Statistical Arbitrage. Thought of the Day 123.0


In the perfect market paradigm, assets can be bought and sold instantaneously with no transaction costs. For many financial markets, such as listed stocks and futures contracts, the reality of the market comes close to this ideal – at least most of the time. The commission for most stock transactions by an institutional trader is just a few cents a share, and the bid/offer spread is between one and five cents. Also implicit in the perfect market paradigm is a level of liquidity where the act of buying or selling does not affect the price. The market is composed of participants who are so small relative to the market that they can execute their trades, extracting liquidity from the market as they demand, without moving the price.

That’s where the perfect market vision starts to break down. Not only does the demand for liquidity move prices, but it also is the primary driver of the day-by-day movement in prices – and the primary driver of crashes and price bubbles as well. The relationship between liquidity and the prices of related stocks also became the primary driver of one of the most powerful trading models in the past 20 years – statistical arbitrage.

If you spend any time at all on a trading floor, it becomes obvious that something more than information moves prices. Throughout the day, the 10-year bond trader gets orders from the derivatives desk to hedge a swap position, from the mortgage desk to hedge mortgage exposure, from insurance clients who need to sell bonds to meet liabilities, and from bond mutual funds that need to invest the proceeds of new accounts. None of these orders has anything to do with information; each one has everything to do with a need for liquidity. The resulting price changes give the market no signal concerning information; the price changes are only the result of the need for liquidity. And the party on the other side of the trade who provides this liquidity will on average make money for doing so. For the liquidity demander, time is more important than price; he is willing to make a price concession to get his need fulfilled.

Liquidity needs will be manifest in the bond traders’ own activities. If their inventory grows too large and they feel overexposed, they will aggressively hedge or liquidate a portion of the position. And they will do so in a way that respects the liquidity constraints of the market. A trader who needs to sell 2,000 bond futures to reduce exposure does not say, “The market is efficient and competitive, and my actions are not based on any information about prices, so I will just put those contracts in the market and everybody will pay the fair price for them.” If the trader dumps 2,000 contracts into the market, that offer obviously will affect the price even though the trader does not have any new information. Indeed, the trade would affect the market price even if the market knew the selling was not based on an informational edge.

So the principal reason for intraday price movement is the demand for liquidity. This view of the market – a liquidity view rather than an informational view – replaces the conventional academic perspective of the role of the market, in which the market is efficient and exists solely for conveying information. Why the change in roles? For one thing, it’s harder to get an information advantage, what with the globalization of markets and the widespread dissemination of real-time information. At the same time, the growth in the number of market participants means there are more incidents of liquidity demand. They want it, and they want it now.

Investors or traders who are uncomfortable with their level of exposure will be willing to pay up to get someone to take the position. The more uncomfortable the traders are, the more they will pay. And well they should, because someone else is getting saddled with the risk of the position, someone who most likely did not want to take on that position at the existing market price. Thus the demand for liquidity not only is the source of most price movement; it is at the root of most trading strategies. It is this liquidity-oriented, tectonic market shift that has made statistical arbitrage so powerful.

Statistical arbitrage originated in the 1980s from the hedging demand of Morgan Stanley’s equity block-trading desk, which at the time was the center of risk taking on the equity trading floor. Like other broker-dealers, Morgan Stanley continually faced the problem of how to execute large block trades efficiently without suffering a price penalty. Often, major institutions discover they can clear a large block trade only at a large discount to the posted price. The reason is simple: Other traders will not know if there is more stock to follow, and the large size will leave them uncertain about the reason for the trade. It could be that someone knows something they don’t and they will end up on the wrong side of the trade once the news hits the street. The institution can break the block into a number of smaller trades and put them into the market one at a time. Though that’s a step in the right direction, after a while it will become clear that there is persistent demand on one side of the market, and other traders, uncertain who it is and how long it will continue, will hesitate.

The solution to this problem is to execute the trade through a broker-dealer’s block-trading desk. The block-trading desk gives the institution a price for the entire trade, and then acts as an intermediary in executing the trade on the exchange floor. Because the block traders know the client, they have a pretty good idea if the trade is a stand-alone trade or the first trickle of a larger flow. For example, if the institution is a pension fund, it is likely it does not have any special information, but it simply needs to sell the stock to meet some liability or to buy stock to invest a new inflow of funds. The desk adjusts the spread it demands to execute the block accordingly. The block desk has many transactions from many clients, so it is in a good position to mask the trade within its normal business flow. And it also might have clients who would be interested in taking the other side of the transaction.

