The price confirmation filter

Price confirmation is an important indicator. According to Robert Aronson, the complex algorithm has a higher chance of working that a simple algorithm. What is a simple algorithm? A system that tests a single indicator is a simple algorithm. If we layer the system with various steps, it becomes a complex algorithm.
We have illustrated the Jiseki Cycle, the rankings, the Jiseki Pair Cycle, the running signals for various Jiseki cycle crossover, the divergence plots of various assets benchmarked to cash and divergence plots of various assets benchmarked to an index. Today we add the price filter to our list of query. This makes our approach of signal selection a complex algorithm.
How did we do that? We first generated a query for plotting a histogram of rankings with the following steps.
1) Take the universe of 3000 assets
2) Select from this universe the sub group of all US Indices and ETFs.
3) From this list generate all the negative outliers below 20% rankings.
4) On this list filter out stocks where the Jiseki weekly is greater (>) than the Jiseki monthly cycle
5) To check if step 4 list also has a positive price confirmation filter out the 6) list for assets that have price 5 week > 20 week average
7) After this make all possible pair combination between this list and filter out the top fifth relative performing ideas.
8 )  Is the pair Jiseki cycle i.e. S&P Telecom vs. S&P Banks positive (J1>J2) or negative (J1<J2).
9) Is the relative performance (RP) S&P Telecom vs. S&P Banks positive (5 week RP average >20Week RP average) or negative.
10) Take out the best top performing but least ranked assets from this list.
11) Plot the histogram for this list.
12) Analyze this list technically
We got 68 US Indices and ETFs in step 5, which we filtered out the following 11 assets. Many of them belong to the early economic sector viz. realty and technology. This brings us to the basic question. If technology and real estate are the best long ideas is the broad market going up or down?
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Our Jiseki Time cycles are seasonal patterns of strength or weakness in assets. They are derived from percentile rankings from 1 to 100. The higher the percentile more the chance for an asset to weaken and worst the ranking, better the chance for the respective asset to outperform. 100 is top relative performance and 1 is worst performance. The idea is that performance is cyclical. A top performer will underperform in future and vice versa. A top relative performer is also the worst value pick and the top relative underperformer is the best value pick. Jiseki is another name for Performance cycles, time triads and time fractals. The signals are illustrated as a running portfolio and as Jiseki Indices. These signals can be used by fund managers for relative allocations, traders for leverage bets and high net worth clients for selective trades.
Jiseki Interpretation. Signals are interpreted as crossovers between various Jiseki Cycles. All three Jiseki cycles (Jiseki 1,2 and 3) depict different time frames. Example: An asset is ranked above 80 percentile and all the three Jiseki cycles are pointing lower, this suggests a running SHORT SIGNAL. Our Jiseki Indices use different kind of exits based on price and Jiseki Cycles. We have color coded the (Jiseki 1>Jiseki 2) SHORT zones with brown sandy (burlywood) and grey (Jiseki 1>Jiseki2) for LONG SIGNALS.
Dr. Ionut Nistor is the co-author of Performance Cycles paper published in Kyoto Economics Journal in March 2009. Ionut is a professor of Corporate Finance at Babes -Bolyai University and a post doctorate fellow at the Kobe University in Japan. He is fluent in Japanese, Romanian and English.
 
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