THE JISEKI WORST

Mukul Pal ·



It was on 26 Aug 2009, we first talked about the loser’s index. We are still not there to present you the first ever Jiseki Worst Portfolio or Loser’s index. But keeping the tradition of talking about the worst performers, today we illustrate the first equity curve of the Jiseki worst portfolio among 1000 global assets. A graphical representation of the change in value of a trading account over a time period. An equity curve with a consistently positive slope would generally indicate that the trading strategies of the account are profitable, while a negative slope would indicate that the account is in the red. The global portfolio contains CNX 100 stocks, S&P 500 components., Brazil 30, China 30, Commodities, Agricultural assets, global indices etc.
1) Every week we look at the worst Jiseki rankings.
2) Filter for the worst 30 components.
3) Look for the Jiseki cycles turning positive.
4) Allocate equally among 30 stocks creating a portfolio.
5) Review every week.
6) If there is an exit signal, close the stock and reallocate the cash in a new stock signal.
From the May 2010 to May 2011 highs, ‘THE JISEKI WORST’ not only delivered absolute positive returns of 37 percent but also outperformed all of SSEC Shanghai 20, DOW 30 and Sensex 30. Since the current NIFTY and market outlook remains negative sub 4,750 levels, THE JISEKI WORST should continue to outperform. In the weeks ahead we will be generating INDIA specific JISEKI WORST Portfolios. And considering we are not looking beyond 4500-4000 Nifty at this stage, the JISEKI INDIA WORST could just turn out to be a top investment opportunity. Watch this space.
To read more about THE JISEKI INDICES download the latest ALPHA reports from the Orpheus e-store.


Avinash Barnwal is Master of Science in Statistics and Informatics from IIT Kharagpur. He has worked on human response time at Department of Psychology, University of Amsterdam.  Avinash is a Quantitative Analyst at Orpheus developing money management solutions and building statistical models to address temporal challenges.