Big Data in Quantitative Trading Research and Algo Development

Big Data is data sets that are complex data sets, typically with large volume. Examples of Big Data in FINTECH include historical market data, news service information, tweets, and sentiment data.  Challenges in using big data include capture, storage, security, analysis, and visualization. Data scientists use Big Data (including alternative data) for predictive analytics. CloudQuant’s quantitative crowd researchers use historical market data, news data, and sentiment data to develop predictive trading strategies that are tested using a complex, proprietary backtesting trade simulator.


Principles by Ray Dalio: Systemize Decision-Making

Industry News: Machine Learning and Artificial Intelligence for January 2, 2018

Increasing Automation in Offices Paying Off for Advisory Firms

…ThinkAdvisor. “The main reason, in my opinion, for the automation, is that it costs less, and is faster in terms of being more responsive to the end customers.” The automation may come from the use of artificial intelligence, machine learning or even older forms of technology. “Automation, even without taking artificial intelligence into consideration, provides faster, more accurate information at a significantly lower cost,” Davis said. “I don’t believe there are any drawbacks with respect to back-office operations.” Vasant Dhar, a professor of information systems at New York University, also sees that some back- … 2017-12-27 00:00:00 CloudQuant Thoughts: Automation works. Most people think automation at a “macro” level though. We are thinking about automation in every step of our lives. What can we do to automate our daily tasks without having to think about what can some programmer do for us? Automation tools like Jenkins, Python, even MS Excel Macros that make our professional lives more productive will always help. Yet we also believe that you need to automate based on what is important to you. In 2018 we will be working to systemize our decision making. We want all of us to compound our understanding using a principle-driven approach to decisions to improve our product, our client relationships, and our own lives.
Principles by RayDalio: Systematize Decision-Making

Principles by Ray Dalio: Systemize Decision-Making

Outlook 2018: Alastair Hawker, Quantitative Brokers

…he fact remains that MiFID II has been enormously resource-consuming for the industry on both sides of the Atlantic despite it being an EU regulation. What changes do you expect to see in regards to artificial intelligence in 2018? As a firm, we have spent a lot of time researching and discussing AI/machine learning this year. Undoubtedly, it’s a huge area that will continue to grow and become part of everything in the industry. The next step will be better understanding the applications and limitations of AI/machine learning, and there will be a move away from it being a buzzword to being able to develop true use… 2017-12-29 08:00:35+00:00 CloudQuant Thoughts:  This article states that the demand for Quants and Technologists has been “relentless” in FINTECH. We agree. The best sources of candidates for these skills are going to be colleges like the University of Chicago where we get many of our interns. However, that doesn’t mean that you can’t participate. The best people are not the current students. The best people are the subject matter experts that grow their own skills. Pick up your skills. Attend online classes on Python, Math, and AI. Learn how to apply statistics. Many people are using our own platform to grow their quant skills this year. Here are a couple of resources that I have used:

Machine Learning for Trading

…Direct link to article: The purpose of this paper is to discover whether it is possible to train a machine-learning algorithm to behave as a risk-adverse investor by using a dynamic model involving transaction costs. Transaction costs are frequently overlooked due to the complexity of integrating them into the learning algorithm used to train the trading system. By specifying a series … 2017-12-29 00:00:00 CloudQuant Thoughts: Not everyone was taking time off over the new year. Some new research for Machine Learning and Trading was posted.

How Do You Vote? 50 Million Google Images Give a Clue (AltData from Photos)

…rd car project generated a host of intriguing connections, not so much startling revelations. In the most recent paper, and one published earlier in the year by the Association for the Advancement of Artificial Intelligence, these were among the predictive correlations: ■ The system was able to accurately predict income, race, education and voting patterns at the ZIP code and precinct level in cities across the country. ■ Car attributes (including miles-per-gallon ratings) found that the greenest city in America is Burlington, Vt., while Casper, Wyo., has the largest per-capita carbon footprint. ■ Chicago is the … 2017-12-31 00:00:00 CloudQuant Thoughts: The best quote in this article is “The significance of the project, experts say, is a proof of concept — that new information can be gleaned from visual data with artificial intelligence software and plenty of human help.” This is a huge new area of Alternative Data. We find projects like this to be really interesting. What happens when you apply this to the number of cars in a commuter or factory parking lot? Can you get predictions on economic factors that represent tradeable factors?

