Polish language version of the bubble hunter

I just created Polish language version of the bubble hunter link here. “Łowca Baniek” blog will be rather focus on the Eastern Europe, bubble hunter will remain my main conceptual notepad

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Reflexivity and Eastern Europe (or can Ukraine be a Lehman Brothers of Eastern Europe?)

I was expecting this article to come sooner or later but when I read it this morning in FT I cannot say that I’m happy because for the time being I’m still living in Eastern Europe.

Not so long ago the consensus about Eastern Europe economies was that they are FUNDAMENTALY sound and those economies should decouple from global slowdown. At that time I wrote that this is not sustainable process and that the decoupling will be followed by the recouping to the rest of the world . Now after the first wave of debt/currency crises went through the Eastern Europe the consensus story has been changed somehow into more doom and gloom story. But now some say that Eastern Europe is almost FUNDAMENTALY cheep (i.e. here)
I think this way of thinking is FUNDAMENTALY wrong as markets are not efficient pricing machines Some/Most market participants believe that the markets tend toward equilibrium but equilibrium is just only first approximation how the market works.



My critique is not new. Milton Friedman said that idea of fully efficient market is inherently contradictory. In order to remove market inefficiencies we must have traders who are motivated to exploit them. But if the market is perfectly efficient there is no possibility to make excess profits. While efficiency might be true at first order, it cannot be true at second order: There must be on-going violations of efficiency that are sufficiency large to keep traders motivated. The misconception of efficient market is even obvious now than ever before, because it was the intervention of the authorities that prevented financial market from the total meltdown, not the market themselves. Indeed non-equilibrium nature of the markets is especially visible in the sharp price movements occurring at the booms and (especially) crashes which are accompanied with massive price jumps. Question is how in first place the market gets to “critical” point. The Eastern Europe decoupling story was based on the fact that economic growth in recent years was strongly based on domestic demand. Domestic demand was continuously stimulated by credit growth and budget deficits. At the beginning of the process the credit growth was limited and its impact on the price assets was limited. However lending usually stimulates economy. A strong economy tends to enhance the asset values, increases country creditworthiness and also often tigers local currency appreciation. As the asset prices grows the banks are more willing to lend because (i.e.) the value of the collaterals is growing the more credit is available the stronger economy grows. This positive feedback process continues until a point is reached where credit cannot grow fast enough to stimulate economy. By that time the asset value strongly depends on the credit growth and as the credit growth fails to accelerate further the asset values starts to decline. At the “critical” point the process reverses. Declining prices of assets/collaterals decreases the banks willingness to lend which has depressing impact on economy. Since creditworthiness/collateral has been pretty fully utilized at that point, a decline may precipitate the liquidation of loans which in turn may make the decline more precipitous.

This is very, very simplified vision of the process which leads to asset bubbles. However one of the features of the process is that Economic FUNDAMENTALS ARE NOT EXOGENOUS to the process. Unfortunately is not my idea but George Soros reflexivity which he defines as a “two-way feedback loop, between the participants’ views and the actual state of affairs. People base their decisions not on the actual situation that confronts them, but on their perception or interpretation of the situation. Their decisions make an impact on the situation and changes in the situation are liable to change their perceptions”
(Unfortunately Soros is not good at math but it’s easy to show that his reflexivity idea is a system of differential equations. More formal model definition and solution to the systems of “Reflexivity” differential equations you can find here in excellent V.I. Yukalov D.Sornete paper).