The block desk could end up having to sit on the stock because there is simply no demand and because throwing the entire position onto the floor will cause prices to run against it. Or some news could suddenly break, causing the market to move against the position held by the desk. Or, in yet a third scenario, another big position could hit the exchange floor that moves prices away from the desk’s position and completely fills existing demand. A strategy evolved at some block desks to reduce this risk by hedging the block with a position in another stock. For example, if the desk received an order to buy 100,000 shares of General Motors, it might immediately go out and buy 10,000 or 20,000 shares of Ford Motor Company against that position. If news moved the stock price prior to the GM block being acquired, Ford would also likely be similarly affected. So if GM rose, making it more expensive to fill the customer’s order, a position in Ford would also likely rise, partially offsetting this increase in cost.

This was the case at Morgan Stanley, where there were maintained a list of pairs of stocks – stocks that were closely related, especially in the short term, with other stocks – in order to have at the ready a solution for partially hedging positions. By reducing risk, the pairs trade also gave the desk more time to work out of the trade. This helped to lessen the liquidity-related movement of a stock price during a big block trade. As a result, this strategy increased the profit for the desk.

The pairs increased profits. Somehow that lightbulb didn’t go on in the world of equity trading, which was largely devoid of principal transactions and systematic risk taking. Instead, the block traders epitomized the image of cigar-chewing gamblers, playing market poker with millions of dollars of capital at a clip while working the phones from one deal to the next, riding in a cloud of trading mayhem. They were too busy to exploit the fact, or it never occurred to them, that the pairs hedging they routinely used held the secret to a revolutionary trading strategy that would dwarf their desk’s operations and make a fortune for a generation of less flamboyant, more analytical traders. Used on a different scale and applied for profit making rather than hedging, their pairwise hedges became the genesis of statistical arbitrage trading. The pairwise stock trades that form the elements of statistical arbitrage trading in the equity market are just one more flavor of spread trades. On an individual basis, they’re not very good spread trades. It is the diversification that comes from holding many pairs that makes this strategy a success. But even then, although its name suggests otherwise, statistical arbitrage is a spread trade, not a true arbitrage trade.

Asset Backed Securities. Drunken Risibility.

Asset Backed Securities (ABS) are freely traded financial instruments that represent packages of loans issued by the commercial banks. The majority are created from mortgages, but credit card debt, commercial real estate loans, student loans, and hedge fund loans are also known to have been securitized. The earliest form of ABS within the American banking system appears to stem from the creation of the Federal National Mortgage Association (Fannie Mae) in 1938 as part of amendments to the US National Housing Act, a Great Depression measure aimed at creating loan liquidity. Fannie Mae, and the other Government Sponsored Enterprises buy loans from approved mortgage sellers, typically banks, and create guaranteed financial debt instruments from them, to be sold on the credit markets. The resulting bonds, backed as they are by loan insurance, are widely used in pension funds and insurance companies, as a secure, financial instrument providing a predictable, low risk return.

The creation of a more general form of Mortgage Backed Security is credited to Bob Dall and the trading desk of Salmon brothers in 1977 by Michael Lewis (Liar’s Poker Rising Through the Wreckage on Wall Street). Lewis also describes a rapid expansion in their sale beginning in 1981 as a side effect of the United States savings and loans crisis. The concept was extended in 1987 by bankers at Drexel Burnham Lambert Inc. to corporate bonds and loans in the form of Collateralized Debt Obligations (CDOs), which eventually came to include mortgage backed securities, and in the form of CDO-Squared instruments, pools of CDO.

Analysis of the systemic effects of Asset Backed Security has concentrated chiefly on their ability to improve the quantity of loans, or loan liquidity, which has been treated as a positive feature by Greenspan. It has also been noted that securitization allowed banks to increase their return on capital by transforming their operations into a credit generating pipeline process. Hyun Song Shin has also analysed their effect on bank leverage and the stability of the larger financial system within an accounting framework. He highlights the significance of loan supply factors in causing the sub-prime crisis. Although his model appears not to completely incorporate the full implications of the process operating within the capital reserve regulated banking system, it presents an alternate, matrix based analysis of the uncontrolled debt expansion that these instruments permit.

