Geeta Ma’am & Kathalaya find a new audience : India Inc Here’s a link to an article in the telegraph

Books on derivative pricing come in all shades and colors. Some books give a brief introduction of derivatives at a leisurely pace and then suddenly the content becomes very mathematical. There are some books that have theorems and lemmas all through. There are some books that talk about risk-neutral pricing giving very little intuition about the concept. In the gamut of books available, I think this book stands out for a couple of reasons.

Via efincareers : Quant traders working in investment banking are not happy. Squeezed by regulations that curb investment banks’ prop-trading activities and by cost-cutting that means that pre-crisis compensation packages have been consigned to history, job dissatisfaction is at an all-time low, according to industry observers. Quantitative PhDs who would have usually gravitated towards high-paying roles in the financial sector are looking for alternative career paths, while those already working in banking are seeking to move on.

Stumbled on to an interesting comment on crossvalidated which I think is a nice way to warn against using techniques such as best subset regression, forward step regression, backward step regression etc. Wanting to know the best model given some information about a large number of variables is quite understandable. Moreover, it is a situation in which people seem to find themselves regularly. In addition, many textbooks (and courses) on regression cover stepwise selection methods, which implies that they must be legitimate.

The paper by Bin Zhou, titled “High Frequency Data and Volatility in Foreign-Exchange Rates” is one of the first papers in the finance literature to address the problem of volatility estimation in the presence of market microstructure noise. Here’s my document that explains the rationale and the math behind the estimate.