AI and Deep Learning in 2017 – A Year in Review

…ry of the year was probably AlphaGo (Nature paper), a Reinforcement Learning agent that beat the world’s best Go players. Due to its extremely large search space, Go was thought to be out of reach of Machine Learning techniques for a couple more years. What a nice surprise! The first version of AlphaGo was bootstrapped using training data from human experts and further improved through self-play and an adaptation of Monte-Carlo Tree Search. Soon after, AlphaGo Zero (Nature Paper) took it a step further and learned to play Go from scratch, without human training data whatsoever, using a technique a technique … 2017-12-31 14:59:46+00:00 CloudQuant Thoughts: A very good review of 2017. There has been a lot happening out there and it is difficult to stay up to date. This is one of the reasons that we publish this news every week.

Your Year on Kaggle: Most Memorable Community Stats from 2017

…2017 has been an exciting ride for us, and like last year, we’d love to enter the new year sharing and celebrating some of your highlights through stats. There are major machine learning trends, impressive achievements, and fun factoids that all add up to one amazing community. Enjoy! Public Datasets Platform & Kernels It became clear this year that Kaggle’s grown to be more than just a competitions platform. Our total number of dataset downloaders on our public Datasets platform is very close to meeting the total number of competition dataset downloaders – both around 350,000 … 2017-12-26 00:00:00 CloudQuant Thoughts: Kaggle is proof that crowdsourcing works.

AI Weekly: AI democratization depends on tech giants

…urrently hoovering up much of the world’s AI talent supply? Google chief scientist Fei-Fei Li has talked about it in relation to tensor processing units, and CEO Sundar Pichai in relation to AutoML, machine learning made to create machine learning. Microsoft CEO Satya Nadella describes democratization as putting AI in the hands of “every developer, every organization, every public sector organization around the world.” The implications of AI that touches every industry and sector of society demand that tech giants consider democratization beyond championing the use of their own AI services. This year, step… 2017-12-28 00:00:00 CloudQuant Thoughts: It also depends upon the people. It has to be interesting and rewarding.

Meet The Woman Behind Woebot, The AI Therapist

…ms. And this pace is really too fast for our systems to respond. While I was at Stanford I started collaborating with Andrew Ng in his lab and started to become really interested in the potential for artificial intelligence to be able to address this in a meaningful way. I decided to leave academia and really pursue and test different technologies with a view to be able to launch something as a direct to consumer product. There’s just such a huge need for something like that. Woebot came from a lot of design sessions and really trying to craft not just how to build an effective support for mental health online but … 2017-12-31 00:00:00 CloudQuant Thoughts: Women are innovating in all areas of technology. We love seeing ventures like this one succeed.

Esperanto exits stealth mode, aims at AI with a 4,096-core 7nm RISC-V monster

…Monster Although Esperanto will be licensing the cores they have been designing, they do plan on producing their own products. The first product they want to deliver is the highest TeraFLOP per Watt machine learning computing system. Ditzel noted that the overall design is scalable in both performance and power. The chips will be designed in 7nm and will feature a heterogeneous multi-core architecture. There are 16 of the large OoOE ET-Maxion cores with their own private L1 and L2 caches. Additionally, Ditzel said they plan on putting 4,096 ET-Minion cores – each with everything noted above. That is, each o… 2018-01-01 10:45:47+00:00 CloudQuant Thoughts: Wow. Sounds interesting. Wonder if their product is available on AWS or Google cloud. Does anyone know?