The systemic problem introduced by asset backed securities, or any form of sale that transfers loans made by commercial banking institutions outside the regulatory framework is that they allow banks to escape the explicit reserve and regulatory capital based regulation on the total amount of loans being issued against customer deposits. This has the effect of steadily increasing the ratio of bank originated loans to money on deposit within the banking system.

The following example demonstrates the problem using two banks, A and B. For simplicity fees related to loans and ABS sales are excluded. It is assumed that the deposit accounts are Net Transaction accounts carry a 10% reserve requirement, and that both banks are ”well capitalised” and that the risk weighted multiplier for the capital reserve for these loans is also 10.

The example proceeds as a series of interactions as money flows between the two banks. The liabilities (deposits) and assets (loans) are shown, with loans being separated into bank loans, and Mortgage Backed Securities (MBS), depending on their state.

Initial Conditions: To simplify Bank B is shown as having made no loans, and has excess reserves at the central bank to maintain the balance sheet. The normal inter-bank and central bank lending mechanisms would enable the bank to compensate for temporary imbalances during the process under normal conditions. All deposit money used within the example remains on deposit at either Bank A or Bank B. On the right hand side of the table the total amount of deposits and loans for both banks is shown.


Step 1: Bank A creates a $1000 Mortgage Backed Security from the loan on its balance sheet.


Step 2: The securitized loan is sold to the depositor at Bank B. $1000 is paid to Bank A from that depositor in payment for the loan. Bank A now has no loans outstanding against its deposits, and the securitized loan has been moved outside of banking system regulation. Note that total deposits at the two banks have temporarily shrunk due to the repayment of the loan capital at A. The actual transfer of the deposits between the banks is facilitated through the reserve holdings which also function as clearing funds.


Step 3: As Bank A now has no loans against its deposits, and is within its regulatory capital ratios, it can make a new $1000 loan. The funds from this loan are deposited at Bank B. The sum of the deposits rises as a result as does the quantity of loans. Note that the transfer of the loan money from Bank A to Bank B again goes through the reserve holdings in the clearing system and restores the original balance at Bank B.


Step 4: Bank A securitizes the loan made in Step 3 repeating Step 1.


Step 5: Bank A sells the MBS to the depositor at Bank B, repeating Step 2.


Step 6: Bank A makes a new loan which is deposited at Bank B, repeating Step 3.


Step 7: Bank A securitizes the loan made in Step 6, repeating Step 4.


Since the Deposit and Loan positions of the two banks are identical in all respects in Steps (1,4), (2,5), (3,6) and (4,7) the process can continue indefinitely, resulting in expansion of the total commercial bank originated loan supply independent of central bank control.

This is a simplified version of the flows between loans, deposits, and asset backed securities that occur daily in the banking system. At no point has either bank needed recourse to central bank funds, or broken any of their statutory requirements with respect to capitalisation or reserve requirements where they apply.

The problem is the implicit assumption with reserve based banking systems that bank originated loans remain within the banking system. Allowing the sale of loans to holders outside of the regulated banking system (i.e. to entities other than regulated banks) removes these loans from that control and thus creates a systemic loophole in the regulation of the commercial bank loan supply.

The introduction of loans sales has consequently created a novel situation in those modern economies that allow them, not only in causing a significant expansion in total lending from the banking sector, but also in changing the systemic relationship between the quantity of money in the system to the quantity of bank originated debt, and thereby considerably diluting the influence the central bank can exert over the loan supply. The requirement that no individual bank should lend more than their deposits has been enforced by required reserves at the central bank since the 19th century in Europe, and the early 20th century in the USA. Serendipitously, this also created a systemic limit on the ratio of money to bank originated lending within the monetary system. While the sale of Asset Backed Securities does not allow any individual bank to exceed this ratio at any given point in time, as the process evolves the banking system itself exceeds it as loans are moved outside the constraints provided by regulatory capital or reserve regulation, thereby creating a mechanism for unconstrained growth in commercial bank originated lending.

While the asset backed security problem explains the dramatic growth in banking sector debt that has occurred over the last three decades, it does not explain the accompanying growth in the money supply. Somewhat uniquely of the many regulatory challenges that the banking system has created down the centuries, the asset backed security problem, in and of itself does not cause the banks, or the banking system to ”print money”.

