ORMI Indices and Analytics

Orpheus’ Solutions
Indexing: The Market Capitalization Methodology was first developed probably 150 years ago. Mr. Axe and Ms. Houghton were the first to build the Axe Houghton Index. Charles Dow’s work came later, sometime in the 1880s. Market capitalization methodology has been challenged globally for a few broad reasons. Why? First, because it gives more weight to winners, runs after performers, is predisposed to run after growth, away from value and hence forces investors to pay an undue price for owning the “good”. Robert Arnott made a complete case of how market capitalization methodology is a flawed approach to indexing, in his work on Fundamental Indexing. Then, there was Jensen’s alpha, which was a proof that most fund managers don’t beat the market.
Orpheus takes the indexing methodology further by proving the following. 1) Though running after winners is a losing approach; it does not make the market capitalization methodology redundant. 2) Suggests that divergence between assets can easily be used to enhance alpha. 3) It’s not about value vs. growth or momentum vs. reversion but about risk preference and holding period. 4) Data is a good proxy for value; growth; momentum or reversion. 5) Illustrates superiority of Orpheus indexing framework above the competing methodologies.
How Orpheus redefined the 100 year old ‘Mean Reversion’?
Regression to the mean was discovered in the nineteenth century by 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.
Mean Reversion Failures and End of 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 become 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.
On one side behavioral finance uses mean reversion to suggest that markets are not all random, but on other side fails to acknowledge that understanding mean reversion failure is a bigger science than highlighting behavioral anomalies. The five aspects Thaler points out in his paper (a term he confidently used to suggest that behavioral finance will be the only form of finance left) are 1) The equity premium puzzle, 2) Predictability, 3) Dividends, 4) Volatility and 5) Volume myth. All of these five aspects can be explained as mean reversion failures.
Redefining Mean Reversion; Extreme Reversion
Mean reversion phenomenon is not specific to stock market data, but data from any natural system. We proved this by using rankings derived from price performance data. A test for random walk hypothesis can be done by Dickey and Fuller [1979, 1981] and the Philips and Perron [1988, PP] method. 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 (Social Science Research Network)] we tested a database of composite group of assets for more than a decade. We created various groups of assets and ranked them on a scale of 0.1% to 100% based on their performances over various holding periods. The ranking groups had more than 1000 assets each.
We tested this list of assets for change in ranking percentile. Positive change in ranking percentile suggests an outperformance and vice versa. The percentage number of reverting stocks increased to 60% as we reduced the reversion limit up till 50% ranking for different groups. This way we redefined ’Mean Reversion’ to ’Extreme Reversion’, as outliers were showing reversion in rankings and consequently reversion in performance.
Momentum; Reversion and Risk Preference
Active and Passive are two different risk preferences. It’s like the school of thought which says value is better than growth. We all have a risk preference, what if my risk preference is not about holding value (reversion) for the long term, but playing with growth (momentum) for a shorter term. The investing community does not comprehend this risk preference. The fruit market is for everybody, somebody needs apples, somebody needs oranges, and somebody grapes. If we don’t sell Beer to the Wine drinker, why do we undersell the Active as Stone Age to sell the glorious Passive and vice versa. There is no customer surprise, delight, satisfaction in the financial industry today. “This is the only solution”. We disagree.
Our framework marries momentum with reversion, value with growth according to a preferred risk preference.
Methodology; Styles and Universe
The Index can select, allocate, across any respective group components (Example S&P 500, DOW 30, BSE500, Sensex 30, FTSE 100, ETFS, Commodities etc.). RMI uses rankings and related statistical variables and allocates based on various risk preferences and investing styles among the filtered assets or group.
ACTIVE STYLE is a periodical entry and exit signals like the RMI Active US, RMI Active Toronto, RMI Active India. The difference between them is the underlying universe. RMI Active US and RMI Active Toronto selects components from the respective Universe. Active styles are cash conserving, absolute return Indexed models. They actively enter and exit a position and go cash if needed.
THEWORST 20 STYLE is about selecting the worst components from top 100 Universe (USA, Canada, UK, India etc.). This is a quarterly rebalanced portfolio and is more about relative performance vs. the underlying top 100. This style is not a cash conserving absolute return model, but about beating its respective peer universe. Because of the idea of negative outliers outperforming, the worst 20 style outperforms the universe. So it’s portfolio basket easier to create and hold.
