Archive for the ‘Time Triads’ category

The Intermarket Jiseki (Cycles)

Intermarket analysis has become an essential part of a technician’s toolbox. Using R we have created this illustration where all the quarterly Jiseki Cycles for Indian Energy have been plotted.

The illustration tells us which are the worst quarterly components, which are the best and it also tells us there tendencies respective to each other. For example Petronet and SEAMEC is the only Jiseki cycle which are relatively increasing compared to the rest of the energy components.

These are quarterly Jiseki performances which can indicate intermediate trends in sectors or sector components. This is why we call it ‘The Intermarket Jiseki’.


Avinash Barnwal is Master of Science in Statistics and Informatics from IIT Kharagpur. He has worked on human response time at Department of Psychology, University of Amsterdam.  Avinash is a Quantitative Analyst at Orpheus developing money management solutions and building statistical models to address temporal challenges.


Time Analytics - Is Correlation and Jiseki connected?

 

Jiseki is a performance ranking idea for an asset in a group for different holding periods. Conventional tools don’t look at sectors as a proxy of a group but not components perse. Our idea of extreme reversion is designed to understand performance cyclicality.

This week we look at the Indian Energy sector correlation from Oct 2009 to 2011 and juxtapose it with change in quarterly performance rankings during that period. The correlation of the energy sector components was made with Reliance.

What we could observe? The higher the correlation of the stocks with the Reliance the worst the stocks did in performance and the lower the correlation of the stocks with Reliance the better they did in performance.

Petronet for example moved up 50% in Jiseki performance rankings during the period along with Castrol. While the high correlation and positive correlation stocks with reliance like Seamec, Suzlon saw not only a drop in rankings by 50% but also absolute price loss.

The connection of correlation with Jiseki change in rankings might seem strange. But it’s not because if Reliance is at the top of the group, it will underperform and because it’s a sector leader, anything correlated positively correlated with it will also underperform.

This is simple logic, which the data expresses visually. Does the data tell us something else? The histogram also tells us that the only stock which should have fallen and did not fall as much was Reliance. This is what we may call a sector leader’s premium, which keeps us away from Reliance as a buy opportunity confirming what we wrote recently in the article, “should I buy Reliance?”


Avinash Barnwal 
is a final year master student of Statistics and Informatics at IIT Kharagpur. He has worked on human response time at Department of Psychology, University of Amsterdam.  He has worked on marketing analytics for the Customer Intelligence Unit, HDFC Bank . Avinash is passionate about developing statistical models and believes that statistics could address temporal challenges.


The Time Topology

 

Human studyof scale invariant natural patterns invariably stops at Pareto exponentiality. US scholar Albert Bartlett pointed out the difficulty to grasp ramifications of exponential growth, stating: “The greatest shortcoming of the human race is our inability to understand the exponential function”.

This paper summarizes the philosophy of Time Topology and builds a historical and statistical case to explain that just like patterns in natural systems even Time is patterned. This on one side looks plausible but on the other leads us to a critical Cartesian debate because Time is the common (x-axis) element against all the other natural (Y- axis) systems. Patterns can’t exist on both the Cartesian levels. This would mean that either Time (the only patterned element) gives (order and disorder) pattern to all natural systems or there is some other mysterious force or just patterns and no mystery (Mandelbrot).

Download the paper from SSRN


The Happy Jiseki (Cycle)

 

We took and still take pride in writing about ideas that could not be found on Google. Getting indexed was a great feeling. But then SEO happened and the fun sport became big buck soccer. It was not about what content you created, it was more about how well tagged and searched and researched you were.  But then Time is a strange being, it keeps turning. This is why cycles happen, growth and decay happens and level playing fields get recreated.

Google search is powerful tool. Maybe the most powerful internet tools of our times. But history suggests that there are few sustaining ideas which last beyond a century. Can Google evolve beyond a century? What if we have Inflation, war, social unrest, food crisis, power and food shortage? How key would internet be 100 years from now? Is there something beyond information? If everything is exponential including the accelerating universe (Nobel Prize 2011), how can information generation and access not be exponential? And if everything exponential is also prone to decay, why can’t the information society give way to something else, something newer? These are hard questions to ponder. Well change is hard to predict and we have little clue what will happen.

We decided to test our algorithms on Google search data. Emotions are important for economics. We took a group of emotions and ran a ranking test on them to see a trend, a Jiseki cycle, to not only see which emotion was a top ranker and which was the worst ranker but also to anticipate whether the society is getting happier or not….

This article was written for Business Standard

To read this article and for regular updates on behavioral finance, performance cycles and market forecasts subscribe to Orpheus Research Time Triads Update.

Time Triads, Time Fractals, Time Arbitrage, Performance Cycles are terms coined by Orpheus Research. Time Triads is our weekly market letter. The report covers various aspects on TIME patterns, TIME forecast, alternative research, emerging markets, behavioral finance, market fractals, econohistory, econostatistics, time cyclicality, investment psychology, socioeconomics, pop cultural trends, macro economics, interest rates, derivatives, money management, Intermarket trends etc.

