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Digital Subscriptions > The Hedge Fund Journal > February 2017 > CTA Kaiser: 19 Years of Evolution

CTA Kaiser: 19 Years of Evolution

Reading the runes of market regimes

Kaiser, which has offices in Melbourne and London, returned 10.28% for its Kaiser Global Diversified Program’s Class A in 2016, a year when the average CTA was slightly down (the SG CTA index ended 2.86% lower). This disconnect is not unusual: the programme has a low correlation with the BarclayHedge BTOP50 index, with an average historical correlation of 0.3.

“We trade over different time frames, which provides a sound reason for our low correlation,” explains founder Tony Kaiser. The programme’s median holding period is three days, hence the SG Short Term Traders Index – up 0.31% in 2016 – is is another benchmark, which could complement broader CTA indices that can include long-term, medium-term and short-term technical CTAs, not to mention some systematic and quant macro funds that use fundamental data. Indeed, Kaiser’s peer group CTAs are sometimes defined as other short-term traders, such as Amplitude, Boronia (also headquartered in Australia), Crabel, R.G. Niederhoeffer and QuantMetrics.

This does not imply that Kaiser has a similar return pattern to these managers, however. Correlations within the short-term trader universe are lower than the coefficients between mediumand long-term CTAs. As well as ploughing their own return profiles, short-term traders tend to pursue differentiated approaches, in terms of philosophy, process, execution techniques and risk management. Here we outline some of Kaiser’s distinguishing features.

Many CTAs build models. Those that are agnostic in predicting when particular models will perform will always keep all models switched on, while others “time alpha” by switching between and rotating around models. Kaiser is in the former camp and argues that “models are almost irrelevant because they only perform if the market regime suits the model.” The programme’s core focus is “identifying market regimes, states and drivers,” says Kaiser. This provides a multi-resolution understanding of time series, which provide context when entering and exiting trades.

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