EconoFiction

Derivatives are Speculative Capital

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3 Okt , 2019  

In recent decades, an ever-increasing proportion of the profits of private banks has been generated by financial activities far beyond mere borrowing and lending of money. Commercial banks generate their profits through the endogenous creation of credit and through the trading of foreign exchange and, in particular, securities and derivatives. In order to hedge or speculate, private banks themselves create complex securities – derivatives such as credit default swaps, options and futures on interest rates and currencies. Derivatives appear in banks’ balance sheets either positively as an asset or negatively as a liability. If the value of a derivative falls into the negative range, it is a liability, while the derivative as an asset is always in the positive range of the market value, i.e. it is currently worth more than it was paid for. Nevertheless, derivatives are not based on a pure accounting process, rather they are to be understood as speculative capital and at the same time as a power technology.
If the market value of a classic economic object (goods such as clothing, food, computers, etc.) is directly affected by a loan, and this in turn can be massively influenced by the trade in a derivative, then one can really maintain the previous hierarchical order of the classes of three economic objects (goods, credit, derivative), whereby one still speaks above all of synthetic securities as purely derived securities, of derivatives? How is the hierarchy between economic objects really to be understood? The classical barter transaction requires an immediate transfer of the physical object/goods for money (value and value only change the form; value, which ideally exists as a price in the goods, passes in the form of money to the seller of the goods (MEW25): 363)), and this has to be regarded as an invariant, symmetrical requirement on the economic property of the classical commodity-money relationship, while in credit this invariant requirement on immediate payment of the object is omitted – money now has the potential to grow within the specific time horizon of a promise relationship; with the derivative, the invariant requirements to which the credit is still subject dissolve further, with the result that the economic property of the object finally assumes the freedom to fold, twist and bend or devour. The derivatives thus have a more powerful economic and topological reality than the other economic objects or events, also with regard to their registers of reality, which can be described with Deleuze as potentiality, topicality and virtuality. The virtual causality of the derivatives should also be understood as determinant, performative and material, i.e. the effects of the derivatives push for real material consequences. What must be added at this point is that capitalist companies are exposed to a whole range of risks, be it that they cannot find buyers for their products on the market, be it that the goods they need for their own production processes are too expensive, or be it certain risks associated with the development of interest rates and exchange rates, whereby derivatives inevitably come into play as forms of hedging (and not just speculation). Tony Norfield stresses above all the function of derivatives as hedging instruments.1 (Norfield 2011: 110)
In this text, we refer to “assets” (commonly understood as assets) as specific forms of credit and fictitious and speculative capital. We assume a progressive differentiation of three different classes of financial assets: a) the generic asset, b) the synthetic asset, and c) the securitized synthetic asset. The category “generic asset” includes forms of credit (loans, mortgages, etc.), fictitious capital (shares and bonds) and vanilla derivatives (forwards, options, futures), while the category of synthetic asset includes complex derivatives (CDS, TRS, etc.) (cf. Lozano 2013) Synthetic derivatives are generally to be understood as a form of speculative money capital in latency – latency or liquidity in so far as derivatives still have to be realized in money. Securitised synthetic assets such as CDOs may contain securities, loans and credit defaults swaps (CDS). Investors can be divided into those who go long by benefiting from incoming payments from debtors and those who go short and benefit from credit defaults. Thus, these types of CDOs do not simply involve investors, but rather a actor and counter atcor, so that the profits of the one is the loss of the other. However, the parties do not have to hold a claim via ownership of the underlying asset to hedge against the volatility of the CDO, as is the case with classical insurance, but this itself becomes the source of revenue and profits.
