That’s fair. I’d been thinking about the general class of “people who need money now for an emergency,” many of whom find it difficult to secure credit, rather than the class of “people who have a lot of wealth in non-liquid forms who need money now for an emergency,” who presumably don’t.
I was thinking more in terms of “there’s an expenses function e(t), and a cash availability function s(t), and a cost function f( e(t) - s(t) ), and this cost function is zero at e(t)-s(t) = 0, but is a lot softer at e(t) > s(t) than people fear due to credit cards and lines of credit, and can be quite costly at s(t) >> e(t)”
Except that e(t) and s(t) really should be probability distributions, but that just hurts my head to try and explain coherently. This is literally my fourth attempt at writing up a better description of the reasoning behind my posts.
If e(t) is slightly bigger than s(t), you borrow money from credit cards or other lines of credit at poor interest rates, then pay off those debts in the however many days it takes to get liquid cash from other sources (say, stocks). If e(t) is much bigger than s(t), then you negotiate a payment plan or suffer the consequences of not being able to pay expenses right now.
And of course there’s the time costs in optimizing this sort of thing. A percentage point for a thousand dollars over a year comes out to ten dollars, which I roughly approximate as an hour of time. Which means that you probably ought to spend your optimization power on minimizing the amount of work you need to put into your finances. Which, in turn, means automatic bill payment, and regular transfers of excess cash from your checking account into your preferred investment account.
That’s fair. I’d been thinking about the general class of “people who need money now for an emergency,” many of whom find it difficult to secure credit, rather than the class of “people who have a lot of wealth in non-liquid forms who need money now for an emergency,” who presumably don’t.
I was thinking more in terms of “there’s an expenses function e(t), and a cash availability function s(t), and a cost function f( e(t) - s(t) ), and this cost function is zero at e(t)-s(t) = 0, but is a lot softer at e(t) > s(t) than people fear due to credit cards and lines of credit, and can be quite costly at s(t) >> e(t)”
Except that e(t) and s(t) really should be probability distributions, but that just hurts my head to try and explain coherently. This is literally my fourth attempt at writing up a better description of the reasoning behind my posts.
If e(t) is slightly bigger than s(t), you borrow money from credit cards or other lines of credit at poor interest rates, then pay off those debts in the however many days it takes to get liquid cash from other sources (say, stocks). If e(t) is much bigger than s(t), then you negotiate a payment plan or suffer the consequences of not being able to pay expenses right now.
And of course there’s the time costs in optimizing this sort of thing. A percentage point for a thousand dollars over a year comes out to ten dollars, which I roughly approximate as an hour of time. Which means that you probably ought to spend your optimization power on minimizing the amount of work you need to put into your finances. Which, in turn, means automatic bill payment, and regular transfers of excess cash from your checking account into your preferred investment account.