The question of what exactly constitutes money in modern banking systems is a non-trivial one. As the examples above show, bank loans create money in the form of bank deposits, and bank deposits can be used directly for monetary purposes either through cheques or more usually now direct electronic transfer. For economic purposes then, bank deposits can be regarded as directly equivalent to physical money. The reality within the banking system however is somewhat more complex, in that transfers between bank deposits must be performed using deposits in the clearing mechanisms, either through the reserves at the central bank, or the bank’s own asset deposits at other banks. Nominally limits on the total quantity of central bank reserves should in turn limit the growth in bank deposits from bank lending, but it is clear from the monetary statistics that this is not the case.

Individually commercial banks are limited in the amount of money they can lend. They are limited by any reserve requirements for their deposits, by the accounting framework that surrounds the precise classification of assets and liabilities within their locale, and by the ratio of their equity or regulatory capital to their outstanding, risk weighted loans as recommended by the Basel Accords. However none of these limits is sufficient to prevent uncontrolled expansion.

Reserve requirements at the central bank can only effectively limit bank deposits if they apply to all accounts in the system, and the central bank maintains control over any mechanisms that allow individual banks to increase their reserve holdings. This appears not to be the case. Basel capital restrictions can also limit bank lending. Assets (loans) held by banks are classified by type, and have accordingly different percentage capital requirements. Regulatory capital requirements are divided into two tiers of capital with different provisions and risk categorisation applying to instruments held in them. To be adequately capitalised under the Basel accords, a bank must maintain a ratio of at least 8% between its Tier 1 and Tier 2 capital reserves, and its loans. Equity capital reserves are provided by a bank’s owners and shareholders when the bank is created, and exist to provide a buffer protecting the bank’s depositors against loan defaults.

Under Basel regulation, regulatory capital can be held in a variety of instruments, depending on Tier 1 or Tier 2 status. It appears that some of those instruments, in particular subordinated debt and hybrid debt capital instruments, can represent debt issued from within the commercial banking system.

Annex A – Basel Capital Accords, Capital Elements Tier 1

(a) Paid-up share capital/common stock

(b) Disclosed reserves

Tier 2

(a) Undisclosed reserves

(b) Asset revaluation reserves

(c) General provisions/general loan-loss reserves

(d) Hybrid (debt/equity) capital instruments

(e) Subordinated debt

Subordinated debt is defined in Annex A of the Basel treaty as:

(e) Subordinated term debt: includes conventional unsecured subordinated debt capital instruments with a minimum original fixed term to maturity of over five years and limited life redeemable preference shares. During the last five years to maturity, a cumulative discount (or amortisation) factor of 20% per year will be applied to reflect the diminishing value of these instruments as a continuing source of strength. Unlike instruments included in item (d), these instruments are not normally available to participate in the losses of a bank which continues trading. For this reason these instruments will be limited to a maximum of 50% of tier 1.

This is debt issued by the bank, in various forms, but of guaranteed long duration, and controlled repayment. In effect, it allows Banks to hold borrowed money in regulatory capital. It is subordinate to the claims of depositors in the event of Bank failure. The inclusion of subordinated debt in Tier 2 allows financial instruments created from lending to become part of the regulatory control on further lending, creating a classic feedback loop. This can also occur as a second order effect if any form of regulatory capital can be purchased with money borrowed from within the banking system

Conjuncted: Banking – The Collu(i)sion of Housing and Stock Markets


There are two main aspects we are to look at here as regards banking. The first aspect is the link between banking and houses. In most countries, lending of money is done on basis of property, especially houses. As collateral for the mortgage, often houses are used. If the value of the house increases, more money can be borrowed from the banks and more money can be injected into society. More investments are generally good for a country. It is therefore of prime importance for a country to keep the house prices high.

The way this is done, is by facilitating borrowing of money, for instance by fiscal stimulation. Most countries have a tax break on mortgages. This, while the effect for the house buyers of these tax breaks is absolutely zero. That is because the price of a house is determined on the market by supply and demand. If neither the supply nor the demand is changing, the price will be fixed by ‘what people can afford’. Imagine there are 100 houses for sale and 100 buyers. Imagine the price on the market will wind up being 100000 Rupees, with a mortgage payment (3% interest rate) being 3 thousand Rupees per year, exactly what people can afford. Now imagine that government makes a tax break for buyers stipulating that they get 50% of the mortgage payment back from the state in a way of fiscal refund. Suddenly, the buyers can afford 6 thousand Rupees per year and the price on the market of the house will rise to 200 thousand Rupees. The net effect for the buyer is zero. Yet, the price of the house has doubled, and this is a very good incentive for the economy. This is the reason why nearly all governments have tax breaks for home owners.

