Archive for the ‘Research Updates’ category

RMI India Active 10 Feb

After you select the RMI model which fits your risk preference, the key question investors ask is “How should one come on model?” RMI Models are customizable for any risk preference and do not suffer from starting point bias. So it can be customized from wherever you begin. The RMI India Active 10 initiated in February has gone 70% invested. And considering the average holding period of any RMI Active 10 style for most global regions is around 200 days, we might just have our leading bullish signal for the Indian market pre-election. RMI Active is absolute capital conserving models which are designed to outperform their respective universe. RMI Active India 10 back-tested model has delivered 23% annualized at a 6% lower volatility than the respective top 100 India universe benchmark.

Enjoy the latest RMI Active India 10 February

IBB Nasdaq Biotech up 100%


There are various ways to select a big sector winner. Any sector ETF investment which delivers more than 30% over 12 to 24 months can be considered a big winner. We can adopt various tools and techniques to do so; inter-market analysis, macro economic analysis; sentiment analysis or we can look at the RMI ETF Active 10.

The model selected the NASDAQ Biotech Index back in 13 April 2012. The sector is a big winner with 118% upmove since the point of entry. Now ofcourse we can ask how did the model manage to select the respective winner? How did it know? The RMI Active Indexing solutions use the best of momentum and reversion approach to select out of the globally top traded ETF. And IBB was not the only big winner. PJP Powershares Pharmaceutic was the other above 100% winning trade. Above this the model had more than 5 above 30% movers.

The universe contains North American ETFs, which is why we have benchmarked the group to a composite of TSX and S&P500. The benchmark delivered 12% annualized with a standard deviaion at 13%. The Active 10 ETF outperformed the benchmark delivering 14% annualized with a standard deviation at 12%.

Enjoy the latest RMI Active ETF.

Orpheus Global Webcast

The Educational Web Series is a webcast seminar held at least 3 times a month featuring recognized industry professionals in a one hour long presentation – free to our membership! In the past, we’ve had such noted technicians as Martin Pring, Ned Davis, Dennis Gartman, Thomas Dorsey, Charles Kirkpatrick, CMT, and Ralph Acampora, CMT. From this page, you’ll get a glimpse of our immediate upcoming schedule and even have the opportunity to register yourself for one of these live webcasts.

5 Feb 2014

Momentum and Reversion

Momentum and Reversion are considered two different strategies, styles of investing. A few even believe that 25 years of research has failed to marry Momentum with Reversion. It’s the same way a few researchers feel about value and growth, or low or high beta etc. What if a framework could explain the divergence between M&R and how they can be redefined and understood? This could open up a new approach to signal identification and classification. The webcast will build a case for explaining M&R using Intermarket Analysis, Performance Cycles and other Behavioural Finance cases. The talk will showcase a new framework based on data universality and how M&R can be redefined, comprehended and applied for trading and investment.

Speaker Profile

Time is a social construct and we see time through the life and nature around us. Understanding Time could give a unifying theory to research of a few thousand years and also bring more than a conventional thought down. It’s a revolution. Mukul has written and spoken globally on the geometry of TIME, patterns, risk and investing; has a data innovation patent filed in his name; is an enthusiastic R data scientist and runs Orpheus Risk Management Indices, a global Indexing company. The company has built and manages the multi strategy and multi styled Indices. Mukul is the author of “Risk Management Indexing”, a book on the new Indexing approach. He is also a ranked author on the Social Science Research SSRN network. As a speaker he has been invited to speak at various platforms like the Bombay Stock Exchange, Prague Stock Exchange, Bucharest Stock Exchange, Market Technicians Association New York, Canadian Society of Technical Analysts, Saxo Bank, Thomson Reuters, TED, Princeton University, University of Chicago etc.



The Customized Active

Lot of times we get queries regarding, the paper model looks good, but there are few fresh entries. How do I go on model?

We did an extensive white paper on start point bias (Market Scenario Analysis), to explain how starting point bias does not affect the performance of the RMI. The starting point case was built to show our ability to customize a solution and explain to a large institutional client who wanted to run the RMI models for any starting point bias. We understand the RMI paper model and starting point convergence issues, which any investor may have.

How long will the RMI model performance converge or showcase in my portfolio? The convergence may happen in a few months, half a year or more. We have just tested that the starting bias does not affect performance, we have not tested for convergence or how long it may take for a fresh RMI model to converge with a back tested model. The results have shown that over few months or year, the model performances with different starting points are marginal.

