OTAS Integrates Estimize Estimates

OTAS clients will be able to analyze Estimize’s data and identify where the crowd-sourced consensus diverges from traditional estimates.

Estimize Estimates

London based analytics provider OTAS Technologies is to deliver crowd-sourced Estimates provider Estimize’s earnings estimates data via its OTAS Portfolio Analytics App suite.

The new “Estimize Stamp” will cover a universe of 2,150 US stocks in the OTAS Core summary, and will allow users to quickly visualize where divergences occur in consensus between Wall Street estimates and those of other market experts. When used collaboratively with other Core Summary stamps, the Estimize Stamp will provide insight into the potential impact on equity prices.

OTAS clients will also have the ability to contribute their own estimates, which will enhance and deepen the coverage of the Estimize dataset in the long term.
“By integrating Estimize estimates into OTAS Core Summary, we are able to provide another unique data offering directly into our clients’ workflow for idea generation and risk management,” says OTAS chief executive Tom Doris in a statement.

G4S, Lloyds, Burberry: How artificial intelligence spots insider trading before a stock hits freefall


Burberry shows multiple insider transactions after warning in 2012, including CEO & Chairman. The stock mean reverted and made new highs.

Machine learning algorithms can warn investors when a particular stock is going to fall by predicting likely instances of insider trading (when information that’s not in the public domain is capitalised upon by people in the know). This can be done by analysing previous occasions when company insiders did apparently well-timed trades in their own stocks, and recognising these patterns.

This might seem deceptively simple, but it isn’t, explains Tom Doris, CEO of OTAS Technologies, a London-based market analytics and machine learning trading system. While company executives are required to file details of transactions in their company’s stock, most insider trades are few and far between: a needle in a haystack.

Doris told IBTimes UK: “We look at all of the insiders, the directors of companies, and we see all of their historical transactions in their own stock. If you are the chief financial officer of Vodafone, any time you buy or sell Vodafone stock, you’re obliged under regulation to file details of those transactions. So that would include the amount that you bought or sold, when you did it and what price you got and the reason, if any, for the transaction. There is an enormous database of all of these transactions for all of the world’s listed stocks and we go and we basically back-test all of the insiders and we find the ones that are apparently good at timing their own stocks.”

G4S at the Olympics

A good example of insider trading activity detected by OTAS prior to a big price fall was when insiders at security firm G4S all started selling their stock right before the Olympics announcement that was very damaging to the company’s share price – detectable in advance because of historical precedents.

“Normal back-testing techniques wouldn’t really have uncovered those kinds of signals,” noted Doris. “But the new techniques that we apply now can take a very small number of data points and identify when there’s some suspicious activity going on or some people seem to be trading off material inside information that’s not yet public. So the next time this person buys or sells stock, we can say, ‘hey Mr portfolio manager, this guy at G4S, or at Tesco or at Pandora, or any of these other companies – every time he sold stock in the last five years it’s been very bad for the stock, therefore you should be paying attention to this transaction.’

“It’s deceptively simple in some ways. But the problem is that an insider typically will not make a lot of trades so if you use old style statistical techniques on a guy who has had two or three trades in his lifetime, it will just come back as inconclusive, even if he has gotten all three of them right. It’s not enough of a data set to say conclusively that he’s trading off inside information. Whereas, if you or I look at the price charts and see that the three times over the course of five years that he has traded the stock, it has jumped up significantly within a month of him trading and he caught three out of the five major jumps in the stock over that five year period. You and I know immediately that it looks suspicious and it looks like he got information.


There were a number of sizeable sale transactions in Lloyds shares through the summer of 2015 by various ranked insiders. The Government was in the process of disposing with part of its RBS stake in early August and it was thought that Lloyds shares (having significantly outperformed its peer) would be the funding trade.

“So a lot of it is taking things that humans are quite good at and translating that back into a new statistical methodology and using new techniques to kind of embed that domain expertise that comes very naturally to us on a single basis. When you systematise it and put it into an algorithm obviously you can run it on thousands of stocks and hundreds of thousands of transactions.”

OTAS sees opportunity in applying machine learning techniques to filter, highlight and push concrete evidence to human decision makers where there are big gaps between a historical situation; where it would not be feasible for a portfolio manager to stay on top of all of the news and all the research for a given company from 20 years ago. Doris said this is an area not really policed in any way; a lot of companies have lock up periods ahead of an earnings announcement where there is material non-public information and they prevent their employees from trading their stock. “In terms of systematic ways to identify people who appear to have an uncanny ability to get their trade timing right, we are not aware of any other system in existence that does that other than the one that we have invented.”

High Frequency Trading

Doris, who has worked for hedge funds and holds a PhD in neural networks, points to misconceptions about how AI and machine learning is used to assist people at hedge funds, or quants in general, to predict future price moves. This is partially the case on a very short time scale, but actually the people who make the most money out of high frequency trading, for instance, are more interested in predicting if somebody is going to buy stock aggressively in the next couple of seconds. “The idea of predicting what the price is going to be, or predicting what the next three months will unfold, is not really something that anybody in finance really spends a lot of time on. The ones who are very good at quant and high frequency can have predictions that go out for a couple of seconds or a few minutes at the most.