In complete contrast to investment in industrial production processes, which must necessarily have a positive result for the company, speculation with derivatives may also generate profits from economic events such as falling profit rates, insolvencies or shortages if the conditions formulated in the derivative contracts are met in the future. Short selling is a good example of this: you borrow a security in anticipation of falling prices, then sell it and buy it back at a later point in time when the price of the security has fallen, so that the price difference leads to a profit. Speculation can now be seen as an important operational category, i.e. a method that focuses on the future generation of profits. Even the management of balance sheets, whereby balance sheets are to be understood as a social, power-related production process with which numerical artefacts are written down, can today be understood as part of artificial speculation and is therefore indispensably linked to the production of future profits. Speculation, arbitrage and hedging as characteristics of risk and portfolio management (a portfolio of stocks is efficient precisely when it generates the highest profit with the least risk; the aim is to distribute profits that more than merely compensate for losses) are today directly linked to the organisation of capitalist production and circulation.
In principle, three forms and strategies of trading in fictitious and speculative capital can be distinguished today: Arbitrage, hedging and speculation. (Cf. Malik 2014: 336f.)
Arbitrage aims to realize a risk-free profit by means of a simultaneous execution of certain financial transactions on at least two or even more markets. You buy a stock on a stock exchange – if it has different prices on two or more stock exchanges – at a certain price and then sell it at once again on another stock exchange at a higher price (instantaneously) and thus achieve a risk-free profit. Arbitrage is a means by which the volatile financial field in which the assets are traded remains liquid, but as soon as the arbitrage opportunity arises, it is immediately closed by those very players who have benefited from it.
In hedging, derivatives are used to minimize the risk resulting from future changes in economic market variables. The position taken with the conclusion of a derivative contract is intended to compensate for the risk inherent in the change in the price of the underlying or a liability. If the derivative contract is redeemed at maturity, its holder makes a gain (or loss) on it that offsets (or does not off-set) the loss (or gain) arising from the movement in the price of the underlying or liability. Today, non-financial companies tend to hedge much more than financial companies, which are particularly active in the field of speculation.
Speculation means that derivative contracts are bought or sold in order to generate profits from the future operationalisation of the difference between the fluctuating prices of the underlying and the prices of the derivative, i.e. to monetize the difference between the strike price and the spot price when the derivative contract matures. However, this is only half the truth, because speculation (and hedging) operationalizes above all the price movement of the derivatives themselves, with the changes in the derivative prices leading to a change in the speculator’s profit-loss balance sheets (and not in the underlying assets). Delta hedging, which is used to calculate the price of an option, means that profits can be made with an option, no matter in which direction the underlying moves, as long as there is sufficient volatility, measured as implied volatility, i.e. the inversion of the Black-Scholes formula. Speculators must carry out complex risk management when trading derivatives. In general, speculators are given various opportunities to work with a higher leverage than a traditional investor who is involved in industrial production processes. The speculator, as will be seen in more detail, is primarily concerned with the prices of the derivatives themselves and thus speculation indicates that the derivatives markets2 are by no means to be understood as markets in which the purchase or sale of the underlyings is a priority, which means that they are not regarded as markets for such investments with which companies make profits by managing the difference between the turnover or selling price and the production costs of the goods. The volume of speculative trading today exceeds that of hedging many times over.3 Financial companies in particular are constantly mixing the three different strategies, i.e. speculation with hedging and arbitrage.
Usually the generic asset (forwards, futures, options) is defined as a financial contract whose value is derived from something else called the “underlying”. (Esposito 2010: 152-153) This underlying can be the price of the financial instruments or derivatives themselves or the prices of shares, bonds, indices, interest rates, commodity prices, etc. can take over the function of the underlying, but external factors such as the yields of wheat harvests or bananas can also take over the function of the underlying. In no case is the derivative identical to the underlying, because the owner of a futures contract who wishes to buy one tonne of copper at a given time is not the owner of the copper, but becomes so only when the contract is executed at a given time. Until that time, the derivative contract can be sold and profits or losses can be realised with it, depending on how the copper price develops. Thus, the writing of speculative derivative contracts seems to be entirely focused on the capitalisation of the spreads of strike price (fixed in the contract) and spot price (market price of the underlying) at maturity of the contract. We will see that this is not true either.
