Archive for the ‘Time Triads’ category

The probability myth

Probability was not just about randomness, but about proportion.

Do you know how many times you use “Probably” in a day? The word refers to the possibility of a certain event happening. Irrespective of our ability to calculate probability, we frequently estimate, compare and make decisions based on probability. It is a subjective degree of belief in the occurrence of an event. The concept of probability has philosophical, psychological and scientific interpretations. Putting simply, probability of an event is the ratio between the number of favorable events and the number of all equally possible cases.
Evolution of probability theory
Initially probability theory was inspired by games of chance in the 17th century. However its complete axiomatisation had to wait until Kolmogorov’s ‘Foundations of the Theory of Probability’ in 1933. Over time, probability theory found several models in nature and became a branch of mathematics with a growing number of applications. In physics probability theory became an important tool in Thermodynamics and Quantum Physics.
Probability is the reason why a vast majority of phenomena from nature and society are considered stochastic (random). Their study cannot be deterministic. Probability theory deals with the laws of evolution of random phenomena. Rolling a die, tossing a coin pushed us to focus on prediction taking us away from the initial relative ratio proportion of probability. The distraction towards random elements was owing to the details like the initial impulse of the die, the die’s position at the start, characteristics of the surface on which the die is rolled, and so on. A drunkard reaching home, the time it takes him to travel a fixed distance varies because of random elements (traffic, meteorological conditions, amount of alcohol, etc). These were the details which forced us to assume that the essential conditions of each experiment are unchanged (“ceteris paribus”).
This focus on prediction and cause and effect took us to develop experiments and its results and focus on developing methods to study random phenomena. This was despite the fact that an equal aspect of probability is about relative frequency. How many times you may repeat an experiment in identical conditions, the relative frequency of a certain result (the ratio between number of experiments having one particular result and total number of experiments) is about the same.
Event focus, evolution of phenomenon, quantity focus and conditions focus complicated this further. Probability is not the expression of the subjective level of man’s trust in the occurrence of the event, but the objective characterization of the relationship between conditions and events or between cause and effect. The probability of an event makes sense as long as the set of conditions is left unchanged. Any change in these conditions changes the probability and consequently the statistical laws governing the phenomenon. So, if the initial conditions can never stay constant, can science ever find a solution?
This is why the notion of a butterfly ruling our life seems valid and this is the same reason why the idea of long term predictions is considered impossible. Will our life remain random? And will we ever come out of this quandary that even though systems are deterministic, meaning that their future dynamics are fully determined by their initial conditions, with no random elements involved, they are still chaotic? Isn’t it strange living this deterministic chaos?
We want to believe life is random, though the same random theories talk about relative proportion and patterns. We want to develop theories of randomness, though we have scientific history of predictability and order in physics. The drunkard’s behavior has an order, but we don’t consider it one. Human beings have problems with extremes. If there is an extreme mankind can’t explain, we get into thoughts of disorder, unpredictability, lack of equilibrium and inefficiency. The very fact that market crisis is a case of inefficiency for us, while earthquakes are natural predictable disasters, also shows our double standards in our treatment of extremes. We built economics around normalcy and when Mandelbrot proved that extremes were normal, our whole world of order seems to have collapsed.
Are we addressing extremes?
What are we doing now to address it? We are creating new subjects, econophysics, econoscience, econobiology and behavioral finance address the extremes. Though we have done a good job illustrating extremes in economics (far away from normalcy), we are still struggling with explaining the order in this chaos. We can’t seem to know why there is an order in these extremes, why do they repeat. Just because we can’t seem to explain the timing of the extreme, we say everything is random. Because if we would call it ordered, we would be expected to know the recurrence of the next extreme.
The Time decay
Showcasing an order in time would prove that there are no butterflies causing Armageddon. It would also prove that randomness is not owing to initial conditions, but because there is a limit to which one can understand and model time. Last time we illustrated cases on global assets and how time decayed in a similar form. This time we have picked up some random events like the chronology of Indian history starting Indus valley civilization from 3000 BC to the latest political elections, the chronology of battles starting ‘The Marathon battle’ in 490 BC till ‘The Battle of Dien Bien Phu’ in 1954, the chronology of US Naval history starting the commissioning of building six frigates on 27 March 1794 till the recent 200 year anniversary in 1997 and the chronology of Roman Empires starting Augustus in 27 BC to Romulus Augustus in 475 AD. Guess what? The so called random events in time decayed proportionally.
Now what is the probability that time decay in four random events in history decay in a similar exponential way? And what is the chance that this time decay in historical events is similar to the time decay in global assets like Gold, Oil, Dow, Sensex, BET, etc.? Well, for us, at Orpheus, the probability is 100 per cent, as we are not speaking about a chance decay, we are speaking about a pattern of time. Bloggers like Paul Kedrosky from ‘Infectious Greed’ talk about the end of behavioral finance illustrating how Richard Thaler’s fund underperformed. This is an old post, but the very fact that practical utility of the behavioral models is challenged on the web, suggests that there is more work to be done.  Apart from the behavioral models, what really surprises us, is how the world bought into the story of butterflies in Brazil setting off tornados in Texas?
Time is too bland to become a hot selling story. But it is indeed shocking how, helpless human beings, are pitched to be unaware of the black swan. Randomness gives humans a feeling that they are lost in a labyrinth. But, if the man is indeed in a labyrinth, a constant failure to search for a route will force him to see failure patterns and, sooner or later, he will find a way out of the maze. Even if humans are greedy and fearful, they are not dumb with a blank page in their head, ready to drift with the wind where it takes them. The wind has a direction in its drift. Nothing propagates in life if it is random, nature cannot be random, propagation, growth is ordered, because the time we live in has proportion, pattern and decay.

