‘Worldwide, HNI investors allocate 15-20% to quant fund strategies’

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When the markets are trending, it is time to be around. But then there are so many choices and decision making can get arduous. Lotus India Asset Management has now introduced India’s first quantitative fund that uses mathematical models to take decisions. Rajiv Vijay Shastri, head-business development and strategic initiatives, Lotus India AMC, and an expert on structured products spoke with Akash Joshi of The Financial Express on the finer aspects of ‘quant’ funds. Excerpts:

Tell us more about this new initiative of yours?

The work on this product started more than a year ago when we built this model for investing in the equity market. We were busy back testing and live testing this product for different scenarios and when we were satisfied, we launched this product.

This is the first pure ‘quant’ fund available to Indian investors. There have been quasi quant products that are more like fund of funds that track mutual fund performance over a period and then based on their models, invest in these funds. In that sense, this fund is a pure quant fund that invests directly into equities, based on a model that we have developed and tested extensively.

So how will it operate and importantly, how will it be different from other funds?

Well, it’s different in a lot of ways.

It invests only in 11 stocks and 9% of the corpus only will be invested in each of the 11 stocks. So its 99% invested all throughout.

The advantage of a quant fund is based on the concept that there are ways of interpreting market data that can be managed by a computer; it does not take into reckoning the softer aspects. See, there are two basic models of investing, one is the discretionary model and the other is a rule-based model.

What we have seen in India is the discretionary model, where there is industry and company research done and the fund manager then decides what he thinks best. In a rule-based approach there is absolutely no discretion. The model has a signalling power and this is pre-tested, back tested in different scenarios. So we have an idea how the fund would operate in different situations. This cannot be done with a discretionary fund.