Tag: machine learning

machine learning

EC’s Updated AI Plan Still Attracts Criticism

The European Commission has published an update outlining the next steps for its efforts to build trust in AI and machine learning by creating what it terms “a European approach to artificial intelligence”. The plans have attracted criticism from the Center for Data Innovation, a non-profit research institute.
In 2018 the EC established a High-Level Expert Group (HLEG), which was tasked with creating policy and investment recommendations to help the Commission deal with the technological, ethical, legal and socio-economic challenges that can arise from the broader use of AI. Upon launch, the EC said it wanted to strengthen the EU’s competitiveness in this area.

Refinitiv Survey Finds AI Widely Used But Data Inadequate

A new Artificial Intelligence/Machine Learning survey launched by Refinitiv has found that while the use of these techniques is pervasive in the financial community, poor quality data impedes their ability to leverage the advantages.
The survey found that 90% of the c-level executives and data scientists surveyed have already deployed machine learning, while all of the c-level participants said it is core to their business strategy.
On the downside, 43% cite poor quality data as the biggest barrier to adoption followed by a lack of data availability (38%).

Ensemble Capital Signs with Numerix

Singapore-based absolute return global AI fund Ensemble Capital, has gone live with Numerix’s Oneview Asset Management solution for risk and portfolio management.
Founded by former JP Morgan FX option traders Atsuo Ogaki and Damien Loh, Ensemble Capital uses machine learning and deep learning AI algorithms to analyse market data, forecast moves and trade currency and currency options in order to generate uncorrelated returns to traditional asset classes. Ensemble’s proprietary AI models instil discipline and provide a systematic approach to markets.

In the FICC of It

Scepticism abounds in this week’s In the FICC of It podcast as Colin Lambert and Galen Stops take a look at the latest bank to unveil a digital markets strategy – including all your favourite buzzwords. While Stops believes this is the latest move in what will be a growing trend, our podcasters also wonder whether it’s not really just a rebranding exercise?
They then move into more traditional areas and discuss JP Morgan’s survey on FX market conditions, and while they agree with a lot of the findings, there are one or two areas that raise an eyebrow, not least around internalisation and AI.
AI-generated trading and liquidity are also the forefront as they move on to share their thoughts around the flash crash in Jardine Matheson stock last week in Singapore, including asking the question, what does it mean for market maker programmes and certain order types?
The discussion then moves on to look at the latest FX turnover surveys from the world’s FX committees, with particular attention on three interesting/puzzling (delete as appropriate) elements of the UK report surrounding RMB, NDFs and voice brokers.
The podcast ends on with Lambert praising “the optimism of youth” after Stops highlights what he thinks could be a very important line at the end of the latest document detailing an FX-related fine in the US – in other words, the cynic in him won the day!

Survey: FX Traders Cite Liquidity as Top Daily Concern

The availability of liquidity is the biggest daily issue facing FX traders right now, according to a new survey by JP Morgan.The survey results come from 200 of JP Morgan’s largest Institutional clients, with the majority being FX traders and the rest being rates and commodities traders.In total, 40% of survey respondents cited liquidity availability as the biggest day-to-day issue facing traders in 2019, with 25% instead pointing to efficiency of process, 18% to best execution requirements and 17% to price transparency

Mosaic Launches FICC Analytics Product

FICC data analytics company Mosaic Smart Data has launched a new feature for its MSX platform enabling users to instantly generate text reports on their trading activity data using machine learning.
The feature will be available to all MSX users and will allow a trading activity report, which would take a member of staff hours to create, to be generated instantly.
The firm says the new service uses a machine learning technique called natural language generation (NLG), meaning MSX can generate trading activity reports on any set of analytics on the platform including both voice and electronic trade data.

Survey Highlights Hedge Fund AI Usage

Artificial intelligence (AI) and machine learning (ML) are reshaping the alternative investments landscape, but professional financial managers still make the most pivotal decisions, according to a new survey from BarclayHedge.

In a sample of 55 hedge funds that responded to the survey, 56% said they use AI/ML to inform investment decisions, with most of the firms that use these tools saying that they do so in order to generate trading ideas and optimise portfolios.

Well over half of the respondents, 58%, have used AI for three or more years, while 37% have used the technology for five-plus years.

Hedge fund managers were among the earliest adopters of advanced algorithms and artificial intelligence techniques, which helps explain why a plurality of survey respondents said they have been using AI/ML for more than five years.

AI in Trading: Human Ingenuity on Steroids

One of the key benefits of the use of artificial intelligence (AI) tools for trading is that it can massively enhance human capabilities, explains Andrej Rusakov, CEO of Data Capital Management.

“The way I see it is that AI can really put human ingenuity on steroids,” he says. “What I mean by that is that it really allows you to take way more data points into account and find structures in data sources that are impossible for the human eye to spot.”

Rather than displacing humans, Rusakov explains that this technology is most effective when it is deployed in tandem with a human understanding of how markets work. When building strategies, his firm uses this understanding of markets and then codifies and enhances them by using AI, and in particular machine learning, tools to find new patterns in different data sets.

Understanding the Limits of AI 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.

CMC Markets Partners with Tradefeedr, Adds Alexa Capabilities

Online broker CMC Markets has partnered with Tradefeedr, a data science platform built for financial markets, to deploy cloud based machine learning to improve trading analytics and intelligence around liquidity management.
The firm says that the additional capabilities provide for the ingestion, cleansing and store of massive amounts of market and transactional data; high performance computing infrastructure for inspecting, intersecting and querying massive data sets, including data visualisation tools and APIs for extracting the results of analysis for further analysis.