But let’s come back to the main subject and let’s try to find out what may come next. Financial linkages/Interlinkages in Eastern Europe are very tight. With the increase in the foreign ownership of the banking system in Eastern Europe the degree of financial interlinkages among Western Europe and Eastern Europe has also grown substantially i.e. Austria’s lending exposure to Eastern European countries top 80% of GDP ( IMF Paper with the statistics you can find here). As the economy slows the processes which lift asset prices is in full reverse as investors starts to withdraw the money. The liquidation of the loans takes time: the faster it has to be accomplished, the grater the effect on the value of the collateral . In the bust the reflective interaction of the loans between collateral becomes compressed within very short time of period the consequences can be catastrophic (reflexivity works both ways)

For several years Ukraine economy was flying on cheep credit and high steel prices now both engines has been lost which is not only the case of Ukraine but also for several countries in the region (i.e. Romania, Bulgaria). And now we are in self reinforcing process of loans liquidation which reinforces the drop of asset prices. Because of the size of Ukraine and close financial interlinkages acrros the Europe the comparison of Ukraine potential default to Lehman Brothers bankruptcy and its implications for the whole financial system makes sense for me

End of Part ONE

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Money has often been a cause of the delusion of multitude

“…Money has often been a cause of the delusion of multitude. Sovereign nations have all at once become desperate gamblers and risk almost their existence upon the turn of the piece of paper…””…Men it has been well said thinks in heards it will be seen that they go mad in herds while they only recover their senses slowly and one by one..”
The quotation comes from the book “Memoirs of Extraordinary Popular Delusions and the Madness of Crowds” written by Charles MacKay in 1852. (The complete version of the book you can download here). In volume one of the book author describes the Mississippi scheme, the South-Sea Bubble, the tulipomania among others market bubbles and crashes from the past. After reading all that stories I had strange feeling that those stories aren’t quite different from those which I’m reading nowadays in the newspapers. A striking feature of the crisis (then and now) is that the situation evolved rapidly and appeared to be driven by emotion. Now word “FEAR” appears in almost every news or article covering present market/economic events. Over/(lack of)confidence, fear, gloom, doom, crowding aren’t concepts closely related to good old-fashioned rationality but are related to the out of equilibrium processes . In contrast to that modern economics is based on equilibrium models, which assume the rationality of the economic agents and put emphasis on the importance of expectations. Don’t get me wrong. I’m not calling to get rid of the equilibrium models from economics (because they are useful) but I think that the current crisis shows the limitations of the mainstream paradigm.
The source of the crises was originally precipitated by the levels of the credit that are difficult to justify as rational. I’m not talking here just about UK,US homeowners who got a large amounts of loans with no money down. I’m also talking about whole nations (i.e. Iceland, Hungary, Ukraine, South and Eastern European Countries, Baltic countries) which were flown with almost free credit assuming that those countries will grow only faster and faster and will be able to payback its debt in the future.
Is the crisis a simple consequence of madness of the crowds, completely orthogonal to the equilibrium model? I don’t think so but it’s obvious to me that lenders were way too optimistic in their assumptions and maturation of this systemic instability led the system to the critical zone and to an inevitable crash
This blog is about non-equilibrium processes and especially about power laws in economics. Power law distributions imply that rare events (like October crash) are occurring with a finite non-negligible probability in the complex systems. Is therefore meaningful to ask the following question: How is the dynamics of a complex system affected when system undergoes to extreme event? In other words in the following posts I will focus on the market dynamics after the large crises trying to answer the question how long will take the transition phase to bull market.

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This is bottom . SP will hit 1300 mark in December

In the post published on this blog earlier I was predicted that in October the market will test July lows. It is always difficult to precise estimate the “critical“ point when the market will turn but I feel that it may happen within next few days or even today. Here are my arguments:



1) Blogosphere is full of doom and gloom stories. Number of posts in blogs with some including the word ”crises” jump to 350

2) IMF is turning to more gloomy tone. Just 3 Months ago IMF revised up the GDP forecast for US and EUROPE but now in the latest WEO they suggest that US economy will tank

3) Politicians around the globe are not only calling for actions but they already advanced in legislative process (US). Even in Europe politicians woke up and will meet on EU mini summit this weekend. (politicians are always well behind the curve)

4) All my colleagues are bearish, Now most of CNBC ‘s guests predict recession

My general point is being that I feel like only optimist isle surrounded by ocean of pessimism and gloom. It sounds like classic contrarian argument which may sounds odd in the eve of US earnings season. But financial markets are far beyond supply and demand curves. This is very misleading picture of the market. It implies that the investors base their decisions on the fundamentals, whereas the goal of the market participants is to make money. Only if the market prices reflected the fundamentals accurately would it make sense for them to be guided by those fundamentals and in that case nobody could make money than anybody else – this is an absurd conclusion!

