LearnLog

 Dec 2008

Listening to the podcast on SIAM on Dark matter. Inspiring and invigorating. Here are a few terms I understood at a very high level. Need to do a lot more reading.

• Dark Matter
• Dark Energy
• Velocity dispersion as a means of detecting satellites of a Galaxy
• Red Shift (heard it before)
• Ionization after big bang before the formation of helium and hydrogen
• How stars are formed (ultraviolet heats up the gases to make them collapse into a star)

It is fascinating to listen to the
Oct 2007

While reading the offerings of Majestic, came across the term Computational Finance today. Never heard it before. So I Googled it and as expected, found a wikipedia entry.

Computational finance or financial engineering is a cross-disciplinary field which relies on mathematical finance, numerical methods and computer simulations to make trading, hedging and investment decisions, as well as facilitating the risk management of those decisions. Utilizing various methods, practitioners of computational finance aim to precisely determine the financial risk that certain financial instruments create.

Generally, individuals who fill positions in computational finance are known as “quants”, referring to the quantitative skills necessary to perform the job. Specifically, knowledge of the C++ programming language, as well as of the mathematical subfields of: stochastic calculus, multivariate calculus, linear algebra, differential equations , probability theory and statistical inference are often entry level requisites for such a position.

Is this a bit antiquated? Why is C++ such an essential part? Why not Java or Python or Ruby or any of the 10 popular languages? Is it the availability of class libraries? Performance?

Anyway, did not know about stochastic calculus, multivariate calculus either.