A distinction must be made between derivatives which – as in the OCT markets – are negotiated directly between two partners and therefore do not require a standardised form (forward contracts) and derivatives which are integrated into complex promise chains (options, futures), which are in the circulation cycles of the financial markets and are burdened with the inflexibility of standardisation, and can only be typified and classified by very specific actors who have the economic power to do so.4 This necessarily requires an energetic and liquid market that makes these circulations possible, a market that is always also a practical, performative construct and a socially produced fiction that is believed by the market participants and must be constantly recreated (liquidity in the face of uncertainty), and of course is at the same time an object of theory.5
The simplest form of derivative is a forward contract, an over-the-counter forward transaction consisting of the agreement to buy or sell an asset/object/goods (underlying) at a fixed price and at a future date. (Cf. Malik 2014: 340f./ Hull 2011: Chapter 2) If you undertake to buy the underlying at a certain price when the forward contract matures, you take the long position, the sale (delivery of the underlying object) includes the short position. If, at the fixed time, the current market price (spot price) of the underlying is higher than the contractually agreed delivery price (strike price), the long position makes a profit and the short position has to accept a loss. The delivery prices are regulated in off-exchange clearing houses and certain costs are incurred at maturity.
Let us take a simple example and assume that K is the delivery price of the underlying commodity at maturity T, S is the market price on the delivery day and q is the quantity of the commodity that is delivered, where we are in time t. The person who wants to buy takes the long position and the person who wants to sell takes the short position. The former agrees to pay K times q on a certain day, and later receives something that has the value S times q (unknown until t1). This is a swap of cash flows. For the long position (buy), the forward contract has the value F for the whole period t before maturity. If Ft is the current forward price in t, then the value can be written as follows (Sotiropoulos/Milios/Lapatsioras 2013a: 77):
Formula
r is the interest rate. And t is the remaining time to maturity. If the price F in the time t is higher than the price K originally stipulated in the contract, then the long position, namely the discounted difference F-K. Ultimately, the “value” of the forward contract can be positive or negative, it indicates the gains and losses of both parties and includes the capitalization of promises and risks and the corresponding future income. John Milios understands the forward contract as a commodity sui generis (capital as capital).
The future contract contains a contractual agreement concluded on the stock exchanges between two parties to buy or sell a certain quantity of an item/goods/indexes at a fixed future date and at a price fixed in the contract that differs from both the current and the future market price of the corresponding item. (ibid.: 343f.) If the market price of the object rises, the buyer makes a profit, and vice versa he loses. In contrast to forward contracts, the success of futures contracts does not depend exclusively on the agreements of the respective parties to the contract, but also on the possible future exchange of contracts on the stock exchanges, with the result that the prices of the futures contracts can vary according to the respective market trends and forces. They rise when more traders take a long position than a short position. (Cf. Hull 2011: Chapter 2.3)
Options are derivative contracts that contain the right to buy (call) or sell (put) underlyings up to a certain point in time (maturity) and at a fixed price without having to execute the option. The price of a call option, with which one can buy a commodity or security at a certain future price, but does not have to, varies from zero to an infinite number. The use of options is mainly for hedging purposes. (Malik 2014: 346f.) In contrast to forward and future contracts, there are costs involved in acquiring the option. There are two basic types of options: The right to buy something at a fixed price in the future is called a call option (call), the right to sell is called a put option (put). When you sell, you take the short position, and when you buy, you take the long position. (Cf. Hull: Chapter1) The relationship between strike price and maturity is called convexity. Options create a relationship between the future and the present so that future cash flows can have a calculated value in the present by comparing different risk profiles.

