Archive for the ‘Time Triads’ category

The excitement cycles

National Aeronautics and Space Administration
Sunspots

A J Tchijevsky’s excitement cycles, reopens the debate of Time.

The success in the new age is a lot different from what we experienced 11 years back. The shy public which needed market research surveys to bring out feedback is keener to offer comments. There were 30 odd comments on the Oil forecast, 398 comments on a dirty sport tackle on the yahoo sports blog and 425 comments on the 13 year old Everest climber. Are we in excited times? Or do you think we as a society are a bit less excited than what we were a few years back? Do these times polarize us as a society? Do we become indifferent? Is there some way we can quantify excitement? Can this quantification help us forecast? Can it tell us before our odds of success or failure? Can it tell us how to plan our investments and life? Can it tell us what movies to make? What products and business to launch? Does this excitement ever fall? Simply we are asking ourselves is excitement cyclical? And if it is cyclical, is cyclicality a science? But before we come to the science part, how time cycles are measurable and how it can revolutionize our understanding of the world around us, let’s have a closer look at excitement.

In December 1926, at the annual meeting of the American Meteorological Society Professor A J Tchijevsky’s (researcher at Astronomical Observatory, Institute of Biological Physics, Archeological Institute, Moscow) paper was presented, which elaborated the index of Mass human excitability, 500 B.C. - A.D.1922. This index showed a consistent pattern of 9 waves of excitability per century over the entire span of 2422 years. The index was compiled from detailed statistical researches in the histories of 72 countries and nations of the world.

Tchijevsky found not only that this index was characterized by the 11.1 year cycles, but that the crests of these cycles tended to correlate with crests of sunspot cycles. “In the paper published in the Cycles magazine of Foundation of Cycles 1968 issue professor quotes” As soon as the sunspot activities approaches its maximum, the number of important mass historical events, taken as a whole, increases, approaching its maximum during the sunspot maximum and decreases to its minimum during the periods of the sunspot minimum. Each cycle is divided into four periods. Minimum of excitability (3 years), Growth of excitability (2 years), maximum of excitability (3 years), decline of excitability (3 years).

Over nearly a hundred years since the research was published, a few things have changed. In the extreme point of the cycle’s course, the tension of the all human activity falls to the minimum, giving way to creativity and a general decrease of military or political enthusiasm, by peace and peaceful creative work and a disintegration of masses. The last sunspot cycle started in 1998, peaked in 2000 and bottomed in 2009. The society emerges out of excitability lows.

Now this is where the observations begin. The human excitability is at a 11 year low and we are in a few years of growth and prosperity. This might sound surprising and contrary to popular belief that we are in for a double dip recession. Excitability cycles tell us that from the lows in 2010, a multiyear equity bull should emerge. But there are strange coincidences here? Excitability cycles are not only in sync with sunspot cycles but also with a decade long Clement Juglar cycles.

The scientists say, don’t show me cycles and patterns coincidences everywhere. Show me the proof. Even professor Tchijevsky’s work did not get so much popularity as few could explain why excitability index was leading the sunspot cycles by an average 12 months. At some stage of thinking cyclists wondered that there was a force that affects both human beings and sunspots simultaneously. Proving why periodicity happened takes time cycle analysis to a scientific level.

Scientific rationalism against Time can be sticky ground. Specially because there is a lot more than empirical proof out there which suggest that time is mathematical and ordered, the reason for the coincidences, sunspots, growth etc. The first proof is History itself. Though the society uses the cliché that ‘history repeats’, it never asks is repetitive history not periodicity, recurrence in time, time cyclicality? Other clichés like ‘space and time are unruled by any law’ interferes with the truth. The whole idea is that if Einstein could not understand time, who can? History was always considered knowledge not science. Karl Lamprecht, German Historian showcased the order, history’s practical purpose was always considered doubtful. How naive of us.

Time is exponential and it is the one which gives nature and society its cycles. Periodicity and recurrence happens in society and stock markets because of this order. Time is why everything natural is cyclical, even human excitement. We can connect Sun with excitement or anything else, our behavior as a society is predictable. It was too much of a truth then when Professor Tchijevsky was jailed. How much of it is a truth now? We will see.

This article was written for Alrroya

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Oil at 300 - Can or Can’t

More than focusing whether Oil at 300 can’t happen, the society should prepare for a scenario “what if it can happen?”

I made a technical and time cycle case for Oil’s last dip to 60 before it heads to 300, suggesting that the commodity cycle is 30 years long and considering commodities worldwide bottomed around 2000, a continued upside of commodities including Oil till 2015 is a possibility. My observations were also in context of a previous forecast, “The Oil rocket” published globally on 12 May 2008 both on print and the world wide web. In that feature I suggested that after Oil falls to sub 70 levels (from then extremes at 125), it should head above 300.

