Identifying and evaluating horizontal support and resistance levels: an empirical study on US stock markets
AbstractWe propose a novel rule-based mechanism that identifies Horizontal Support And Resistance (HSAR) levels. The novelty of this system resides in the manner it encloses principles, found in well known technical manuals, used for the identification via visual assessment. The drawing of these levels derives from historical locals, rather than denoting support (resistance) levels from the lowest (highest) price levels of precedent constant time intervals. We further proceed in evaluating whether these levels are efficient trend-reversal predictors, and if they can generate systematic abnormal returns. The dataset used includes adjusted for dividends and splits, daily closing prices of stocks listed on National Association of Securities Dealers Automated Quotation (NASDAQ) and New York Stock Exchange (NYSE) for the last 2 decades. Our results are aligned with the efficient market hypothesis. More concretely, support levels outperform resistance ones in predicting trend interruptions but they fail to generate excess returns when they are compared with simple buy-and-hold strategies.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Taylor and Francis Journals in its journal Applied Financial Economics.
Volume (Year): 22 (2012)
Issue (Month): 19 (October)
Contact details of provider:
Web page: http://www.tandf.co.uk/journals/routledge/09603107.html
You can help add them by filling out this form.
reading list or among the top items on IDEAS.Access and download statistics
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael McNulty).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.