(The Black-Scholes equation, a performative mathematical method and a model for calculating the price of an option, became famous because to some extent it can be used to deduce the gains and losses of options through recursive adaptations or dynamic hedging strategies, or, to put it another way, to neutralize directional risks in the financial markets using the performance of the Black-Scholes equation. The two inventors of the formula assume that unforeseeable events will occur in the future with a similar contingent spread as events have occurred in the past, so that risks prove to be predictable to a certain extent insofar as they can be derived from past developments. And the rational investors – this too is one of the prerequisites that Black/Scholes make – behave like particles in a liquid (Brownian motion), whose exact location cannot be predicted, but the dispersion of their motion and its realization can. Thus creditors and debtors can apparently decide without risk on a risk structure preferred by them. Under these conditions, the cash flows of different assets (options and shares) are compared, i.e. current and future volatility are equated.
In the Black-Scholes formula, the price of an option is calculated using a differential equation containing five variables: Strike price, maturity of the option, risk-free interest rate and the price and volatility of the underlying asset. The only unknown factor in the equation is the volatility of the underlying, which can at least be estimated by historical data or by calculating the implied volatility.
Risk neutrality is a non-mathematical parameter designed to guarantee a derivatives market that is sui generis free and immune to any socio-economic differences and events that might allow derivatives to be priced differently. This excludes arbitrage, i.e. the same derivative cannot have a different price in Frankfurt than in London and on this basis it is further assumed that the model undoubtedly allows a derivative to be perfectly hedged. A security can be

have no more than a single price (law of one price). The law thus seems to be confirmed by the axiom that arbitrage is impossible in a sufficient market, and that if arbitrage opportunities arise due to market anomalies, the spread between two different prices is instantaneously closed, even though the possibility of arbitrage is always present in financial markets in real terms.
In the name of pure mathematics, an idealized perfect homogeneous space must be assumed, which prevents arbitrage and understands it as a purely external matter, in which it cannot do more than what it often does, namely to inflect or bend prices. The Standard Model rules out the possibility that an option not only gives the holder the opportunity to do something at a certain point in the future, but also opens up options for him. Today, however, it is not only a question of optimising returns, but also of increasing the number of options. Holding an option gives the holder the right (not the obligation) to do something at a certain time or not to do it at all – so it gives him a choice, or in other words, the option gives him optionality. This, which is often neglected in financial theory, always includes social demands that exist in social relationships and networks and are related to future cash flows.
The Black-Scholes equation implies that pay-off is specified at maturity and then runs backwards in time to determine present values. It is not considered that deflationary or inflationary processes can take place, and it is assumed that counterparties can never be insolvent. If one takes into account factors and changes in liquidity, changes in the supply/demand ratio, disturbances in the risk-free interest rate, arbitrage opportunities, etc., the equation quickly becomes too complex and hardly applicable in practice. The equation rather installs a clean financial mathematics of rational agents6 , i.e. it presupposes the totality of the market as a mathematical representation and as a natural institution, thus out of sight the market as part of the construction of a socio-economic form that allows capital itself to circulate today through the financialization of life, and mathematization reinforces this assumption even more if the agents simultaneously presuppose the market as an imaginary totality – the market as a continuous set of transactions that maintain liquidity.
With implicit volatility, the risk profile of the underlying and the option is compared, which is called dynamic replication (the comparison of a known instrument with an unknown one). There are already options with market prices on the market. If the market moves in a random walk, then the prices of the assets also move in the same progressions, i.e. the volatility is stochastic and non-constant, and therefore the volatility parameter requires an operator that is deterministic and chaotic at the same time. Any operator trying to create future volatility therefore needs differential equations that work with non-linear functions. The Black-Scholes equation is therefore inverted and the market price of the option is introduced to calculate the implied volatility, i.e. to determine the future price movements of the option. This practice leads to different volatilities and not – as Black-Scholes assumes – to constant volatilities (unforeseen events in the future do not occur with the same dispersion as comparable events in the past when volatilities fluctuate). With the assumptions Black-Scholes make, there could be no market where volatility and uncertainty play a significant role. And yet the model possessed and possesses an extraordinarily high performance, inasmuch as the widespread use of the model generated the price movements constructed with it in part in the first place and did not simply reproduce them; the data at the beginning of the use of the model did not correspond to it.)
