REMINISCENCES OF A STOCK OPERATOR

by Edwin LeFevre. recommended by more than one trader, to give an accurate feel of what being a trader is really like. one trader i talked to described trading as a spiritual experience, that you have to do a gut check every day when you have that much on the line. amazon has a nice annotated copy available that gives good historical background information and explanation of some of the things that are harder to understand now. but gutenberg has the original up.

pybtex

if i ever need to mess around with beastly bst (bibtex style) files, i won't. i'll switch to pybtex, which looks like it's a lot more fun to use.

quant topics i should learn

looked through a big glossy from wilmott's certificate in quantitative finance. saw some terms that i wasn't sure i knew about. so here's a list, so i can make sure i learn about them and i don't need to take any of their classes. fokker-planck and kolmogorov the radon-nikodym derivative girsanov's theorem yield, duration, and convexity stochastic and spot-rate models affine stochastic models heath, jarrow and morton reduced-form model and the hazard rate structural default models cds pricing, market approach synthetic cdo pricing risk of default, structural and reduced form copulas brownian bridge (monte carlo?) sobol' (quasi monte carlo?) crank-nicolson black-litterman (portfolio management) levy copulas (cdo pricing) fixed income: bgm, black 76 variance gamma vg le'vy stochastic monetary policy models for interest rate derivatives gram-schmitdt process

how i became a quant

very good book to get a feel for the kind of personalities in the quant world and peeks into the various places that quants work. also small glimpses into the types of problems quants work on. neil chriss has some interesting refs for using binomial and trinomial tree to match price/volatility of all available options simultaneously for european and american options. also, some other work he did on optimization of portfolio transition/liquidation combining transaction cost/liquidity with risk of holding a position too long. probably worth a look. peter j\"{a}ckel makes some interesting comments about (not surprisingly) the monte carlo method with low-discrepancy sequences in finance, in particular about getting good results with sobol' numbers in high dimensions. andrew weisman, big shot at merrill lynch, gives some warnings about the silicon ceiling: don't appear too nerdy or academic or people will think you can't make decisions. other aspects of the culture are more like a dog pack than a meritocracy. also, information-free performance enhancements: smoothing, selling volatility, and doubling up. use cvar to help with nonsymmetric hedge fund returns, resampled optimization to deal with difficult error estimation. risk metrics are ordinal, not cardinal, quantities. chapter 23 has an interesting reference to market microstructure -- using supply and demand curves on the level of bid/ask spread and probabilities of tick movements. also, a ref to a publisher that prints classic biographicals on turn-of-the-century market operators.