Long time ago John Keynes formulate his beauty contest thought. He was arguing that the stock prices are not only determined by “fundamental” factors but mostly how the crowd of investors will behave in the future. In Keynes’view, the optimal strategy is not to pick those faces the player thinks the prettiest, but those the other players are likely to think the average opinion will be, or those the other players will think the others will think the average opinion will be, or even further along this iterative loop. Beyond a certain point this self-validating feedback loops become unsustainable and market crash (this is valid for both boom and bust cycles) (This type of cooperative behavior may be bay be model well by Ising model )
We were in the negative feedback loop since the beginning of September and we are approaching the “critical” turning point. It obviously doesn’t mean that reality will change. Still the deep recession is ahead of us and but that’s different story. The end year rally is just ahead of us.

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Worst case scenario is most likely to be avoided

This is the worst financial crises since the great depression and now is clear that its not only about Wall Street but Main Street is hit badly as well. Again George Soros and Nouriel Rubini were right. But is not end of the world.

Today I was listening to Mohamed El-Erian co Head of Pimco (link here). I must admit I really like his suggestions to help global financial system. In his opinion today’s coordinated global central banks effort to liquidate the world financial system was step in right direction. But it still looks like all taken measures are not sufficient to prevent the worst case scenario. Mohamed is calling for emergency package which would include coordinated interest rate cut across the globe and capital injection. I think that the package which he called “4 bazookas fired at once” is type of the solution which is urgently needed now.

Although the current drop in stock indexes may be felt as disaster but it is not. Let’s put current situation into perspective. The chart shows the cumulative loss from the last maximum to the next minimum of the S&P500 index over the period of last 40 years. This statistics is called Drawdown. Drawdown is defined as a persistent decrease in the price over consecutive days and its distribution measures how the successive descents influence each other.

At normal times assumption about independence between the successive returns holds very well. However the large drops are not independent. At “special” times they may be burst of local dependence of the returns. In other words large loses can generate even bigger loses. It may be explained by psychological crowding effect or by risk management rules (stop loses triggering) etc. In last 40 years biggest drawdown took 33% of its value within 4 days.

So far FED, US Treasury and most recently ECB, BOJ, BOE actions prevents worst case scenario to materialize. But authorities must stay ahead of the curve and additional measures are needed (4 bazookas). I convinced that all needed measures will be implemented and floor for the global indexes will be put around current levels.

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In October S&P 500 index is likely to retest recent lows

This post is an update to the S&P500 prediction posted on this blog earlier in July. The prediction comes true as well as oil bubble burst forecast issued here. However the S&P index did not plunge as low as 1150 points but the critical time prediction was quite accurate. Also it has to be remembered that critical time obtained from LPPL models is only the most probable point of trend reversal. Financial markets are complex and open systems and its valuation oscillations are driven both by endogenous end exogenous factors. In July In my assessment S&P500 price dynamics was strongly affected by SEC naked short-selling ban on the stocks of major financial institution. But take me correct I don’t think that SEC decision was wrong on contrary I think it was absolutely correct and needed as it break negative feedback loop.



Here I want to make an update to my earlier prediction of S&P500 based on LPPL model. An LPPL model applies concepts of criticality from statistical physics however I will not focus here on the theory complex systems (nice and easy to read easy on complex system and LPPL models you can find here .)

