Archive for June, 2012

The Fundamental Filter

Food and Personal Products - Risk Metrics
.also introducing the Fundamental Filter

Though a fundamental filter adds value to a filtering process for stock selection, fundamental data lacks history. Many of the fundamental data points are released quarterly by the company. There is little data history fundamentalists can use to statistically measure a sector or stock performance relative to a group. For example there are few Indian stocks in the BSE500 that have 30 years of fundamental data. This means that not only is it tough to create a fundamental database with 120 quarters for a universe (say 500 components) but also that fundamental analysis for a group of stocks to a certain degree may remain empirical and static. This is a limitation for us too as we try to create a fundamental filter above our statistical filters for stock selection.

In this latest ALPHA we have studied 33 Food and Personal Products sector components from the Indian BSE 500 universe. We have created fundamental filters as static snapshots for 24 of them (available data). We have taken the following fundamental filter parameters. 1) P/E 2) Dividend Yield 3) P/B 4) P/Revenue and a few other parameters like 5) Market Cap 6) Beta 7) Volatility (90 days).

We combined the ranking filter and fundamental filter. And from the 24 list of stocks we chose the ones which have less than 30 P/E multiple, a positive dividend yield, a positive ROE, a P/B less than 30, Price/Revenue less than 5, Beta lower than 1, 90 day volatility less than 40% and also have a positive Jiseki cycle (Difference of monthly from weekly), pointing higher.

We obtained a list of stocks after the fundamental filter, which we filtered further using the ranking and price trend screens. Most of the fundamental filter stock passed through the ranking and price filter screens. This confirmed that value play components were similar whether one used a statistical filer or fundamental filter. This report carries the running signals for the sector components, Jiseki Cycles and other risk metrics.

Enjoy the latest Alpha.

Fundamental Fiters

This condition filtered 8 out of 24 stocks viz. Godrej, EMAMI, Tata Global, Godfrey Philips, VST Industries, Jyothy Labs, Bajaj Corp and Tata Coffee. It might look surprising but none of ITC, HLL and Gillette made it to this list. This suggests that even fundamentally speaking components of the food and personal product sector diverge on a classification of value play or already strong.

 Download the special FMCG and Personal Product Sector Report


Dr. Ionut Nistor is the co-author of Performance Cycles paper published in Kyoto Economics Journal in March 2009. Ionut is a professor of Corporate Finance at Babes -Bolyai University and a post doctorate fellow at the Kobe University in Japan. He is fluent in Japanese, Romanian and English.

The Bric Model from a Japanese Perspective
Ionut Nistor - Econohistory


Remembering the 1990′s

 

Markets are natural beings, this is why patterns and market structure repeat. The ongoing structure on Nifty from 2009 has a stark similarity to the market structure from 1996 to 2003. Now this is conventional pattern watching much different from machine learning, but if the similarity is to be believed we are in for a larger bull like the one seen from 2003 lows. Since the current structure (2009-2012) is  a third of what we saw in 1990’s even a proportionate extrapolation can take us to Nifty 7000. And we should keep in mind that if the structures are similar, a large break of 4,700 can be ruled out.

You can read the complete article in Business Standard

Mukul Pal, is a Chartered Market Technician, MBA Finance and a member of the reputed Market Technicians Association (MTA). He has more than a decade of Capital Market experience dealing with derivatives and global assets. He has worked for Bombay Stock  Exchange, multinational Banks and brokerage houses in leading research positions before starting on his own in 2005. He is the President of the MTA Central and Eastern European Chapter.


INDIA 30 ORMI © Running Signals

..also Introducing ALPHA on WEB

The latest INDIA 30 ORMI © update carries a portfolio update from May 2011 till date. Our risk management benchmark is up 7.5% for the period. This is 15% up compared to the Sensex 30. An index or portfolio performance is connected to the starting period. Testing a methodology in a stagnating and negative time is putting the idea to a real test. The period from May 2011 has been extremely choppy for Indian markets. Though INDIA 30 ORMI © also experienced whipsaws, it conserved cash and remained positive after 12 months. Since ORMI © indices are designed for passive more than 3 months average holding period, it is tough to simulate it for a shorter period of time than 12 months.

Just like the 2009 and 2007 simulations which we published in previous issues, even the 12 month ORMI is totally invested with 30 components. This suggests that ORMI assumes outperformance for the selected 30 components. This is a positive sentiment indicator for us.

The latest feature also introduces new graphics for our members who want to pick and choose from among the INDIA 30 components and also want to understand the INDIA 30 components a bit more. Our members can also judge, which INDIA 30 components are better to enter now and which ones can be held on too..

1) ..based on holding period, recent entries.
2) ..based on returns, which ones are continuing to grow.
3) ..based on technical perspectives and levels.
4) ..based on Cycles and Rankings
5) ..based on other risk metrics.

