Bramaan.com is an online facility for the valuation and risk management of interest rate derivatives.

Bramaan.com provides everything needed to quickly determine the net present value, the accrued interest as well as the value of a basis point for virtually any interest rate swap contract. This includes, but is not limited to, the development of custom software platforms and the implementation of processes and procedures for the daily administration, risk-management, quantitative analysis, accounting and trading of the previously mentioned financial instruments.

Further details can be found here:
http://www.bramaan.com/

Modern portfolio optimization started with Markowitz Efficient Frontier, Heuristic search and optimization is a new approach for solving complex problems that overcomes many shortcomings of traditional optimization techniques. Heuristic optimization techniques are general purpose methods that are very flexible and can be applied to many types of objective functions and constraints, especially where the objective function is non-convex and has many local minima. This is in particular the case when the risk is expressed as VaR, expected shortfall, Omega, maximum loss etc., and when the future returns of the individual assets are modelled as scenarios.

An interesting paper "A Data-Driven Optimization Heuristic for Downside Risk Minimization" demonstrates how to apply Heuristic optimization method under constraint of downside risk, code can be downloaded at http://comisef.eu/?q=resources_data_driven_opt, take a look if interested.

Consumer Credit awareness website, CreditChoices.co.uk reports that Major British lenders such as Abbey Mortgages will not be returning to the practice of issuing 100% mortgages in the near future. In fact most UK lenders are requiring as much as 20% deposits on home purchase loans. While on the surface this may seem an unfair adjustment, one must also consider that those generous loans were based upon inflated real estate values. Further the larger sum that one finances the larger the monthly payment will be. This latter statement illustrated by using the remortgage calculator found at Credit Choices. So we combine these two factors and arrive at a unique conclusion... we are better off without 100% mortgages and easy credit. Consider this, a house costing £200,000 just two years ago is selling for around £150,000 today. With a deposit of 20% or £30,000 there remains a principle due of £120,000 pounds. This results in a difference of over £500.00 monthly! Imagine the total cost over 25 years. Even factors such as mortgage protection are more costly on the larger loan. Yes many of us may not have the larger sum to place as deposit but that does not negate the data showing that 100% mortgages do no one any favour.

Simtools.xla and Formlist.xla are add-ins for Microsoft Excel (version 5 and later). Simtools adds statistical functions and procedures for doing Monte Carlo simulation and risk analysis in spreadsheets. Formlist is a simple auditing tool that adds procedures for displaying the formulas of any selected range.

Selected features include:
Inverse cumulative-probability functions;
Functions for working with correlations among random variables;
Functions for decision analysis;
Functions for analyzing discrete probability distributions;
Functions for regression analysis;
Functions for randomly generating discrete distributions;

Download Simtools.xla and Formlist.xla add-ins and instructions at http://home.uchicago.edu/~rmyerson/addins.htm

CreditMetrics is a framework for measuring credit risk of portfolios of traditional credit investments (for example, loans, commitments to lend, financial letters of credit), fixed income products, and market-driven instruments subject to counterparty default (swaps, forwards, etc.).

It is a lot more complex than RiskMetrics, and thus requires a deliberate inspection. Actually, within the CreditMetrics framework, users are confronted with a mixture of choices. For instance, CreditMetrics grants users to follow one of four different approaches to calculating correlation among several credit types-historical data, bond spreads, equity correlations or consistent constants.

Here is an Excel 7.0 spreadsheet demonstrating how to use CreditMetrics to compute credit risk of a portfolio, technical document is free to download at http://www.ma.hw.ac.uk/~mcneil/F79CR/CMTD1.pdf. Functions for calculating the CreditMetrics risk model in R are at: http://cran.r-project.org/web/packages/CreditMetrics/index.html