Archive for the ‘Performance Cyclicality’ category

THE TIME ARBITRAGE

STAT.ARB

I remember meeting Ajay Shah, Professor and Columnist in 2000, during my early days as a derivatives analyst in Mumbai. He talked about how speculators-arbitrageurs and hedgers together create the magic in derivatives market. It was indeed magical as from its humble beginnings when nobody believed in the potential of markets and badla was still considered the real thing, we came a long way. Little did then we realize that in less than 10 years we would be illustrating the gaps in the hedge ratio and our understanding of hedging and arbitrage activity. Hedge was the basic premise for establishing the derivatives markets in India. The L C Gupta committee report delved on this in detail illustrating it in the evolution and economic purpose of derivatives.

Readers who would have read our half yearly outlook on India (28 July) would have seen how illusionary the hedging process is. If between 24 sector pair trades one could create 32% annualized returns with the maximum ruling at 173% (Sensex – Real) and only six out of 24 pairs delivering less than 5% annualized returns, there was something about hedging or pair returns we do not know. One might also say, “what about BETA?” (the sensitivity quotient between assets). We are comparing sector indices here and if you think beta argument can really disprove these results, it is a tough task. We can demonstrate not only returns between highly correlated and similar beta assets but also between an asset and its own stock future (Long Nifty – Short Nifty Futures). The best part is that it’s all very simple.

So what happened? Did the hedge ratio fail? How could a conventional risk management idea make money or for that matter lose it? If you were long Sensex and short BSE Real, you would have lost 173% annualized. The idea is not just about lack of trading instruments. India doesn’t have well traded sector futures and options, as market participants focus more on stock futures than understanding or trading sectoral exposures.

Are we correct in saying that Hedge funds did everything but hedging that’s why they went under? Did we ever think that there could be gaps in the hedging theory and that’s why what was not supposed to sink, drowned? The idea that in the long term it works could also be an illusion, as there are costs involved and hedging as an activity is more about minimizing losses rather than eliminating them. The very reason there are not very many companies offering hedging solution. Did Hedging outfits suffered because the cost of hedging was exorbitant?

The arbitrage philosophy

Understanding hedging has a lot to do with how we comprehend the hedge process. Arbitrage pricing theory (APT) is a general theory of asset pricing that has become influential in the pricing of stocks. APT holds that the expected return of a financial asset can be modeled using the sensitivity factor aka beta coefficient. The derived rate of return will then be used to price the asset. If the price diverges, arbitrage should bring it back into line. Arbitrage is the practice of taking advantage of a state of imbalance between two or more markets and thereby making a risk-free profit. The theory was initiated by the economist Stephen Ross in 1976.

This back into line philosophy is at the heart of the hedge failure. This could also be the reason why we as a society are running farther from understanding risk than getting closer to comprehending it.

History of statistical arbitrage

How far we are from understanding cyclicality, time and fractals and how poorly we implement them in our strategies can also be understood by studying the history of statistical arbitrage. Statistical arbitrage aka stat. arb was started in 1985, a decade after the APT.  Reversion to mean was born. In his recent book Statistic Arbitrage, Andrew Pole comprehensively delves into stat arb. Pair trading was a simple idea of trading similar historical prices. The strategy was based on reversion, which occurs everywhere and anywhere. This was a sign of fractalled nature, but the author barely mentions the term (three times) in his 257 page work.

Despite the lack of fractal details, the normal distribution in prices needed for reversion in prices is dismissed as an erroneous claim. Fractal watchers do the same as heavy tails and power law are the mathematical explanation for fractals.  The author spends a few chapters of the book explaining why stat. arb. was beset with problems starting from 2000 and how the strategy exhibited a diminished economic potential. He cites ideas like more advanced algorithms, volatility, vagueness of practitioners, and lack of knowledge on part of the investors.

The author asks a lot of relevant questions like how does one identify when a price is away from the mean and how much? How long will the return to mean take? Are heavy tails the reason for frequent miscalculation and underestimation of risk? Why simple probability theorems cannot guarantee reversion which is challenged by heavy tails? Why we must always learn from the predictable occurrences, however odd they may look at first sight? Why we should be buying in weakness and sell in strength?  Why patterns of stock prices are occurring at least two higher frequencies above in time scales? Why LTCM failure could have been linked to higher time frequency patterns? Why Gauss is not the God of reversion?

But the book fails to admit time cyclicality and builds its case mostly through reversion. Somewhere simplistic thinking takes over simple thinking. Like how to judge whether a spread tomorrow will be greater or smaller. If it’s greater than the mean today it will be smaller tomorrow. Pole also looks at reversion to mean as more magical than the fractalled nature of markets. Though he mentions that mean reversion involves temporal dynamics and time frequency analysis, temporal aspects are the source of profits, trades at a point of time are the means with which the opportunity is exploited, but there is not even one mention of time cyclicality in the book. It’s not the first time that we have missed the idea.

Missing the idea

The idea dismissed by Pole that simple probability theorems cannot guarantee reversion are strangely the same ideas explored by other reversionists. Larry Connors of Trading markets searches for statistical probabilities that help traders profit when stocks revert to the mean. “The further prices stretch away from the mean on a short term basis, the sharper they snapback”, Connors was quoted in Bloomberg Markets. Connors and Ceaser Alvarez, are ex Microsoft engineers who worked on the development team of excel program. They seek to identify tradable price patterns based on statistical probabilities. The duo works with a large database of 8.5 million trades.

Robert Shiller’s MacroMarkets’ is also not free of mean reversion. In his 1993 book, MacroMarkets: Creating Institutions for managing society’s Largest Economic Risks, the author talks about unmanaged risk and the need for a risk management solution. To hedge Oil risk MacroMarkets introduced a new way to include Oil in a portfolio. Dubbed Macroshare $ 100 Oil UP and Macroshare $ 100 Oil DOWN exchange traded securities issued by paired trusts. According to a Bloomberg market report, “the trusts have an income distribution agreement under which assets flow from one to another in proportion to the level of the benchmark”.

As OIL moves above or below 100, the funds flow from one bucket to the other. This is supposed to be a hedging mechanism to help people. Whether we call it an innovative solution, this is still a pair attempt at managing risk. Pair trading based on reversions are far from perfect and prone to failure. The idea about comprehending markets is tougher than the idea of comprehending market cyclicality. This is why teaching market participant’s cyclicality by creating more pair offers is just adding to the already oversaturated market. The market is already trying to take a detoxifying pause from structured products.

The behavioral finance idea of losers vs. winner’s index has more merit because it illustrates cyclicality. The only unfortunate part is that behaviorologists don’t admit that the idea of selling winners and buying losers is the central idea of performance cycles.

Conclusion

A hedge is not only imperfect but inefficient and costly. Statistical arbitrage is a euphemism for Time arbitrage, performance cycles and till the time we don’t focus attention on TIME our attempt to understand risk will fail. We will have someone or something to blame then. According to Paul Samuelson, “Financial engineering is like science that can help mankind or create atomic bombs”. We will worship Beta and then pronounce it dead, rechristen it later as Jenson Beta, but there is one think we will intuitively avoid, cycles of time.

