India 30 Review and the Fundamental Filter
INDIA 30 ORMI © 06 July 2012
…India 30 Review and the Fundamental Filter
In the current review of the INDIA 30, we have updated the running signals with current prices as of 6 July open. The Index has pushed up marginally. 26 signals are in profit while 4 are negative. Apart from setting up a dynamic monitoring process, today we have introduced the fundamental filters for the India 30 components. Why fundamental? INDIA 30 ORMI © is an index based on the statistical idea of mean reversion and just like price performance data even fundamental data is prone to reversion. A top P/E stock is prone to reversion while low P/E stocks are prone to see a growth in value. Keeping this in mind we have introduced the fundamental filters to understanding which fundamental outliers INDIA 30 should own or disown.
Though a fundamental filter adds value to a filtering process for stock selection, fundamental data lacks history. Many of the fundamental data points are released quarterly by the company. There is little data history fundamentalists can use to statistically measure a sector or stock performance relative to a group. For example there are few Indian stocks in the BSE500 that have 30 years of fundamental data. This means that not only is it tough to create a fundamental database with 120 quarters for a universe (say 500 components) but also that fundamental analysis for a group of stocks to a certain degree may remain empirical and static. This is a limitation for us too as we try to create a fundamental filter above our statistical filters for stock selection.
We have created fundamental filters as static snapshots. We have taken the following fundamental filter parameters. 1) P/E 2) Dividend Yield 3) P/B 4) P/Revenue and a few other parameters like 5) Market Cap 6) Beta 7) Volatility (90 days).
After we laid out the fundamental filters we observed that despite its gains Wockhardt (WCKH) was both a performance and Price/Book outlier. The top performer in our list was telling us, “I am fundamentally expensive even if I am still in the India 30 list”. Same was for Gillette. The stock was a Price/Book and Price/Revenue outlier. Unlike WCKH, Gillette had already corrected and was the top loser in the portfolio. Even G is telling us I am fundamentally expensive and an outlier. A similar story featured in I, P, H, R and ZEE.
The fundamental filter screened out new outliers and improved our selection process. And whatever was not screened out was added confirmation to our remaining holdings. We did a technical check on the stocks and the final 10 which we would still buy today were M, H, H2, H3, P, B, S, N, K, Edelweiss Financial.
This current feature lets us combine the ranking filter with fundamental filters. We can create a query from the India 30 or any list of stocks. For example one can chose the components which have less than 30 P/E multiple, a positive dividend yield, a positive ROE, a P/B less than 30, Price/Revenue less than 5, Beta lower than 1, 90 day volatility less than 40% and also have a positive Jiseki cycle (Difference of monthly from weekly), pointing higher. This report carries the running signals for the sector components, Jiseki Cycles and other risk metrics.
Enjoy the latest Alpha.
JISEKI CYCLES
The risk metrics are driven by our Jiseki Time cycles, which 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.
Domnita Pascut is the founding member of Orpheus Capitals. Her interest in charts and market patterns was an extension of her keen understanding of social mood and sentiment. How charts could say so much intrigued her. She worked on market patterns, economic research, cyclicality and economic history. It was her liking for history which helped her see the cyclical natures of markets and patterns. Domnita now spearheads the extreme reversion anlaytics developed at Orpheus. She uses Jiseki Performance cycles and combines them with various risk metrics to analyse markets and filter out trading signals.