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Digital Subscriptions > The Hedge Fund Journal > Issue 125 - August 2017 > FORT INVESTMENT MANAGEMENT

FORT INVESTMENT MANAGEMENT

26 years of adaptation and outperformance

PROFILE

(L-R): Dr Sanjiv Kumar and Dr Yves Balcer

Among CTAs, Washington DC area and New York-based FORT is highly unusual in that its absolute performance since 2008 has been very similar to its numbers in the 15 years from 1993 to 2008, when expressed as a spread over risk free rates. This persistent outperformance has propelled the strategy’s returns further ahead of the SG CTA index (of which FORT Global Contrarian has been a constituent since 2016). What is more distinctive is that FORT’s absolute risk-adjusted returns have actually been higher post-crisis than pre-crisis. “It cannot just be luck to have outperformed the CTA index on average for more than 20 years,” says co-founder, Dr Sanjiv Kumar. Part of the superior returns are attributable to FORT’s somewhat differentiated trend following strategies having outpaced most others, but FORT has also developed trend-anticipating and non-trend strategies that contribute to its various multi-strategy offerings. A summary of the standard program suite is shown in Table 1 (other combinations can be customised).

Table 1

Though FORT’s strategies are 100% systematic and quantitative, Kumar argues that the founders’ heritage in discretionary macro provides a different perspective from the mainly Chicago-oriented exchanges and brokerages that spawned many CTAs. Kumar, and co-founder Dr Yves Balcer, managed $25 billion fixed income portfolios for the World Bank, employing a discretionary macro approach. A background in academia is another differentiator, as both founders pursued PhDs before moving into portfolio management.

The limits of statistics

The doctoral research was less formative than the real world experience however. Some systematic and quantitative firms set great store by using the latest and most advanced statistical techniques, but Kumar thinks that the defining quality of FORT’s model-building mind-set is adaptation rather than statistical methods. “Our PhDs provided a useful foundation of knowledge and broad training in maths, stats and economics that was critical in starting the company. But we also realise the limits of this knowledge – you must know what you don’t know,” says Kumar.

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