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The Time Decay

The exponential decay of time proves that all the focus on studying news, information, prices, psychology and mathematical order are indirect ways to study time.

Growth and decay has always been associated with nature, assets, life but rarely with time. From Apr 08 - Mar 09 we have been publishing ideas linked with time cyclicality and fractals and starting Mar 09 we have expanded the idea of time coining ideas like time triads, time fractals, time arbitrage and performance cycles. We have illustrated long short pair trading cases between India - China, Czech - Poland, BSEOIL vs. Sensex, Gold vs. Oil, Nikkei vs. India, Soya vs. Shanghai and many other single asset ideas.

We talked about the work of a few Nobel Prize winners, work of various experts, authors and thinkers over the last 250 years (and more). Euclid, Leonardo Fibonacci, Adam Smith, Thomas Malthus, Maynard Keynes, Vilfredo Pareto, Pierre Francois Verhulst, Karl Marx, Charles Dow, Karl Lamprecht, J M Draper, George Cantor, Ralph N. Elliott, Kinglsey Zipf, Joseph Kitchin, Clement Juglar, Brian Berry, Daniel Kahneman, Benoit Mandelbrot, Robert Shiller, Hersh Shefrin, Martin Pring, John Murphy, Theodore Modis, Bill Meridian, William Strauss and Neil Howe, Tony Plummer, Eugene Stanley, Robert Prechter etc. We covered a lot of market research literature to illustrate a few simple ideas. First: Time cyclicality was a reality. Second: Over a few hundred years, research (mathematical, historical, scientific, market related, psychological) overlapped. Third: Time was the pulse or the soul of everything.

The third idea is and will be contested as it simplifies many life times of work. It challenges Mandelbrot’s Chaos theory assumption and fractalness of nature. Time and price can’t be fractalled at the same time so it consequently proves that Elliott wave theory of price is actually a theory of time. The idea of time fractal also moots that efficient and inefficient market theories (behavioral and others) are two faces of the same coin, the real risk comes from time translation and Pareto principle is because of time triads.

To demonstrate my case, I shall take global assets, isolate time periodicities and illustrate time decay. If time decays similarly across respective assets over various periods of studies then there is indeed something about ‘Time’ that can’t be ignored. I took the following assets, Gold, Dow, Oil, Indian Sensex, Indian CNXIT futures (technology Index Futures), Japanese Nikkei, Romanian Blue chip BET and Euro Dollar currency pair. I took all the available history from my Thomson Reuters 3000 Xtra terminal. Some data periods were from 1955, a few from 1965 and majority from 1990′s.

