This gallery contains 6 photos.
Which of these pictures come from a random normal distribution and which come from a mixed distribution? plot(rnorm,-3,3); mix <- function(x) { rnorm(x)+rnorm(x-3) } plot(mix(x), -3,3);
GARCH stands for Generalized Autoregressive Conditional Heteroskedasticity. To translate, skedasticity refers to the volatility or wiggle of a time series. Heteroskedastic means that the wiggle itself tends to wiggle. Conditional means the wiggle of the wiggle depends on something else. … Continue reading →
μ dt + σ dWt, my #$$ The simplest model of a stock price movement is that the log of the price moves in a direction, plus some noisy drift (like adding a Gaussian W𝓽 at every timestep). Agustin Silvani … Continue reading →
No-arbitrage conditions are so often assumed in economics papers that they’ve come to seem magical. As I read more books by arbitrageurs, the obvious has become apparent: real people have the job of making financial markets equilibrate. Given that companies … Continue reading →
Should I buy this? (Source: http://www.amazon.com/gp/product/0821849743?ie=UTF8&tag=hiremebecauim-20&linkCode=as2&camp=1789&creative=9325&creativeASIN=0821849743)
“The advantage scientists bring into the [investing] game is less their mathematical and technical ability than their ability to think scientifically.”—James Simons, founder of Renaissance Technologies [Q]uants are forced to think deeply about many aspects of their strategy that are … Continue reading →
PIMCO offers Black Swan protection fund
This gallery contains 6 photos.
Which of these pictures come from a random normal distribution and which come from a mixed distribution? plot(rnorm,-3,3); mix <- function(x) { rnorm(x)+rnorm(x-3) } plot(mix(x), -3,3);