 


The New Normal

 

The “New Normal” was an innocuous quote by Mohamed El-Erian, Pimco  suggesting an uncertain future, sluggish growth, international discord, low return on capital etc. Such is the reach of media that ‘The New Normal’ has become a buzz word. It signifies the times we live in. It talks about new change, a new time. But is “the New Normal’ old wine in new bottle addressing “This time it’s different or this time it’s definitely bad”.
Social Networks are the new normal. I juggle between my offline and online networks. We are sharing so much information that we can’t really differentiate real information from noise. On one hand it might cause disorientation and on the other hand identifying patterns in presumed random chaos might be the only way out. Is it really that uncertain? Or do we lack big picture tools?

During the recent trip to a MTA (Market Technician’s association) chapter meeting in Budapest, a colleague mentioned how DAX was hard to trade and behaved like a Struţocămila, a special Romanian term describing an animal with features of both Ostrich and camel. His point was the DAX was…

This article was written for Business Standard

To read this article and for regular updates on behavioral finance, performance cycles and market forecasts subscribe to Orpheus Research Time Triads Update.

Time Triads, Time Fractals, Time Arbitrage, Performance Cycles are terms coined by Orpheus Research. Time Triads is our weekly market letter. The report covers various aspects on TIME patterns, TIME forecast, alternative research, emerging markets, behavioral finance, market fractals, econohistory, econostatistics, time cyclicality, investment psychology, socioeconomics, pop cultural trends, macro economics, interest rates, derivatives, money management, Intermarket trends etc.

 


Revisiting Microfinance

We are working with a group of experts to improve our performance cycles for the microfinance space. The aim is to understand credit risk. Microfinance lenders were criticised for profiteering from unfairly high rates of interest. This made it imperative to review practices, understand the universe of microfinance variables and see if an objective system could be arrived at to assist the sector players.

Though microfinance has a moralistic role of creating social impact, it’s hard to draw the line between profit and a social cause. What happened in Andhra Pradesh with SKS has created a flutter among players. The ‘for profit’ players attempt to walk the tight ‘social cause’ rope. Also, we have an economic cycle that connects consumption patterns, basic demand and economic growth to microfinance. And, a downward economic cycle hurts all finance players, whether micro- or conventional finance.

This is why we took up the challenge to build an industry-wide model for the sector. Microfinance is a bit different compared to conventional finance. On one side are social impact variables like poverty alleviation indicators and, on the other, are financial variables and microfinance institutions that are a part of the listed exchange market. The approach that identifies outliers in a group of stocks could also do the same for social variables. The idea of seasonality is not only about a sector’s good or bad behaviour over a period of time, but also about its quarterly performance in an overall bad year. Our performance cycle approach could also look at social variables like poverty, infant mortality and trends in the health services….

This article was written for Business Standard


INR Q4 Seasonality - II

This is what we mentioned on 25 Dec 2010

INR weakness seasonality may persist. One simple reason is the unbroken 0.618 Fibonacci support at 44. Price confirmation is king. Till INR breaks 44 low we continue to look atleast at a multi month weakness on INR against USD, even if not primary. Above this we don’t see the move down from 2009 top as a clear five. Markets have enough capability to burn time in stagnation or weakness. The ongoing complex corrective could just persist till H1 2011. What does this tell us about equity? This tells us that Nifty VIX broad basing formation should not be ignored as equity could surprise early 2011. And since we are in larger complex corrective in Indian equity also, performance cycles (relative performance) should be used to reduce out of overstretched sectors and accumulate into best potential outperformers.

The above view had a forecast for the Rupee and the stock markets. Now Rupee is up and markets are down. The other key observation was that seasonality could have a polarity. Some Q4 inflexions strengthen the INR on a primary degree and the subsequent Q4 inflexion weakens the INR. This is no magic, seasonalities are about phase changes and markets just have two phases, a trend and countertrend phase. We can call it positive and negative etc.

Today we have taken the time ratio for these inflexion points. Since time has statistical properties, the time ratio proportionality can be seen in INR Q4 inflexions too. Between two subsequent periods, one can observe equality, 0.6 or 1.6 ratios. Now if we should project these ratios in time INR could weaken against the USD till Dec 2011 or till Dec 2013 to attain this proportion. This is clearly beyond our Sep time forecasts for the market and an extended negativity.

This article was written for ATMA.


The Ising Model

The Ising model is a mathematical model of ferromagnetism in statistical mechanics. The model consists of discrete variables called spins that can be in one of two states. The spins are arranged in a lattice or graph, and each spin interacts at most with its nearest neighbors. The goal is to find phase changes in the Ising model, as a simplified model of phase changes in real substances.

In 2000 while working on the Murphy’s Price - Volume - Open Interest I started scribbling arrows in a 3 by 3 grid writing about how Price - Volume - Open Interest (PVO) should define trends. The PVO model looked like an Ising model.

