To rapidly ramp up coverage, a new analyst at a leading sell-side investment bank wanted to build six complete financial models of large mining companies in just two weeks. The models involved historical data, forecasted financials and a complete valuation. She wanted a team of two offshore associates who were experts in accounting and valuation concepts, and who also could help her draft company initiation reports after building the financial models. Irevna, drawing from its pool of talent, was able to quickly put together a team with the appropriate skill sets—a finance-major MBA with an undergraduate degree in mining from Berkeley, and a rank-holding CPA with expertise in accounting and valuation concepts. This team hit the ground running, and helped her accomplish her targets within the demanding timeframe.

The associates spent the first month in New York, working shoulder-to-shoulder with the client during the 'firedrill' situation—and now continue to work with her on ongoing research from India.

The analyst at a client Investment bank wanted to create a portfolio of companies based on certain valuation- and transaction-based parameters, which he believed could outperform the market.

The Irevna associate took this idea as a starting point and turned it into a product—from testing the hypothesis using advanced regression analysis, to stock selection, back-testing and devising a method to periodically rebalance the portfolio. The selected portfolio has been found to beat the benchmark index by a wide margin since 2001, and is now being taken live by the investment bank, in exactly the composition recommended by Irevna.

A universe of 2700 stocks—constituents of three leading world indices—was used to test the hypothesis and for stock selection. Operationally, a well-defined procedure helps the portfolio to be re-balanced on a monthly basis. The portfolio was found to considerably outperform a bear market, and match a bull market—suggesting uses as a defensive strategy or a hedging tool.

Clients often wish to explore ways to independently verify forecasting and valuation numbers determined through standard industry models. In this particular situation, a buy-side firm wanted to verify 'conventional industry estimates' of the European telecom markets—and wanted Irevna to come back with an innovative and independent method of forecasting the market size. Irevna employed various statistical techniques like trend fitting and multiple regression to estimate the market size—by relating the market size data to various other related parameters like telecom capital expenditure and current penetration levels. In many other similar situations, faced with different sell-side research with differing estimates, buy-side firms have often used Irevna to get independent estimates of markets size and company valuations.