Archive for the ‘Research Updates’ category

Neck to Neck


If there was one real test for an ACTIVE strategy it was beating the benchmark S&P 500. A secular market is hard to beat. And S&P 500 has been one secular unrelenting BULL from 2009. Any ACTIVE strategy that could beat the S&P 500, great proof. RMI US 30 just seems to be reaching there running neck to neck. As we head into NOV end, the RMI US 30 was marginally higher than the benchmark. Well we still have a month to go, but how did we do it? Nothing seems more important than being invested and this is what the RMI did, stayed invested and it remains invested.

Enjoy the latest RMI US 30 Active


India Active; 90% invested

RMI India Active 10

Enjoy the latest RMI India Active 10

ZUM, ATX best


ZUMTOBEL is the top allocation of RMI ATX Prime. Enjoy the latest update.

UBS, STOXX 50 worst

UBS (1)

UBS is the worst allocation for the RMI. Why? Read more about it in the latest RMI STAUXX 50.

What’s with OCADO?


OCADO is a running signal in the RMI Active UK 20. And the stock has moved up 50% in the last 95 days. This is definitely an outlier, but that’s what RMI does identify negative outliers at low risk entry points. A few of them just end up moving from the worst to best, like OCADO has done over the last 6 months, moving from 100 to 400. OCADO is in the retailing technology and also an online retailer. At 2 billion GBP, OCADO can be easily considered a regional sector major. The RMI UK Active 20 is up 30% for the year compared to FTSE 100, which is up 13% for the year.

Enjoy the latest RMI Active UK 20.


Market Scenario Analysis


Risk Management Indexing index construction methodology has showcased it’s workability across markets, assets, risk preferences. In this white paper we illustrate the working of RMI across different market scenarios, a bull market, a bear market and a sideways market. We had such market scenarios over the last decade across regions. For this paper we have taken the DAO 30 and STAUXX 50 RMI models (The RMI versions of the DOW 30 and STOXX 50).

Scenarios: Different market scenarios translate to different starting points. There has always been a question regarding what if the RMI would have started in a different point of time. The idea was to assume different periods of growth and decay all not necessarily ending in the ongoing Nov 2013. Different periods of testing would test the methodology over different volatility conditions and remove any starting point bias.

Rebalancing strawman: Another discussion regarding rebalancing periods also becomes pertinent at this stage. The debate about whether to rebalance or not to rebalance takes another direction; as Arnott points out in, “Rebalancing still works”, writing a counter argument against Paul Merriman’s, “Why rebalancing could be a huge mistake”. Arnott said “Merriman has merely put forth, and knocked down, a flimsy and meaningless straw man. His argument requires that an investor, who values a particular asset mix at the outset, has no cares about how far that mix may drift away from that starting mix over time. If rebalancing is useful for asset allocation, it’s useful within segments of the stock market”. Merriman had suggested that rebalancing could work between stocks and bonds but not among stocks itself. Even Jason Hsu (Arnott’s team) points out in,“why we don’t rebalance”.“Despite all of the intellect and adaptive learning that we bring to bear, sadly human beings with our changing risk aversion are poorly suited as stewards for managing long-term returns.

But is rebalancing the only contributor to alpha? Just because investors suffer from behavioral errors and are ill equipped to understanding and time value, should rebalancing as an idea be overemphasized? Though rebalancing could be understood as a point of divergence warranting a need for allocation, but a superior allocation methodology could work across rebalancing periods and rebalancing period can just become another optimizable quant variable. The RMI methodology works across rebalancing periods.


Sharpe Ratio: Where Ra is the asset return, Rb is the return on a benchmark asset (taken as 1%), such as the risk free rate of return or an index such as the S&P 500. E[Ra-Rb] is the expected value of the excess of the asset return over the benchmark return, and {sigma} is the standard deviation of this excess return.

Summary: Periods of study; both the Indices have been studied for a minimum of 4 years and max of 10 years with starting data from 2000. The outperformance periods across returns, annualized returns and volatility was skewed in favor of the RMI. In case of the DAO 30, only one period of underperformance over 17 test cases and two periods of marginal higher volatility (less than 0.1%). The RMI methodology can work very well on a few markets. STAUXX 50 is one of the best cases for RMI just like TSX Toronto. The STAUXX 50 beat its benchmark in all the 17 cases (across volatility and returns). Looking for an underperforming case would be no more chance, but a cooked up case.




To download the latest report please visit

For knowing more about ORMI Indices mail us for details or contact a sales representative.

Presentations and Primers: ORMI Indices and Analytics

RMI Toronto beats the S&P TSX


A key test for trading systems, quant strategies or models is how they behave in different market conditions. At any point of time there are markets which are positive, negative and sideways. This is quite normal as at a group level market components are witnessing different performance cycles. The RMI US Active 30 was benchmarked against the S&P 500, when the respective benchmark has been in a secular upside.