I remember meeting Ajay Shah in 2000, during my early days as a derivatives analyst in Mumbai. He talked about how speculators-arbitrageurs and hedgers together create the magic in derivatives market. It was indeed magical as from its humble beginnings when nobody believed in the potential of markets and badla was still considered the real thing, we came a long way. Little did then we realize that in less than 10 years we would be illustrating the gaps in the hedge ratio and our understanding of hedging and arbitrage activity. Hedge was the basic premise for establishing the derivatives markets in India. The L C Gupta committee report delved on this in detail illustrating it in the evolution and economic purpose of derivatives.

Readers who would have read our half yearly outlook on India (28 July) would have seen how illusionary the hedging process is. If between 24 sector pair trades one could create 32% annualized returns with the maximum ruling at 173% (Sensex – Real) and only six out of 24 pairs delivering less than 5% annualized returns, there was something about hedging or pair returns we do not know. One might also say, “what about BETA?” (the sensitivity quotient between assets). We are comparing sector indices here and if you think beta argument can really disprove these results, it is a tough task. We can demonstrate not only returns between highly correlated and similar beta assets but also between an asset and its own stock future (Long Nifty – Short Nifty Futures). The best part is that it’s all very simple.

So what happened? Did the hedge ratio fail? How could a conventional risk management idea make money or for that matter lose it? If you were long Sensex and short BSE Real, you would have lost 173% annualized. The idea is not just about lack of trading instruments. India doesn’t have well traded sector futures and options, as market participants focus more on stock futures than understanding or trading sectoral exposures.

Are we correct in saying that Hedge funds did everything but hedging that’s why they went under? Did we ever think that there could be gaps in the hedging theory and that’s why what was not supposed to sink, drowned? The idea that in the long term it works could also be an illusion, as there are costs involved and hedging as an activity is more about minimizing losses rather than eliminating them. The very reason there are not very many companies offering hedging solution. Did Hedging outfits suffered because the cost of hedging was exorbitant?

The arbitrage philosophy

Understanding hedging has a lot to with how we comprehend the hedge process. Arbitrage pricing theory (APT) is a general theory of asset pricing that has become influential in the pricing of stocks. APT holds that the expected return of a financial asset can be modeled using the sensitivity factor aka beta coefficient. The derived rate of return will then be used to price the asset. If the price diverges, arbitrage should bring it back into line. Arbitrage is the practice of taking advantage of a state of imbalance between two or more markets and thereby making a risk-free profit. The theory was initiated by the economist Stephen Ross in 1976.

This back into line philosophy is at the heart of the hedge failure. This could also be the reason why we as a society are running farther from understanding risk than getting closer to comprehending it.

History of statistical arbitrage

How far we are from understanding cyclicality, time and fractals and how poorly we implement them in our strategies can also be understood by studying the history of statistical arbitrage. Statistical arbitrage aka stat. arb was started in 1985, a decade after the APT. Reversion to mean was born. In his recent book Statistic Arbitrage, Andrew Pole comprehensively delves into stat arb. Pair trading was a simple idea of trading similar historical prices. The strategy was based on reversion, which occurs everywhere and anywhere. This was a sign of fractalled nature, but the author barely mentions the term (three times) in his 257 page work.

Despite the lack of fractal details, the normal distribution in prices needed for reversion in prices is dismissed as an erroneous claim. Fractal watchers do the same as heavy tails and power law are the mathematical explanation for fractals. The author spends a few chapters of the book explaining why stat. arb. was beset with problems starting from 2000 and how the strategy exhibited a diminished economic potential. He cites ideas like more advanced algorithms, volatility, vagueness of practitioners, and lack of knowledge on part of the investors.

The author asks a lot of relevant questions like how does one identify when a price is away from the mean and how much? How long will the return to mean take? Are heavy tails the reason for frequent miscalculation and underestimation of risk? Why simple probability theorems cannot guarantee reversion which is challenged by heavy tails? Why we must always learn from the predictable occurrences, however odd they may look at first sight? Why we should be buying in weakness and sell in strength? Why patterns of stock prices are occurring at least two higher frequencies above in time scales? Why LTCM failure could have been linked to higher time frequency patterns? Why Gauss is not the God of reversion?

But the book fails to admit time cyclicality and builds it case mostly through reversion. Somewhere simplistic thinking takes over simple thinking. Like how to judge whether a spread tomorrow will be greater or smaller. If it’s greater than the mean today it will be smaller tomorrow. Pole also looks at reversion to mean as more magical than the fractalled nature of markets. Though he mentions that mean reversion involves temporal dynamics and time frequency analysis, temporal aspects are the source of profits, trades at a point of time are the means with which the opportunity is exploited, but there is not even one mention of time cyclicality in the book. It’s not the first time that we have missed the idea.

Missing the idea

The idea dismissed by Pole that simple probability theorems cannot guarantee reversion are strangely the same ideas explored by other revisionists. Larry Connors of Trading markets searches for statistical probabilities that help traders profit when stocks revert to the mean. “The further prices stretch away from the mean on a short term basis, the sharper they snapback”, Connors was quoted in Bloomberg Markets. Connors and Ceaser Alvarez, are ex Microsoft engineers who worked on the development team of excel program. They seek to identify tradable price patterns based on statistical probabilities. The duo works with a large database of 8.5 million trades.

Robert Shiller’s MacroMarkets’ is also not free of mean reversion. In his 1993 book, MacroMarkets: Creating Institutions for managing society’s Largest Economic Risks, the author talks about unmanaged risk and the need for a risk management solution. To hedge Oil risk MacroMarkets introduced a new way to include Oil in a portfolio. Dubbed Macroshare $ 100 Oil UP and Macroshare $ 100 Oil DOWN exchange traded securities issued by paired trusts. According to a Bloomberg market report, “the trusts have an income distribution agreement under which assets flow from one to another in proportion to the level of the benchmark”.

As OIL moves above or below 100, the funds flow from one bucket to the other. This is supposed to be a hedging mechanism to help people. Whether we call it an innovative solution, this is still a pair attempt at managing risk. Pair trading based on reversions are far from perfect and prone to failure. The idea about comprehending markets is tougher than the idea of comprehending market cyclicality. This is why teaching market participant’s cyclicality by creating more pair offers is just adding to the already oversaturated market. The market is already trying to take a detoxifying pause from structured products.

The behavioral finance idea of losers vs. winner’s index has more merit because it illustrates cyclicality. The only unfortunate part is that behaviorologists don’t admit that the idea of selling winners and buying losers is the central idea of performance cycles.

Conclusion

A hedge is not only imperfect but inefficient and costly. Statistical arbitrage is a euphemism for Time arbitrage, performance cycles and till the time we don’t focus attention on TIME our attempt to understand risk will fail. We will have someone or something to blame then. According to Paul Samuelson, “Financial engineering is like science that can help mankind or create atomic bombs”. We will worship Beta and then pronounce it dead, rechristen it later as Jenson Beta, but there is one think we will intuitively avoid. How can it be so simple?