In May 2008, Oil was so much on market’s mind that I got mails regarding Oil hijacking retirement plans and top brokers soliciting buying call options. That was then in May 2008. Oil dropped to 39 and the second part of the forecast started to unfold from Dec 2008. Now that market woke up to the reality that pension plans got disrupted by sovereign risk rather than Oil, brokers might have another strategy on Oil. In the new context defending a May 2008 forecast is not easy. The technical reasons I gave had little penetration as the web community bombarded the forecast. So I will stick to plain speak to address the queries of the non believing majority.

The story that above 125 dollar a barrel renewables get attractive quoted 50 dollars as the inflexion point a few months back. The question here is how can you quantify that 300 can’t happen before renewables are embraced by the society? Thinking green does not just need Oil prices to go up, it needs an extreme pain when electricity bills start to matter. And that may not happen till the society pays multiple times of what it pays for Oil today. It might be only then that we the investors might really care about the global warming and have a desire to save the world. It will be only then we might think of switching of the LED of our computer screen and teach our children about energy conservation.

Thinking that an article appearing in media regarding Oil 300 is an attempt to scare the society and make money is a naive self concocted conspiracy theory. Institutions don’t make money like this and if only society was that easy to scare. There have been speculators in war times. People don’t stop speculating in war times, what scare are we speaking about here, when all that matters to us as a society is to make a bit more profit.

Another reason sighted against OIL 300 is the US energy self sufficiency. Who judges the time till US becomes energy self sufficient? It took more than a few weeks to plug the Oil leak. Estimating time is hard. And a lot can happen till efficiencies come in. Regarding death of Oil at 300, one should speak to Theodore Modis (Futurologist). Assets don’t die they just become unpopular. How can you quantify when Oil become unpopular? And why can’t it go to 300 before it starts to get unpopular? In an old time Oil 40 “scared” everybody, and then the scare shifted to “Oil 100″. Why can’t it go to “Oil 300 scare”? Oil 300 is just a small aspect in the larger picture.

Oil 300 evokes more ideas about some life style discomfort than about its impact on the society. Only a few might understand that Oil 300 could happen owing to a war like situation? But why and when should a war happen? These are more uncomfortable questions a society may not want to ask or address. If you read cycles literature there are studies on war cycles too.

Another idea against Oil 300 is that it can’t happen because of demand and supply. Demand and supply is an illusion. Gold does not just move based on demand and supply of gold. It also moves in anticipation of markets across time frames, shorter to larger. Gold also moves up in greed and fear. How do you quantify what’s driving gold, greed of fear? Behavioral finance suggests markets don’t know how to subtract and add. A majority assigns narrow intervals when it comes to targets. So how can we measure demand and supply? And how is Oil different from gold anyway?

The real debate is to think what if Oil 300 was probable. Rather than focusing on Oil 300 can’t happen. Credit crisis can’t happen. Bankruptcies can’t happen. Emerging markets correcting 60% can’t happen. Multi decade rise in interest rates can’t happen. Food prices rise can’t happen. Inflation can’t happen. Oil 300 or Gold 3000 can’t happen. Illusions and contesting forecasts are easy, studying 3000 years of interest rate history, studying inflation cycles, proving cyclicality as a mathematical science and separating the probable from the possible very tough.

Enjoy the latest Waves.OIL 

Trif Rares, the contibuting columnist for the Waves Energy. Rares got interested in forex trading and followed it up with an early interest in technical analysis. While practicing technicals he covered many other global assets and found similar patterns and formations across global assets. This is when he moved to Elliott Wave analysis. Now he specializes in energy assets. Rares graduated in finance and followed it up with post graduate studies in management. He combines Elliot Wave with classical technical analysis tools. He correctly depicted the May 2010 top in Oil and is forecasting a large multi year bottom in natural gas. You can follow up his work on Ticks Global and Orpheus Energy Research reports.

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WAVES.OIL is a perspective product published once a week. The report covers BRENT, WTM, XLE (Energy SPDR), top energy stocks, Natural Gas and related FUTURES. The product highlights Primary (Multi Month) and Intermediate (Multi Week) price trends. The report illustrates key price levels, price targets, price projections and time turn windows. The product uses Elliott waves, traditional technical analysis tools and sentiment indicators. REUTERS RICS: BRT-, WTM-, .XLE , CVX.N, XOM.N, IPNG, NG-P-CAL

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The gold exponential

Exponentiality is associated with herding not with value. Exponentiality can be defined as rising inclination in prices, larger gains in smaller time which visually looks like a rocket headed into sky or a bottom less pit. A look at Gold prices suggests this positive exponentiality.

Exponential Function

Look at platinum in (1999-2008), look at zinc (2003-2006), look at Dow (1974 – 2007).  Just to make the case clearer we have juxtaposed Dow (1974-2007) with gold (1999-2010), they look similar. Now this is not the classic intermarket chart we see every day, as gold is considered an asset of bad times, while Dow is for good times. Gold is also known as the crisis commodity that prospers in tough times. So the important questions one can ask is are we in an ongoing crisis as rising gold prices suggest? Or are we looking at an ending crisis as exponentiality and topping of gold suggests?

