Welcome to the HCL blog! We work on enabling Financial applications over the novel architecture of NPS.

The NPS architecture holds solid promise for financial applications! Databases are increasinly becoming bottlenecks for scalaibility. This is particularly true of financial domain where the data-volumes are increasing by leaps and bounds. Portfolio management and Risk management software have to analyze this massive volume of data to make ""intelligent" decisions.

Let me list some of the interesting financial applications here. There are obviously more and more. Here is a small list:

• Calculating Implied Volatilities of the underlying in the current market

• Consider an investment bank selling options and futures. If they price their options wrongly, market onlookers would just simply make risk-free profits out of it. So, the banks need to examine the trades happening in all the exchanges to arrive at the implied volatilities of the underlying security before pricing a derivative based on that security. This involves analyzing live and historical exchange data and this is where the NPS holds a lot of promise.

• Calculating historic volatities of various assets by examining historical data

• Historic data is useful only when it comes to recent history. The stock price modeling fundamentals assume that old stock prices and the path with which a stock price has been attained is immaterial. The Hull book(bible of finance) recommends a period of 21-days for inferring any meaning out of historical data.

• Historical volatilities can enable a user to see how volatile an underlying security is! Highly volatile assets tend to change prices (upwards or downwards) by huge amount and are quite un-predictable.

• Calculating historic volatilites for comparing and contrasting companies involves analyzing and sorting historical data and is a huge work! On the NPS, we were able to arrive at historical volatility chart with a click of a button on your Excel spreadsheet! As simple as that! Above all, one can leverage the MPP architecture without forgoing code-readability -- which is a very important factor when it comes to software maintenance.

• Pricing stock options

• Binomial, Trinomial, Monte-carlo simulations are common ways of pricing stock options! All these can be computed over the top of the NPS appliance itself and viewed in a spreadsheet

• Managing portfolios

• Consider a portfolio of stock options and stocks. This one has to remain delta-neutral and this requires the market be quite closely watched - Sells and Buys have to be triggered automatically on examining stock price movements

At HCL, we are developing these algorithms over NPS and are seeing impressive performance!

If you happen to come to NUC 08, you are most welcome to visit our stall to get a glimpse of what we are upto and how it can be useful to you.

Watch out this space. We will be posting more here.