Employment derivatives: Difference between revisions

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 {{a|myth|{{image|Ironmountain1|jpg|}}}}{{d|Employment derivatives|/ɪmˈplɔɪmənt dɪˈrɪvətɪvz/|n|}}Financial instruments designed to manage the risk of employment variability. First developed in the early part of this millennium by derivatives pioneer and perennial boiler of pots, {{author|Hunter Barkley}}.
 ====Genesis====
-{{Drop|W|hen midway through}} his annual rant about the meaningless of life as viewed through the lens of income, Hunter Barkley had an epiphany. He knew his own pay packet was an unhedged contingency in his life: the perpetual disappointment it rained upon his sorry existence was well beyond his practical control. He knew, too, that his experience was common to the great dreary sweep of humankind as it blearily clambered across the clanking gears of global industry.
+{{Drop|W|hen yet another}} junior customer services manager quit for a crypto startup, Hunter Barkley had an epiphany. Just as his own salary was an unhedged contingency apt to rain disappointment across his meagre aspirations, so was his experience common to the great, dreary sweep of humankind that clambered blearily across the clanking gears of industry. There was only one way to medicate, and that was to quit, and catch one of the waves of hysteria that periodically swept the market.
-That was not his revelation, but this: just as that great collected horde of wage-slaves were at the several whims of wanton Gods, so too were their bosses. Logically, they ''must'' be: they were on the other side of the same trade.
+That was not the revelation, but this: just as the great collected horde of wage slaves were at the whims of wanton Gods, ''so too were their bosses''. Logically, they ''must'' be: the firms were on the other side of the same dispiriting trade.
-Ergo, firms were long what their servants were short — only at a ''far greater scale''. Businesses — particularly ''boring'' businesses — bobbed ineptly at the mercy of hysteria’s fickle ebb and flow.
+Firms — particularly boring ones — were ''long'' what their servants were ''short'', only ''at far greater scale''. They bobbed ineptly at the mercy of hysteria’s fickle ebb and flow.
-A single servant has one unit measure of this risk; her master has, literally, ''thousands''. An employer of turgid multitudes — a good-sized bank, for example — would be locked in constant struggle with those batty tides just to prevent its pedestrian, but vital, operations personnel from being washed away.
+A single worker has but one unit measure of this risk; her master, literally, ''thousands''.
-The foe upon this reckoning was the swarm of exciting but stupid enterprises propelled at any time by that deluded current of techno-optimism. ''Why'' they believed [[this time is different|things to be different]] this time scarcely mattered — there was always some hare-brained hot take to glom onto — but it often had to do with technology.<ref> Inventions like the internet, web commerce, credit derivatives, [[distributed ledger|distributed ledgers]], [[large language model|large language models]] are typical examples.</ref>
+One who deploys a turgid multitude — a good-sized bank, for example — is locked in constant struggle against those batty tides just to prevent pedestrian, but vital, operations personnel from being washed out to sea.
-At the height of any such craze, merely stemming an outward stampede could cost a bank ''billions'' of dollars. Then, as the inflated expectations in the new sector foundered, the bank would find itself spoilt for choice of excellent available workers, but absurdly overcommitted to pay those it had managed to retain. The usual means of correcting this was tactical redundancy, but that was expensive and tended to dent the morale of even those who got to stay.
+The foe, upon this reckoning, was those exciting but stupid enterprises propelled at any time by the prevailing delusion. ''Why'' they believed [[this time is different|things to be different]] this time scarcely mattered — there was always some hare-brained hot take to glom onto — but it often had to do with technology.<ref> Inventions like the internet, web commerce, credit derivatives, [[distributed ledger|distributed ledgers]], [[large language model|large language models]] are typical examples.</ref>
-In any case, this employment cost volatility bore little relation to the bank’s own performance, none at all to its employees’. It was a simple measure of that background market euphoria.
+At the height of a given craze, merely stemming an outward stampede could cost a bank ''billions'' of dollars. Then, as the inflated expectations in the new sector foundered, the bank would be spoilt for choice among the throngs of excellent, suddenly available, workers, but unable to act on the opportunity, being overcommitted to those it had managed to retain. The usual means of correcting this was tactical redundancy, but that was expensive and dented the morale of even those who got to stay.
+In any case, this employment cost volatility bore little relation to the bank’s own performance and none at all to its employees’. It was a simple measure of that background market euphoria.
 ====An idea====
 {{drop|H|unter Barkley’s experience}} as a junior [[interest rate swap]]s trader provided a perfect analogy and gave him an idea. ''Why not hedge away this volatility?''
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 If this seemed like a bad trade for lexrifyly, over time it was not: firstly, cash was cheap, and lexrifyly didn’t care: what was money, when it came to it? Secondly, Barkley’s models demonstrated that the looney bid could invert in any number of circumstances: a market crash, hawkish monetary policy, the arbitrary dissipation of mass hysteria or the sudden onset of incipient tech winter.
-For these contingencies the ERS was a natural hedge.  While wide-scale redundancies and hiring freezes gripped the fintech sector, the boring old banking industry would box on as it always had done. At that point, a fintech that was short ''[[π]]” under an [[Employment rate swap|ERS]] would have a sensible amount of cash coming in from its bank counterparty to keep the lights on.
+For these contingencies the ERS was a natural hedge.  While wide-scale redundancies and hiring freezes gripped the fintech sector, the boring old banking industry would box on as it always had done. At that point, a fintech that was short ''[[π]]'' under an [[Employment rate swap|ERS]] would have a sensible amount of cash coming in from its bank counterparty to keep the lights on.
 ====The “PIEBOR” submission process====
 {{Drop|I|t was easy}} enough to quantify a bank’s presumptive wage bill since, once you controlled it for hysteria, it was more or less a fixed rate. But what about the ever-changing hypothetical wage bill of a startup? How to gauge that in real-time? And what was to stop a startup gaming the rate easily, by just pretending its actual preparedness to pay stupid money was lower than it really was?