From discretionary to systematic, how trading changing in the next 10 years

At the end of the day, the business of investment management is the business of information management. I think the algorithmic approach is very good approach to do it.

Here from Malta and UK, we have research and solutions based on these concepts

Leda Braga, 48, is considered the most powerful female hedge fund manager in the world.

In January, she launched her fund, Systematica Investments, a computer-driven fund.

With $8.8 billion in assets, Braga manages more than any other female hedge fund manager and more than many other funds run by men.

Before heading out on her own, Braga spent 14 years managing BlueCrest’s biggest fund — the computer-driven BlueTrend fund.

Before that, she worked with BlueCrest’s founders at JPMorgan as a quantitative analyst on the firm’s derivatives research team.

The Brazilian-born portfolio manager, who holds a Ph.D. from Imperial College, joined BlueCrest when she was 34-weeks pregnant.

In the male-dominated world of Wall Street, Braga said she hasn’t experienced difficulties.

“What can I say? Me, personally, I’ve always liked to work,” she said at the CNBC Delivering Alpha Conference held at the Pierre Hotel in midtown Manhattan on Wednesday.

“She’s so impressive,” one attendee was overheard saying.

The Future of Trading

The “queen of the quants,” as Braga is sometimes known, told the room that in the next ten years, the systematic approach the trading — the one she deploys — will prevail.

When it comes to making trades, there are two contrasting approaches —discretionary and systematic. Discretionary trading relies on the fund manager’s own decision-making. Systematic trading uses computer models, research firm Preqin explained.

“I think in a world where there’s regulatory pressures, investor pressure for lower fees … I think the systematic approach will prevail in the long run. I think the next ten years for sure,” Braga said.

During her talk, Braga shared an anecdote from a previous conference where an audience member questioned the merits of algorithmic trading.

A man sitting in the front row challenged her method, saying: “All you’ve got to forecast to the future is the data.”

Braga rebuked him, saying, “You think the discretionary guy has what? A crystal ball?'”

“At the end of the day, the business of investment management is the business of information management. I think the algorithmic approach is very good approach to do it.”

Braga conceded that systematic trading does face a “stumbling block” — something called “algorithmic aversion.”

Research from UPenn’s Wharton has found that even if an algorithm consistently outperforms a human forecaster, people are more likely to lose confidence in the algorithm than the human after they both make the same mistake.

The reason, according to an HBS paper on the research, is that there’s a belief the human forecaster can make improvements and learn from the mistake.

But Braga says algorithms can improve too.

“[We] know these things work and yet we shy away from them,” Braga said. “We scrutinize the algos with a lot less tolerance than we scrutinize human action.”

Braga thinks that over time people will become more “amiable” toward algorithms — especially since we live in a world full of them, from Apple to Uber.