If we look at the element of time gold has been rising for a record 10 years without a retracement more than 38.2%. The metal has not witnessed a fall bigger than 9 months in time. While the Dow price exponential structure (1974-2007) topped in Oct 2007 and crashed 50%. Building on the case, we have more of a topping case for gold here and an easing crisis rather than what seems to be out there.

Out there we have sovereign risk, euro under attack, more than 12 month old recovery and if we look at the sentiment indicator, all time historical highs on gold will generate bullish sentiment extremes . This means more of an exhausting, up but topping case than otherwise.  To understand gold further we also plotted the precious metals against Euro and Japanese Yen. The aim was to take out the dollar bias. Gold denominated in Euro and Yen both were at weekly momentum extremes. Gold in Yen was still below 1980’s high and Gold denominated in Euro was gapping in the Reuters 3000Xtra charts. Considering EURUSD has also gapped recently on daily data, we are not surprised that price gaps on gold euro are conspicuous.

A closer look at industrial metals also suggest down structures. How can industrial metals correct while gold and silver push higher? Is this not a non confirmation? Even now things don’t add up if you are expecting a primary (more than 9 months)degree crisis. Things add up, if we assume intermediate negativity on equity markets not heading into Q4 followed by a global recovery.  We will have to wait and see how the respective picture unfolds.

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The Competitiveness Cycles

Competitiveness is a redundant idea, if we ignore cyclicality.

Competitiveness is a comparative concept of the ability and performance of a firm, sub-sector or country. It’s a ranking system based on a host of parameters. The Global competitiveness report 2009-2010 from the World Economic Forum measures competitiveness based on 12 pillars.

First is the Institution pillar, which aims at quantifying the direct role played by the state in the economy of many countries. The whole structure of competitiveness stands challenged now that the world faces sovereign risk. How can you rank a country in competitiveness if it is being bailed out? Or should we ask how competitive a country is to emerge out of a sovereign risk crisis? This is a question conventional knowledge can’t answer. Another pillar is the macroeconomic stability, which again the report says could be a double edged sword if interest rate payments and inflation rises? How competitive you are as a nation compared to others if global interest rates rise?

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The Oil Algorithm

On one side we have computer algorithms, which are blamed for Dow 1000 point move, all the panic in volatility and the 10 dollar move on oil etc. On the other side we have the hands on Elliott approach, which does not need high number crunching computers. Orpheus has been covering Oil for since early 2005.

In May 2008 (oil made a high of 133) we wrote “The Oil Rocket”. We said “Nothing can rise exponentially, even if it’s OIL. The asset’s exponential rise is more an indication of an ending trend and not vice versa. The OIL rocket can never become a satellite, no asset can. And the almost ninety degree inclination to new highs is destined to collapse. Few Wall Street brokers looked at this as a great time to solicit mass mailing lists for OIL CALL options. Well we don’t subscribe to the OIL end era yet, but if the best broker suggests buying CALLS with such confidence, we definitely don’t know something he knows or something everybody knows. At this stage what we can see is a sentiment euphoria which is hard to sustain. The five legged fractal structure both starting 1999 till 2008 and the smaller five legged sub structure starting in 2007 seems complete. We don’t see OIL above $ 125 and it’s time for PUT and not a CALL. Oil should push to sub dollar 70 levels.”

While we talked about 70 dollars Oil while it was at all time highs, we also mentioned that after the fall the move up to 300 should begin. In the feature “Oil 2012” carried on 15 Aug 2008 we said. “Oil is headed to 300 and higher till 2015.”

Oil fell to sub 40 in Dec 2008. In our 18 Dec feature on WTM vs. Brent we said “Above 40 reversal on OIL does give us a good turn around case. And we continue to look higher on OIL.” 26 Jan 2009, in “Oil ready to reverse” we said “50 is a psychological level and a push back up to 50 is an intermediate reversal. A move up on OIL could push OIL up in higher territory near 70.” Oil move up till Jun 2009. In Aug 2009 “Gasoline Futures” we said, “Oil is completing a flat and after a dip down should push up to new highs”. Successive reports on Oil on 28 Oct, 20 Oct mentioned “Prices should continue to push higher till 90”. Dips around 75 levels were pointed out as corrections. 16 Nov 2009 we said “ The sub minor correction should end soon and push higher to 85-90 levels”.