A complex system is a system composed of interconnected parts that as a whole exhibit one or more properties (behavior among the possible properties) not obvious from the properties of the individual parts. Financial markets and economy as a whole is a complex system buildup with a large number of interconnected elements.

The characterization and understanding of complex systems is a difficult task, since they cannot be split into simpler subsystems without tampering the dynamical properties.
One approach in studying such systems is the recording of long time series of several selected variables (observables), which reflect the state of the system in a dimensionally reduced representation

Data series generated by complex systems exhibit fluctuations on a wide range of time scales and/or broad distributions of the values. Some systems are characterized by periodic or nearly periodic behavior. In these cases, the dynamics can be characterized by scaling laws. Such dynamics are usually denoted as fractal or multifractal, depending on the question if they are characterized by one scaling exponent or by a multitude of scaling exponents.

If one finds that a complex system is characterized by fractal dynamics with particular scaling exponents, this finding will help in obtaining predictions of the future behavior of the system.
In 2000-2003 anti-bubble/bear phase The S&P500 index shows clear oscillations with 5 sharp local minima and the self similar structure and the scaling exponent was easy to find.

The local minima are dated as follows: m5=12-Oct-2000; m4=20-Dec-2000; m3=04-APR-2001; m2=21-SEP-2001; m1=23-July-2002.

Log-Periodicity means that that the ratios of the distances between the consecutive repeatable minima should be constant equal to the preferable scaling ratio λ which is a signature of Discrete Invariance Scale(DSI)

(Mn-Mn+1)/(Mn+1-Mn+2)=(Mn+1-Mn+2)/(Mn+2-Mn+3)=λ
Using the previously determined minima M1,…,M5 we get

(m1-m2)/(m2-m3)=λ1=1.79
(m2-m3)/(m3-m4)=λ2=1.62
(m3-m4)/(m4-m5)=λ3=1.52

It shows that all scaling ratios are comparable and if it would be known ex-ante it would help to find next local minima in the bearish trend giving significant upper hand. More detailed discussion about 2000-2003 S&P500 index anti-bubble period you can find in D.Sornete works (link here 1 2 3)

The main disadvantage of the Shrank’s transform presented above it that it needs quite a long time series to determine the preferable scaling factor of the system. Although in the current bearish pattern of the S&P 500 index also shows strong oscillations but the time series is much shorter and its much harder to determine the scaling parameters. So instead of Shrank’s transform I implemented the Lomb spectral analysis. I done the computation in Matlab using procedure written by Brett Sholeson. After visual analysis of the S&P500 index I chose for critical time tc=10-10-2007, then the data was detrended.



The Lomb periodogram (chart 2) exhibit an extremely significant peak close to log-frequency f=w/2π=2.6 with the amplitude larger than 60. Second peak is close to 2w log frequency which suggest the presence of harmonic anagular. The visual structure of the current S&P500 time series with double minima pattern also suggest suggest the presence of a rather strong harmonic at the angular logfrequency.

The data fit quite well to the formula. Numbers on horizontal are counting the distance in trading days from the critical time tc=10-10-2007
Below I put the chart with the forecast for S&P 500 index from the LPPL model. The forecast suggest that the next minima S&P500 index will reach in October/November and the index should rally into year 2009 when the trend should turnaround toward new minma.

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RBS issues global stock alert – The S&P 500 to slump by more than 300 points by September

Today RBS issued a global credit and stock alert as inflation paralyses the major central banks. In the interview for UK daily telegraph Bob Janjuah the bank’s credit strategist said “ A very nasty period is soon be upon us”

I haven’t seen the RBS report but judging from the interview I suspect that the main argument for issuing the alert is stagflation story.
The RBS prediction is going along my own expectations. However main argument for nasty drop of the global indexes is the interplay between investors ( a negative feedback loop). In coming days I plan to publish here several articles explaining how the negative feedback loop is now present in stock markets and how it is likely to trigger selloff within several next week s

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