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The TIME Index

timeindexing1

Can we trade time as an asset class?

On one side we have comments like will the equilateral triangle lose symmetry as time triads move and on the other side is a clear idea of time triads being an empty philosophy. A controversy is a start, at least there is a debate, a thought. Volatility has been around since markets started trading, but it was not until 1993 that the idea started trading as a VIX index. Now we have hedge funds trading volatility, as an asset class. Will the market evolve to trade new asset classes? Can the market trade time as an asset class? Can we have something called time indexing?

As a start it looks counterintuitive. We are already trading time indirectly, but how can you trade time directly? And even if you could, how will you commoditize time as an asset class? Before we understand how time triads can itself become an asset class, one should realize that indexing techniques over the last centuries have moved from price weighting to free float to fundamental indexing. The idea of a benchmark is simple and investible.

So what’s time indexing? The time index tracks the performance of a pair of assets, a quantifiable study of pair performance. Pairs can be between Nikkei- Bovespa, Dow Industrials – Dow Transports, Gold – Oil, Sensex – Dow, Sensex – Gold or between any two economic time series. Pairs can tell us a lot about markets and where we are headed tomorrow. But what do pairs have to do with time? When you are long on an asset class and short on the other, you are taking out the price and just trading on time. This is why long Dow Industrials and short Dow Transports (or vice versa) is a pair idea, which lets us trade time as an asset class. Now conventionalists may argue, what fun is it to trade two indices, which move up and down together?

This is where we come in. Performance cyclicality was highlighted first time in the Kyoto University journal, Nistor, Pal. The paper illustrated performance cycles between Nikkei and the other BRIC countries. The research proved that performance between two economic zones illustrated through the countries composite equity index was not just cyclical, but even quantifiable. One of the conclusions of the paper was demonstrated through our feature here ‘Long India – Short China’. The pair delivered 50% over a quarter. Markets are quantifiable and they allow even regional indices to be pegged against each other profitably. What the paper demonstrated was that irrespective of the tight or lose correlation of an asset, performance cyclicality can be demonstrated at all time frames. The paper was indirectly demonstrating time fractals, triads.

There are some clear advantages of trading on time triads, time indexing, or say performance as an asset class. Being long and short two high correlated assets can reduce market risk i.e. offer market neutrality. This makes the strategy attractive. What is the investment world looking for? The first and foremost is a reduction in risk. For example shorting Nsebank and going long on Nifty reduces portfolio volatility and captures performance between the two sector indices creating relative alpha. Now this strategy may not perform better in a trended market, but it will surely outperform stagnation or declining market. The pace of wealth destruction and changing risk appetites also makes time indexing a viable option.

So what’s at the soul of the investment strategy? It is the ability to isolate the performance cycle. How do you do it? First, you accept that cyclicality of time exists and Kitchin, Juglar, Berry and Strauss were thinkers and not just illusionary pattern watchers. Second, one should understand that cycle regularity is not just about equality but power law proportionality. Third, one should start connecting or overlaying larger time fractals with smaller fractals. This again brings us to time triads, triangle in a triangle essence.

What kind of pairs? Large capitalization against Small capitalization indices, value vs. growth indices, mid economic vs. late economic etc. what if we go wrong? Well! If you can invest in a naked asset with a risk return history, you can invest in a market neutralizing, capital conserving simulated spot time index too. Above all if speculative volume can trade anything that moves, this is still an open source model. What about risk management? A diversified time index with many components could take care of emerging risk from the strategy.

We have been carrying pairs in this feature starting 2004. Frankly speaking it took us a lot of time to comprehend that what we were really trading, pairs or time. It took us more time to understand the fractal aspect in the subject. Long India, short China was one such pair we featured profitably. We have illustrated Oil – Sensex, CNXIT – Sensex, BSE500 -Sensex and many such pairs to highlight not only performance cyclicality but also market, economic perspectives and direction. We are not very far from the first Indian TIME index.

Another example of performance cyclicality can be built around the three pillars of global economy, Gold, Dow and Oil. So what does the Gold – Dow pair (ratio line) tell us? It says that Gold has hit an intermediate underperformance low against not only Dow, but also Sensex. This means that long Gold, Short Dow (Sensex) should be profitable pair for more than a few weeks. Even the larger primary performance cycle is also up in favor of Gold and against Dow. The respective performance cycle has been working from 1976 with an average 5 year cyclicality. The last cycle turned up in 2008 and should complete sometime in 2012. This means there is more for Gold ahead against American equity. This could mean that Dow should underperform and fall against Gold, Gold should rise or outperform Dow or Gold should fall but less compared to Dow. The very fact that Gold did not collapse against anything also suggests that the underlying larger cycle of Gold (2008-2012) outperformance against Dow continued to work.

If we need more confirming evidence we can look at Dow – Oil pair (ratio line). It might seem like a counterintuitive pair, but though Gold and Oil belong to the same commodity class, they can behave differently. Unlike Gold, Oil has pushed up to cycle highs against Dow. This could be owing to extreme oversold levels, reprieve in recession worries, or simply putting volatility cycles ruling OIL. There could be a thousand more reasons to explain why Oil shot up against both Gold and Dow. What really matters is where is the performance cycle (time oscillators) between Oil and Dow headed now? The respective pair has reached an extreme against Oil and is non confirming suggesting topping Oil performance against Dow. This means that the OIL intermediate topping could be near. Even if Dow pushes up above 8,800-9,000 levels in the ongoing leg, Oil needs magic to sustain and push to further highs against Dow. So if Oil is turning down against Dow, and Gold is turning up against Dow, what equity strength are we speaking about for the next few weeks? We have a history of contrarian calls from Oil at 100, when we said the oil rocket was not sustainable. The MAR low call on markets and Bsemetals compelling valuations where made at a time when $5 was thrown as another achievable figure for Oil. We are at $70 now.

dowoilgold

Performance cycles (time oscillators) are easy to understand, but they become tougher to grasp when you start to explain them fundamentally. The real counterintuitive thinking is not how we can have long Dow and Short Oil and still call Gold as a performer, but how time indexing can revolutionize how we understand and trade time as an asset class.

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Obama n the Yale Hirsch cycle

Though we stayed out of political forecasting, predicting the elections, we know a few who predicted it right. Bill Meridian of CYCLES RESEARCH was on top of events with his Obama call. Now of course one can analyze why it happened. Maybe the anti incumbent factor, or the age factor, but market technicians saw it coming quite a while ago. Bob Prechter’s socionomics was also on dot. Socionomics, the science of history and social prediction talks about women being in power, as the social mood changes. This was the reason Bob stuck to his Hillary call over Obama. But a closer observation and one can see that women in power is a mood change. And so is the choice of the first African American president. It is rather more unconventional than a woman president. So social mood is about different choices. A positive mood could translate to a conventional choice and a negative mood is unconventional or shocking. We are in a large bear market already so the Obama choice had already sunk in. No wonder the election results were unequivocal.


