We use the power of data analytics to comb through 1,000 companies and find undiscovered, under-value companies which are unlikely to reduce in price.

Research has shown that purchasing shares at a discount to their cash flows produces super-normal returns. This has been shown to work across countries and geographies over long time periods.

Simple, mechanical methods such as shortlisting companies on the basis of P/E, EV/EBITDA, P/B, P/FCF etc., have shown to give extra-ordinary returns - better than almost any mutual fund, and have given results comparable to the world's most legendary investors.

However, such deep-value methods are rarely practiced in the real world because they go through very, very long periods of under-performance, sometimes lagging the market for 5 to 7 years.

In spite of growing sales and profitability, a ridiculously cheap company can remain cheap forever.

It is said that there is no free lunch in investing, the reason such a deep-value approach gives superior returns is because it does not work every single year.

But....

Data analytics has changed the way we invest.

Newer research from across the world has found additional tools to supplement the traditional screening tools such as P/E and EV/EBITDA.

By applying forensic ratios, the companies with bad accounting can be weeded out.

By using quality filters we are left with only under-valued companies which are high quality.

And then we use price momentum to avoid value traps.