On 23 Nov 2009 update we mentioned that a termination pattern ending diagonal was in. On 14 Dec we said “another attempt at 80-90 prices before turning lower or is the top already in.” 10 Jan 2010 we talked about potential oil topping with targets back to 60. 9 Feb, “Chevron tops at 80” was released. 17 Mar 2010 we said “Oil was completing wave B up after which the C wave down should begin” 14 Apr “Oil remains topping”. 28 Apr “Intermediate reversal is here”. 02 May Oil topped at 86 in our anticipated resistance zone 85-90 and pushed lower in one week 10 dollars lower to 75.

The current ongoing move on Oil should move to anticipated targets till 60. As ending diagonal formations generally retrace completely. This should be our last and best opportunity to buy Oil for a move up till 2015. Oil 300 remains our preferred view. What this means for economics? What this means for society? What this means for inflation is again not too hard to understand. You really don’t need an algorithm for this.

For regular updates on Oil and other energy assets subscribe to Orpheus Energy Research. Enjoy the latest WAVES.OIL

Trif Rares, the contibuting columnist for the Waves Energy. Rares got interested in forex trading and followed it up with an early interest in technical analysis. While practicing technicals he covered many other global assets and found similar patterns and formations across global assets. This is when he moved to Elliott Wave analysis. Now he specializes in energy assets. Rares graduated in finance and followed it up with post graduate studies in management.  He combines Elliot Wave with classical technical analysis tools.  He correctly depicted the May 2010 top in Oil and is forecasting a large multi year bottom in natural gas. You can follow up his work on Ticks Global and Orpheus Energy Research reports.

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WAVES.OIL is a perspective product published once a week. The report covers BRENT, WTM, XLE (Energy SPDR), top energy stocks, Natural Gas and related FUTURES. The product highlights Primary (Multi Month) and Intermediate (Multi Week) price trends. The report illustrates key price levels, price targets, price projections and time turn windows. The product uses Elliott waves, traditional technical analysis tools and sentiment indicators. REUTERS RICS: BRT-, WTM-, .XLE , CVX.N, XOM.N, IPNG, NG-P-CAL

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Cycles of Entrepreneurship

I was at an entrepreneurship workshop conducted by Peter B. Zaboji. Peter was a professor at Insead and also a corporate restructuring expert. He turned around a loss making company with 10,000 people taking Tenovis to management case books. Peter’s aim was to implant the entrepreneurship fire in his audience and assist entrepreneurs with a road map towards private equity. Peter came with an elite list of speakers. Piroska Zoli (a silicon valley netpreneur) and Imre Hild (a financial innovator from Hungary) were two of the seven speakers.

Ideas and cases

Coming from an economic background I could relate more to Imre’s idea. He found an opportunity selling LARE (Life Annuity for Real Estate) to a selected Hungarian audience. LARE is now a part of OTP (Hungarian Bank). Imre saw the opportunity, a need for a financial instrument for war widows, who had no one to hand over their real estate assets and hence the need to commoditize it in their life. For a fixed annuity, the widows would sell their land to the bank. The idea pushed Imre in the list of successful financial innovators for the region.

Peter consistently emphasized on looking at the glass half full rather than the half empty highlighting the marketing genius of Dietrich Mateschitz, an Austrian entrepreneur. During his visit to Thailand in 1982 he discovered that Krating Daeng (a local drink) that helped to cure his jet lag. Red Bull was born.

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WAVES.OIL - Intermediate reversal is here

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WAVES.OIL is a perspective product published once a week. The report covers BRENT, WTM, XLE (Energy SPDR), top energy stocks, Natural Gas and related FUTURES. The product highlights Primary (Multi Month) and Intermediate (Multi Week) price trends. The report illustrates key price levels, price targets, price projections and time turn windows. The product uses Elliott waves, traditional technical analysis tools and sentiment indicators. REUTERS RICS: BRT-, WTM-, .XLE , CVX.N, XOM.N, IPNG, NG-P-CAL

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Waves.Oil - Remains Up but Topping

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WAVES.OIL is a perspective product published once a week. The report covers BRENT, WTM, XLE (Energy SPDR), top energy stocks, Natural Gas and related FUTURES. The product highlights Primary (Multi Month) and Intermediate (Multi Week) price trends. The report illustrates key price levels, price targets, price projections and time turn windows. The product uses Elliott waves, traditional technical analysis tools and sentiment indicators. REUTERS RICS: BRT-, WTM-, .XLE , CVX.N, XOM.N, IPNG, NG-P-CAL

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Revisiting Time Triads

The paper was first published on Jan 21, 2009. We had posted a brief profile earlier. This is the complete work.

