Another excel / VBA source for volatility calculation, including option based volatility such as implied volatility of Black Scholes model, volatility surface construction, Heston parameters estimation from option prices, etc; and a list of time series volatility calculation, for example, ARCH, ARIMA, EGARCH, EWMA, GARCH, GJR...

One thing you should be aware is some of the files involve a call to NAG library, one of the major benefits of the NAG Library is its inherent flexibility, it can be used by programmers developing in traditional languages, or by users of modern software packages and programming environments, like Microsoft Excel. Both of my former company and my current university have NAG library installed, so download & read more at your choice at http://php.portals.mbs.ac.uk/SerHuangPoon/Teaching/DataandProgrammes/tabid/973/Default.aspx and http://www.nag.co.uk/numeric/nagandexcel.asp

Visual Basic in finance application has been introduced many times in this blog, one especially useful book was reviewed in an old post Option Pricing Models and Volatility Using Excel-VBA. Here is another VBA finance site perhaps of your interest. As the site describes:


at the moment the number of VBA codes is only a few, some useful files include:
Swaps Tool:  Comprehensive tool to manage equity swap resets and set up new deal templates
Dividend Points: Retrieves Index Weights and Dividends Data from Bloomberg and Calculates Index Dividend Points
CA Tool: Dividends and Corporate Actions notification tool
Volatility: Building Volatilty Surface and using the SABR model for calibration
Trading Tool: Simple tool to set buy/sell targets and track prices and dividends

Visit the site if you are looking for VBA finance codes.

Credit Default Swap (CDS) has existed since the early 1990s, and the market increased tremendously starting in 2003, the outstanding amount was $62.2 trillion by the end of 2007.

You can download the ISDA CDS Standard Model source code at ISDA. Should you like to dig further, here is a list of CDS paper I personally feel useful to understand the pricing methodology:

Reduced form
Longstaff, Mithal et al. (2005) assume premium is paid continuously, set the values of the premium leg and protection leg equal to each other.  
Pan and Singleton (2008) apply a reduced form model to Mexico, Turkey, and Korea sovereign CDS, show that a single-factor model for default spread following a lognormal process captures most of the variation in the term structures of spreads.
Nashikkar, Subrahmanyam et al. (2011) assume default process be constant and calculate CDS par yield in reduced-form framework.
Ren-Raw Chen (2008) assume risk-free rates and default rates are correlated and solve the CDS pricing model explicitly used reduced-form.
Hai Lin (2011) value corporate bonds and CDS simultaneously using reduced form model, for CDS part, the authors assume there are both default and non-default part, and solve the model by assuming the two parts are independent.
Jankowitsch, Pullirsch et al. (2008) attribute the difference between corporate bond yields and CDS premium to one covenant of CDS: cheapest-to-delivery option, and solve the covenant by relating it to recovery rate. Their empirical analysis doesn’t support liquidity premium.
Carr and Wu (2010) propose a dynamically consistent framework that allows joint valuation and estimation of stock options and credit default swaps written on the same reference company. By assuming the stock price follows a jump-diffusion process with stochastic volatility, the instantaneous default rate and variance rate follow a bivariate continuous process, the authors solve the reduced form model analytically.
Brigo and Alfonsi (2005) introduce two-dimensional correlated square-root diffusion (SSRD) model for interest-rate and default process, then price CDS with Monte Carlo simulation.
Zhang (2008) use a three-factor model, namely interest rates, firm-specific distress variable, and hazard rate. The author is able to link hazard rate with interest rates by assuming the former is a function of the latter, then he solves the model analytically and applies to Argentina sovereign CDS.

The reverse mortgage calculator offers you a brilliant opportunity to generate the loan estimates and will help you to get an idea on the amount of money that you will get at the end of reverse mortgage. However, you should realize that these calculators are just a tool to give you a brief idea on what you can expect to receive when you enter into a loan agreement.

If you want to use a reverse mortgage calculator then you need to get your hand on some information first. Some of these are really simple, and ask for some basic information like date of birth, area code, estimated worth of your house etc.

Often we have to face the problem of solving a stochastic differential equation, and even more often there is no analytic solution, in another words, numerical monte carlo simulation is applied. I don't need to write much about this topic as here is a fantastic paper on it already: An Algorithmic Introduction to Numerical Simulation of Stochastic Differential Equations, in which the author builds around 10 MATLAB programs, and the topics covered include stochastic integration, the Euler–Maruyama method, Milstein’s method, strong and weak convergence, linear stability, and the stochastic chain rule.

M files:
Euler–Maruyama method: http://personal.strath.ac.uk/d.j.higham/em.m

Milstein’s method: http://personal.strath.ac.uk/d.j.higham/milstrong.m

more can be downloaded at here.