What did I do with this data? I detrended the price. I was left with an oscillator on an x-axis with calendar dates. These calendar dates were nothing but time cycles with time periodicities in days, weeks, months, hours etc. I sorted the time periodicities on a descending basis in number of days and plotted them. I got the following charts (illustration). All the charts not only looked similar but decayed in an exponential way. Students of Pareto principle, mathematics, econophysics and Mandelbrot fractals will say “so what is surprising here? This is a clear expression of power law.” Look again at the charts, there is no price in the charts. It’s just time decay. Above that the similarity of the charts are irrespective of the asset and the period of study.

What does this mean? This means that time grows and decays exponentially and because of which asset prices seem to grow and decay exponentially in a power law basis. It also means that either time is exponential or price is. Both can’t grow and decay at the same time exponentially. This also proves that all the focus on studying news, information, prices, psychology, sentiment and mathematical order are indirectly ways to study time.

If you look at the charts and cases further you will see that most assets when plotted on a daily basis had an average periodicity of 15-20 days, when plotted on a weekly basis had an average periodicity of 66-77 days, when plotted on a monthly basis had an average periodicity near 400 days. Now that it all looks coincidental, I plotted the data of all the days from 23 Apr 1997 since I first wrote in Business Standard. Guess what? Over the respective publishing period of near 13 years, the time difference between my features also decayed exponentially.

In conclusion, the power law 80-20 rule that has been omnipresent in nature, markets, and societies turns out to be also present in time. This aspect proves that time is not a linear moribund constant but a living pulsating variable which gives life to everything else. If global traded assets and a time series of a decade long personal event create similar patterns, we cannot keep living the illusion that time has no pattern and mathematics. The idea of randomness falls on its face, when mathematics and order gets associated with time. Time fractals are the reason why opportunities – crisis, war – peace, creation - destruction will recur irrespective of any human effort. The exponential growth and decay of time suggest that we have a lot of unlearning to do. And before we do that, we should give time cyclists there due place in history of research, atleast at par with psychologists, technicians, historians and mathematicians.

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The Oil correction

Oil is moving near Jun levels. Inability to trend are signs of an exhausting trend. This means that intermediate multi month trend should see Oil prices net lower below 70. The interesting aspect however is to understand whether it will make another attempt at 80-90 prices before turning lower or is the top already in.

We inverted the minor (Fig 2) Oil chart to understand the price structure. Till we see a clear break at illustrated channel levels, another leg to complete the final 5 wave structure can’t be ruled out. Now there is no rule which says that the ongoing structure is a five wave subdividing structure and not a three wave corrective. A closer look at XLE, Chevron, heating oil and Gazprom suggests that there is further upside left. So if the respective energy components suggest positivity, we rather wait for a clear break at 70 before jumping in with a view that the multi week top on Oil is in and prices should now push to 60.

60-55 are aggressive down targets for Oil as the larger multi year perspective for Oil remains bullish. Any multi week dips on energy commodity assets are reentering dips.

Enjoy the latest WAVES.OIL.

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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 Orpheus Newsletter - 8 DEC 2009

Keeping It Simple

Detachment is a spiritual mantra that works well in markets too.

When price movement bothers you while you sleep and causes you dreams of paradise or nightmares, you are suffering from the real capital market crisis. It is easier said, but if you can’t keep cool in markets, you are at the wrong place. Markets need a lot of detachment if you really want something constructive and valuable to come out of the vocation. How can one detach from profits and losses? If you think you are getting complacent, think again and tune up. Read more…

TIME ANALYTICS - ECONOHISTORY

Alpha.Energy – Is 0.9 correlation between Chevron – Brent tradable?
ALPHA.INDIA: Can HDBK – ICBK pair diverge 100%?
ALPHA.ROM: Revisiting BET vs BRD
ALPHA.INDIA – Indian Pairs
ALPHA.ROM – What is better BRD or TLV?