ABSTRACT

Ralph N. Elliott1 wrote the wave principle in 1938. In 1975  Benoit B Mandelbrot2 coined the term fractal3 and in 1982 published his ideas in ‘The Fractal Geometry of Nature’. The  book brought fractals into the mainstream of professional and popular mathematics. In February 1999, Benoit Mandelbrot submitted an article to Scientific American called ”A Multifractal Walk down Wall Street.” In the article, he discussed how fractal geometry can be used to model the stock market curves. The enclosed research reworks the Mandelbrot Multifractal from a time cycle rather than trend perspective to prove that time fractal is more proportionate than the price fractal and is the real law of nature, which drives everything in nature. The case is validated by illustrating power law curves in time cycle periodicities. Power law4 is seen across nature and in a diverse social trends. The power law in prices is a subject of extended study, but there has been no research attempt made to prove power law in time cycle periodicities. Testing cycle periodicity needs large historical data. Long term time series are difficult to obtain and many emerging markets have seen stock market trading activity only start a decade back.  The continued prosperity after 1980’s was a reason why time fractals did not get researchers attention, unlike price fractal which was actively studied and researched. The fact that what we can see is what we can relate too more also made researchers focus more on price than time, which is less visible. Cycles are not conventionally believed to be patterns. Patterns are understood either conventionally or as Elliott wave fractals. Even few Elliott wave practitioners have admitted the limitation of the Elliott Wave structure as being more sharp on form than on time. These were few reasons why time time fractals remained  unproven. This study further connects its findings with the existing research on various economic cycles finally extending the proof to a long – short intermarket strategy on an asset  pair.

The structure of the paper will be in following steps .

1: Cycles underlie fractals and Mandelbrot’s multifractals can be redrawn from a cycle perspective. This suggests that time cycles are fractals that showcase self similarity with a factor of 3. They are also more proportionate than price fractals.

2: The above mathematical proportion X, X/3, X/9, X/27…. can also be seen in the economic group of cycles (Fig. 1)  viz. William Strauss and Neil Howe5, Brian Berry6, Clement Juglar7 and Joseph Kitchin8, which are also connected by 3.  This hence is not a chance event but owing to time fractal nature. This means that if we isolate the Kitchin (K) cycle of 40-44 months, which is widely witnessed, we could identify lower hierarchies i.e. K/3, K/9, K/27 etc.  We kept in mind the cycle characteristics before isolating the K factor.

- - -K/9-K/3-‘K’ KITCHIN-JUGLAR-BERRY-STRAUSS- - -

- -K/9-K/3-K-3K-9K- - -
3: Now if we assume that time fractals can be isolated, similar cycle periodicities can even be witnessed and isolated in intermarket ratio lines, which are independent of price.

4: We tabulate the cycle periodicity and test it for power law distributions.

5: We test the K/9 time fractal periodicities on intermarket9 ratio line on two assets though a long-short strategy.

TIME FRACTALS VS. PRICE FRACTALS

The term fractal, as Mandelbrot defined it, refers to a curve in which distinct parts are smaller scales of the whole curve. A multifractal is formed by a curve pattern being repeated at smaller and smaller time scales. Mandelbrot used a 3 wave pattern, the first and last being in the direction of the general trend, the middle against the general trend. A picture of his example from the article “A multifractal walk down wall street” is illustrated in Fig 2. Mandelbrot multifractals focused on the price and not the time. This is the reason why price fractals and time fractals seem disconnected. We as a society can relate more to what we can see and feel. Time is an underlying variable, which is tougher to relate compared to price. This is one reason why the debate regarding who saw it first, Elliott or Mandelbrot is inappropriate when we realize that time fractals are more proportionate than price fractals. If one redraws  Mandelbrot’s multifractals from a time cycle (up leg and down leg) rather than from a price trend (up leg -  down leg - up leg) perspective, the same multifractals emerge out as time fractals Fig 3. Not only the iterations break up in the same proportion X, X/3, X/9, X/27 but the time fractals also are more homogeneous that the price multifractals in Fig.2.

THE KITCHIN CYCLE ( THE K FACTOR)

Tony Plummer10 in his book ‘Forecasting financial markets’ does give reference to time cycles as a triad of patterns11. Though Plummer comes close to the idea of a power law and self similarity in cycles, he does not give a proof for the same. He mentions that “if the triad theory is correct, then the pattern should repeat themselves in a fractal like fashion across all genuine cyclical time”. Plummer also talks about the time aspect of the cycle along with the cycle pattern (Fig.4). The cycle pattern is represented by the move from 0 to C i.e.., 1–2–3 up and A–B–C down. It then consists of three lower-level (sub-) cycles, each of which itself contains the archetypal six-wave pattern. According to Plummer, each of these lower-level cycles will itself consist of three cycles. In other words, the cycles are nested within each other. In all cases, significant lows can be expected to occur one-third and two-thirds along the time elapse of the next higher cycle that contains it. Similarly, important highs occur at one-sixth, one-half and five-sixths along the time elapse of that higher-level cycle.

In 1923, Joseph Kitchin reported a short-term, three- to five-year, business cycle. There is a huge amount of evidence that the central periodicity of the short-term Kitchin cycle is somewhere between 40 and 44 months that is, somewhere between 3.33 and 3.67 years. These periodicities can be found in prices.