The $15 Minimum Wage Movement Is Winning, And That’s Bad News For Cashiers

… business enterprises do not have tax payers to pay the bills. This means that they must find other ways to cope with minimum wage hikes like the substituting of workers with automation equipment and artificial intelligence software. That’s especially the case for shopping malls and other retailers that have been under pressure from competition from on-line retailers; and restaurant owners who have been facing soaring rents and all sorts of labor regulations. In fact, Wal-Mart, Target, Home Depot and the like have been experimenting with self-checkout counters, while McDonald’s, Panera Bread and other franchise ou… 2018-01-01 00:00:00 CloudQuant Thoughts: We wonder if there are tradeable ideas here? Which traded companies are seeing a boost in sales as automation replaces workers?

AI operators will play a critical role as bots redefine the workplace

…omewhere between them and us is the AI operator, whose ability to speak robot will help man and machine move beyond these initial growing pains. Tomer Naveh is chief technology officer at Albert, an artificial intelligence marketing platform for the enterprise…. 2017-12-29 00:00:00 CloudQuant Thoughts: This answers some of our previous questions.

The 12 Worst Tech Pitches Of 2017 That I Can Remember, Ranked

… Lalafo can extract a lot of information just from a single image. Then analyse and compare it, suggest a price and show the listing to people who are the most likely to be interested in it. By using machine learning and analysing multiple data sources for each user, Lalafo wants to alert you when you stopped using that cool brown bag or chic green jacket seen in your selfies. Lalafo wants to help you remember what you have and make suggestions for what you may want to sell next, how much money you could make and how many people would like to buy it. 2. … 2017-12-30 00:00:00 CloudQuant Thoughts: Really? I had to read this out of morbid curiosity. Ouch.
chicago cityscape and sears tower

STAC MidWinter Conference January 10-11, 2018

CloudQuant will be participating in the STAC MidWinter Conference on January 10-11 2018. Our CEO, Morgan Slade, will be a panelist on the Artificial Intelligence panel discussion.
Stock Market, Quantitative Strategy, Trading, and Algo Development Industry News

Industry News: Machine Learning and Artificial Intelligence for December 26, 2017

Never Mind Bitcoin. China Loves AI Stocks

…ofit estimates. And yet it’s one of the hottest stocks in China, gaining 117 percent this year as of Dec. 18, thanks to the latest investment craze sweeping the country’s $7.5 trillion equity market: artificial intelligence. Iflytek and other AI-related companies are dominating gains among large-cap Chinese stocks. The buying frenzy has added $61 billion of market value to China’s five most popular AI plays, vaulting some into the ranks of the world’s most actively traded securities. BOE Technology Group Co., a Beijing-based maker of LCD panels that’s developing a system to help drivers avoid traffic accidents, had… 2017-12-20 00:00:00 CloudQuant Thoughts:  “AI-related companies are dominating gains among large-cap Chinese stocks…” Hmmm. Makes one wonder what sort of classifications would allow you to identify a company as “AI-Related”. Our industries are categorized and standardized. For example, Moriningstar uses 11 standard classifications: Basic Materials, Communication Services, Consumer Cyclical, Consumer Defensive, Energy, Financial Services, Healthcare, Industrials, Real Estate, Technology, Utilities) Do these still make sense to you? Where does Amazon properly fit? Are they a Consumer Cyclical because they are a retailer? Should they be considered Technolgy because they host computers? Maybe you as an algo creator or data scientists should think in terms of creating your own classifications based on what the company is doing today. What companies fall into your category of “AI-Related”? How are they doing in comparison to other companies that haven’t launched AI-Realted projects? Looks like there is an opportunity here for you to seek alpha!