INDIA

WAVES.INDIA – NSEBANK ALTERNATE
CHANNELS.INDIA – NTPC. ANTICIPATED AND HAPPENED
CHANNELS.INDIA – EARLY ECONOMIC MINOR CORRECTIVES
WAVES.INDIA – NO CLEAR SIGN OF AN IMPULSE YET
CHANNELS.INDIA – TELECOMMUNICATIONS REMAIN DOWN
WAVES.INDIA – CNXIT. ANTICIPATED AND HAPPENED
CHANNELS.INDIA – ENERGY SHOWS SIGNS OF NEGATIVITY
CHANNELS.INDIA – EARLY ECONOMIC – ANTICIPATED AND HAPPENED SPECIAL
WAVES.INDIA – PREFERRED CONTINUES TO LOOK LOWER

ROMANIA

Waves.Romania – BETC (3) top is here
Channels.Bvb – Early Economic Update – Moving average special
Channels.BVB – Late Economic Update – Monthly Perspective
WAVES.ROM – Positivity continues
Romanian Sentiment Review – Dubai vs. Bucharest
CHANNELS.BVB – Mid Economic update – Montly Perspectives on Industrials

GLOBAL

Waves.Forex – USD/JPY headed higher
Waves.Forex – CABLE continues to point lower
WAVES.GLOBAL – Nikkei ready to outperform BVSP(Brazil), IRTS (Russia), SSEC (China), Sensex (India)

NEWS

Member’s Post
Integrity Research: The Payment Paradox
National Day of Romania


Keeping It Simple

Detachment is a spiritual mantra that works well in markets too.

When price movement bothers you while you sleep and causes you dreams of paradise or nightmares, you are suffering from the real capital market crisis. It is easier said, but if you can’t keep cool in markets, you are at the wrong place. Markets need a lot of detachment if you really want something constructive and valuable to come out of the vocation. How can one detach from profits and losses? If you think you are getting complacent, think again and tune up.

“The market does not beat them. They beat themselves.” stated Jesse L. Livermore, a stock trader from the beginning of the 20th century, known for making and losing several multi-million dollars during the major stock market crashes (1907 and 1929). Traders are human beings above anything else and behave accordingly. More often than not, our behavioral errors interfere with our cold-minded trading and screw up our thinking. “This time it’s different.”, “This time we know better.”, “We will not make the same mistakes again.” How many times do we hear that in the trading world? And yet the same behavior repeats itself over and over again, in different times and different shapes, but with the same substance.

Behavioral finance has gained a lot of ground over the last decades, mainly because analysts all over the world realized that the main driver of the prices (supply and demand) is human psychology. The aggregated trader mentality is far more complex than we can imagine and the study of it revealed interesting aspects, proving that usually it is not as rational as we would expect it to be. It teaches us important facts about how humans differ from traditional economic assumptions.

How does the mind of a trader work?

In order to understand behavioral finance and crowd behavior on the capital market, first of all we need to understand the factors that influence the trader mindset. As Jeffrey Kruger, a senior writer at Time magazine and the author of Simplexity would say, traders are “misled” by many things. Let us put these factors in two main categories, depending simply on their source, external or internal.

The most important external factor is “everyone else”, the trading crowd, the general opinion. We form an opinion about the others. We believe them to be either smart or stupid, either right or wrong, then choose one of the two main psychological trading strategies: “go along to get along” or be a contrarian. Then we have other external factors like payoffs, scale, psychological and academic background, social structure, external advisory and resources.

Maybe the most misleading and yet powerful internal factor is the trader instinct. “My feeling is “. I am sorry to say, but that feeling of yours is not quantifiable. Intuitions are good but they are not a system. Whom do we trust more than ourselves, our own hunches, past experience and well-learnt lessons? Overconfidence is by far the most common behavioral error and can lead to irrational decisions, dangerous trading and therefore, huge losses. This is the point where trading is a lot like gambling for a significant part of the players.

When trading becomes gambling

The fact is that most of the market players are attached to the idea of profits. We are in love with the capital market. Trading makes us feel alive. Even investing gives an aura of safety, but there is so little we know about markets that any feeling of safety is an illusion. After a certain stage, it’s not about the money anymore, a bigger loss won’t kick us out of the market, we will return every time with the hope of winning. Sometimes the win does happen and develops into a powerful stimulation for further trading.