The INDIA 30 ORMI © is our standardized offer for an INR 10 lakh investment. The other customized ORMI indices work with enhanced filters of market capitalization, volume, fundamental filters, statistical filters etc.

And last but not the least, we are happy to introduce the new ALPHA on WEB. The new feature uses the latest R Markdown technology. How is this feature different?

1) Now we don’t have to pick and choose elements like rankings, cycles or signals.
2) The feature contains all elements in one place.
3) A web based research also makes for easy viewing.
4) Updation and maintenance of the research feature is easy.

Enjoy the latest Alpha.

FHCL (Future Capital) and Thomas Cook are undergoing corporate action.

JISEKI CYCLES

The risk metrics are driven by our Jiseki Time cycles, which are seasonal patterns of strength or weakness in assets. They are derived from percentile rankings from 1 to 100. The higher the percentile more the chance for an asset to weaken and worst the ranking, better the chance for the respective asset to outperform. 100 is top relative performance and 1 is worst performance. The idea is that performance is cyclical. A top performer will underperform in future and vice versa. A top relative performer is also the worst value pick and the top relative underperformer is the best value pick. Jiseki is another name for Performance cycles, time triads and time fractals. The signals are illustrated as a running portfolio and as Jiseki Indices. These signals can be used by fund managers for relative allocations, traders for leverage bets and high net worth clients for selective trades.

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.


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.


Sensex Pair 30 - Risk Metrics

On 14 June 2012 we introduced the Jiseki Cycles for Sensex 30, on 20 June we published risk metrics on the Indian Banking sector and on 21 Jun we carried an Indian Sector Special. Today we introduce a new web service called Sensex Pair 30. This service looks at the dynamics of all Sensex components vs. Sensex. The dynamics include relative performance, Jiseki pair cycles, various Risk Metrics and running signals.

This web service illustrates intermediate multi week performance perspectives for the Sensex components and fulfills the following objectives.

1) It identifies the strongest Sensex Component.
2) It identifies the weakest Sensex Component.
3) It identifies the outperforming and underperforming components in the Sensex.
4) It generates running signals for all 30 Sensex pairs (Sensex vs. it’s components)

Since Sensex is the average of the 30 components, we should see half of the Sensex components outperforming the Index and half of them underperforming. But in reality we witnessed a skew, there were half of the Sensex components outperforming. Another 10 were stagnating and value plays. Only 5 components were clearly underperforming the Sensex. What does this tell us? This tells us that performance is not equally distributed. It’s disproportional. The best Sensex component was HLL and the worst was GAIL.
In this update we have added new elements to the Sensex pair 30 subgroup. We have added a Risk Matrix based on ranking, a risk matrix based on price, group analysis, ranking histograms and Jiseki cycles. The latest ALPHA goes about analyzing the Sensex pair 30 components based on performance rankings and cycles.

The risk metrics are driven by our Jiseki Time cycles, which are seasonal patterns of strength or weakness in assets. They are derived from percentile rankings from 1 to 100. The higher the percentile more the chance for an asset to weaken and worst the ranking, better the chance for the respective asset to outperform. 100 is top relative performance and 1 is worst performance. The idea is that performance is cyclical. A top performer will underperform in future and vice versa. A top relative performer is also the worst value pick and the top relative underperformer is the best value pick. Jiseki is another name for Performance cycles, time triads and time fractals. The signals are illustrated as a running portfolio and as Jiseki Indices. These signals can be used by fund managers for relative allocations, traders for leverage bets and high net worth clients for selective trades.

 

Enjoy the latest Alpha.

For more such interesting updates visit the Reuters Store or mail us for subscription details.

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.

Michesan Anna-Maria, discovered her interest of markets immediately after completing her graduate studies in Economics. She followed it up with post graduate studies in corporate finance. A host of research work in behavioral finance, option strategies and quantifying market sentiment followed. Anna covers Indian equity and combines Elliott, Time Fractals and Time Analytics to deliver accuracy across time frames.


The Vicious Forecast

It took me a long time to learn that instruments and forecasts don’t make money, risk management does. If you are in capital markets, forecasting is paid work, a job, a vocation. Predictions are all over the place. What’s a prediction? Euro will die or Nifty will reach 8,000 or Gold will rise are all predictions. “That new Tom Cruise film will be a hit.” Whenever we say “will”, we attach a 100% probability to the event. A lot of times I ask, “How can you be 100% sure?”

Is there a way to outperform the market and not use a prediction? Well we may not have cured ourselves from the forecasting passion (or vice) yet, but as we move towards systems, the only forecast we would like to do is that performance is cyclical and the worst performers of yesterday become the winners of tomorrow. This phenomenon of reversion is not a prediction or a forecast, but a visible reversion seen in outliers. But then what should we do about our need to forecast or follow our intuitions.