 

 

Today I will try to explain the 10 year old analogy. In an antiferromagnet there is a tendency for the intrinsic magnetic moments of neighboring valence electrons to point in opposite directions. When all atoms are arranged in a substance so that each neighbor is ‘anti-aligned’, the substance is antiferromagnetic. Antiferromagnets have a zero net magnetic moment, meaning no field is produced by them. Antiferromagnetism can be considered like a neutral market as anti aligned spins (Fig. 1) are similar to non confirmations. Many non confirmations also mean undecided market.

From a PVO perspective, it could be a stock with a positive spin and another with a negative spin causing the aggregate market to be neutral.With the passage of time the neutral situation leads to a topping or bottoming situation, in other words a market bias, spin, direction, Ferromagenetism. A topping, where a market reverses direction sees the price pointing lower, volume leading higher and drop in open interest position (as longs square off – Fig 3). On the other hand a bottoming market ready for reversal is when the prices point up, volumes are still lackluster and negative, but open interest starts to build up new long positions (accumulation – Fig 2). This confirmation among stocks finally gives a negative and positive bias to the market. This is how stock markets could have a physics parallel in the Ising model spins. The Ising model could also validate the weight of evidence approach in technical analysis.

This article was written for ATMA.

 


Patterns, predictions and possibilities

I am reading Critical Mass, Philip Ball. It talks about patterns in nature and in market and how they are scientifically linked. The author does a tremendous job showcasing order in a presupposed random world. In one of the chapters the author illustrates how financial crashes and statistical mechanics overlap.

The log periodic behaviors in markets have a distinctive signature. The system is prone to oscillatory periodic fluctuations. In an economic context this would be analogous to periodic business cycles. But log-periodic variations are not like the regular oscillations of a light way or a turning fork. Instead the peaks and troughs of the waves get closer together. At the critical point itself they pile up on top of one another.

French mathematical physicist Didier Sornette, based at the University of California at Los Angeles has research extensively on the subject and is convinced that market crashes are log periodic.

Despite much proof Sornette admits with some chagrin that trying to make a genuine prediction of a crash is a thankless task. There are, he says, at least three possible outcomes.

1: No one believes the prediction, but the market crashes anyway. Then critics will say it is a just a lone, lucky correlation with no statistical significance. Besides, what good is a warning if it fails to avert a crash.

2: Many investors believe the prediction, get triggered into panic buying a selling, and thereby cause a crash - that is, the prediction becomes self fulfilling.

3: Many investors believe the prediction and take careful compensatory action so that a crash is averted - that is, the prediction becomes self defeating.

That’s the problem with the dream of predictability in economics: future market behavior depends on what traders and investors believe that behavior will be, so the act of predicting the future (if it is taken at all seriously) is likely to change it.”

I agree with Sornette, when it comes to the lucky correlation, most technicians must have experienced that at some point of time in their life. The second point Sornette gives a causal explanation of how internal market dynamics causes non equilibrium (or crash) sate. The third aspect is Sornette’s way of escaping a bad forecast, as much before Sornette and log periodic behavior, Benner laid down his predictive tool. The clock predicted most lows and highs on popular averages 100 years after its construction. Now as we head into Benner 2011 lows, the forecast would become hindcast months from now. It would be interesting to see Benner going wrong here in 2011. In any case, right or wrong, we would not elevate Benner to a statistician or thinker who got it wrong. He would remain a part of an archaic history of counter-intuitive cycles.

This article was written for ATMA.


Elliott, Timing and China

As a chart of the week, we have taken SSEC China (The Shanghai Index). China has been always been of key interest to the world. India looks at it to understand relative growth in China compared to India. On an Elliott perspective, SSEC seems to be making a cycle structure expanding diagonal with another final ongoing 5 cycle wave. The 1 and 2 primary circle of the 5 cycle wave seems complete and we are headed into the 3 primary cycle wave up.

This means that despite all anticipated negativity Chinese SSEC should head higher from 2011 lows. Now we have added multi month and multiyear Jiseki cycles along with the Elliott count. The multi month Jiseki is already turning up from worst rankings near 20 percentile and the very fact that cycles lows are non confirmed by higher lows in price suggests that our 2011 low anticipation could be correct. On the larger multiyear Jiseki structure the cycles are down for the last 4 years. SSEC has been falling and underperforming global assets since 2007 now. The rankings and cycles are still high and we have no change of trend confirmation on multiyear Jiseki cycles. The confirmation will only come when all the 3 cycles (red, blue and grey) turn up.

One should also keep in mind, that final 5 wave Elliott structure could also see a non confirmation from long term cycles. In conclusion the Jiseki timing model suggests potential multi month primary upside before anything. We anticipate support coming in soon enough for SSEC.

This article was written for ATMA.

Time Triads, Time Fractals, Time Arbitrage, Performance Cycles are terms coined by Orpheus Research. Time Triads is our weekly market letter. The report covers various aspects on TIME patterns, TIME forecast, alternative research, emerging markets, behavioral finance, market fractals, econohistory, econostatistics, time cyclicality, investment psychology, socioeconomics, pop cultural trends, macro economics, interest rates, derivatives, money management, Intermarket trends etc.