Other times we lose it all. Our love turns into hate or ignorance at least. Either way, it is an extreme sentiment, overwhelming or disappointing, but above all other things, ‘irrational’. Replace “trading” with “gambling” and there you have the kind of behavior common in casinos. The stock market anomalies can be explained with our emotional extremes, over- and under-reaction, greed and fear and, as Robert Shiller (Yale) called it, “magical thinking”.

Isn’t this overconfidence and trading addiction the one that causes emotional extremes, bubbles and huge volatility on the capital market? How can a stock’s price move so far away from its intrinsic value if not influenced by emotional extremes and trader’s expectations? When bubbles develop, fundamentals fail and the mystic spirit of the market takes over. Shiller said that these are the moments when market players go a little crazy. How can we predict the degree and length of the madness?

How can we beat the market if we don’t understand human and market behavior and the way this behavior changes cyclically? If our behavior is cyclical, then how do we break out of the cycle? Or is this cycle natural and the only thing we need is to time our reactions better? It would be extremely convenient to sell at a top and buy at a market bottom. The answer is not to change the cycle, but to synchronize our own calls according to the market rhythm.

How do we keep it simple?

So how do we avoid all this madness? How do we “trade safe”? How do we maintain a healthy relationship with the market and not fall madly in love with it? Mark Twain said that “History may not repeat itself, but it does rhyme a lot.” On the other hand, a famous poker player admitted that “Poker is like life, most people don’t learn from their mistakes, they only recognize them.” Can we develop such a skill to analyze our own behavior and avoid repeating the same mistakes over and over again?

Acceptance is key. We need to accept our bad calls and move on. Wealth is created by getting it right most of the time, not necessarily all the time. The aftermath of market crashes and crises should be valuable lessons for the future. Are we really capable of learning and keeping it simple?

Anna Maria Michesan, Orpheus Capitals, Global Alternative Research
(With contributions from Mukul Pal)

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THE ORPHEUS NEWSLETTER - 30 NOV 2009

The Hedge Opportunity. Performance cycles indicate that Hedging could be an opportunity and not just an imperfect risk management technique. The history and the idea. Hedging is one of the first ideas modern finance taught us. Hedging as an exercise was started for a farmer, who wanted to insulate himself from movements in agricultural commodity price. The commodity prices fluctuate and create a risk. If the actual price of agricultural commodity rises a lot between planting and harvest, the farmer stands to profit, but if the actual price drops, it could lead to a loss. A hedge allowed the farmer to sell a number of wheat futures contracts equivalent to his crop size at planting time. This way he could effectively lock in the price of wheat. Now he no longer cares whether the current price rises or falls, because he is guaranteed a price by the contract. Overtime the risk management shifted to stock prices. Change the farmer for a stock trader, who believes that the stock price of Company A is volatile and could fall. He offsets the position with the index or another sector peer, now if the market falls and the stock, the investor has locked in a price and will not lose. read more.

The Inefficient Pair. A recurring divergent performance on an equity pair could redefine alpha. Robert Arnott’s, Research Affiliates LLC, has received a patent for an indexing methodology that selects and weights securities using fundamental measures of company size, such as dividends and sales. Fundamental indexing has gained popularity with $27 billion tracking the indices. This is 3% of the total investments tracking the S&P 500. Apart from the fact that the patent gives intellectual rights to Research Affiliates and generates license fee for the company, the revolution here is challenging the benchmark. read more.

TIME ANALYTICS - ECONOHISTORY

ALPHA.INDIA – TCS VS NIFTY UP 60%
ALPHA.INDIA – Grasim to outperform L&T
ALPHA.ROM – Can BRD outperform BETXT by 100%?
ALPHA.CEE – CENTRAL AND EASTERN EUROPE INDICES
ALPHA.ENERGY – Long Gazprom, Short Chevron
ALPHA.GLOBAL.INDICES – Long Nikkei, Short Brazil (BVSP)
ALPHA ENERGY: Chevron moves up in rankings
ALPHA.GLOBAL – Short Pfizer, Long J&J continues

