4 ms·
"Information can cause one of three price reactions: up, down, or flat." Then there is no cause. Prices change somewhat randomly whether there is some inform
by gbog 14y ago
"Information can cause one of three price reactions: up, down, or flat."
Then there is no cause. Prices change somewhat randomly whether there is some information or not. The only correct predictive model is something like " there is 80pc chance that the price will be between -10 and 30 of its current value". Anything else is reading in a crystal ball.
I didn't invent any of these, read Thinking Fast and Slow if you have any doubts.
- JumpCrisscross 14y agoBy price reaction I meant deviation from the path without the information. I was qualitatively representing the ensemble, i.e. parametric space, of possible price movements on (-∞, ∞) by mapping them to up <- (-∞,0), down <- (0,∞), and flat <- 0. Let Px(t) be the price at time t. Px(t+δ) given Px(t), i.e. P[Px(t+δ)|Px(t)] is D = Gaussian(Px[t], vol) in an efficient market. We know relevant information is going to be added to the market at t+δ, but we do not precisely know its content until t+δ. The market can, however, make an educated guess. This information is a kernel with a central tendency* and an entropy, i.e. second moment, H. The price at t+δ is now D' = Gaussian(Px[t], vol + Hω), where ω is the weight of the information. Since H and ω are both positive we can see that D' is platykurtic with regards to D. D'-D, the impact of knowing that salient information will hit the market at a certain time, looks like a short butterfly P&L. Thanks for the book recommendation; I enjoy Kahneman's work. *If ω were very low or H very high, e.g. a unitary distributed kernel would have infinite Shannon's entropy, you are correct in assuming that it would have no impact on D', i.e. D'-D would be zero.