Future looking bright for active management

… said Keith Lewis, head of Americas for T. Rowe Price Group Inc.’s global investment services division, Baltimore. Technology on the rise Industry insiders also foresee technology — everything from artificial intelligence and big data to machine learning and risk analytics — will play a significantly increased role within money management. “AI and big data being used to generate alpha is incredibly important. Likewise, with risk analytics to construct portfolios,” said Geraldine Buckingham, BlackRock (BLK) Inc. (BLK)’s global head of corporate strategy in New York. “Every asset manager has to consider how the role of technology plays into their business,” she added. … 2017-12-25 00:00:00 CloudQuant Thoughts: Quantitative portfolio managers have always relied on technology and innovation. We have seen portfolio managers move from using Bloomberg terminals and excel spreadsheets 20 years ago to using Jupyter Notebooks, Python, and sophisticated data science techniques today. Any money manager who isn’t using innovative data science into their daily jobs is likely to fall behind on their ability to keep up with changing markets. The recommendation to diversify into alternative investments in this article provides an interesting and compelling argument. Environmental, Social, and Governance (ESG) in one’s portfolio is a great idea. We strongly believe that portfolio managers should add technical and quantitative skills to their personal skills portfolio to help them grow in capabilities to serve their investors.

FinTech Start-Up ForwardLane’s New APIs for Personalized Insights

…FinTech Start-Up, ForwardLane’s New AI APIs for Personalized Insights ForwardLane, a FinTech start-up based in New York City, is a next generation artificial intelligence (AI) company using machine learning to aggregate and scale firm-specific content, market data news, investment research, product materials, and strategic analytics for financial professionals to deliver personalized stories for their clients. ForwardLane’s two configurable APIs leverage natural language processing and deep learning AI for advisory, sales and distribution professionals. The first… 2017-12-20 00:00:00 CloudQuant Thoughts: At the Newsweek AI conference in early December our CEO pointed out that there are hundreds of Alternative Data (AltData) providers and the number keeps growing. Using natural languge processing to develop trading signals from written and spoken content is on the increase. Numerous data scientists are using some of these AltData sources in their trading algorithms already.

Sophisticated cyber threats and being ready for GDPR are major concerns for finance sector IT pros

…ted to modernisation. Respondents were also asked to rank the relevance of various emerging technologies, and cited Intelligent Process Automation as the most useful to their business, followed by Artificial Intelligence (35 per cent) and Predictive Modelling (33 per cent). Blockchain ranked lower in terms of perceived relevance (25 per cent) and was only currently used by a fifth of those surveyed within their organisation. Fintan Galvin, chief executive officer at Invotra, says: “It’s clear from our study that finance technology professionals understand the need to drive change. But, they are charged with pr… 2017-12-21 00:00:00 CloudQuant Thoughts: Cyber threats aren’t going away. This has been a major initiative for the financial industry over the past 5 years and will continue to grow.

Automation Will Create More Fulfilling Work

…cale unemployment. In fact, SpaceX and Tesla co-founder Elon Musk, along with Bill Gates and Stephen Hawking, have expressed such concerns. Last month, amidst North Korean tensions, Musk tweeted that artificial intelligence (AI) posed a greater risk than the country’s nuclear capabilities. This is not the first time Musk has voiced caution on the topic; he’s repeatedly said that AI and automation are the “biggest risk we face as a civilization” and that “robots will do everything better than us.” In response, Facebook CEO Mark Zuckerberg has challenged Musk, calling “people who are naysayers and try to drum up these… 2017-12-25 10:56:05-05:00 CloudQuant Thoughts: Fearing innovation has never helped grow an economy. We all value the innovations that advance our society. Yes, in some cases that technology is a “job killer” but at the same time, it opens opportunities in other areas. I was recently reminded of how innovation changed the world in watching Hidden Figures. The movie showed the introduction of the computer to NASA. While the mathematicians could have resisted and complained about the “job-killing” possibilities of the computer they didn’t. They saw that the computer brought opportunity. With a little re-tooling, a little effort, and without fear they learned the new skills needed to be valuable. Robots may do some things better than us. Ok. We all know that. So What? The rate of change is ever increasing. Let the robots have the old stuff as we focus on the future! Robots are incapable of automating innovation.