“The markets are reasonably efficient and are very good at pricing in information and HF traders have a role to play in that. It’s a very good way of getting information about a stock into the public domain; that’s how they function and as a result material information doesn’t really stay private for the length of time that it would need to stay private in order to have a prediction that would last for anything more than several minutes. It’s by virtue of the markets actually functioning correctly that those opportunities simply don’t exist.”

He also pointed out that global investment houses with billions under management have strict investment mandates which must be adhered to. They tend to be more interested in flagging risk and volatility and avoiding the torpedoes in their portfolio, than some brand new black box signal guaranteed to make money. “Somebody running a portfolio at a big fund manager with tens of billions of dollars in equities might have 100 to 200 positions in stocks and two or three of those positions in any given year are going to be down 25%, and they are the ones that really hurt the performance. The other 100, they are going to track the market more or less and you might have a little bit of skill in terms of loading up on some of the better ones, but in the long run it’s limited. It’s all about trimming the losers. So if you have better systems that can identify when there is a risk of those kind of draw downs, that’s really where the juice is and the value added.”

Hedge funds and AI PhDs

There has been plenty of ink recently about hedge funds secretly incorporating AI divisions. Doris takes a philosophical view: “I think there has always been more hype than action around this stuff. It’s a great way of building your assets and asset allocators are possibly the root cause of this; they are prone to being disproportionately impressed by a roomful of PhDs claiming that they are doing ground-breaking work.

“It’s something that allocators look for and therefore the hedge funds respond to that – whether they are doing it or not, they will say they are. And usually you can find some area of your operation which is doing something that can be characterised as AI or ML and they roll those out whenever the allocators or the investors come to town. But these days you probably need a room of PhDs just to stay on top of your risk and compliance requirements, never mind managing portfolios.”


The system also works for megacaps in the DJ industrial average

OTAS launches Intraday 2iQ Insider Transaction Data

LONDON, 07 March 2016OTAS Technologies (OTAS), a specialist provider of market analytics and trader intelligence, today announced an enhanced product offering with 2iQ, a behavioral finance research firm that provides insider transaction data for over 45,000 stocks worldwide. OTAS Core App will redistribute on a real time basis 2IQ insider transactions combined with their unique proprietary insider star ranking to give OTAS clients real-time information on insider dealings to help drive intelligent investment decisions and focus their attention where it is needed most.

2iQ provides a variety of insider transaction data, from analyst researched transactions, filing footnotes and information on transactions related to company events. Using its in-house team of analysts, the firm captures data across over 100 data sources on more than 45,000 companies in 50 countries globally. Available immediately, OTAS clients will have access to real-time insider information through a 2iQ insider stamp, including optional alerts on insider deals that provide live updates on insider transactions.

Tom Doris, CEO of OTAS Technologies, said: “Traders today require a new depth of market intelligence and analytics to maintain a competitive edge in the market, including fast access to data on insider transactions and holdings. Our partnership with 2iQ gives our clients access to this unique data set in the most efficient and automated way and as quickly as the data is available so they can make the best trading decisions possible.”

Patrick Hable, Managing Partner and Founder at 2iQ, adds: “As a leader in the trading analytics space we chose to partner with OTAS as a comprehensive source for gauging insider sentiment at the company, industry or country level. Being integrated on their platform has created increased market visibility, greater awareness and recognition for our solution and the partnership gives us access to an intuitive analytical tool that allows our data to be displayed in the best possible way whilst also expanding its reach to OTAS’ growing client base. We look forward to building on this relationship over the next few months.”

TIM Group and OTAS Technologies Partner To Provide Trade Analytics

New partnership integrates TIM Investor intelligent sentiment into the OTAS Apps

London, 1 March 2016TIM Group, provider of the world’s leading network for broker trade ideas, and OTAS Technologies, the global leader for next-generation market analytics and trader intelligence, today announced the integration of TIM Group’s intelligent broker analytics within the OTAS Apps. The partnership will provide mutual clients with unique, predictive, and actionable market sentiment immediately at the point of decision making.

TIM Group’s analytics have been seamlessly integrated into OTAS trade decision support services. Combining TIM Investor’s proprietary insights with OTAS open architecture means intelligent content and insight on global markets can be shared easily to the OTAS Apps in real-time, with users immediately able to take advantage of the broker information.

“OTAS clients are some of the most progressive global institutions, who expect unique information and leading edge analytics that deliver enhanced trading decision support,” said Tom Doris, CEO of OTAS Technologies. “We are committed to having an open application that integrates with our clients’ workflows and their preferred third parties. Partnering with a unique content provider like TIM Group is one of the ways we are able to do this. We are excited to deliver TIM Investor’s intelligent sentiment to our global client base.”

Colin Berthoud, Co-Founder of TIM Group added: “TIM Group has 4,000 broker sales trade idea contributors at over 300 firms globally. By partnering with OTAS we are now able to provide our shared clients with unparalleled insight and analysis, that will significantly and positively impact their decision making. We are looking forward to working with the OTAS team to deliver best-in-class services to our clients.”