The call option speculates on the future development of the price of the underlying (the rise in the share price) and is redeemed if the price agreed in the contract is below the market price at maturity (European option) or before that (American option). If the desired event occurs, the holder of the option has the right to buy at a fixed price and if he does not exercise the option due to certain other circumstances, the right expires and the small option fee is lost for him. Put options, on the other hand, will be exercised by the holder if the price agreed in the contract is higher than the market price. (ibid.) There are two types of operators, the writer and the reader of an option, the former writing optionality and selling it to the latter for a fee.
In general, it is important here that one can rely not only on the price movements of shares, securities, currencies, etc., but also on the speculations affecting them, i.e. on market fluctuations or volatilities of a higher order.7 Most options, especially exotic options, are to be classified as non-conventional, non-linear derivatives containing contingent claims (contracts between two persons, whereby the payoff is based on uncertain future events). This implies so-called non-linear delta hedging, where the delta measures the variable rate between the price of an option and the price of an underlying asset, a rate that is constant in the standard model and remains invariant. Delta hedging consists of an operator determining the delta of the portfolio “correctly” so that the price movements of the option and the price movements of the correlative reference position are close to equalization; the infinitesimal approximation of the two price movements implies that the delta of the portfolio is not strictly zero at any given point in time, but tends at least towards zero. The delta is constantly in a process of becoming zero. And this delta neutrality is to be achieved by acceleration, i.e. the movement is to go ever faster towards zero. In order to hedge dynamically with such second-order derivatives, they must be continuously recalibrated, i.e. a financial method must be found to force an endless deterritorialization of the option towards zero, which can only be asymptotic; continuous replication is always dynamic.
Swaps are highly complex futures contracts that are traded on the OTC markets. They agree certain conditions for the exchange of future cash flows and cash flows (cash capital flows, income or yield flows) and fix the respective dates on which future payments are to be made and the mode by which these payments are calculated. (Cf. Malik 2014: 351/Hull 2011: Chapter 5) With the help of swap contracts, which emerged in the early 1980s, comparative cost advantages can be generated: For example, one exchanges uncertain cash flows with variable interest rates for sums of money with fixed interest rates, thus trading the risk of price erosion against the risk that a loan will not be repaid. Take a simple example to illustrate this: a company that borrows money at fixed rates in the long run would like to take the opportunity to borrow funds at a variable rate or for a shorter period than is normally possible in fixed-rate markets. A second company, mainly active in the variable-rate markets, is looking in the longer term for funds or loans at an acceptable rate in the fixed-rate market. Now, the swapping of future interest amounts, resulting from fixed-rate market loans and variable-rate market loans, prefers under certain circumstances both companies, i.e. both companies pay lower interest rates in the future than they would have paid without the swapping deal. Finally, the profit is split between the two parties. Interest rate swaps had a market value of $12.6 trillion in 2009. (Sahr 2017: Kindle Edition: 4979)
Swap contracts do not necessarily have to meet the contractual requirements that are common in conventional insurance markets, where, for example, the seller of an insurance policy must hold the corresponding sum of money available in the event of default. The consequence of the exemption from the restrictions found in the classical insurance markets is that there are even more intensive links, dependencies and entanglements between the financial companies (and their sizes; balance sheet total) that provide credit and insurance, which in turn leads to lower prices for credit swap contracts and thus a reduction in net costs and the associated expansion of credit volumes.