THE EXTREME REVERSION STYLE recreates the top benchmarks and sector indices. It’s an all invested strategy. For example the Dow 30, TSX 60, Sensex 30 or various regional sector indices like Banking, Auto, Energy, Health Care etc. Why do we need to recreate the top benchmarks? There is a section of market that is not active and wants to outperform or assume exposure to top blue chip components and sector indices like Energy.
THE RELATIVE PERFORMANCE STYLE recreates the top benchmarks and sector indices using relative performance. It’s an all invested strategy. For example the Dow 30, TSX 60, Sensex 30 components, or the GSPTSE 50, or various regional sector indices like Banking, Auto, Technology, Pharma etc.
THE BEST 20 STYLE is about selecting the best components from top 100 Universe (USA, Canada, UK, India etc.). This is a periodically rebalanced portfolio vs. the underlying top 100. This style is not a cash conserving absolute return model, but about beating its respective peer universe. It’s a portfolio basket easier to create and hold.
THE LONG-SHORT STYLE; THE SHORT STYLES; THE TACTICAL STYLE are some of the other RMI Styles
Ebooks
Risk Management Styles
Risk Management Models (Rest)
Risk Management Models (ETF)
Real Money
The Extreme Reversion (Brief)
Jiseki Query
5 Year Rolling Return Cases – Simulating Fundamental Index
Multiple_Jiseki Cycles USA and Toronto Top 30
Multiple_Jiseki_Cycles Index_and_Commodity
Divergence Cyclicality
Presentations, Product Profile, Summary
The recorded link for the Orpheus Global Webcast – Performance Cyles – Filters, Signals and Indices
Prezi presentation for the webcast
ORMI – Brief Presentation
ORMI – Product Profile
ORMI – Product Summary Apr 2013
ORMI – Active Performance
The Orpheus Risk Management Framework
Budapest Conference 19 Sep 2013
Orpheus Risk Management Indices ORMI © (India)
ORMI INDIA Active 30
ORMI INDIA Extreme Reversion TECH
ORMI INDIA Worst 20
ORMI INDIA Extreme Reversion PHARMA
ORMI INDIA Extreme Reversion AUTO
ORMI INDIA Extreme reversion Ifty 50
ORMI INDIA Relative Performance Ifty 50
ORMI INDIA Relative Performance Senzex 30
ORMI INDIA Extreme Reversion Senzex 30
ORMI India Active IFTY 5 13.09.13

Orpheus Risk Management Indices ORMI © (Global)
ORMI US 30
ORMI DAO JONES 30
ORMI Toronto 15
ORMI UK Worst 20
ORMI Australia
ORMI US Extreme Reversion SNP
ORMI North America Active 30
ORMI North American Fixed Income 10
ORMI Toronto Extreme Reversion TSAXE 60
ORMI Global Active ETF
ORMI Austria Extreme Reversion ATX Prime
ORMI Japan Nikkei Active 20
ORMI Japan Extreme Reversion 23.08.13
ORMI UK Active 20 28.08.13
ORMI UK FTSE 100 Extreme Reversion 28.08.13
Orpheus sub-advisor services for Portfolio Management
CM RMI Toronto 15 Performance Profile
CM RMI US 30 Performance Profile
Case studies
Godrej up @ 572%
The Apple Top
Yahoo, Rona, Marissa and Jiseki
Madras Cement up @ 53%
Dow @ 14000
Dow fall and Brokers rise
Prestige Estate exits @ 54%
Hathway exits @ 15% gains
Where is Indian Banking headed
Remembering NHPC
Remembering HLL
Too late for United Spirits
RMI Toronto Shines
RMI India Models Outperform
RMI US Scores 9 to 3
Babcock up 70%
The Priceless MasterCard
The Dollarama Trend
FAQ
FAQ – The ORMI Indices
Orpheus Webinars
Orpheus WEBINAR Schedule
Research and White Papers
Style Comparative Analysis
Momentum and Reversion
Drawdown Analysis
Market Scenario Analysis
SSRN – Social Science Research Papers