So if we now replace the X factor witnessed from time fractals (derived from redrawing Mandelbrot’s multifractals) with the K cycle factor, which is widely seen and accepted, then the K factor should subdivide in a similar proportion as the X factor (X. X/3, X/9, X/27 ….). And we should see it across assets, and across any time series irrespective of the Y axis. Lack of long term data and the need for a workable investment strategy was another reason why we chose the K cycle as a workable time frame to break down. Moreover economic cycles research did not go below Kitchin, the very reason this study focused sub K level. The rate of change oscillator was used to illustrate the K cycle and the other K factors.

ISOLATING THE K FACTOR

CYCLE TRANSLATION AND PATTERN DISTORTION

Cycles are about pattern and periodicity. Pattern being the stronger of the two cycle characters. The focus was on identifying self similar nesting structures (Fig. 5), three smaller cycles nesting under the larger cycle. Care was also taken to identify cycle pattern distortions (Fig. 7), to illustrate potential improper cycle isolation and identification. Just like price fractals, smaller time fractals are effected by larger time fractals which drive them. The very reason for translation (Fig. 6) when the peak of a cycle shifts owing to the larger cycle above it causing cycle pattern distortion.

Once cycles have been properly categorized in the K factor and sub K factors, the cycle periodicities can be used for forecasting purposes12.

INTERMARKET STRATEGY

Owing to the easier access to information, global markets have seen an increasing interest in instruments and assets.  This on one side has seen a rise in trading volume, but at the same time made market relationships harder to understand. Intermarket analysis coined by John Murphy13 has an increasing relevance in these times. The subject’s main hypothesis is that technical analysts need to broaden their chart focus to take these intermarket correlations into consideration. Analysis of the stock market for example without consideration of existing trends in the dollar, bond and commodity markets are simply incomplete. Murphy suggests that financial markets can be used as a leading indicators of other markets and, at times, confirming indicators of related markets.

The writer of the study wanted to test time fractals on intermarket ratio between two assets, specially because they worked independent of price and were a good proxy to demonstrate fractal nature of time. Murphy’s Intermarket analysis also illustrated the nature of performance cyclicality irrespective of the intermarket ratio between two asset prices.  Murphy also talked about cyclicality between large asset classes like commodities and equities. This was nothing but larger time fractal K factors under action.

However, intermarket analysis (Fig . 8 ) owing to its focus on trend over time just like the Elliott Wave theory fails to quantify the time element in the investment approach. The perspective signals mentioned in Murphy’s intermarket analysis rely on conventional tools like breaking of a trendline and indicative patterns on the intermarket ratios.

The Fig. 8 depicts the price of asset A, asset B and the ratio between them. The K factor is identified from the respective ratio line. This addition of the time fractal to the intermarket ratio line gives the intermarket  strategy. (Fig .9)

POWER LAW

A power law is a mathematical formula which states that as a phenomenon increases in scale, it also decreases in frequency. Time cycles also reduce in number as the time scale increase (K/9 to K/3 to K). Power laws appear widely in physics, biology, earth and planetary sciences, economics and finance, computer science, demography and the social sciences. For instance, the distributions of the sizes of cities, earthquakes, solar flares, moon craters, wars and people’s personal fortunes, stock indices and prices all appear to follow power laws.

A power-law distribution is also sometimes called a scale-free distribution. Because a power law is the only distribution that is the same irrespective of the scale. This is also called as scale invariance. A closely related concept to scale invariance is self-similarity. In mathematics, a self-similar object is exactly or approximately similar to a part of itself (i.e. K= 3*K/3).  The whole has the same shape as one or more of the parts. Self-similarity also means that any magnification would lead to a smaller piece of the object that is similar to the whole. Many objects in the real world, such as coastlines, are statistically self-similar with all parts of them showing the same statistical properties at many scales. Self-similarity is a typical property of fractals. Self similarity also appears in time cycles, as a large cycle encompasses smaller cycles, which in turn have smaller cycles nesting under them.

The power law can be described as…P(x)= cx-α

Here, α is the scaling exponent. The distribution is an exponential function, which takes a straight line form when we move on a logarithmic scale.  lnP(x)= lnc-αlnx

Formally, this sharing of dynamics is referred to as universality, and systems with precisely the same critical exponents are said to belong to the same universality class. Working on the assumptions that time cycles belonged to the same universality class and were self similar fractals, we pulled out the k factor intermarket ratio  cycle periodicities to test for power law distribution.

THE K TREE

Many emerging market index pairs and top Dow Jones components were paired to isolate the K factor for cycle periodicities. The self similarity appeared in most cases. About 3 Kitchin cycles, nearing a decade of daily data was tested for the study. The author has illustrated the detailed workings of the following three intermarket  ratio lines.