The performance differential between real and model may be more for Active 10, considering it has just 10 stocks. If owing to starting customization you have slightly different 10, the performance differential may not be marginal. But that does not change the working of Active 10. The starting point could be just a good feeling of buying fresh. Because at this stage RMI Models do not know how long a winner would persist and when it will revert. Active entries don’t exit till there is a price confirmation. RMI models are designed as benchmarks and need no discretion. We believe all running entries should be bought irrespective, as exits are clearly defined.

Here is the running UK customized active performance from 1 Jan 2014.

RMI ® Active IFTY 5

What if you would have a choice to simulate the NIFTY 50 by 5 stocks instead of 50. That means using just five stock allocations you can not only simulate NIFTY 50, but do it at 9% lower standard deviation compared to NIFY 50, with 70% average invested cash and more than 180 days average holding for each component. Above this your RMI portfolio just fell 30% in 2008 compared to 60% for Nifty, you have an average worst case drawdown near 15% and about 50% chance of outperforming Nifty any running year. All comparisons to NIFTY are owing to lack of a disruptive active benchmark accomplishing an Active 5 selection out of top 50 in India. In real terms an Active model cannot be compared to NIFTY. The IFTY 5 delivered an annualized 10% (2% above NIFTY) from July 2006.

Well this is not stellar performance, as we are used with a much better ACTIVE 10 performance, but considering capital protection, lower volatility, ease of execution and a stock selection mechanism highlighting the top 5 India blue chips, Active IFTY 5 caters well to the Indian investors and global participants looking at the best in India.

We created ACTIVE IFTY 5 (updated for version 3) for the signal driven Indian market, where traders crave for stock picks. It’s still hard to simulate this portfolio on Options owing to low liquidity even in the top 50 stocks. So this remains a spot only portfolio for us. All simulations for 2 times and 3 times are just simulations and should not be attempted using derivatives.

The Dollarama Trend

At 6 billion dollar market capitalization, this is not just any discount store. The store sells Cleaning supplies, Toys, Candy, Grocery, Gifts, Healthcare products, Kitchenware, Stationery, Party Supplies, Hardware. The game is sourcing, pricing and distribution. The competency comes from history, size and real estate. And then consumption does the rest.

This was our last exit from the RMI Toronto 10, up 75% in 475 holding days. BCE was another top exit at 65%.

The RMI Toronto Active 10; holds components for an average 313 days, delivered 40% annualized (over 10 years), at 18% Standard deviation; and outperformed secularly in all the 12 years. This compared to the TSX; at 6.5% annualized, 18% Standard Deviation and secular under-performance against RMI over the last 12 years.

The Priceless MasterCard

MasterCard was a one way road from 2009 lows. On Jan 30 the stock was 135. Now it’s at 800. This means a return of near 500%. This means more than 100% returns annually. Even if for a moment we accept that it was humanly possible for you to pick up MA there in Jan 2009, because you are a contrarian, because you trained under Warren, or maybe you are just too good. Now if we tell you to repeat this by picking not one but three stocks from Jan 2009. We know it’s going to get harder and nearly impossible if we tell you to pick a portfolio of 10. We don’t think any available artificial intelligence could accomplish this feat. This is why if we can capture a part of this ALPHA, it’s a hallmark of a good system. If we can repeat this performance for multiple markets we have the RMI Active approach.

The RMI US Active identified MA more than 900 days back delivering 200% from Jun 2011. The other two near 200% winners were VISA and Gilead. Now one may question what the Credit Card companies knew which everybody who questioned the uncertain pit did not? Well these are all questions that accompany hindsight bias, maybe VISA and MA themselves did not know what rockets will power them. At the end of day what matters are results not cause; affect and explanations.

The RMI US Active 10; holds components for an average 267 days, delivered 28% annualized (over 10 years), at 16% Standard deviation; and out of 12 years outperformed all 12. This compared to the US 100; at 4% annualized, 20% Standard Deviation and secular under-performance against RMI in the last 12 years.

Babcock up 70%

Babcock was set up in 1891. A Scottish structural engineer Sir William Arrol was the first board member. He was the son of a spinner and started work in a cotton mill at only 9 years of age. He started training as a blacksmith by age 13, and went on to learn mechanics and hydraulics at night school. In 1878 he built the Caledonian Railway Bridge over the Clyde, and in 1882 he reconstructed this Tay Rail Bridge. Today Babcock is a global engineering support services Company, working on Defence and Security, Support Services, Marine and Technology. The company does maintenance work on the United Kingdom’s nuclear submarine fleet.