Since 2000, the financial markets have seen the massive spread of a new type of synthetic security called credit default swaps (CDSs). These are contracts under which a policyholder insures himself with an insurer against the default of a reference debtor, for which the insurer pays a fee from the insurer in the agreed period. The parties thereby negotiate the risk of default by the debtor or a similar credit event. The more likely it is that the reference debtor will become insolvent, the higher the insurance fee will be, a fee that is considered by the insurers to be a return.8
Now, if the CDS is resold, the holder of a CDS can succeed in making a profit only by managing time: The holder concludes a policyholder contract for the period t0 to t2 and signs a second insurer contract for the period t1 to t2 at time t1. If the CDS has a government bond as reference, he speculates that the creditworthiness of State X will deteriorate over time because (for him as insurer) the fees will increase, with the result that he may earn higher insurance fees in the period t1 to t2 than he himself has to pay in fees (as policyholder) in the period t0 to t2. (Cf. Mühlmann 2013: 32) In the period t0-t2, the probability of a credit default or insolvency increases, whereby t2 can be regarded as a segment that can be arbitrarily shifted in time, at the end of which there may also be insolvency. The CDS transactions can be used to manipulate the interest rates that states have to pay for their bonds, i.e. these will rise if the prices for credit insurance are driven up. It is assumed that the probability of the occurrence of a credit event (e.g. insolvencies of companies or states) increases over time, so that consequently the fees for insurance transactions rise the closer one gets to the catastrophe point that radically breaks off the previous economic dynamics, which means that from the onset of the catastrophe, the kairos, one has to deal with qualitatively new time courses and structures. (ibid.: 38) The speculator’s risk here is that if he acts as both policyholder and insurer, he will also have to reckon with losses.
This type of insurance economy includes an asymmetric time machine, insofar as the irreversible time of the risk (the insolvency of a debtor implies irreversibility – if it occurs, then an insurer who has negotiated a CDS with the creditor of a reference debtor must do so), the creditor) is mixed with the reversible period of the risk in which the risk appears to be cancelled, since an insurance company as a first-degree insurer that has sold a CDS to a bank can take out a second insurance policy as a policyholder. If the first-degree insurer has to pay the full amount of the loan to the bank (because of the insolvency of one of its debtors), the same amount will be reimbursed by a second-degree insurer, making the first-degree insurer’s insolvency a reversible time event. An investor can also insure himself against the default of a securitised loan (CDO) by purchasing a CDS, the price of which is higher the more likely a CD0 default is expected, which can occur at any point in the securitisation chain.
It is easy to see that viral effects can occur with this type of chaining of the CDSs, because the actors act simultaneously as insurers and insured parties, i.e. within a combinatorics of inverse links. (Mühlmann 2013: 34f.) Mühlmann writes: “In the viral chain, all money is only borrowed from a lender who in turn has borrowed it, who insure his own lender, while the one who lent him the money also borrowed the money and insure himself when he lent him the money”. (ibid.: 186) The increase in chance up to the catastrophe usually implies an increase in yields, but entropies or losses cannot ever be ruled out. After all, in the end only those actors generate profits who leave the business shortly before the real catastrophe (e.g. the insolvency of a company or state). (ibid.: 116) So CDSs are always traded with a specific time structure and its contingency.
The extraordinary growth of the markets for CDSs, which practically did not even exist in the 1990s, is shown by the fact that in 2007 they contained contracts with a volume of 45.5 trillion dollars (New York Times, Arcane market is next to face big credit test, 17.2.2008). According to Aaron Sahr, 2007 was a year in which the CDS chains hedged loan sums of 58.2 trillion dollars. (Sahr 2017: Kindle Edition: 4991) The reason for this enormous growth was the same as for the CDOs: it enabled the

The aim is to achieve high profitability for private banks and other financial institutions, albeit in a different way from CDOs. When banks sell CDSs, they receive fees, even more so, the purchase of CDSs allows them to save money, since the bonds on the balance sheet, which have a weak credit rating, require significant capital reserves to compensate for the risk that a debtor can no longer pay. If the default risk is now reduced by a CDS contract, then the capital reserves can also be reduced and new money funds released in order to expand one’s own business. And today even the CDS risks are hedged and thus apparently reduced.