BRENT vs. WTM (Brent vs. Midland)

GE vs. CAT (General Electric vs. Caterpillar)

XOM vs. CVX (Exxon vs. Chevron)

The above pairs were purposely chosen owing to their high and poor correlation. BRT-WTM correlation was 0.99, XOM-CVX correlation was 0.97 and GE – CAT correlation was at 0.12 for the period under study.  All of the pair cycle periodicities depicted the underlying K factor hierarchy.

INTERMARKET STRATEGY

The strategy has three parts. First the author has carried a visual of three iterations of the K factor on the intermarket ratio line (Fig  12, Fig. 14, Fig. 16).

Second part includes the distribution and tabulation of the time cycle periodicity of the respective pair.

The tables (Table 1, Table 3, Table 5) carries the periodicities in days in column A. The calculations for B and C are enclosed.

B = Periodicity in days*STDEV + Mean

C= NORMDIST (B,STDEV, MEAN, FALSE)

Where STDEV is standard deviation and NORMDIST is the normal distribution functions.

Third part (Table 2, Table 4, Table 6) is the working of the long short strategy, where the author goes long on numerator A of the intermarket ratio under study while simultaneously selling the denominator B from the pair. The entry number of days is the same as the time cycle periodicities carried on the second part of each working. The exit number of days are taken as half of the K/9 cycle. The author has tested the strategies for an average 3 Kitchin cycles. Underlying spot prices on the two assets making the pair are used. There is also a stop factor of 10% put to see how many times the pairs lose more than 10%. The strategy assumes a leverage factor of 1. The last column is the net annualized returns.

A few important aspects linked with time fractals based strategies is that the fractal illustrates the performance cyclicality clearly. For example the GE-CAT conventionally showcased a secular underperformance of GE against CAT. This was for all the time period under study. However, despite such an underperformance of GE against CAT, the K factor allowed us to trade long GE vs. Short CAT strategy successfully over the K/9 time frame (102-131 days) with exits on an average of 54 days. Even the other two pairs viz. BRT-WTM, and XOM-CVX are highly correlated pairs that even from a conventional long short strategy are not easy to trade. The time fractals based intermarket strategy delivers consistent returns on both the pairs. This proves that even a conventional underperformer or highly correlated assets can be traded against its sector leader (performer) or sector peers respectively, if the time fractal is isolated well. This reinforces the idea of time fractal being better than the price fractal.

All the three pair cycle periodicities show power law distributions.

The average entry number of days for the three pairs were 111, 102, 131 for GE-CAT, BRT-WTM and XOM-CVX respectively. The exit number of days for the three pairs were 54, 50 and 66 in the same order. The stop loss of 10% was hit twice in 80 readings, once on both GE-CAT and XOM-CVX pair. The average annualized non leveraged return was at 54%.

CONCLUSION

The proof  of the superiority of the time fractal over the price fractal  clearly emerges when we redraw Mandelbrot’s multifractals and put to test intermarket ratios cycle periodicities for power law and as an investment strategy . The K factor indicator assists in this process. The author relies on both high and low correlated pairs to showcase the performance cyclicality over the K/9 factor time frame.  All strategies under study return positive gains. The intermarket ratio strategy introduced first time ever in this research redefines long-short technique as a time fractal strategy. The strategy can be used by fund mangers across different assets and time frames, aggressively or passively by altering the K factor. The study has assumed a leverage of 1, but real market leverage can change the profile of the strategy. Overall, time fractals is a subject which traverses beyond capital market forecasting and can be utilized in many areas of scientific research.

FOOTNOTES

1.Ralph N. Elliott, Father of the Elliott Wave Principle and author of the Nature’s Law.
2.Benoit B. Mandelbrot, is a French mathematician, best known as the father of fractal geometry. The Mandelbrot set, named after him is a set of points in the complex plane, the boundary of which forms a fractal.
3.A fractal is generally “a rough or fragmented geometric shape that can be split into parts, each of which is (at least approximately) a reduced-size copy of the whole, a property called self-similarity.”
4.A power law is a special kind of mathematical relationship between two quantities. If one quantity is the frequency of an event, the relationship is a power-law distribution, and the frequencies decrease very slowly as the size of the event increases.
5.William Strauss and Neil Howe presented a strong case for an intergenerational, 85- to 99-year cycle.
6.Brian Berry pointed to the presence of a generation-length, 25- to 35-year, cycle.
7.Clement Juglar reported a medium term, seven- to 11-year, cycle.
8.Joseph Kitchen reported a short-term, three- to five-year, business cycle.
9.Intermarket ratio is a line built from price series of two different assets.
10.Tony Plummer is a time cyclist and author of the book ‘Forecasting Financial markets’.
11.Triad of Patterns are the classic six wave pattern structure found in cycles with 1-2-3-a-b-c legs.
12.Forecasting purposes can include price, macro and micro economic, social trend and scientific forecasts.
13.John Murphy is a market technician considered as the father of modern technical analysis.