Facebook to demote posts fishing for Likes

… Facebook worries it might be bad for you, adds a mute button “To help us foster more authentic engagement, teams at Facebook have reviewed and categorized hundreds of thousands of posts to inform a machine learning model that can detect different types of engagement bait,” the company said in a blog post. “Posts that use this tactic will be shown less in News Feed.” The company said it will have stricter demotions for repeat offenders. It added that page administrators looking to increase brand reach on the site should “focus on posting relevant and meaningful stories.” The update will be rolled out over … 2017-12-18 00:00:00 CloudQuant Thoughts: Nice. Hope that their machine learning and data science team have truly found a way to have a more authentic user engagement. Did you notice the link to the previous link? In this case Facebook has created new opporutinities using AI. The jobs created here didn’t exists last year. Learning how to use big data to improve the user experience is a high growth job opportunity.

Generational Tech Shift to Transform Trade Lifecycle

…tion of new technologies. As global financial markets continue to evolve, the real opportunities are yet to be delivered in transparency and efficiency for investors.” Distributed ledger technology, machine learning, portfolio optimisation techniques and the cloud are being used today but the paper said the challenge for markets and policy-makers is to harness this potential while managing its new risks. “Neither legacy systems nor policy inertia should be allowed to stifle this generational opportunity,” added NEX. Mark Whitcroft, founding partner at venture capital firm Illuminate Financial Management, s… 2017-12-18 03:39:54+00:00 CloudQuant Thoughts: The idea of using best of breed components to put together a trading system, or a regulatory system isn’t new. Making use of third-party components without violating license agreements or intellectual property is going to be a real challenge in our trading industry.

Today in Technology: The Day the Horse Lost Its Job

…erviced cars and that utilized motorized vehicles for transportation and delivery. [17] There are interesting insights to be gleaned from the shift from horses to automobiles. As with automation and artificial intelligence in our own day, it was a shift driven by new technology. But it wasn’t driven by technology alone, and its ultimate impact in many ways was by no means predictable at the time. As one author has noted, what appears today as obvious – the transition from horses to cars – was in many respects far less than inevitable. As she points out, “the replacement of animal power took a particular form that … 2017-12-21 00:00:00 CloudQuant Thoughts: Another historical reference, written rather nicely, to remind us that the innovations caused by AI and Big Data shouldn’t be feared and should be embraced. Plus, who can resist reading an article that includes firemen and horses?

‘Decision intelligence platform’ Element Data raises another $2.6M to fuel growth

…n Element Data is now $7.8 million. The fresh cash will help the year-old company increase sales and marketing efforts for its flagship product, Decision Insights Computing Engine (DICE), which uses artificial intelligence and machine learning to help people make decisions based on a broad range of criteria. It’s been a busy 2017 for Element Data, which bought three companies this year and now employs 25 people. In April, it acquired the technology and team of PV Cube, a Seattle machine learning startup led by two vets of Microsoft Cortana and Bing. In October, it bought the assets and patents of BehaviorMatrix, a… 2017-12-24 20:05:46+00:00 CloudQuant Thoughts: We wonder what sort of AltData is available from them. Is anyone in the crowd interested?
85 Percent of Data is Unstructured

Is Crowdsourced Data Reliable?

“Bring us your ideas and we will share the money with you,” agreed Morgan Slade, CEO of the crowdsourced algorithmic trading startup CloudQuant. “For us, engagement means breaking it down into a contractible problem.”