Yet, another way of driving the price of houses up is by reducing the supply. Socialist countries made it a strong point on their agenda that having a home is a human right. They try to build houses for everybody. And this causes the destruction of the economy. Since the supply of houses is so high that the value drops too much, the possibility of investment based on borrowing money with the house as collateral is severely reduced and a collapse of economy is unavoidable. Technically speaking, it is of extreme simplicity to build a house to everybody. Even a villa or a palace. Yet, implementing this idea will imply a recession in economy, since modern economies are based on house prices. It is better to cut off the supply (destroy houses) to help the economy.

The next item of banking is the stock holders. It is often said that the stock market is the axis-of-evil of a capitalist society. Indeed, the stock owners will get the profit of the capital, and the piling up of money will eventually be at the stock owners. However, it is not so that the stock owners are the evil people that care only about money. It is principally the managers that are the culprits. Mostly bank managers.

To give you an example. Imagine I have 2% of each of the three banks, State Bank, Best Bank and Credit Bank. Now imagine that the other 98% of the stock of each bank is placed at the other two banks. State Bank is thus 49% owner of Best Bank, and 49% owner of Credit Bank. In turn, State Bank is owned for 49% by Best Bank and for 49% by Credit Bank. The thing is that I am the full 100% owner of all three banks. As an example, I own directly 2% of State Bank. But I also own 2% of two banks that each own 49% of this bank. And I own 2% of banks that own 49% of banks that own 49% of State Bank. This series adds to 100%. I am the full 100% owner of State Bank. And the same applies to Best Bank and Credit Bank. This is easy to see, since there do not exist other stock owners of the three banks. These banks are fully mine. However, if I go to a stockholders meeting, I will be outvoted on all subjects. Especially on the subject of financial reward for the manager. If today the 10-million-Rupees salary of Arundhati Bhatti of State Bank is discussed, it will get 98% of the votes, namely those of Gautum Ambani representing Best Bank and Mukesh Adani of Credit Bank. They vote in favor, because next week is the stockholders meeting of their banks. This game only ends when Mukesh Adani will be angry with Arundhati Bhatti.

This structure, placing stock at each other’s company is a form of bypassing the stock holders

– the owners – and allow for plundering of a company.

There is a side effect which is as beneficial as the one above. Often, the general manager’s salary is based on a bonus-system; the better a bank performs, the higher the salary of the manager. This high performance can easily be bogus. Imagine the above three banks. The profit it distributed over the shareholders in the form of dividend. Imagine now that each bank makes 2 million profit on normal business operations. Each bank can easily emit 100 million profit in dividend without loss! For example, State Bank distributes 100 million: 2 million to me, 49 million to Best Bank and 49 million to Credit Bank. From these two banks it also gets 49 million Rupees each. Thus, the total flux of money is only 2 million Rupees.

Shareholders often use as a rule-of thumb a target share price of 20 times the dividend. This because that implies a 5% ROI and slightly better than putting the money at a bank (which anyway invests it in that company, gets 5%, and gives you 3%). However, the dividend can be highly misleading. 2 million profit is made, 100 million dividend is paid. Each bank uses this trick. The general managers can present beautiful data and get a fat bonus.

The only thing stopping this game is taxing. What if government decides to put 25% tax on dividend? Suddenly a bank has to pay 25 million where it made only 2 million real profit. The three banks claimed to have made 300 million profit in total, while they factually only made 6 million; the rest came from passing money around to each other. They have to pay 75 million dividend tax. How will they manage?! That is why government gives banks normally a tax break on dividend (except for small stockholders like me). Governments that like to see high profits, since it also fabricates high GDP and thus guarantees low interest rates on their state loans.

Actually, even without taxing, how will they manage to continue presenting nice data in a year where no profit is made on banking activity?

Financial Entanglement and Complexity Theory. An Adumbration on Financial Crisis.