Speculators could have betted on the results, the Obama or the McCain CALL option, the latter being cheaper than the Obama in the money option (Obama was consistently leading). But there was a limitation when you had to use the understanding or knowledge of the political landscape on the DOW futures. ‘The DOW reprieve’ we carried on 29 OCT highlighted 9,600 as an ending C wave and not the start of a 3 wave. The election result had no impact on DOW and it is where it was on 29 and did not move out of the FLAT A-B-C formation (RIGHT) we illustrated.

And now if we see the formation correct, the new president won’t be able to halt the slide of DOW to a new low. Presidential cycles are bigger than presidents and even a great leader can not change the course of the market, short term or long term. The Yale Hirsch presidential cycle has worked with uncanny precision since 1954. The cycle challenges the straight line theory of prosperity and growth of market and the theory of bottomless markets. Business and economy move in cycles. The US presidential cycles have been studied for over 60 years. Yale Hirsch also wrote about winter gains and autumn crashes. The 3RD-4TH year witnesses gains 3 times more than the 1ST and 2ND year. There were of course exceptions when the cycle did not work like that in 1986.

The reason for exceptional gains in the later part of the term is owing to heroic steps made in the 2nd and 3rd years. No heroic steps are made in the second term. The cycle also talks about no economic or market correction in the first 2 years. The crash happened in 1987 in the Regan era, for Clinton it was in the fourth year, in 2000. For Bush it was in the 3 year starting Oct last year. And most times market forms significant lows in the 2nd year with average gains at 50%.

The current presidential cycle projects a 2010 rise. Then comes the BENNER cycle lows in 2011. The Clement Juglar business cycle also seems incomplete and 2008 is too early for a decade low. All these cycles overlapping together in the last few years of the decade suggest a complex structure rather than a simple unending collapse.

The only positive four DOW 30 stocks in our tracker also seem to exhaust. So a marginal new low below OCT lows can not be ruled out. On the positive side, the only stock positive for the last 3 months is J P MORGAN at a positive 5%. When the financial crisis throws up a banking stock as a winner, markets are definitely discounting all negativity. Any leg lower from here should be the final one for atleast few quarters.


Agricultural CYCLES

Give a choice, humans would like to erase the down part of the cycle. Living with an up cycle is convenient. But the balance of nature is very intricate, and we as masses don’t understand it. This is why it is hard to appreciate growth and decay in markets. What we accept as natural, we fail to relate to in our economic life. Why this disconnect?

tree_roots
There are few reasons. First, we think we are too important, maybe more important than nature. Second, our knowledge is limited. Third, we are emotional, self involved, overconfident and shortsighted. So understanding large down cycles is simply incomprehensible. The connections between nature, market behavior and economics have been written for decades. The Nile flood – drought cycles fluctuated every 18.6 years. The behavior had a strict periodicity to be just a random chance. But the cycle ended after a dam was built on the river. The river Nile cycle might have harnessed by human ingenuity, but there are many cycles beyond our reach. And even the best efforts of man can just delay them, marginally. We attempt to push out the decaying cycle, sometimes wishfully, out of our life, but then the cycle exerts itself and overpowers us.

Food cycles have been linked with drought and flood cycles for a long time. Based on data collected from 1680 till 1790, Duvick and Blasing (1981) concluded that droughts are cyclical and may occur twice per century. Studies have also proved how food cycles are linked to weather and climate cycles, which in turn have a strong connection with sunspot cycles. Sunspot cyclicality has witnessed a periodicity of 9.3 years. The activity has been monitored for 400 years. And it was an economist William Stanley Jevons who first suggested that there is a relationship between sunspots and crises in business cycles. He reasoned that sunspots affect earth’s weather, which in turn, influences crop yields and, therefore, the economy. Since 1991, the Royal Observatory of Belgium keeps track of sunspots as the World data center for the Sunspot Index.

And evidence continues to mount that the most significant changes in earth’s climate can be traced to the effects of solar activity. To illustrate sunspot numbers were plotted along with the levels of Lake Michigan and Huron. A correlation was seen between sunspots and lake levels. Climatologists have long found a connection between solar activity and climate. And if the sunspot cycle is fairly predictable, climate cycles must be for real and if that’s true, we have a base for explaining Agricultural cycles and agricultural commodity prices.

But we as humans give less weightage to simple observations. Markets look at myriad factors in the grain and bean complex rather than a single cause. These factors include production techniques, government policies, changing demand patterns, and worldwide politics. But it’s the weather and climate change, which are the most important. Cycles are average periodicities found in historical data. Often these occurrences were either longer or shorter than average. The more consistent the cycle, the closer all occurrences come to the ideal period. Understanding of agricultural cycles, and the factors contributing to high and low can help an investor or farmer understand how favorable weather can enhance production leading to a drop in prices and vice versa.

And apart from the large 50 year drought cycles, cyclists have studied short term cycles in agro commodities. There are 39- 44 month soybean cycles. Some other interesting aspects are that major bull markets in corn and beans don’t come more than 48 month apart. Rises in beans generally takes over three years with the first year rise around 25%. Soybeans exhibit 18 year cycle bottoms. Four good growing seasons are rare. And links have been even seen in volcanic and agricultural cycles of 9.3 years, which also are seen in sunspot cycles. This all might look strange, but the complexity has an order.

Sugar cycles can be explained from a market sentiment point of view. If we take the S&P sugar Index, historically the Index has underperformed both DOW and the Indian Sensex. But sugar started outperforming DOW and Sensex from May 2007 and Oct 2007 respectively. A positive society tends to be happy and health conscious. This is the reason rising equity and secular uptrend generally sees a fall in sugar consumption and vice versa.

Building on the case of food cycles, intermarket ratios also highlight underperformance and performance cycles. S&P agricultural index, a composite of all agricultural commodities has been underperforming DOW since 1974. And just like Sugar the composite index has started outperforming DOW from May 2007. Since 1975 the agricultural composite has underperformed the CRB commodity index, suggesting that agricultural commodities performed the worst among commodities are were out of favour for investors. This too seems to change, as the agricultural complex starts to deliver. Agricultural commodities have caught up with alternative energy index NEX and are now at parity with alternative energy performance. But compared to Oil and Gold, agricultural commodities continue to give subdued performance. Agricultural commodities have underperformed Gold and Oil since 1999 and 1970s respectively.

On the price performance basis though agro prices are off their historical highs with Wheat down 40% (Since Feb 2006), Sugar down 35% (since Feb 2006), Cocoa down 16% (since Jul 2008), Cotton falling since 1995 (down 87%), Corn down 31% (Since Jun 2008) and even Coffee, which we gave a positive view in March 2007 (after which it turned up 60% from sub 100 levels to 160) has also retraced 20% from its historical (since Feb 2008). But despite these down moves agricultural commodities have weathered the equity recession and the composite agro index is already positive for the year. This was owing to the recovery in Sugar, Cocoa, Corn and Soya. This means two things, first that the food crisis maybe far from over and second agricultural commodities remain an outperforming asset as the agricultural cycles start to look up. Another reason for agricultural complex outperformance might also be the bottoming 9 year sunspot cycle, a strange fundamental cycle, we might never understand, just experience.


