Stockholm (HedgeNordic) – Taaffeite Capital Management (TCM) last week won an award at the prestigious CTA Intelligence US Awards 2019 in New York for its strong returns for the last 5 years.
The prestigious CTA Intelligence US Awards recognizes the best performing North American CTAs and managed futures funds. Winner in the category Best CTA long term performance under $500m was Taaffeite Capital Management.
“We are thrilled to be recognized for our hard work and strong results and this award is a reflection of our team’s profound experience and expertise. But we do not only take pride in creating a successful result. Unlike many other quantitative funds, we also allow great transparency in the investment process and always make sure that potential investors truly understand what we do,” says Taaffeite co-founder and CEO Howard Siow. Recently, TCM was also named the second-best performing CTA for the last five years from Barclay Hedge. The results are based on Martin Redgard and Marco Veterani’s results, whom took over the management of the fund during the fall off 2018. With the help of artificial intelligence, TCM has been able to identify and translate into profitable trading opportunities the market’s movement patterns.
“A mediocre strategy can be an exceptionally good strategy, just by removing a large percentage of the losses.”
“When it comes to quantitative AI trading, many funds try to let the computer find trading opportunities that cannot always be logical to the human mind. This can be risky as it reduces the understanding of why a position is opened and what it should achieve. On the other hand, the human senses may misjudge the markets and miss a lot of the information that quantitative AI systems can pick up. Quantitative trading can also reduce risk by adding discipline when it comes to closing loss-weighted positions,” says Martin Redgård, CIO at Taaffeite Capital Management (pictured left).
However, TCM has reversed the equation and instead of trying to find a golden formula that outwits the market in all situations, classic well-known trading strategies are used. AI is instead used to identify and discard the positions that would have been a loss. Redgård adds. “A mediocre strategy can be an exceptionally good strategy, just by removing a large percentage of the losses. The objective is to be the foremost and obvious placement without correlation with the stock exchange in a portfolio.”