Template:M intro design System redundancy: Difference between revisions

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 ====Assembling a risk period out of snapshots====
-Here is the appeal of datamodernism: you can assemble the appearance of temporal continuity — the calculations for which are gargantuan — out of a series of data snapshots, the calculations for which are merely huge. Processing capacity being what it is — still limited, approaching an asymptote and increasingly energy consumptive (rather like approaching the speed of light) — there is still a virtue in economy. The shorter the window of time we must represent, the better. The listed corporate’s quarterly reporting period is one such arbitrarily short timescale. Commentators lament how it prioritises unsustainable short term profits over long term corporate health and stability — it does — while modernists, and those resigned to it, shrug their shoulders with varying degrees of regret, shake their heads and say that is just how it is.
+The object of the exercise is to have as fair a picture of the real risk of the situation with as little information processing as possible. Risks play out over a timeframe: the trick is to gauge what that is.
-For our purposes, another short period that risk managers look at is the ''liquidity period'': the longest plausible time one is obliged to hold onto a given period of risk before one can get out of it. This is the period over which one can measure — guestimate — one’s maximum potential unavoidable loss.
+Here is the appeal of [[data modernism]]: you can assemble the ''appearance'' of temporal continuity — the calculations for which are ''gargantuan'' — out of a series of data snapshots, the calculations for which are merely ''huge''.
-This differs for different assets. For equities, for the most part it is almost — not quite, and this is important — instant. It is generally treated as “a day or so”.
+Information processing capacity being what it is — still limited, approaching an asymptote and increasingly energy consumptive (rather like an object approaching the speed of light) — there is still a virtue in economy. Huge beats gargantuan. In any case, the shorter the window of time we must represent to get that fair picture of the risk situation, the better. We tend to err on the short side.
-For an investment fund it might be a day, a month, a quarter, a year or longer. For real estate it is realistically months, but in any case indeterminate.
+For example the listed corporate’s quarterly reporting period: commentators lament how it prioritises unsustainable short term profits over long term corporate health and stability — it does — while modernists, and those resigned to it, shrug their shoulders with varying degrees of regret, shake their heads and say that is just how it is.
-Generally the more liquid is your investment, the better you can control its risk.  But liquidity, like volatility, comes and goes. It is usually not there when you most need it.  So we should err on the long side when estimating liquidity periods in a time of stress.
+For our purposes, another short period that risk managers look to is the ''liquidity period'': the longest plausible time one is stuck with an investment before one can get out of it. The period of risk. This is the time frame over which one measures — guestimates — one’s maximum potential unavoidable loss.
-But there are strong incentives to keep it as short as possible. Calculability for one.
+Liquidity differs by asset class. Liquidity for equities is usually almost — not quite, and this is important — instant. Risk managers generally treat it “a day or so”.
-====Glass half full and multidimensionality====
+For an investment fund it might be a day, a month, a quarter, or a year. Private equity might be 5 years. For real estate it is realistically months, but in any case indeterminate. Probabilistically you are highly unlikely to lose the lot in a day, but over five years there is a real chance.
-Here is where history — real history , not the synthetic history afforded by data modernism — makes a difference.
-For we might say the realistic range a stock can move in in a liquidity period — its “gap risk” — is relatively stable. Say 30 percent of its market value.  This value we derive from a few technical and fundamental things: the fundamental book value of a business, the presumption that there is a sensible bid and ask, so that the stock will oscillate around its “true value”. What that is you can derived from a sufficiently long observation period (the more illiquid, the longer you need, as the bulls and the bears must iron each other out).
+So generally the more liquid the asset, the more controllable is its risk.  But liquidity, like volatility, comes and goes. It is usually not there when you most need it.  So we should err on the long side when estimating liquidity periods in a time of stress.
-But modernist techniques are not good at estimating that period. Their optimal period, remember, is infinitesimal. A still life. In a still life, a glass half full and a glass half empty look exactly alike. We apply the same metric to them: ''assuming the market value is fair, how much could I lose in the time it would realistically take me to sell''?  30 percent, right?
+But there the longer the period, the greater that change of loss. And the harder things are to calculate. We are doubly motivated to keep liquidity periods as short as as possible.
-====Liquidity period - how long is your risk period====
-====Snapshots of a glass half full are a bad proxy====
+====[[Glass half full]] and multidimensionality====
+Here is where history — ''real'' history, not the synthetic history afforded by [[data modernism]] — makes a difference.
+''On a day'', the realistic range in which a stock can move in a liquidity period — its “gap risk” — is relatively stable. Say, 30 percent of its [[market value]].  (This [[market value]] we derive from technical and fundamental readings: the business ’s book value, the presumption that there is a sensible [[bid]] and [[ask]], so that the stock price will oscillate around its “true value” as bulls and bears cancel each other out under the magical swoon of [[Adam Smith]]’s [[invisible hand]].
+But this view is assembled from static snapshots which don't move at all. Each frame carries ''no'' intrinsic risk: the ''illusion'' of movement emerges from the succession of frames. Therefore [[data modernism]] is not good at estimating how long a risk period should be. Each of its snapshots, when you zero in on it, is a still life: here, shorn of its history, a “[[glass half full]]” and a “[[glass half empty]]” look alike.
+We apply the our risk tools to them as if they were the same: ''assuming the market value is fair, how much could I lose in the time it would realistically take me to sell''?  Thirty percent, right?
+But they are ''not'' the same.
+If a stock trades at 200 today, it makes a difference that it traded at 100 yesterday, 50 the day before that, and over the last ten years traded within a range between 25 and 35. This history tells us this glass, right now, is massively, catastrophically over-full: that the milk in it is, somehow, freakishly forming an improbable spontaneous column above the glass, restrained and supported by nothing by the laws of extreme improbability, and it is liable to revert to its Brownian state at any moment with milk spilt ''everywhere''.
+With that history might think a drop of 30pc of the milk is our ''best'' case scenario.
 === It’s the long run, stupid===