The October low

bull_large

October lows have extreme sentiments linked to them making them great multi month, multi year and in some cases multi decade bottoms. We are nearing October 2008. If this looks like just another calendar date, think again.

The month of October has a special place in econohistory. But, somewhere the significance has been lost. There are many reasons. First, we as human beings are more interested in highs than lows. Second, a crisis gets more attention when it begins not when it ends or pauses. Third, masses can never attach more significance to a calendar month than they can to news. We like stories not some non-descript month of the year.

Fortunately or unfortunately, October has played a key role in economic cycles from documented history as back as 1869, when United States faced its first major financial and gold crisis. ‘Black Friday’, as it became known, was the result of an attempt by financiers, Jay Gould and James Fisk, to corner the gold market. In those days, Treasury’s surplus gold was sold for greenbacks, which was used to buy back government bonds. Because the gold market was small, the federal government was essentially able to set the price; selling more of the Treasury’s gold reduced the price, while selling less raised it.

The Panic of 1907, also known as the 1907 Bankers’ Panic, was another financial crisis after 30 years in the United States. The stock market fell nearly 50 per cent from its peak in 1906, the economy was in recession, and there were numerous runs on banks and trust companies. The contagion spread across the nation and lead to the closing of banks and businesses. The panic was followed by a second crash, which occurred in October 1907.

The stock market crash of 1973–74 was a crash that lasted between January 1973 and December 1974. Affecting all the major stock markets in the world, particularly the United Kingdom, it was one of the worst stock market downturns in modern history. The crash came after the collapse of the Bretton Woods system over the previous two years, with the associated ‘Nixon Shock’ and United States dollar devaluation under the Smithsonian Agreement. It was compounded by the outbreak of the 1973 oil crisis in October of that year.

Then was the Black Monday crash on October 19, 1987, a date that is also known as Black Monday, was the climactic culmination of a market decline that had begun five days before on October 14th. The DJIA fell 3.81 per cent on October 14, followed by another 4.60 per cent drop on Friday October 16. But, this was nothing compared to what lay ahead when markets opened on the subsequent Monday. On Black Monday, the Dow Jones Industrials Average plummeted 508 points, losing 22.6 per cent of its value in one day.

The Russian financial crisis (also called “Ruble crisis”) hit Russia on 17 August 1998. It was exacerbated by the Asian financial crisis, which started in July 1997. Given the ensuing decline in world commodity prices, countries heavily dependent on the export of raw materials, such as oil, were among those most severely hit. The markets bottomed in October 1998. The RTS Moscow current collapse of 30 per cent year to date makes it one of the worst performers in global equity indices. And coincidentally we have similar conditions now like we had in 1998 with falling commodity and crude oil prices. We mentioned about the strong connection of commodity boom with Russian and Brazilian markets in ‘Revisiting BRICS’ (January 2008).

October 1998 has a strong connection with equity markets worldwide. The low happened in DOW, BVSP, NIKKEI, DAX, SENSEX along with RTS. And strange as it may seem, DOW retested this low again in October 2002. The market downturn of 2002 again happened across the globe including India in October. Dow Industrial has a history with October in the year 1869, 1907, 1929, 1958, 1960, 1966, 1974, 1987, 1990, 1998, 2002 and now we are here nearing October 2008. The story repeats when you take Nikkei, but the occurrences shift sometime from October to November. Brazil BVSP has a similar pattern in 1994, 1998, 2002, 2007, 2008. Even German Dax repeats the sequence in 1990, 1992 and 1998.

The Chinese crisis labelled as another Black Tuesday occurred in February 2007 when China fell 9 per cent; the worst ever fall in a decade. This made global headlines. But, all this 9 per cent pales in comparison with the 61.8 per cent fall in Shanghai composite since October 2007 leading to October 2008. This near 12 month fall is the real October crisis heading for another October low, retracing gains of seven years.

In all this Octobers that we have mentioned above there was an exception. This was the crisis that happened nearly 30 years after the crisis ridden 1900′s. This was the famous October 29, 1929 crash. This crash did not stop at the October low. First it was the Black Thursday (October 24), followed by Black Monday (October 28) and then the Black Tuesday on October 29. On Black Tuesday, the Dow Jones Industrial Average fell 38 points to 260, a drop of 12.8 per cent. The Dow Jones Industrial Average lost 89 per cent of its value before finally bottoming out in July 1932. This was the great depression.

October lows have extreme sentiments linked to them. This makes them great multi month, multi year and in some cases multi decade bottoms. After 1929 October breach, Dow Jones has not breached another October low. The only marginal breaches we saw were in the sideways bear market of the 1970′s when October lows were retested on multiple occasions.

Cycle lows are more important then cycle highs. Contagions are more synchronous than tops. The classic reason is the lack of mass interest that lows evoke. This makes them more solid and unflappable. Above this wealth destruction destroys social mood. It quietens the party goers, sometime for a generation. A famous quote by Richard M Salsman, American Economist, goes like this “Anyone who bought stocks in mid-1929 and held onto them saw most of his or her adult life pass by before getting back to even.”

“The fundamental business of this country is on a sound and prosperous basis,” President Hoover, in October 1929. “The economic fundamentals of this country remain sound”, Ronald Reagan, in October 1987 are clear historical precedence regarding the worthless of news, as Ralph N Elliott pointed out in 1930’s. October connects us like nothing else. Elliott also mentions about the French economist Pigou in his market letters, published by the New Classic Library. Pigou discussed at length psychological errors and their relation to booms and depression. He maintained that an error of optimism tends to create, throughout the community, a certain measure of psychological interdependence until it leads to a crisis. Then the error of optimism dies and gives birth to error of pessimism. We are nearing October 2008. If this looks like just another calendar date, think again.


The Gold CYCLE

The 34 year gold cycle guides liquidity flow from equity to gold, as money shifts from paper to hard assets.
crisis
Peter Cogan mentioned about the Gold crisis cycle of 34 years in his article on predetermined periodic cycles of optimism and pessimism. The 1967-68 Gold crises, which climaxed with the end of Bretton Woods system followed the 1933-34 Gold crisis. The article written in 1969 issue of CYCLES was visionary and is the only reference in nearly 70 years of CYCLE literature. But the more interesting part is that the CYCLE is still valid and working. After the gold crisis of 1967-68 we saw the crisis of 2000, where people believed in technology stocks and the paper dreams they offered compared to the hard asset.

