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Strategies & Market Trends : TA-Quotes Plus -- Ignore unavailable to you. Want to Upgrade?

To: Richard Estes who wrote (8957)	3/13/1999 5:57:00 PM
From: Nine_USA	Read Replies (3) \| Respond to of 11149

Richard, What you say in post 8957 is a lot closer to my methodology. There are still differences which are not too important and not worth pursuing. <<I deduce that based on your mindset it would be appropriate to trade high priced stocks.>> Here, I did not make myself clear. Price level is just one of 56 variables which I have identified which I have found to be positively correlated to subsequent performance. Some are based on price, volume and their derivatives (like QRS and moving averages}. Others are fundamental like yield, SIC performance, debt, marketcap, short, float, and many others. I am sure that by itself, price level is not sufficient as a basis for investment. But assigning weights to all variables I have backtested and found to contribute to return, lets me pursue the posibility that enough variables will sum (or hopefully, more than sum) in the direction of improving performance for me to expect to outperform the best performing stock indices, Say the SP500 or the Nasq 100. <<I haven't seen your scans or database to understand what variables are present. I can't jump to that being true in the universe of stocks.>> I haven't concluded that my results to date will project equally well in the future. But I don't see any reason why it is not POSSIBLE to obtain excellent results with my approach. Most readers of this thread are doing what I do with 3 exceptions: a) by and large, ignoring the fundamental part of the data. b) implicitly, EQUALLY weighting each qualifying compare in their scans. c) they are not backtesting with 'data, as it then existed'. The last point is important. If one did a backtest on the QP2 database today and price level of 70 or more as of 1 year ago were required, YHOO would not qualify because price would show as 20.50. But the then trading price was 82 since the stock had 2 2-1 splits during the last 12 months. To the QP2 user doing backtesting today, the effect of splits is to reduce the ostensible %returns of the high price range stocks have split FROM, and erroneously increase the %returns of the lower price ranges these stocks have split into. Maybe this partly explains why you haven't seen the correlation of price and performance which I find. Again, I don't wish to exaggerate the importance of price level to me. It is just one of 50 to 60 which I use.