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Digital Subscriptions > The Hedge Fund Journal > Issue 134 – Aug 2018 > Aquila’s Algert Global Equity Market Neutral UCITS

Aquila’s Algert Global Equity Market Neutral UCITS

Exploiting fundamental, behavioural and cognitive biases


Algert Global CEO and CIO, Dr Peter Algert, founded the firm in 2002, and counts himself very lucky to have been close to the genesis of quantitative equity investing namely the University of California, Berkeley and BARRA, where he studied and worked in the 1980s.

“We can honestly claim that this is where quant equity started. Berkeley Professor, Barr Rosenberg, started the eponymous BARRA (Barr Rosenberg Associates); John Andrew McQuown, the M in KMV, launched first the index fund at Wells Fargo in the 1970s, which became Barclays Global Investors (BGI) and later joining Dimensional Fund Advisors; Richard Grinold moved from academia to become global head of research at BGI and Peter Muller, who had studied at Princeton, set up PDT (Process Driven Trading) after a spell at MSCI BARRA. Many staff at Algert are connected to that pool of DNA,” says Algert.


Common foundations underlie the investment philosophies of all these quantitative equity managers. “We believe that markets are not entirely efficient, but are hard to beat, and it is best to do so with a strong and complementary set of teammates. Our philosophy and culture encourages rigorous, disciplined research, grounded in strategies that make sense economically and to fundamental investors. We take sensible investment ideas from traditional long/short equity funds and use systematic expertise to apply the insights to a huge universe of stocks, which we believe would be impractical for a traditional discretionary approach” says Algert.

Dr Peter Algert, CEO and CIO, Algert Global

Algert believes there are mis-pricings in equity markets due to well documented behavioural and cognitive biases that often prevent investors from rationally processing information. In some cases, they are slow to adapt to news, in other instances these biases lead to over-reaction (e.g., overconfidence bias, representativeness heuristic). Often, investors are misled by how data is framed by companies.

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