Crisis, as Chinese put it is danger with opportunity. The 2000 Gold crisis created more than a decade long opportunity. And the 34 year cycle projects the next crisis near 2030. What does this mean? This means that there is more upside on Gold to come on one side and second a majority as usual will get trapped buying Gold near 2012-2015 highs. This is how long term cycles work.
They originate from the time necessary in order that one generation has time to forget the faults of a previous one. And even if neural prosthesis embeds a memory chip in our brain, one really needs to be a good student of econohistory to understand that cycles exist not just in gold, but in interest rates, inflations, inventories, sectors, stocks and above than they are all linked.

The linkage part of cycles between assets is also a loosely knit subject and needs sizeable research inputs. Tom McClellan talked about liquidity waves in his book “Predicting the future”, where he mentioned about money flowing from gold to stocks and vice versa. Though written less than a decade back, the gold connection with stocks is not much talked about. We briefly touched the subject of metals predicting recession in our article Metals Maze (April 14), when we said Gold and other metals are strong forecasting tools for economic cycle upmoves and down moves. We even said that anticipating a recession (February 4) might be an illusion as metals do not suggest that the crisis is yet here. We explained our case using the gold-silver ratio. To strengthen our case we talked about the direction Gold should take in the coming months. In Fools gold (April 28) we said, “Gold is not just a metal, but a predictor of recession. And the anticipated fall of the precious metal can surprise most recession watchers. Gold is ready to come down sub-$800.” On 15th August, Gold touched a low of $773, a drop of 16 per cent from the intermediate negative trend highlighted on April 14.

Gold touched a multi year primary low in August 1999 at $251 and moved sideways till April 2001 at $254. And since then it has nearly quadrupled to $1,030 without a primary fall (more than nine to twelve months). Even the current fall lacks in retracement. Now what we are discussing here is a case for further fall on Gold at least till $700 levels and potentially lower. Intermarket cycles suggest that if the 30 year commodity cycles have to push up till 2015 (fooled by simplicity, May 26), we need more than a few months of fall for commodities to regroup. So a growth and decay progression is what commodities should experience. We wrote about this impending move down in commodities of markets and about a multi month pause in commodities and about the oil rocket (May 12) and its fateful journey lower. We have covered some ground in terms of CRB commodity index down 19 per cent since July and Oil making lows near $109, falling near 25 per cent from the $145 high registered in July. What happens now till first or second quarter 2009 is the key part.

Gold is a commodity leader more important than oil, as oil cannot replace money but gold can. Jack Sauers, Gold cyclist wrote about Gold linkage with market sectors and inflation in 1977. From the investor point of view, gold and gold stocks are looked at as being counter cyclical. That is why when the stock market peaks out and reverses trend, there is usually a rush to buy gold and gold stocks with investor funds obtained when industrial stocks are sold off as Dow Jones drops. There is thus a strong tendency to drive gold prices and gold stocks even higher. After the low of business cycles is reached and recovery starts again, gold and gold stocks are sold off and funds reinvested. Jack also explained why gold sometimes ignore the inflation trend of other commodities on the rising portion of business cycle. As far as the average business cycle of 41 months is concerned, copper and silver rise as the cycle increases due to industrial demand and gold decreases. Only when inflation rate is terribly high, or too apparent to the average consumer, do all metals rise simultaneously as investors lose confidence in paper money.

So the question one should ask is how terrible is this inflation? And does inflation lead commodities or vice versa. If it is a commodity linked inflation, a pause in commodity will also see a pause in inflation for a few months while the long term cycles exert themselves. The equity v/s gold cycles for Nikkei, Dow and Sensex also suggest that we are heading for seasonally positive time for equities compared to Gold. This means that a multi month pause in equity market fall, a bear market rally beginning from cycle lows in October 2008 might be in. We mentioned about the late economic cycle and how it is linked to the 41 month Kitchen cycle. Sensex fall for the last 8 months also pushes us towards completion of the first leg down in the late economic cycle. Every cycle has three legs and the current late economic cycle should complete sometime in 2011-2012.

From a market sentiment point of view, confidence crisis are also of various degrees. First is the crisis linked with earning expectations; second is a political crisis (like we are witnessing in Pakistan); third is a regional or local currency crisis; fourth is a global financial crisis (subprime). Only after this the economy faces a cash crisis when there is a flight of money from paper to hard assets like gold and metals. Markets don’t just bounce from one crisis of lower degree to a larger one immediately. Though this can happen, easing commodity prices belie that fear. We have been crying recession for almost a year now and the DOW remains unflappable near 12,000 (barely 15 per cent down). In conclusion, the current negativity on Gold prices should push prices lower for more than a few months. This should accompany the other commodities, including oil. The countercyclical effect of this should be seen in equities around the world with markets rising for more than a few quarters around the world. And when complacency will return that recession has been averted, the next leg up on Gold, up till 2015 should begin. Global recession does not come just because we are waiting, it will come in due time, when Gold cycles and other intermarket cycles signal.


The Cycle Blindness

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Start of August is the celebration of the richness of harvest. It is a time for festivals. People step out and celebrate. This is seasonally a good time for food and beverage companies. It was during these weekend jaunts out of Cluj, back at the farm house about 80 kms away, we started picking plums and enjoying the natural inspiring beauty of corn fields and farm lands around us.

Did our city life really isolate us from the underlying agricultural economy? Did the harvest cycle stop affecting us? Or are the agricultural, climate, commodity, social behaviour and economic cycles somewhere connected? A common theme runs through all these cycles. They are all linked and have a distinct periodicity. The long term and short term climate cycles establish what we harvest and eat and what we eat is linked to our social, economic growth and expression. And a crisis or a down cycle on any one of these cycles affects all the rest. Though the modern economies are no more agrarian, the current food crisis is increasing inflation and pushing commodity prices higher. The unison of up and down cycles are changing how we celebrate (behave) and remain happy (prosper). Jacob J Van Duijn, talks about how a classified or phased approach to economic development is important to realise that human behaviour as producers, consumers, and investors create cycles. But still a majority of us are unaware of the economic consequences of this behaviour. For example, every generation comes with capital investment ideas and allocation as the previous capital investments become technologically obsolete. This leads to the repetitive investment cycle. But little is learnt from the past.

This creates a gap between our understanding of the economic future and the current socio economic perception. This is one of the reasons humans are generally under prepared for the future. We can’t understand how policy induces monetary cycles or how oil prices or shock induced boom bust cycles and over investment, under consumption, demographics and mass psychology driven cycles can influence and change a growth period into recession or vice versa. There is one more reason why we are cyclically blind. We relate or register more to short cycles. The fluctuations caused by Kitchen cycles (3-4 years) very much determine people’s mood and expectations regarding the short term outlook of the world economy. Because, in the short run it produces the dominant cyclical pattern, most observers tend to overlook the longer term developments which lie underneath. Needless to say, this form of myopia may cause rather wild swings of over optimism and over pessimism. This is why euphoria and pessimism repeat with such regularity.