According to Daniel Kahneman, “Following our intuitions is more natural and somehow more pleasant, than acting against them it’s natural to generate overconfident judgments because confidence, as we have seen is determined by the coherence of the best story. However, we are not all rational, and some of us may need the security of distorted estimates to avoid paralysis. If you choose to delude yourself by accepting extreme predictions, however, you will do well to remain aware of your self-indulgence.”

So much we suffer from forecasting that we just can’t leave an opportunity to predict. ..

You can read the complete article in Business Standard

Mukul Pal, is a Chartered Market Technician, MBA Finance and a member of the reputed Market Technicians Association (MTA). He has more than a decade of Capital Market experience dealing with derivatives and global assets. He has worked for Bombay Stock  Exchange, multinational Banks and brokerage houses in leading research positions before starting on his own in 2005. He is the President of the MTA Central and Eastern European Chapter.


The EURO Nifty

There are many techniques used to understand market patterns. Over the weeks we have used trend lines, momentum, moving averages, Fibonacci, Candlesticks etc. This week we are using something rarely used by market technicians. This technique involves redenomination of an asset in a different currency. Europe is a trading partner for India and looking at a few Indian and global assets after rebasing them in Euro might show interesting insights.

What did we observe? 

To read the latest report download it from our Reuters Store or mail us for subscription details.

Our Jiseki Time cycles are seasonal patterns of strength or weakness in assets. They are derived from percentile rankings from 1 to 100. The higher the percentile more the chance for an asset to weaken and worst the ranking, better the chance for the respective asset to outperform. 100 is top relative performance and 1 is worst performance. The idea is that performance is cyclical. A top performer will underperform in future and vice versa. A top relative performer is also the worst value pick and the top relative underperformer is the best value pick. Jiseki is another name for Performance cycles, time triads and time fractals. The signals are illustrated as a running portfolio and as Jiseki Indices. These signals can be used by fund managers for relative allocations, traders for leverage bets and high net worth clients for selective trades.

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.

 

Dr. Ionut Nistor is the co-author of Performance Cycles paper published in Kyoto Economics Journal in March 2009. Ionut is a professor of Corporate Finance at Babes -Bolyai University and a post doctorate fellow at the Kobe University in Japan. He is fluent in Japanese, Romanian and English.
The Bric Model from a Japanese Perspective
Ionut Nistor - Econohistory


Indian Sectors - Risk Metrics

There is nothing more important for a market perspective than a combined sector outlook. If the weight of evidence for the overall sector outlook is positive, markets should go up and vice versa. Keeping this in mind we have studied 16 Indian sectors today. The combined sectoral outlook is still negative as barely 4 out of 16 sectors are strong. Based on the sector view, we see no recovery on an intermediate multi week basis on India. The broad market could see continued negative pressure well into July.

The sectors also confirm our minor NIFTY view down below 4,700. We need some significant price confirmation from current levels to look for any sustained reversal. Despite this negative outlook, our worst outliers INDIA 30 ORMI © remains totally invested. This continues to suggest that even on an intra - market basis there can be a large divergence, so much so that a section of the market continues to perform while the broad market stagnates or falls.

In this update we have added new elements to the Indian Sectors subgroup. We have added a Risk Matrix based on ranking, a risk matrix based on price, group analysis, ranking histograms and Jiseki cycles. The latest ALPHA goes about analyzing the various Indian sectors based on performance rankings and cycles. We have also carried the running intermediate signals for the respective sectors.

Our Jiseki Time cycles are seasonal patterns of strength or weakness in assets. They are derived from percentile rankings from 1 to 100. The higher the percentile more the chance for an asset to weaken and worst the ranking, better the chance for the respective asset to outperform. 100 is top relative performance and 1 is worst performance. The idea is that performance is cyclical. A top performer will underperform in future and vice versa. A top relative performer is also the worst value pick and the top relative underperformer is the best value pick. Jiseki is another name for Performance cycles, time triads and time fractals. The signals are illustrated as a running portfolio and as Jiseki Indices. These signals can be used by fund managers for relative allocations, traders for leverage bets and high net worth clients for selective trades.

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.

Enjoy the latest Alpha.

Our Jiseki Time cycles are seasonal patterns of strength or weakness in assets. They are derived from percentile rankings from 1 to 100. The higher the percentile more the chance for an asset to weaken and worst the ranking, better the chance for the respective asset to outperform. 100 is top relative performance and 1 is worst performance. The idea is that performance is cyclical. A top performer will underperform in future and vice versa. A top relative performer is also the worst value pick and the top relative underperformer is the best value pick. Jiseki is another name for Performance cycles, time triads and time fractals. The signals are illustrated as a running portfolio and as Jiseki Indices. These signals can be used by fund managers for relative allocations, traders for leverage bets and high net worth clients for selective trades.

