Trading


Wall Street looks towards Silicon Valley for automation

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Wall Street is looking towards Silicon Valley for a more automated environment and a tech-driven approach. A July 2016 report by CB Insights showed that 41 startups may be introducing AI to fintech. Of the many big names, Goldman Sachs remained dominant in backing as many as four companies that use AI in financial technology. As many as 658 AI deals were closed and $5021 billion was spent on funding the AI startups in 2016, according to the report. With total AI investment gaining momentum across different industries, an increasing number of companies are branching out to offer a variety of services that range from credit scoring to regulatory compliance and fraud detection.


AI and Machine Learning: Practical Applications for Asset Management Firms (Part 1 of a 3-Part Series)

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When you hear those terms, what comes to mind is a science fiction movie where machines achieve consciousness--and trouble ensues. At best, you might dismiss the concepts as hype or the buzz word of the day. It's true that the AI/machine learning landscape feels a bit like the Wild West right now, with opportunists promoting solutions when, in fact, they don't actually have a product--perhaps just some roughly defined services--but no technology to back it up. Regardless, AI and machine learning are very real--and very relevant to asset management firms. Unfortunately, traditional asset management and CRM (customer relationship management) systems like Satuit, Protrack, or Salesforce don't have the ability to deliver the benefits of AI and machine learning.


AI, Blockchain Technologies Are Fueling Israeli Innovation Right Now Guest Post

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This article is a guest post on NoCamels and has been contributed by a third party. NoCamels assumes no responsibility for the content, including facts, visuals, and opinions presented by the author(s). Mor Assia is a founding partner at iAngels, an Israeli VC and angel investment firm, and iCapital, an investment platform dedicated to blockchain opportunities. Artificial intelligence (AI) and blockchain are possibly the two most influential technologies currently fueling innovation at this very moment and are expected to create radical shifts in almost every industry. Israeli startups are at the forefront of both of these sectors, receiving notable attention and investments from global players which are further propelling Israeli development in these industries.



6 top disruptive technology trends

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In the world of constant innovation disruptive technologies have become an intrinsic part of strategic and management consulting, causing all leading consulting companies to focus on developing new offerings, in order to keep up with an ever-growing client need. In addition to financial services and the most recent blockchain and cryptocurrency hype, disruptive technologies can be applied to almost every industry. This includes anything from data protection and storage to better pattern recognition that can be used to allow businesses to work more efficiently and deliver a higher level of service to their clients. Artificial intelligence is said to be one of the biggest disruptors on the market. AI is present in our surroundings on a daily basis; examples include Siri, Alexa and Google Assistant that are now present in a large number of homes worldwide.


IDA founder Mr. – IDA – Medium

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Over 200 attendees attended the blockchain meetup in Istanbul, Turkey co-organized by SamuraiSignals and MATRIX AI Network on July 28th, to explore leading edge developments in blockchain. In his talk, IDA cofounder, Mr. Walter Wang outlined four innovations shaping the future of asset digitization. Wang said that the technical basis for asset digitization, is creating a digitized representation of real assets or IP assets in a binary code format -- however, there are currently the following challenges to overcome before the technology can be applied widely. There is an asymmetry in transparency of asset information. How to extend legal protections to digital assets?


Artificial Intelligence (Ai) In Agriculture Market Analysis 2017 and Forecast 2021: Driver, Size, Dynamics, Share, Supply Demand – Redfield Herald

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Artificial Intelligence (Ai) In Agriculture Market Report is prepared after discussion with industry experts studying vital data of Artificial Intelligence (Ai) In Agriculture Market. The market data comprises of market size, market trends market challenges. The report also talks about the challenges faced by new entrants in the Artificial Intelligence (Ai) In Agriculture Market i.e. competitive scenario is mentioned in the report. Region wise country wise analysis of major vendors is also available in the report. For the readerrsquo;s convenience the data is presented in the forms of Parts, i.e.


How Blockchain Will Transform Artificial Intelligence

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The research on improving artificial intelligence(AI) has been going on for more than a decade. However, it was not until last few years before developers were able to create smart systems which showed the true potential of artificial intelligence(AI) that closely resembled capabilities of humans. The biggest reason for the revolution in AI is the advancements in big data. With the recent developments in big data have allowed businesses to organize a large amount of data into structured components which can be processed by the computers very quickly. Another technology which has the potential for revolutionizing and transforming artificial intelligence is blockchain.


Uncorrelated Does NOT Imply Independent

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This is just an aside to describe a misconception that we have seen some money managers make when describing their strategies or portfolios. When you are discussing the correlation of your portfolio to another portfolio or the market in general, the fact that your portfolio may be fairly uncorrelated does not have anything to do with the independence of your portfolio from a reference portfolio or the market in general. In fact, even if the portfolio you have developed is completely uncorrelated, it still probably isn't independent. However, if the performance of the two funds were uncorrelated statistically independent the standard deviation of a portfolio comprised of the two funds would decline to 7.1% compared with 10% for each of the individual funds. Again, uncorrelated does not in any way imply independence (also called statistical independence).


Uncorrelated Does NOT Imply Independent

#artificialintelligence

This is just an aside to describe a misconception that we have seen some money managers make when describing their strategies or portfolios. When you are discussing the correlation of your portfolio to another portfolio or the market in general, the fact that your portfolio may be fairly uncorrelated does not have anything to do with the independence of your portfolio from a reference portfolio or the market in general. In fact, even if the portfolio you have developed is completely uncorrelated, it still probably isn't independent. However, if the performance of the two funds were uncorrelated statistically independent the standard deviation of a portfolio comprised of the two funds would decline to 7.1% compared with 10% for each of the individual funds. Again, uncorrelated does not in any way imply independence (also called statistical independence).