Abstract
In the previous chapter, we concluded that no noticeable autocorrelation exists for daily returns. This implies that knowing the level of the previous day’s return does not help us in forecasting today’s return. The hypothesis we will formulate in this section is that we can artificially create a time series that is somewhat forecastable. We will refer to this new time series as a spread. The claim we are making is that a stock spread has a better chance of being tradable than an individual outright does. This, of course, is a subjective and suspicious statement in and of itself. Bear with me, though for the remainder of the chapter. I am mostly interested in conveying a methodology of thinking rather than a concrete fact about price behavior.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Copyright information
© 2015 Folk Creations, Inc.
About this chapter
Cite this chapter
Georgakopoulos, H. (2015). Spreads, Betas and Risk. In: Quantitative Trading with R. Palgrave Macmillan, New York. https://doi.org/10.1057/9781137437471_6
Download citation
DOI: https://doi.org/10.1057/9781137437471_6
Publisher Name: Palgrave Macmillan, New York
Print ISBN: 978-1-349-46986-4
Online ISBN: 978-1-137-43747-1
eBook Packages: Palgrave Business & Management CollectionBusiness and Management (R0)