INDIA

WAVES.INDIA – NSEBANK ALTERNATE
CHANNELS.INDIA – NTPC. ANTICIPATED AND HAPPENED
CHANNELS.INDIA – EARLY ECONOMIC MINOR CORRECTIVES
WAVES.INDIA – NO CLEAR SIGN OF AN IMPULSE YET
CHANNELS.INDIA – TELECOMMUNICATIONS REMAIN DOWN
WAVES.INDIA – CNXIT. ANTICIPATED AND HAPPENED
CHANNELS.INDIA – ENERGY SHOWS SIGNS OF NEGATIVITY
CHANNELS.INDIA – EARLY ECONOMIC – ANTICIPATED AND HAPPENED SPECIAL
WAVES.INDIA – PREFERRED CONTINUES TO LOOK LOWER

ROMANIA

CHANNELS.BVB – MID ECONIMIC UPDATE – CONDMAG PERFORMANCE CYCLE START TO UNDERPERFORM
WAVES.ROM – BETFI PUSHES LOWER FROM KEY FIB LEVELS
CHANNELS.BVB – LATE ECONOMIC UPDATE – OLTCHIM READY TO TURN UP
CHANNELS.BVB – EARLY ECONOMIC UPDATE – TLV INDICATES EXHAUSTION
WAVES.ROM – BETFI. ABOVE 24,000 GET READY FOR 27,000
CHANNELS.BVB – MID ECONOMIC UPDATE ON INDUSTRIALS
WAVES.ROM – BETFI READY TO OUTPERFORM DOW
CHANNELS.BVB – LATE ECONOMIC UPDATE – UTILITIES ARE POSITIVE
CHANNELS.BVB – EARLY ECONOMIC UPDATE – RESISTANCES TURN INTO SUPPORTS

GLOBAL

WAVES.GLOBAL – DOW. THE CORRECTIVE STRUCTURE SEEMS OVER
WAVES.GOLD – PRICES ARE CONTINUING THE CORRECTIVE STRUCTURE UP
WAVES.OIL – HEATING OIL. FUTURES. POTENTIAL ENDING DIAGONAL
WAVES.GLOBAL – DAX. THE CORRECTIVE STRUCTURE UP SEEMS COMPLETE
WAVES.FOREX – GBPUSD. CONTINUING THE CORRECTIVE STRUCTURE DOWN TILL 1.6
WAVES.GOLD – Gold 1200 is here

NEWS

Alternative Research – Reasons for Optimism
Intergrity Research – The failure of financial analysis
Integrity Research – Outsouring as a profit driver


The Hedge Opportunity

Performance cycles indicate that Hedging could be an opportunity and not just an imperfect risk management technique.

The history and the idea

Hedging is one of the first ideas modern finance taught us. Hedging as an exercise was started for a farmer, who wanted to insulate himself from movements in agricultural commodity price. The commodity prices fluctuate and create a risk. If the actual price of agricultural commodity rises a lot between planting and harvest, the farmer stands to profit, but if the actual price drops, it could lead to a loss. A hedge allowed the farmer to sell a number of wheat futures contracts equivalent to his crop size at planting time. This way he could effectively lock in the price of wheat. Now he no longer cares whether the current price rises or falls, because he is guaranteed a price by the contract. Overtime the risk management shifted to stock prices. Change the farmer for a stock trader, who believes that the stock price of Company A is volatile and could fall. He offsets the position with the index or another sector peer, now if the market falls and the stock, the investor has locked in a price and will not lose.

The Aim

In both cases, the aim of the farmer and the stock investor is to reduce risk. None of them expects this strategy to make a profit. Hedging is a risk management strategy between two assets of a pair. In finance, a hedge is a position established in one market in an attempt to offset exposure to price fluctuations in some opposite position in another market with the goal of minimizing one’s exposure to unwanted risk. The first think they taught us in school was that a hedge is not perfect or perfect hedges are rare. A perfect hedge is the one that completely eliminates risk. Hedging with equity futures uses a technique called beta hedging. Beta is the sensitivity of a stock against the market. To calculate how much quantity to offset, beta is used. The more sensitive the stock, the larger offsetting value is needed. While the lesser sensitive the stock, the lesser the value of the offsetting leg. When two different beta stocks are used in a hedge, beta has to be tracked during the period of the hedge and necessary adjustments to be done when required. Simply putting it is a cumbersome process which at the end of it is supposed to reduce risk, imperfectly.

