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 But there are strong incentives to keep it as short as possible. Calculability for one.
-====Glass half full and multidimensionality====
+====Assembling a risk period out of snapshots====
-Here is where history — real history , not the synthetic history afforded by data modernism — makes a difference.
+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.
-When it is at rest, 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 will oscillate around its “true value” as bulls and bears cancel each other out.
+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''.
-But, because it is assembled from static snapshots which don't move and therefore carry ''no'' intrinsic risk, [[data modernism]] is not good at estimating how long a risk period should be. Each snapshot is a still life in which a “[[glass half full]]” and a “[[glass half empty]]” look alike.
+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.
-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''?  30 percent, right?
+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.
-But they are ''not'' the same.
+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.
-If my 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 it has traded in a range between 25 and 35. This history tells us this glass is massively, catastrophically over-full. With that history might think a drop of 30pc is our best case scenario
+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”.
+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.
+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 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====