As we move from short term to long term cycles the cycle applicability and debate intensifies. More so because what affects us in the long term is still unclear. In 1991, Richard Mogey, Cycle Guru said, “Many have been expecting a Kondrateiff wave (the long term 60-year cycle) to top for nearly twenty years, but it has yet to unfold.” This long-term cycle has been hotly debated and a few cyclists like Tony Plummer, Author and cyclist, suggest the Berry cycle (25-30 years) and Strauss and Howe cycle (90-99 years) as a more valid case over Kondrateiff cycle. Plummer’s case becomes more relevant if you connect power law relationship between Kitchen, Juglar, Berry and Strauss. All are linked with a factor of 3. Three Kitchen cycles make a Juglar cycle, three Juglars make a Berry cycle, three Berry cycles make a Strauss crisis cycle.

Small fluctuations caused by the Kitchen cycle sometimes go unnoticed by the masses. But it is the large Juglar, which registers in the long term memory. Average length of little less than a decade appear to be in conformity with the way people think of time spans, the swinging 60′s, the 90′s etc. Hence Juglar recessions have a deeper impact on mass psychology. Juglar recessions are also deeper than Kitchen recession just like Juglar upswings more sustained than Kitchen upswings.

Juglars are also considered as the most long standing, dominant and periodic. This cycle was identified by Clement Juglar, a French economist in the mid 1800′s. Juglar began his work with cyclical studies in French marriage, birth and death rates. These observations led to similar cyclical behaviour conclusions in interest rate, credit contractions and commercial crisis. His studies concluded that credit contractions and crisis occurred with an average periodicity of 9-10 years. Juglar cycle is also referred to as the pendulum swing of prosperities and liquidations.

A similar 9-12 year cycle is also witnessed in agriculture, social trend and is informally also labelled as the business cycle by economists. There is another business or trade cycle namely the 7-11 year investment cycle also known as the cast iron cycle, which existed 250 years ago and still exists today. Cyclists have discovered more clusters of 10 year cycles. The most reliable is the sunspot cycle of 11.2 years. Sunspot cycles are also known as prosperity cycles. Research by Garcia Mata and Shaffner suggested that low sunspots actually work on the human psyche to influence confidence. Kitchen and Juglar cycles have been known to work on yields also. And of the many other running cycles, Juglar and Kitchen cycles work best for stock markets.

For example, historic lows are generally made in the second year of the decade. 2002 was a historic low worldwide, be it Nikkei, Dow, Sensex, Brazilian BVSP, Russian IRTS, it was everywhere. Juglar slowdowns have also known to degenerate into real crisis and depressions. The Juglar recession cyclicality has been observed since 1721.

But recession is not a singular event. It is linked with both short term and long term cycles. And since excesses happen in stages, correction of market imbalances also does not get over just by price retracement. Hence real recessions generally take time to balance and get into the human psyche. This is why recessions are also about market mood and not just about prices. Prices are just one way to express it. Simply speaking Juglars are real recessions. Historically we have not seen a bigger than a Juglar recession globally. The great depression (1929-1937), the Japanese depression (1990-2002), the American bear market (1965-1975), the Sensex sideways action of the 90’s (1990-2002) were all of Juglar time frames. Shorter recessions are labelled as Kitchen recession. Some European countries experienced a Kitchen recession in 1987, when industrial production came to a standstill. Though irregular, only Kitchen and Juglar could explain the global recession of the 1970′s.

There are other inter-market aspects linked with Juglar cycles. The bond markets generally hit a low on every Juglar low. The bond market rise from 1921-1932 in America is a classic example that can explain how interest rates should behave. American bond markets also hit a low in 1990-1991, ushering in another decade of prosperity. If we consider the Sensex in a Juglar up starting 2002, the cycle should complete anytime between 2011-2013.

This means interests and inflationary conditions should continue to rise for the next 3-5 years. This observation is in sync with the other commodity cycles, which we see peaking around 2012-2015. This also means that what we just saw from January 2008 was a Kitchen or growth recession, the real bust or Juglar recession should start at least a year from now.

The cycle truth is hard to accept. Like technical analysis is a foot note in Elliott, both Elliott and economics is a foot note in cycles. They are larger than life, above any mathematics and fractal science. And this more than 200 years of observed cyclicality can’t be wished away, just because it does not fit our conventional beliefs.

Accepting that we are cycle blind is a step forward to understanding economic uncertainties that surround us. Just like it takes 10 years to become a glassmith, for a global analyst, it takes 10 years to witness the Juglar recession and cycle truth.


Anticipating a recession

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The “R” word is everywhere. It’s being discussed at World Economic Forum at Davos and now we have clients calling in at Orpheus asking us about Recession and how bad it is. And is there a chance that the global depression might be starting. Such worries though important and critical do highlight the mass psychology and how it reads the Federal interest rate cut and subprime crisis as a start of something bigger and problematic.

First and foremost recession is not an event it’s a process. It happens again and again. And when the recession lasts for more than three successive quarters of negative growth and prolongs we call it a depression. We have had one depression in USA and one in Japan from 1929-1932 and 1980-1993 respectively.

A part of market sees this as a sectoral crisis just in the financial sector. But crisis is never sectoral, it’s always linked to credit and is across market. This is why a financial crisis is also called a confidence crisis, as liquidity dries the counterparties panic and everyone wants out at the same time. This is the reason a onetime write-downs might not be enough. New trader’s from Europe keep falling out of the closet. Markets need confidence more than write-down’s. It’s like saying if the FED cuts the benchmark again things will be fine. Some might however look at it differently i.e. if the FED cuts it again we have a more serious problem. In any case FED cut does little to boost confidence, the most needed commodity today. Markets follow their own rhythm, no wonder S&P 500 has rallied on the same day as a Fed rate cut only six of the last 13 times. And if all this was not enough we have Alan Greenspan doubting FED’s ability to avert a recession, everybody seems ready.

But the recession or great depression does not start till we have these negative quarters. All we are doing now is anticipating. And even if we are anticipating are we not a bit too late? The housing crisis started more than a year earlier and has already pushed prices substantially lower. We have more than a million foreclosures. The Philadelphia housing index (HGX) has dropped by 60% from 2005 high and sales of new houses are at 25 year low. Even the subprime has seen a lot of wealth erosion. The overall economic loss is estimated at $ 2.3 trillion. The third indicator, considered as the most reliable predictor of US slow down is the S&P 500, which is still negative for the last seven years as it failed yet again when it reached previous 2000 highs. This suggests that the slow down what we talk about today is already under play for the last few years and that is why anticipating a recession is different from what is happening.

Robert Prechter market thinker compared Dow Jones with Gold and proved that the slowdown is already happening as Dow Jones has crashed 67% compared to Gold over the last 8 years. This he calls as the silent crash. We have mentioned it so many times prior in our write ups saying that though history repeats itself it never repeats in the same way. And this time the slowdown is happening without people around realizing how our real purchasing power is eroding. Gold is near the $ 1000 mark, and Bill Sarubbi, market thinker and world renowned time cyclists puts it at $ 3000 in years to come. What would that mean? That would mean that even if markets locally or globally don’t really crash, the effective value of money will become a fraction of it. And Gold will become the most valuable asset more valuable than real estate or stocks as they are all denominated in paper money. This is already happening not only in America, but across the world. The real value is shifting to Gold and even though we don’t realize this. And we should consider our self lucky if Gold gives us a last dip back sub $ 600 before starting the next big leg up till 2013.