Hedge and Forget Approach

Investing industry is not alien to the idea of hedging and many readers may have attempted an odd hedge atleast once in their investing life. There are very few studies on hedge “inefficiency” and what are the real results of ‘hedge and forget’ cases where no beta tracking and adjustments are done over the period of the hedge. The idea of inefficient pair is linked to the ‘hedge and forget’ approach. If over the period of the hedge a pair diverges more than the risk free rate of interest, hedging is an opportunity to profit contrary to popular belief as a risk management approach. The idea of inefficient pair flies in the face of hedging. If 100% annualized difference between the long and the short leg is what we are hedging against, it really makes sense to profit from them rather than to avoid them.

Hedging and the performance cycle

Hedging as a risk limiting and not a profiting strategy is generational knowledge. Performance cycles prove that hedging or trading pairs is both a cash conserving and profiting strategy provided it is based on performance cycles, time fractals approach. We highlighted large divergences between Indian sector indices in H12009 India outlook and then in Grasim and L&T pair a few weeks back.
Cases

Today we look at a few DOW 30 pairs. This is to challenge the idea that inefficiency is limited to the Indian region. Inefficiency exists globally. We have take three DOW 30 pairs, Chevron - Exxon, JP Morgan- American Express and Microsoft and HP. These are high correlation pairs and selling one and buying the other can be based on fundamental reasons or on mean reversion strategies. The backtested results are poor in the respective strategies, but tested for performance cyclicality for a period of 18 months the strategy delivered an annualized 70% (Chevron - Exxon), 169% (JPM - AXP), 125% (MSFT - HP). Out of 17 signals on three pairs, 7 signals delivered more net gain on the pair compared to individual legs. Conventionally speaking this kind of strategy where net gain on the pair is more than individual legs should be impossible to isolate and very rare. Back testing proof is an academic exercise and implementation and trading with real money another, however isolating such high differences between tightly correlated pair without a single large loss does indicate that hedging might be an opportunity for profit rather than an academic technique for risk management. If hedging is so imperfect than arbitrage opportunities in markets are limitless just like alpha.

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WAVES.OIL - HEATING OIL. FUTURES. POTENTIAL ENDING DIAGONAL

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 Inefficient Pair

A recurring divergent performance on an equity pair could redefine alpha.

Robert Arnott’s, Research Affiliates LLC, has received a patent for an indexing methodology that selects and weights securities using fundamental measures of company size, such as dividends and sales. Fundamental indexing has gained popularity with $27 billion tracking the indices. This is 3% of the total investments tracking the S&P 500. Apart from the fact that the patent gives intellectual rights to Research Affiliates and generates license fee for the company, the revolution here is challenging the benchmark.

We talked briefly about fundamental indexing in our last two features. Putting simply Arnott and his team at Research Affiliates suggest that active investing is a futile exercise and passive investing (indexing) is better, if done using fundamental indexing. The researchers have published many research papers and a book on the subject. In their book Robert Arnott, Jason C. Hsu and John M. West detail out how passive investing outperformed money managers over the long term. Since 1983 for example both average equity mutual fund and average equity mutual fund investor underperformed the S&P500 Index fund by more than 200 basis points.

Arnott makes a case against active management by saying “active managers cannot collectively outpace the indices, relative performance is a zero-sum game, any winners must have losers on the other side of their trades, and the quest for alpha is a zero sum game”. This the authors say happens because selling the most profitable investments run contrary to human nature and buying the bleakest underperformers is against our natural instincts. Neglecting this simple exercise is a source of negative alpha, especially when risk and mean reversion of market is taken into account.

Fundamental indexing assumptions rests on historical back testing which proves that negative alpha comes from first; overreliance on equity, second; ignoring rebalancing opportunities (courage to exit winners), and third; chasing winners (capitalization weighting portfolios). The second and third aspects are similar, but it’s the aspect regarding overreliance on equity that could be relooked at.

