Seasonal Stock Market Trends: The Definitive Guide to Calendar-Based Stock Market Trading (Wiley Trading) |
 | Author: Jay Kaeppel
Publisher: Wiley
List Price: $60.00
Buy New: $32.94
as of 11/25/2009 01:21 CST details
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Seller: indoobestsellers
Rating:  2 reviews
Sales Rank: 91593
Media: Hardcover
Pages: 298
Number Of Items: 1
Shipping Weight (lbs): 1
Dimensions (in): 9.1 x 6 x 1.4
ISBN: 0470270438
Dewey Decimal Number: 332.6322
EAN: 9780470270431
ASIN: 0470270438
Publication Date: January 9, 2009
Availability: Usually ships in 1-2 business days
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Editorial Reviews:
Product Description
There is a seasonal bias to the stock market, and by paying attention to the seasonal market tendencies you can gain an edge in the stock market over the long haul. Seasonality offers a practical approach to investing and trading. What better way to learn how to employ seasonal systems than learning from Jay Kaeppel, a master in the analysis of seasonal trends? Kaeppel walks you through this phenomenon that continues to work consistently, providing you with his ultimate seasonal index to make the calendar work for you. Stock Market Seasonals provides a never-before-seen definitive guide that illustrates how to utilize a combination of four basic seasonal tendencies in order to maximize returns.
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Customer Reviews:
 Enjoyed the book March 3, 2009
TrendTrader
6 out of 8 found this review helpful
The book was well written and informative. I had heard of a lot of the trends in the past, but there were several that were new to me as well.
I recently subscribed to http://www.researchtrade.com. The site researches stocks to uncover historical trends based on calendar as well as company earnings releases. I have found that using their research along with some simple technical analysis produces very good results.
 poor research January 6, 2009
tiger taco (usa)
11 out of 15 found this review helpful
I coded the main system (KTI) presented in the last chapter into Tradestation. The results are spectacular as the author claimed for years 1934 through 2007. "Incidentally", the worst drawdown is for the only year the author didn't have the data for (which is 2008). This is because he didn't separate the available data into test and train subsets which is quite standard technique. Of course, if one tests the results on the same data they used to derive the system rules the outcome will be excellent.
Take this review as a warning.
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