1007/978-3-030-47202-3_5

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().