This first aspect suggests that failure to look at other assets to diversify will create negative alpha over the long term. This means that an investor can not have a pure equity based investment strategy to generate higher returns than the benchmark. Equity has one of widest range of offer. There is equity based on commodity, green assets, renewables etc. If we consider the broad economic cycles panning out multi years of low interest rates or multi years of higher interest rates, interest rate sensitive sector will diverge from interest insensitive sectors. We at Orpheus can illustrate more examples to challenge the idea that pure equity portfolio cannot itself offer internal diversification in a pure equity portfolio to outperform the benchmark. Times are always unprecedented and to accept that equity components as an asset class fall together and rise together could be challenged if one looks at the performance between sectors. If equity components rise together and fall together, there is no business of inter equity sector performance to diverge as much as 100% on an annualized basis. We carried a half year review on Indian markets (India outlook H209) where we illustrated cases with more than 100% annualized divergent performance between sectors. BSE REAL had outperformed BSE Sensex by 173% on an annualized basis from mar lows to 24 July. As anticipated the performance cycle reversed and BSE REAL underperformed BSE Sensex by 27% annualized since the 24 July case. This leads us to question the whole idea of risk premium. Do we really understand the idea of risk premium? Or the market did not know how to measure alpha in the first place? Now we have instruments which let us trade with a leverage of -1 on spot. Did anyone say it’s hard to find negative correlation? Modern finance has a solution.

Suddenly Arnott’s historical back testing on overreliance on equity reason seems challengeable. After the sectoral performance divergence if one can highlight cases of equity pairs built from DOW 30 components or BSE30 (India) components that not only show 100% divergence across recurring periods but also deliver more than what conventional wisdom might find coincidence, the overreliance on equity clause stands open to debate. We took this case in Grasim and Larsen and Toubro, two multibillion dollar blue chips from Indian equity universe. Performance pair cycles can isolate extreme divergences between highly correlated and similar sector peers too. Starting 24 Oct 08 - 24 Mar 09, a Long Grasim – Short L&T strategy returned 72%, while from 25 Mar to 1 July 09, the Short Grasim – Long L&T strategy returned 100%. This might look like a strange coincidence that if you buy one sector peer and sell the other one, the one you sell goes down, while the one you buy goes up. A similar divergence can be showed between Chevron - Exxon, Coca Cola -Kraft, GE-Caterpillar, Pfizer and JNJ and even between equity components and index. How can one explain this divergence? How would the market explain and measure this ability to isolate such performances on a regular basis?

Arnott, the behavioral school, Mandelbrot and many other luminaries don’t accept performance cyclicality as quantifiable across time frames. The idea of alpha or relative performance being a zero sum game is an illusion. If time is fractalled, alpha is infinite and unlike popular belief human greed and fear is finite. Cyclicality is at the heart of fundamental indexing and behavioral finance. Just because majority does not find alpha and only Johan Paulson gets it, does not make passive indexing better than active investing. Active investing like anything will fail if it does not understand time cyclicality, performance cyclicality. Active management is random and unpredictable if it does not comprehend the order of time cycles, time fractals or performance cycles.

Market, asset, performance was always relative. By diversifying in and out of equity Arnott is proposing to capture relative performance between assets contradicting himself by saying when it comes to pure equity it can’t be done. One cannot call the markets as inefficient on one side and tell the alpha seeker that he lives a dream. Everything in markets is a pair. Even if look at single assets, they are paired against a local currency. Fundamental Indexing vs. Mcap investing is relative performance. Arnott says that risk is symmetrical, why not cyclical Robert? The book also mentions that nearly all investment strategies have experienced certain cyclicality with periods of good and bad performance. Who says this performance cyclicality is not quantifiable? A similar question can even be put to Robert Shiller, Yale who illustrates a comprehensive case on how worst value performers in terms of P/E top the performance list a decade later.

I don’t know why only historical back test convinced Arnott that it was best avoiding the performance game. Fundamental index has many merits above traditional indexing, but it’s the way it is pitched against anything active is academically confrontational. The very idea that chasing performance only translates to incremental profits without netting for other costs assumes that all performance  chasing strategies are already understood and there is nothing left to understand regarding performance chasing.

In conclusion, if inter equity performance divergences are quantifiable and if they can be indexed, fundamental indexing stands challenged not only on its premise of futility of active investing but  also as the best available passive investing solution. This seems like a monumental obstacle for a simple inefficient equity pair.


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