This mechanism accelerated the growth of mortgage issuance by US banks in the years prior to the 2008 financial crisis, so that the volume of CDO and CDS transactions continued to grow. The permanently underrated risks (in the context of mortgage origination) also helped this mechanism to grow further, with low central bank interest rates supporting this process. This included the growing use of subprime lending, with private banks increasingly lacking borrowers from 2006 onwards who had the potential to repay their loans. In this context, CDSs can certainly be seen as important catalysts for the growth of financial capital. Their function is, on the one hand, to hedge financial risks and, on the other hand, to adjust banks’ lending to customers in order to increase profitability again at a time when low interest rates are damaging businesses and yields derived from certain investments.

Securitisation
Synthetic derivatives (CDO, CDS etc.) have been added to the classic derivatives (options, futures etc.) since the 1990s. Securitisation of CDOs involves the aggregation of a heterogeneous set of credit/securities consisting of different cash flows and risks into a single security, a single homogeneous pool, which then functions as a single cash flow and a single risk and can be traded on the financial markets.9 This homogeneous pool in turn can be divided into different classes of risks and cash flows, whereby both components change their quality with each division. The newly created classes are called tranches, which can be rearranged in different ways in order to create a multitude of specified risks and the associated cash flows. With each newly added tranche within a CDO, new dependencies on other tranches emerge, which can set in motion further series of additions, gradations and separations; new differentiation processes unfold and, at the same time, dotations that record, register and distribute the respective losses and gains of the various tranches. When the tranches are used to re-differentiate the risks, which is in principle endless, new levels of differentiation constantly emerge, with which series of attachment points and detachment points are constituted. (Lozano 2013) An attachment point is a point that indicates that risks belong to a particular tranche, while reaching a detachment point releases new risks that from now on affect other tranches belonging to a higher level in the ranking of risks.10
Factors such as divisibility, maturity, risk and cash flow are important characteristics of these assets, or to be more precise, the asset is these characteristics. The fungible and intensive virtualization potential of the asset is primary, the possible change of its characteristics, which can lead to an at least theoretically endless, an ad infinitum creation, which puts the risk and the future cash flows into a synchronous relationship as possible, without, however, ever being able to switch off the moments of desynchronization. The simulation market in which synthetic securities such as CDS or CDO are traded today is neither fixed nor flat, neither uniform nor homogeneous, but has to be regarded as non-euclidean or topological and is only moderately limited by the various reference classes to which the asset refers. In this context, the CDO derivatives are to be understood as dynamically composed unorderings, which hold various economic characteristics such as maturity, yield, price, risk, cash flow, etc., which can be plastically unrelated to each other.i. e. they are created and can suddenly be destroyed again, they circulate ad infinitum and non-linear – swarms, vortices and fractals of differential repetition, thousands of plateaus of concentration, compression and dissolution.
