For someone like me who’s always been interested in practical machine learning, it was wonderfully delightful to have found Word2vec, a neural network that intakes text and outputs numerical vectors. It transforms each word in a sentence into a series of numbers that could be used to predict the probabilities of related items, on top of mathematical interpretations of similar words. This means that this method doesn’t need to know the exact definition of the words, and with enough data could better interpret relationships between words than the average human being.
Of course, that’s not all Word2vec could do. It seems that the applicability of the Word2vec (there are 2 distinct models) goes beyond predictive syntax interpretations.
If you’re interested in learning more about the Word2vec and its intricacies, check out:
- This document published by an Israelian computer science PhD (with a link to the PDF).
- A publication by the guys at GOOG on sentence and phrase compositions.
When one reaches an advanced stage of professional practice it’s easy to forget the basics because they are no longer needed or have already been done by entry analysts for you. Although it’s not crucial that one should retain everything, it’s quite useful to reacquaint oneself with the fundamentals from time to time.
Here are some of the finance books I’ve been flipping through recently:
- Finance, by David Whitehurst – this textbook contains decent summary of capital risk, structure, financing methodologies, and some derivatives. It also includes some elementary financial planning and mergers&acquisitions which doesn’t have much substance but good as a light read on industry expectations.
- Introduction to the Economics and Mathematics of Financial Markets, by Jaksa Cvitanic and Fernando Zapatero – you have to expect some hardcore materials when one of the authors’ last name sounds Eastern European, and I’m expectantly trudging through it at a slower pace than the other books. Luckily I’ve encountered a lot of its notations when I was studying for actuarial exams so it’s been making it a bit easier to read. It touches on mainly portfolio modeling techniques, asset pricing, risk mitigation, and a bit on probability theory. The book dedicates two chapters exclusively for fixed income hedging and option pricing, signifying the amount of past research done for these two fields.
- Finance, by Zvi Bodie and Robert C. Merton – aha! Written by one of the Nobel Laureates who revolutionized the options pricing world and also crashed the world markets with the same idea, this book is surprisingly light in terms of difficulty…if it were in English. I’m reading this in Chinese (yes!) to A) get a deeper understanding on modern finance theory, and B) improve my Chinese. So far I’m checking google translate every 2 to 3 pages which is not too bad considering I haven’t yet used it in any professional capacity. The book actually doesn’t go too much into theories but looks at the markets as a whole from both a quantitative and qualitative perspective. The book looks at the evolution of financial markets, then delves deeper into its various components such as accounting, investing time frames, and valuation models. It’s one of the classic reads so I’d recommend it if you are interested in the topic (and perhaps read it in a language you are more adept in).
My GRE is coming up soon and I’m debating whether I should write the GMAT instead, dilemmas!