So though America and emerging markets might be witnessing a fall in value compared to Gold, the relative performance still points positively at what has been created over last seven years in emerging markets is more valuable than what America created in the same time. Plus the level of financial securitization in America or leverage as I might like to call it is much higher in the developed world compared to emerging markets. So even if we may seem to come down together there is always a relative performance. And the adjustments to US slowdown are dynamic and happening all the time. Over the last eight years the US dollar has depreciated 87.5% against the Euro. The slowdown is already taking a toll on the purchasing power parity of Americans. So markets around the world cannot be really clubbed together with looming asteroid and recessions, we do need to factor in local relative currency strengthening also.

Simply putting, all this talk of crisis together is a mass psychology creation. And even if we leave the Gold peg behind, the correlations between Global and local markets is an overplayed statistics. What works is only the short term correlations in contagions, rest correlations are weak and flawed predictability indicator. The world will not come to an end even if the US plays down, as adjustments are happening consistently.

In conclusion, we don’t believe anticipating recession can bring over a more serious chaos than what is already happening. Rather we think the mass psychology element highlights an inbuilt positivity to the whole thing. We in emerging markets are still low on critical mass to get seriously burnt with any global slowdown. And the real crisis may still be months away. And even the worst comes earlier, we can laugh about these terms like the late president Reagan did, when he said, “A recession is when your neighbor loses his job, a depression is when you lose yours”.


Cash and Crash CYCLES

Cash conservation becomes strategic, as the healthy disinflation era is challenged by rising food prices.

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“We learn from history that we do not learn from history,” these famous words of George Bernard Shaw are a befitting reality for mankind. These people he talked about also dabble in stocks and commodities. And a majority of them are oblivious to these written words of fate. It’s the few who understand while the majority perishes owing to short sightedness. The rush of greed has historically overshadowed sanity. Personal skill and the power of state have always been overestimated. Great nations have failed along with revered geniuses in front of market cyclicality. And till the time humans last, our love for speculation and war, boom and busts, creation and destruction, celebration and vilification will continue. The great Manmohan of yester years is the weakest PM ever, says Advani. It is this cyclicality of mass psychology — cheerful today and depressed tomorrow — that pushes us to extreme behaviour where we don’t know how to stop and hence the violent pause, which econohistory quotes as crash.

The ideal time to study econohistory is when sanity matters most and greed busters are needed. We really need them today. And nothing busts greed better than a pinch of econohistory. Spirituality can, of course, do it better than econohistory, but then use of religion to bust greed, seems a tall shot in the age of speculation.

We will stick to econohistory, which exhibits very well how long the current boom will last. The subject relies a lot on cyclicality and makes some bold findings. It proves that every generation has its war. Every market has its crash, big and small. It also proves that economics cycles are driven by credit, which itself inflates and deflates cyclically. There is a shift from paper to hard assets and vice versa.

There are three stages linked with the credit cycle viz hyperinflation, disinflation and finally deflation. Disinflation is a period of low inflation and low prices for food and essential goods. This leads to economic growth. While there is little literature available on the chronology of events, disinflation is the one preferred most by investors and market participants. Disinflation is generally perceived as beneficial. However mass psychology extremes have been know to stretch the benefits to an extreme causing deflation. The most visible example of deflation is the 13-year slowdown of the Japanese economy. The deflation period is one of decrease in the general price level over a period of time. Deflation is the opposite of inflation. During deflation the purchasing power of money increases. Many still consider deflation as a problem of the modern economy because the phenomenon can spiral into a depression.

Hyperinflation on the other hand refers to a period when inflation goes “out of control,” as cash or currency rapidly loses its value. A monthly inflation rate of 20 per cent or more is hyperinflation time. Although there is a great deal of debate about the root causes of hyperinflation, it becomes visible when there is an unchecked increase in the money supply or drastic debasement of coinage, and is often associated with wars, economic depressions, and political or social upheavals.

The worst case of hyperinflation happened in erstwhile Yugoslavia where inflation doubled every 16 hours. Hyperinflation destroys real money. So the talk of hyperinflation in India or the US is a clear misinterpretation. There is a crisis of confidence in hyperinflation. China between 1939 and 1945 is a classic example of government printing money to pay civil war costs. By the end, the currency was flown in over the Himalaya to be destroyed. The chaos often ends with a civil conflict. And there are a lot of zeros in the currency and they keep adding. A majority of countries around the world have experienced this phenomenon. In recent times, itʼs happening in Zimbabwe. There is a crisis of confidence under Mugabe and the country is in a civil strife witnessing the biggest modern-day exodus.

So all our good times rest on how sustainable this current disinflation is, the good inflation. According to a research paper by Marc Hofstetter, Universidad de los Andes , very little is know about the sustainability of disinflations. The paper dispels misconceptions about disinflation and points food as the most essential sustainer of prosperous times. One cannot blame the low sustainability of disinflations during the seventies on rising oil prices as Yale professors Boschen and Weiss state that world food prices are a significant predictor of inflation in OECD nations. And food inflation plays a bigger role in undermining positive disinflation than oil prices. In fact, the significance of oil shocks turns out to be weak. The paper also comments on exchange rate regimes saying that an increase in exchange rate flexibility reduces the sustainability of disinflations.

Disinflations that bring inflation down to low rates of 5 per cent or lower (like we have today) are more likely to succeed in keeping those gains in place. Rogoff (2003) and Razin (2004) add the idea that globalisation played an important role in the recent worldwide disinflation. Since the early nineties, an increasing number of developed and developing countries have adopted inflation targeting regimes to conduct monetary policy, which is ineffective in determining sustainability of disinflation. Politics also seemed to have little effect. The most interesting aspect was the linkage of whether US inflation had something to do with worldwide prosperity since the nineties. Boschen and Weiss found strong evidence that US inflation plays an important role in triggering inflation abroad and US monetary shocks have important consequences abroad ie a higher US inflation reduces the sustainability of disinflations abroad.

What all this means is that if food prices donʼt stop going up, the good times will come to an end. And there is nothing the central banker or the politician can do to sustain it. Grains are up and so are other agro products and this is just the beginning. We are looking at multi-year rises on food prices. We are not bears at Orpheus. And it was here in this column we talked about energy outperformance and software underperformance in Jan 2007. It happened. We also gave you sectoral winners like Reliance Energy which moved up 300 per cent since it appeared in The Smart Investor on June 25, 2007. We highlighted many other outperformers like Reliance Natural Resources and underperformers like Hindustan Zinc which we suggested exiting near Rs 1,000. But unfortunately we see a lot of unsustainable greed at current levels. And highlighting the importance of cash before the crash cycle can never be overstated.