The distribution of the securitized CDOs was organized at the beginning of the 2000s with the help of the principle of “originate and distribute”. (Cf. Marazzi 2011: 36) This form of chaining began on the financial markets in the USA, from where it spread globally, and it proceeded as follows: Since 2001, loans/real estate loans issued have increasingly disappeared from the balance sheets of large credit institutions, securitised according to special rules: Private banks or special purpose vehicles set up by them issued securitised promissory notes purchased by rich investors, servicing the paper-related payments from the original loans (repayments and interest payments). These securities were carved from the outset, i.e. they represented staggered rights to incoming payments, whereby the top tranche with the lowest risk (it consists of the fact that many debtors of the special-purpose company must already default on this paper) was first serviced, if just enough means of payment flowed in from the loans held so far. (Sahr 2017: Kindle Edition: 5028)
The securitisation chain thus begins with the issue of asset-backed securities (here in the form of mortgage-backed securities). These debt securities were initially passed on or sold by private banks to off-balance-sheet special purpose vehicles, often located in offshore centres, who in turn sold them to investors. The principle of pooling and tranching – the bundling and tranching of a security or portfolio, which we have already mentioned above – can then be repeated several times in order to produce complex CDOs from simple bonds or to construct new tranches of securities in new special-purpose vehicles.11
The CDOs, which consisted of mortgage-backed loans and other financial products, were also resold by the special purpose vehicles of the banks on the secondary markets to investment funds, which in turn sold new loan portfolios or new securities tranches to the investment funds. CDOs with different risk gradations were generated in order to then pass them on to potent investors in packages; the combination of safe loans with unsecured loans was part of a credit structuring in which statistically independent risks were calculated, which should always lead to a normal distribution of risks as known from the Gaussian curve, where events are most likely to spread around an average. CDOs therefore contain hierarchically structured claims to payments, from tranches assumed to be safe to the uncertain tranches at the end, with even these risky securities being bought up again and packaged into new payment promises before the 2008 financial crisis. If a company buys the high-risk securities threatened by default in sufficient quantities, the risks can be bundled neutrally and financed by further tranched securities, thus creating third-degree CDOs, etc. The risks can also be bundled and financed by other tranched securities. The patterns of the payment flows of certain debt pools are copied and traded with the help of swaps, whereby the risks are multiplied and only apparently reduced – and profits are of course also realised with the sale of a loan. The astonishing thing was that most CDOs were considered to be less risky than their source material, and were rated with certain ratings depending on the tranches. For investors, the CD0s seemed to be a lucrative investment, an attractive security and an efficient way of dealing with money, while for creditors the credit risk seemed to be reduced. (Sahr 2017: Kindle-Edition: 5093) The reasons for this development were again and again the fact of risk diversification (various payment promises in a portfolio) and the fact that the value of the securities issued did not reach the value of the portfolio of assets. Furthermore, the securities and their credit tranches could be insured by CDS with special companies called “financial guarantors” according to their business models.
The CDOs were often sold at a price lower than the nominal price in order to charge for a certain number of insolvencies from the outset, and at the same time the number of possible insolvencies was to be distributed among as many subjects as possible, as if it were possible to dilute the risks to the point of irrelevance. Not only could the

The high fees generated by these sales also made it possible to better secure the CDO business of the banks themselves. However, the packaging of CDOs into CDOs of CDOs and into CDOs of third order did not eliminate the alinearity and dysynchrony of the structuring of risks, but instead led to an implosion of CDOs and at the same time intensified the dependency of financial institutions on each other by successively increasing mutual credit claims.
We are currently facing a new wave of CLOs (collateralised loan obligations) on the financial markets. The CLO is a fixed or floating rate asset, a type of securitisation covered by collateralised loans. The banks produce a high volume of differentiated CLOs with loans, which can contain between 100 and 200 corporate loans from various sectors. As trustee, a credit institution manages the process of processing corporate loans (collateral, payment, documentation) and prepares a monthly report for investors. The credit portfolios of the CLOs are divided into different classes (A to subordinated (equity) and evaluated by at least one rating agency and traded as listed assets.
Like the CDOs, a CLO bundles high-value loans and high-risk low-quality loans into attractive packages with a high credit rating. In May 2017 there were two deals with a price of $1bn and experts estimate that in 2017 CLOs will be traded with a price of $75bn. Although many loans used as collateral in these deals have junk status, the CLOs are rated up to 50% triple A. Now that credit defaults are expected to increase in waves, the mathematical models would also have to evaluate correlation risks, i.e. the chance of defaults occurring simultaneously. However, for most models used to assess CLOs, it is assumed that the correlations are low. If, however, many defaults occur at the same time, the expected triple-A investments will disappear into nowhere. CLOs are merely CDOs in a new guise.

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