How to build a model which works across markets? A model for all markets has to come from universal laws, something that can see the big picture, and something that can filter out performance even in a lackluster market; something that can understand the spectrum of performances across risk preferences and holding periods.

The S&P TSX has been in sideways action since 2010. Now as we head into 2014, this would make it one of the longest sideways actions among global markets. The RMI Toronto Active 15 has outperformed the benchmark for the last 11 months, delivering 10% for the year and overall 22% annualized over the last 10 years. Both RMI and the benchmark had a similar volatility. RMI methodology is based on a universal law this is why most RMI models outperform their respective universe. RMI Toronto has been pretty spectacular among the RMI models. It has underperformed the benchmark only once in the last 10 years.

Enjoy the latest RMI Toronto 15




RMI US 30 beats S&P 500

Beating the market when it’s in a secular upside is a hard feat. This is why there are few markets that have outperformed the S&P since 2009. RMI US Active 30 however manages to eke out another outperformance by running marginally ahead of S&P 500 this year. The active model remains 90% invested and has an average holding period of 40 days. The RMI US Active has delivered 12.33% annualized return compared to 3.78% for the S&P 500 over the last 10 years. RMI has a standard deviation at 16.6% compared to 18.4% for the S&P 500.

Enjoy the latest RMI Active US 30





Orpheus @ Ahmedabad

” The New Passive ”  - 20 Oct 2013

The investment business is primarily about beating a sector benchmark, or peer funds, or simply delivering more than a composite index. Though 90% of the money managers fail to consistently beat the benchmark, delivering more than the benchmark is considered as a filter which separates the outperformers from the rest. While the market community is focused on this outperformance, little research has been done on financial innovation which recreates, redefines, recalculate the benchmark (composite index) itself, to enhance alpha, reduce risk and extend the passive indexing domain. Very few have attempted this feat like S&P Dow Jones Indices, Russell and Fundamental index, the innovators end up becoming the new market itself. The presentation will talk about the new age global indexing techniques and index enhancing smart beta approaches and how Indian investors and money managers can utilize the new passive for diversification and risk management across Indian asset classes.


Meeting Schedule:

09:45 AM - 10:00 AM : Registrations Open
10:15 AM - 11:15 PM : Educational session 1
11:15 AM - 11:45 AM : Networking Tea
11:45 PM - 13:00 PM : Educational session 2


Ahmedabad Management Association ATIRA Campus,
Dr. Vikram Sarabhai Marg,
IIM-A Road,
Ahmedabad - 380015

Register for the event


Orpheus @ Vienna


Fusion Analysis: Combining Fundamental, Quantitative and Technical Analysis

The MTA is excited to announce a collaboration with Raiffeisen Bank International to present the MTA Annual Meeting – a full day technical analysis educational seminar on November 15th, 2013.  The presentations will be focused around the concept of combined analytical models, or what has been called “Fusion Analysis.”

Delegates will have a chance to hear from leading investment professionals on the intersections of quantitative, fundamental, macro-economic and technical disciplines. As the demands on investment professionals increase, new tools for asset allocation, position sizing, idea generation (specifically relating to emerging markets), sector rotation and a consultative portfolio management strategy are paramount.

This is a great opportunity to build relationships among the Toronto investment community and takeaway practical strategies for your investment practice.


8:00 AM – Registration and Breakfast

9:00 AM – Opening Remarks

9:15 AM – Session #1: Global Macro Outlook for European Markets with Bernd MaurerRobert Gillingerand Valentin Hofstatter

In this session each of our three panelists will present their investment approach and how they combine fundamental, technical and quantitative inputs to their overarching strategy. The panelists will address sectors and individual stocks that present attractive opportunities through the end of 2013 and beyond.

10:45 AM – Networking Break

11:15 AM – Session #2 with Robert SchittlerBrian Whitmer, and Andrew Simpson-Parker

Elliott Wave Utility: Long-term macro to daily trading strategies.

12:30 AM – MTA Presentation: Global Growth of Technical Analysis with Tyler Wood

The speaker will present on a variety of topics pertaining to the MTA, such as the CMT Program, Body of Knowledge, and reliance on technical analysis.

1:00 PM – Lunch Session and Professional Networking Opportunity

1:30 PM – Session #4: Behavioral Finance: Understanding Crowd Psychology for Risk and Return:with Patrick OberhaensliMukul PalRon William, & Alexander Spiroglou

3:30 PM – Networking Break

3:45 PM – Market Forecast Panel and General Q&A

5:00 PM – Professional Networking and Cocktail Reception