Archive for August 8th, 2012

INDIA 30 ORMI ©

The latest INDIA 30 ORMI © Index update carries the equity curve from 2006 till date. The Orpheus Risk Management Index (ORMI) is up 450% since then. The Nifty topped in Nov 2010 and 2011-2012 have been stagnant years. The ORMI Index is up 8% since Nov 2010, while Nifty is still 8% down from the Nov 2010 high. Nifty is moving up and down in choppy action since December last year. While India 30 has held ground and is running 22 components now.

In the latest enhancements we have an improved cash allocation, reduced drawdowns and better exits.

Mean Reversion

Regression to the mean was discovered and named late in the nineteenth century by [Sir Francis Galton], a half cousin of Charles Darwin and a renowned polymath. What is truly noteworthy is that he was surprised by a statistical regularity that is as common as the air we breathe. Regression effects can be found wherever we look, but we do not recognize them for what they are.

Behavioral Finance

Mean Reversion concept has been extensively used by behavioral finance experts to challenge conventional economics, which considers markets totally random. Behavioral finance has now proved that extreme groups regress to the mean over time.

Findings of reversion in stock prices towards some fundamental values remain in literature for a decade. [DeBondt and Thaler -1985] using overreaction showcased that a stock experiencing a poor performance over a 3-5 year of period subsequently tend to outperform that had previously performed relatively well. This implies that, on average, stocks which are ‘losers’ in terms of returns subsequently become ‘winners’ and vice versa.

Researchers in finance have long been interested in the long-run time-series properties of equity prices, with particular attention to whether stock prices can be characterized as random walk (unit root) or mean reverting (trend stationary) processes. If stock price follows a mean reverting process, then there exists a tendency for the price level to return to its trend path over time. If stocks which are losers becom winners that means they are showing the property of mean reversion. Fama and French (1988) also report mean reversion in U.S. equity market using long-horizon regressions, and Poterba and Summers (1988) document evidence of mean reversion using the variance ratio test.

Stationarity

Test for random walk hypothesis can be done by Dickey and Fuller [1979, 1981] and the Philips and Perron [1988, PP] method. ADF and PP tests are not so strong to test stationarity (mean reversion) because the test fails to detect slow-speed mean reversion in small samples. Hence the failure to reject the null hypothesis may not be interpreted as decisive evidence against mean reversion. Because of this inherent problem, researchers have advocated pooling data (testing various time series simultaneously) and testing the hypothesis in a panel framework to gain test power. Choudhuri and Wu [2002] showed the presence of mean reversion in emerging market using panel based test. We have applied the panel based tests on outliers from our performance ranking data.

In our academic submission to [SSRN (Social Science Research Network)] we tested a database of composite group of assets from 2005 to 2011. We created various groups of assets and ranked them on a scale of 0.1% to 100% based on their performances over various holding peridsin last 1.5 years. The ranking data was a weekly time series of 1000 assets.

The worst performers, negative outliers are chosen based on the 81 week performance (1.5 years) i.e. rankings < 20 %. We tested this list of assets for change in ranking percentile. Positive change in ranking percentile suggests an outperformance and vice versa. Then the respective assets are tracked till 2011. All the assets which have reached the 50% rankings limit are tabulated. The assets that changed in rankings from below 20% to above 50% witnessed mean reversion (earlier losers to current winners). A test was made on 20 asset outliers (ranking < 20%), which moved from sub 20% ranking to above 50 % ranking limit during 2008 till 2011 period. Outlier Performance in last 5-6 years suggested that 44% to 25% of these negative outliers witnessed mean reversion tendency. The percentage number of reverting stocks increased to 60% as we reduced the reversion limit up till 50% ranking for different groups.

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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.

Coverage India: CNX100, BSE500 traded stocks and Indian Indices.

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.