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.

Mail us for subscription details or download the report from our Reuters store.

Mukul Pal, is a Chartered Market Technician, MBA Finance and a member of the reputed Market Technicians Association (MTA). He has more than a decade of Capital Market experience dealing with derivatives and global assets. He has worked for Bombay Stock  Exchange, multinational Banks and brokerage houses in leading research positions before starting on his own in 2005. He is the President of the MTA Central and Eastern European Chapter.


THAI SETI heading for a top?

 

To read the latest report download it from our Reuters Store or mail us for subscription details.

Our Jiseki Time cycles are seasonal patterns of strength or weakness in assets. They are derived from percentile rankings from 1 to 100. The higher the percentile more the chance for an asset to weaken and worst the ranking, better the chance for the respective asset to outperform. 100 is top relative performance and 1 is worst performance. The idea is that performance is cyclical. A top performer will underperform in future and vice versa. A top relative performer is also the worst value pick and the top relative underperformer is the best value pick. Jiseki is another name for Performance cycles, time triads and time fractals. The signals are illustrated as a running portfolio and as Jiseki Indices. These signals can be used by fund managers for relative allocations, traders for leverage bets and high net worth clients for selective trades.

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 Global: Dow 30 components, Global Indices, ETF SPDRS, Commodities

Dan-Andrei Rusu graduated in 2005 the Faculty of Economics Cluj-Napoca, “Dimitrie Cantemir” University. In the same year he joined BT Securities as a financial analyst. He is currently the Head of Research at BT Securities and a speaker with Romanian Brokers’ Association. He is an MTA (Market Technicians Association, New York) affiliate and cleared CMT level 1 exam. He is a contributing columnist for Orpheus Capitals for the ALPHA GLOBAL INDICES.


Negative Reversal Suggests NIFTY 4,700

NIFTY Stop lies @ 5,200

For more such interesting updates visit the Reuters Store or mail us for subscription details.

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.

Michesan Anna-Maria, discovered her interest of markets immediately after completing her graduate studies in Economics. She followed it up with post graduate studies in corporate finance. A host of research work in behavioral finance, option strategies and quantifying market sentiment followed. Anna covers Indian equity and combines Elliott, Time Fractals and Time Analytics to deliver accuracy across time frames.


Indian Banking - Risk Metrics

Banking is an early economic sector. How banks will perform in the coming future will decide whether markets are going to head lower or bottom here. This is because banking is a part of the early economic sector and markets don’t rise of the early economic sector (technology and banking) does not participate. The first look suggests that Indian banks are still polarized. Based on Jiseki performance rankings a half of the Indian banks (7 of them) are showing outperformance while the other half are stagnating.

The picture is different on the intermediate multi week price trend filter. We have discussed running signals on the 15 banking components in the report. The key levels for NSEBANK lie at 9,000. If respective levels break we are in for a larger drawdown on banks. It is then the current ranking neutrality should change to a clear negative bias on the sector.

In this update we have added new elements to the Indian Banks subgroup. We have added a Risk Matrix based on ranking, a risk matrix based on price, group analysis, ranking histograms, Jiseki cycles and price SIGNALS. The latest ALPHA goes about analysing the Indian Banking components based on performance rankings and cycles.

Our Jiseki Time cycles are seasonal patterns of strength or weakness in assets. They are derived from percentile rankings from 1 to 100. The higher the percentile more the chance for an asset to weaken and worst the ranking, better the chance for the respective asset to outperform. 100 is top relative performance and 1 is worst performance. The idea is that performance is cyclical. A top performer will underperform in future and vice versa. A top relative performer is also the worst value pick and the top relative underperformer is the best value pick. Jiseki is another name for Performance cycles, time triads and time fractals. The signals are illustrated as a running portfolio and as Jiseki Indices. These signals can be used by fund managers for relative allocations, traders for leverage bets and high net worth clients for selective trades.

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.

Enjoy the latest Alpha.

To read the latest report download it from our Reuters Store or mail us for subscription details.

Our Jiseki Time cycles are seasonal patterns of strength or weakness in assets. They are derived from percentile rankings from 1 to 100. The higher the percentile more the chance for an asset to weaken and worst the ranking, better the chance for the respective asset to outperform. 100 is top relative performance and 1 is worst performance. The idea is that performance is cyclical. A top performer will underperform in future and vice versa. A top relative performer is also the worst value pick and the top relative underperformer is the best value pick. Jiseki is another name for Performance cycles, time triads and time fractals. The signals are illustrated as a running portfolio and as Jiseki Indices. These signals can be used by fund managers for relative allocations, traders for leverage bets and high net worth clients for selective trades.

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.

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.