If data is the new oil, then how trading firms “drill” it in order to generate alpha becomes increasingly important. Galen Stops reports.
So often has the phrase been used recently that it’s in danger of becoming something of a cliché but, apparently, data is the new oil.
To see evidence of this, look no further than the technology giants that have emerged out of Silicon Valley. Yes, Facebook doesn’t charge users money for the social media platform it provides, but is it free? Arguably, users “pay” with the data that they create via their interactions on the platform, which Facebook is then free to use and sell to generate profits.
There is a lot of conversation around Artificial Intelligence (AI) among different participants in the institutional investing pyramid.
Investors are wondering if AI can get higher returns by extracting unexplored alphas or if it can reduce costs, and investment professionals are wondering how machine learning and AI will impact their businesses.
Right now there is a lot of exuberance, optimism, skepticism and fear around AI and the impact that it will have on financial markets. Here I explore five key questions that are important to ask regarding this technology and its role in finance.
Artificial intelligence (AI) and machine learning have become buzzwords in financial services, but while this technology can be applied in finance in numerous ways to improve returns, it also has some significant limitations that market participants should be aware of.
This was the message from speakers at the Profit & Loss Forex Network New York conference, on a panel discussion titled “AI: Regular Quants with a Bigger Bazooka?”
“In my mind the biggest problem with machine learning in its application to finance is the problem of non-stationarity.
The increasing use of AI technology is likely to create incumbent firms that dominate markets, said panellists at the Profit & Loss Forex Network New York conference. However, they also said it might not be the biggest firms in the markets today that become these incumbents.
“I think [AI] is changing the landscape quite a bit,” said Andrej Rusakov, a partner at Data Capital Management, a hedge fund that uses AI tools to develop trading strategies. “People who are missing the wave are going to be left behind, I don’t think there’s any question about it. I think that human day traders will be wiped out, if they’re not already.”
Asset Manager, qplum, has launched a multi-strategy AI managed futures program (QMAP) for qualified institutional clients.
QMAP aims to give investors access to a diversified investment strategy that trades across different geographies and asset classes. It trades futures such as fixed income, equity indices, FX, commodities and volatility. There is a drawdown control-based risk management in place.
The strategy is built using qplum's proprietary, deep learning framework that already powers other portfolios offered by the firm Large amounts of market, economic and other structured data are used to train the models and the entire trading pipeline is fully systematic