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Dow Time Oscillator (updated)

Do you see the non confirmation between time oscillator and price? The non confirmation between the oscillator and price clearly suggests negativity going ahead for DOW. This is a case for an impending reversal. The oscillator structure also looks weak and ready to resolve lower.

This is what we said on 2 Jan 2010 for DOW Jones Industrial Average.

“Any January positivity should be an illusion. The first quarter of 2010 should be negative for DOW.”

Prices are up 0.96% from Jan high (10,729) to March lows (10,832). On one side we were wrong as prices did not reverse, but less than 1% upside is enough choppy action to prove that the best of TIME strength is over for DOW in the ongoing CYCLE.

March 2009 we started illustrating time oscillators with nesting momentum triads. We have been refining it since then. The current form of time oscillator combines three time frames. The oscillator moves like a cycle and should atleast push lower back till zero levels before anything. Time oscillator takes into account three time periods viz. minor (14 days), Intermediate (70 days) and primary (210 days). Here we have illustrated the time oscillator for NIFTY (India 50). The oscillator has clearly topped and should break down below key neckline supports soon. This keeps us looking at a topping price absolute price performance.

Published 2 Jan, 2010

Time Oscillator is a range bound indicator suggesting increase and decrease in time periods. Starting 30 Nov 1988, DOW witnessed a confirming increase in time periods till 30 Sep 1998. From 1998 time oscillator fell till 31 July 2001 along with the prices. Since 30 Apr 2008 the oscillator is falling till date. It is too early to assume that the rise in DOW is a new bull market and 2010 will be a positive year. Till the oscillator sees a further fall till 60-100 levels, the current rise on DOW remains a bear market rally that should correct into 2010.

Primary (multi month) perspective

Intermediate (multi week) perspective

Considering the primary (multi month) time is still pointing lower (above), the intermediate time oscillator at 250 days suggests an intermediate top might be near or already in. Only once since 2002 has the time oscillator breached 300 days.

Minor (multi day) perspective

On the minor time oscillator, the 2009 cycle seems over and prices should get ready to trend. Seeing the minor trend in light of intermediate and primary perspective, any January positivity should be an illusion. The first quarter of 2010 should be negative for DOW.

CYCLES covers global currency pair, global equity, emerging equity, and inter asset cycles. The product studies time cycle, asset outperformance and underperformance signals. The aim is to look at markets as a group and in isolation. This is a monthly perspective product that readers should use in conjunction with our other features like WAVES.GLOBAL , WAVES.INDIA, WAVES.FOREX, WAVES.METALS, WAVES.ENERGY, and other global features. Our economic and psychological world is well connected and cyclical. INTERMARKET CYCLES is a subject coined by us at Orpheus. The subject studies the asset linkages and the fixed periodicity between them. We look at the subject from three aspects. First from the sectoral aspect. As we redefine Equity sector rotation and reclassify global sectors into three broader sectors viz. Early Economic, Mid Economic and Late economic. We juxtapose these three broad sectors on the economic and business cycles. Second we look at subject from the 25-30 year Asset cycles. For example the 30 year Gold cycle and commodity cycle, which is inverse of the 30 year equity cycle or social prosperity cycle. Third we look at inter asset cycles between Gold and Oil, VIX and S&P, Technology and Blue Chips, Local Currency and numerous other asset pairs to look for asset outperformance and underperformance signals.

REUTERS RICS (METALS) - XAU=, XAG= (FOREX) EURRON=, RON=, JPY=, INR=, HUF=, HRK=, GBP=, EURCHF=, CHFRON=, CAD=, =USD, EUR= (GLOBAL) .BVSP, .IRTS, .FCHI, .GDAXI, .GSPC, .DJI, .N225, .SSEC, C.N, JPM.N, BAC.N, AXP.N, AIG.N, DIS.N, HD.N, GM.N, VZ.N, T.N, INTC.OQ, MSFT.OQ, HPQ.N, IBM.N, UTX.N, CAT.N, GE.N, MMM.N, BA.N, KO.N, MCD.N, - WMT.N, DD.N, PFE.N, MRK.N, CVX.N, XOM.N, PG.N, JNJ.N, AA.N (ENERGY) BRT-, WTM- , .XLE , CVX.N, XOM.N , IPNG , NG-P-CAL. (AGRO) COFSAN-4-NYC, SUG-DLY-ISA, .DJAIGCT, CCCI-NYC, CORN.L, C-US2Y-GULF,.SPGSCN, W-RJK-MLQ, .DJAIGWHTR (GREEN) - NEX, G3E.CO, EEN.PA, TEO.PA,.WOWAXPD,.GWE, HSNT.L,GAM, .SPGTCLEN, VWS.CO, FSLR.O, VIE.PA, ITT, .BIOX,ADM, BG, CSAN3.SA, .SUNIDX, QCEG.DE, 3402.T, 3401.T, CLIE.L

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