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| {{freeessay|isda|tail events|}}{{d|Tail event||n|}} | | {{freeessay|isda|tail events|{{image|Tail event|jpg|}}}} |
| {{L1}}'''Statistics''': Of a range of possible independent events, one whose frequency is three or more [[Normal distribution|standard deviation]]s from the mean. An event with a low [[probability]]. <li>
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| '''Work life''': An unwanted outcome you didn’t expect, to which you weren’t paying attention, and, therefore, for which you don’t think you should be blamed.
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| </Ol>
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| Now here is the thing. When we calculate probabilities — when we roll dice — we are in situations of ''known risk''. We don’t know exactly how this particular event will turn out, but we know the range of possible outcomes and the calculated probability of each. No matter how deft our technique, no matter how surprising or extraordinary their trajectory, the dice must come to rest showing one of six equally-sized faces uppermost. No two throws are the same. The trajectory is chaotic, but all this intractable uncertainty is wiped out when the dice come to rest. None of it matters. All that matters is the average. By that we can set our watches.
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| Every fair die has the same characteristics. It is not just that on some some dice the probability is more like ⅐, on others now like ⅕ but, on average, dice work out at all about ⅙. Every die must, within tolerance, behave exactly the same way. Therefore probabilities are a valid means of predicting behaviour.
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| ====Dice rolling as a nomological machine====
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| When we roll dice to ''determine'' an outcome we do not build a statistical model that predicts a ⅙ probability: we build the dice to yield the that outcome. A die is part of what [[Nancy Cartwright]] would call a “[[nomological machine]]”:<ref>This is a ''terrible'', typically ''academic'' label. No doubt it is etymologically accurate, but it is forbidding to a lay reader. Academics , like lawyers, tend to do this while they train and occupy the junior rungs as a self-credentialising device. By the time they sit on the higher rungs, they don’t know any different way of writing.Cartwright is a brilliant thinker, but her writing is dense and hyper-academic. </ref> a carefully designed, constrained, hermetically-sealed simple system, designed to generate a specific theoretical outcome. If over time our dice don’t yield a ⅙ outcome we don't throw out the statistical model: we throw out the ''dice''.
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| The “map” and territory ” are transposed: the dice are the map, the theoretical ⅙ probability is the territory. The map is, as far as engineering permits, ''identical'' to the territory. Now each of us has a difference engine in our pocket, we don’t even need physical dice: we could generate the same outcome, with a random number generating app.
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| The machined dice and the flat, constrained surface con which they fall are not meant to represent our actual reality. They are aspiring to the desired statistical model. They seek to emulate an idealised platonic form. A “loaded” die is a ''flawed'' nomological machine. So is a surface like sand which allows a die to rest on its corner. If you get bad results with a nomological machine you don't chuck out the theory: you chuck out the equipment.
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| Likewise, if, inside your nomological machine there is a mischievous imp who catches and places the die as it sees fit, the conditions for your probabilistic calculation do not prevail. There must be no interfering causal agency.
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| “Nomological machines” are highly constrained, artificial environments. If all their conditions are not satisfied, we can expect the world to behave differently without validating the machine. This is how, as [[Nancy Cartwright]] put it “the laws of physics lie”.
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| In any case, these are the circumstances in which the rules of probability prevail. Should the universe “misbehave” then the conditions required for the nomological machine cannot be present.
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| Boy did I get sidetracked.
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| Normal distributions standard deviations, and confident probabilities require a complete nomological machine where all potential events are known, are independent, and there is no intervening agency that can upset the observed behaviour of the system. If you have all that all risks can be calculated and probabilities assigned.
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| Markets, in the abstract, look just like such a machine. There is a bounded environment, a finite trading day and a limited number of market participants and financial instruments which one can buy or sell. In the modern days of computerised trading everything is very clean, tidy observable, unitary and discrete.
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| ====Derivatives trading====
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| In the context of trading derivatives, things that (a) you didn't reasonably expect and that . (b) bugger up your contract.
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| =====Credit defaults=====
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| A swap being a private, bilateral affair, the most obvious category of tail events is “things which mean your counterparty cannot, or will not, or has not, performed its end of the deal”.
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| Straight out refusal to — repudiation — is rare, at least without the cloak of some kind of dispute as to whether the party was under such an obligation in the first place.
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| Inability is the main player here: generally captured by insolvency, and correlative defaults under other agreements.
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| Much of financial services being a play on [[leverage]] — the name of the game being to earn more, with other people’s money, than it costs you to borrow it — many market participants flirt with various formulations of [[insolvency]] as a basic business model, so there tend to be some pushback on the parameters of these correlative failures and “ostensible inabilities” to perform. Much of a [[negotiator]]’s life is spent haggling about them.
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| Where refusal or inability to perform cannot be proven, actual failure to pay or deliver ends all arguments. If you ''actually'' haven’t performed, it no longer matters ''why''.
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| There is therefore a sort of hierarchy of these events. Actual default is the safest, and most common, default trigger. Bankruptcy is the next — though there is more looseness around some of its limbs, an administrator actually being appointed, or a petition actually being filmed is clean, public and unlikely to prompt many arguments. Default Under Specified Transaction — that transaction being one to which you are directly a party,
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| The remaining events are sketchy and unpopular, depending as they do on private information you most likely won't have about thresholds you can't easily calculate. We may argue till we are hoarse about Cross Default. We will not invoke it.
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| =====Externalities=====
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| There are a category of events which make it impossible even for a solvent counterparty to perform. Change in law, for example — it is not beyond possibility that certain kinds of swaps might be restricted or outlawed altogether<ref>Not long ago the European Union proposed restricting the carbon market to “end users” to discourage financial speculation, for example. This would have rendered certain forward contracts in {{euaprov|Allowances}} involving delivery to non-users illegal.</ref> or Tax events that make the transaction uneconomic as originally envisaged.
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| Secondary events of this kind — things that limit a dealer’s ability to hedge, or materially increase its costs of doing so, tend not to be Termination Events partly this reflects a fact not often stated, but nonetheless true: there is a price at which the parties will agree to terminate any swap. Just because a party doesn't have an economic option to terminate the trade doesn't mean it can't terminate the trade. It always has an “at market” option. In liquid markets during times of fair weather this is a source of great comfort; in illiquid markets and at times of stress, less so. A dealer will say, “I will always show you a price. You just might not mind the price, is all.”
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| Customers have less incentive to break trades if it means realising
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| {{sa}}
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| *[[The map and the territory]]
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