The complex system approach in finance could be described through the concept of entanglement. The concept of entanglement bears the same features as a definition of a complex system given by a group of physicists working in a field of finance (Stanley et al,). As they defined it – in a complex system all depends upon everything. Just as in the complex system the notion of entanglement is a statement acknowledging interdependence of all the counterparties in financial markets including financial and non-financial corporations, the government and the central bank. How to identify entanglement empirically? Stanley H.E. et al formulated the process of scientific study in finance as a search for patterns. Such a search, going on under the auspices of “econophysics”, could exemplify a thorough analysis of a complex and unstructured assemblage of actual data being finalized in the discovery and experimental validation of an appropriate pattern. On the other side of a spectrum, some patterns underlying the actual processes might be discovered due to synthesizing a vast amount of historical and anecdotal information by applying appropriate reasoning and logical deliberations. The Austrian School of Economic Thought which, in its extreme form, rejects application of any formalized systems, or modeling of any kind, could be viewed as an example. A logical question follows out this comparison: Does there exist any intermediate way of searching for regular patters in finance and economics?

Importantly, patterns could be discovered by developing rather simple models of money and debt interrelationships. Debt cycles were studied extensively by many schools of economic thought (Shiller, Robert J._ Akerlof, George A – Animal Spirits: How Human Psychology Drives the Economy, and Why It Matters for Global Capitalism). The modern financial system worked by spreading risk, promoting economic efficiency and providing cheap capital. It had been formed during the years as bull markets in shares and bonds originated in the early 1990s. These markets were propelled by abundance of money, falling interest rates and new information technology. Financial markets, by combining debt and derivatives, could originate and distribute huge quantities of risky structurized products and sell them to different investors. Meanwhile, financial sector debt, only a tenth of the size of non-financial-sector debt in 1980, became half as big by the beginning of the credit crunch in 2007. As liquidity grew, banks could buy more assets, borrow more against them, and enjoy their value rose. By 2007 financial services were making 40% of America’s corporate profits while employing only 5% of its private sector workers. Thanks to cheap money, banks could have taken on more debt and, by designing complex structurized products, they were able to make their investment more profitable and risky. Securitization facilitating the emergence of the “shadow banking” system foments, simultaneously, bubbles on different segments of a global financial market.

Yet over the past decade this system, or a big part of it, began to lose touch with its ultimate purpose: to reallocate deficit resources in accordance with the social priorities. Instead of writing, managing and trading claims on future cashflows for the rest of the economy, finance became increasingly a game for fees and speculation. Due to disastrously lax regulation, investment banks did not lay aside enough capital in case something went wrong, and, as the crisis began in the middle of 2007, credit markets started to freeze up. Qualitatively, after the spectacular Lehman Brothers disaster in September 2008, laminar flows of financial activity came to an end. Banks began to suffer losses on their holdings of toxic securities and were reluctant to lend to one another that led to shortages of funding system. This only intensified in late 2007 when Nothern Rock, a British mortgage lender, experienced a bank run that started in the money markets. All of a sudden, liquidity became in a short supply, debt was unwound, and investors were forced to sell and write down the assets. For several years, up to now, the market counterparties no longer trust each other. As Walter Bagehot, an authority on bank runs, once wrote:

Every banker knows that if he has to prove that he is worth of credit, however good may be his arguments, in fact his credit is gone.

In an entangled financial system, his axiom should be stretched out to the whole market. And it means, precisely, financial meltdown or the crisis. The most fascinating feature of the post-crisis era on financial markets was the continuation of a ubiquitous liquidity expansion. To fight the market squeeze, all the major central banks have greatly expanded their balance sheets. The latter rose, roughly, from about 10 percent to 25-30 percent of GDP for the appropriate economies. For several years after the credit crunch 2007-09, central banks bought trillions of dollars of toxic and government debts thus increasing, without any precedent in modern history, money issuance. Paradoxically, this enormous credit expansion, though accelerating for several years, has been accompanied by a stagnating and depressed real economy. Yet, until now, central bankers are worried with downside risks and threats of price deflation, mainly. Otherwise, a hectic financial activity that is going on along unbounded credit expansion could be transformed by herding into autocatalytic process that, if being subject to accumulation of a new debt, might drive the entire system at a total collapse. From a financial point of view, this systemic collapse appears to be a natural result of unbounded credit expansion which is ‘supported’ with the zero real resources. Since the wealth of investors, as a whole, becomes nothing but the ‘fool’s gold’, financial process becomes a singular one, and the entire system collapses. In particular, three phases of investors’ behavior – hedge finance, speculation, and the Ponzi game, could be easily identified as a sequence of sub-cycles that unwound ultimately in the total collapse.