The stock was up 70% from RMI entry 637 days back. Investors are always looking for best stock pickers. Here are the other two top RMI UK Active 10 picks which delivered more than 50% for 2013. TUI Travel and Prudential also overshot the 50% profit mark for the year. If stock picking is an art, good stock picking year over year is golden hands, and doing this on a portfolio basis; well! we call it RMI Active.!

The RMI UK Active 10; holds components for an average 223 days, delivered 11% annualized (over 10 years), at 14% Standard deviation; and out of 14 years outperformed in 12. This compared to the UK 100; at 2% annualized, 20% Standard Deviation and 2 years outperformance in 14 was more than good stock picking.

So here is the New Year Gift. The Current Running Active UK Active 10 has these current running components. Babcock International, TT TUI TRAVEL, PRU Prudential, CPI Capital, LLOY Lloyds Banking; WPP, JMAT Johnson Matthey, ICAG International Consolidated Airlines Group, RB Reckitt Benckiser, AV Aviva. One of these holdings is running for more than 640 days.

RMI ® India 10 v3

Happy New Year. The RMI Active v3 is a 10 stock portfolio selected from the top 100 India universe. It trades on average 23 trades annually (2.3 trade per component). This gives it an average holding period of 190 days per component. The average cash is 30%. The RMI model is at a new historical high and at 11% has beaten the Nifty (at 5%) (Similar returns for CNX100). The model has relatively outperformed and is all invested now. The exits have been further simplified. We have one trailing exit for protecting profits and one stop loss. RMI’s annualized performance is at 25% vs 9% for Nifty. We have added a new drawdown section which illustrates the weekly losses of more than 10%. We also have a new updated annexure. Enjoy.


RMI US Scores 9 to 3

Like other anomalies, I remember the year ending in ‘5’ anomaly of 2005. The “anomaly” was that year ending in ‘5’ tend to be positive. It was last trading day which nudged the year to positivity. I think it was 31 Dec, which moved up 67 points and put the otherwise sideways year into glory. “Yeah it’s a green”, news byte. This is why few believe that 2015 is going to be stellar. So as the saying goes, “As goes Jan goes the year”. For an active money manager it could be “as goes the year, goes the portfolio”. This is a general positive or negative tendency of the portfolio, not really outperformance or underperformance.

Active money deserves a lot of flak it gets, as it tends to tag, piggy back, rather than stand up on its own. This is why you won’t hear many active performances talking about outperformance vs. S&P500. “It’s tough to beat a bull, bear markets anyway destroy wealth”. Active money is a cry baby.  How many times did you hear this in your newsletter, “market conditions were not helpful”.

Ok! We too are the new kids on the block, claiming to have a superior active approach. Ok! We have limited audited real money history. But what we have, which other Active’s lack, is a framework, which works across assets, across markets, across risk preferences. When something this scalable can be created, it gives us courage to talk about it to the industry and our other Active peers, “you can do it too”, “alpha can be generated without piggy backing”, “low correlation portfolios are possible from the same universe”, “portfolios can perform in all market scenarios”.

Well! This is a journey, and only time will tell how happy money will be licensed under RMI. But at this point of time, just like RMI Toronto we had a real money good year on RMI US too. The real money did lag behind, as the portfolio size was 30. We are introducing Active Version (3) shortly with just 10 stocks. All our Active models may be limited at 10 component size. So coming back, RMI US 30 model delivered another positive outperformance as it inched above the S&P500.

Again this is no great shakes, as it’s Active’s task to outperform. But when we have a secular bull, an active strategy designed to capital conserve is not prepared to just buy and hold. Any sensitive exits, costs it alpha. The reason RMI could still beat S&P 500 despite being active was because of the superior selection framework. Even if the model was designed to last an average 40-60 days holding period per component, it selected just 30 stocks out of 500 stocks. This is a large universe to make superior selections.

An outperformance was the minimum expectation from the model. On average RMI US 30 was up 8% more than the S&P 500 on an annualized basis. This was at a marginal lower volatility. And with this year under its belt, the RMI beats the S&P 500 9 times in 12 periods. We don’t know of any other potential open source models which do this. But having said that, 1% outperformance on an Active compared to the benchmark is a bit below expectation. We are learning, improving our systems, comprehending and training them back. But we can give it to the RMI. It’s like a child, we can’t get upset with him (her). He (she) did what best it could do. And we are happy about that. Have a great Christmas.