Futures Radio Show interviews Morgan Slade December 12, 2017

CloudQuant’s CEO was interviewed by Anthony Crudele of Futures Radios show to discuss topic including Artificial Intelligence, Machine Learning, and Deep Learning applied to algorithmic trading. Alternative datasets are a major topic of discussion. People are saying that data is being created faster than ever before. That really isn’t true. What is really happening is that data is being captured and stored at a faster rate than ever before. Vendors are now making AltData available for traders to change the way that they interact with the markets. This applies to futures and stocks with the popularity of Deep Learning in algorithmic trading strategy development.
Quantitative Strategy, Trading, and Algo Development Industry News

Industry News: Machine Learning and Artificial Intelligence for December 11, 2017

Hedge funds embrace machine learning—up to a point

ARTIFICIAL intelligence (AI) has already changed some activities, including parts of finance like fraud prevention, but not yet fund management and stock-picking. That seems odd: machine learning, a subset of AI that excels at finding patterns and making predictions using reams of data, looks like an ideal tool for the business. Yet well-established “quant” hedge funds in London or New York are often sniffy about its potential. In San Francisco, however, where machine learning is so much part of the furniture the term features unexplained on roadside billboards, a cluster of upstart hedge funds has sprung up in order to exploit these techniques. These new hedgies are modest enough to concede some of their competitors’ points. Babak Hodjat, co-founder of Sentient Technologies, an AI startup with a hedge-fund arm, says that, left to their own devices, machine-learning techniques are prone to “overfit”, ie, to finding peculiar patterns in the specific data they are trained on that do not hold up in the wider world. This is especially true of financial data, … 2017-12-09: CloudQuant Thoughts: Traditional hedge fund managers may be concerned with AI and machine learning. CloudQuant embraces it. We have found that the CrowdSourcing model allows for new talent to join in the research activities. A thousand researchers with access to industrial grade historical market data, backtesting tools, and alternative data can discover new ways of trading that a traditional quant at a hedge fund may not see. Our record of allocations demonstrates that this is working well for us.

Demand for AI Talent Turns Once-Staid Conference Into Draft Day

Actors in robot costumes stood in the lobby of the Westin hotel in Long Beach, California on Sunday night, “Intel Inside” stickers displayed on their foam torsos. People posed for selfies before heading to an upstairs ballroom, decorated with neon purple lighting and plush white leather furniture, for an event that was more party than technology panel discussion. This was one of many attempts by Intel Corp. and other giant corporations to curry favor with artificial-intelligence researchers attending one of the world’s biggest AI conferences, turning what was once an academic event into a recruiting frenzy more akin to the National Football League’s draft day. Tech companies are increasingly competing with one another, as well as banks and hedge funds, to hire experts in AI techniques like neural networking, a kind of machine learning loosely based on how the human brain works. These are the skills behind recent advances in computers’ ability to identify objects in images, translate languages, drive cars and spot financial fraud. More changes are in store for many industries and conferences like this week’s one on Neural Information Processing Systems, aka NIPS, are where … 2017-12-06: CloudQuant Thoughts: It is fun seeing financial firms mentioned alongside the technology firms that you typically expect to see in a conference like this. Anyone in trading will fully understand that trading firms have been very technology-centric for the past decade. The introduction of Machine Learning, Deep Neural Network, and applied AI into the FINTECH discussions, and the recruiting process is not surprising.

This Harvard PhD’s AI Startup Aims to Help Analysts Triple Coverage

…After applying his machine learning programs to central bank policy statements to churn out trading calls, a hedge fund-backed political economy specialist is aiming his sights on corporate earnings announcements. Evan Schnidman, a 31-year-old who set up his own firm after a Harvard University PhD dissertation that looked at the Federal Reserve’s communications, is hoping the approach that lured $3.3 million in a fund-raising roun… 2017-12-11 00:00:00 CloudQuant Thoughts: The article ends with “Demand for data scientists and machine-learning professionals in finance ‘far exceeds the current supply,‘” We see that many universities and programs are gearing up to meet this demand. Those that want to learn and practice skills are always welcome to grow their data science and machine-learning skills on our CloudQuant platform.

3 Questions with Dr. Sean Wise of Ryerson Futures Seed Fund

…inancing round. What do you believe the next major innovation in financial technology will be and why? I believe the next major innovation in financial technology will be the wide integration of AI/Machine Learning into customer service chat-bots. The majority of customer service queries are mundane and routine (e.g. I lost my PIN what do I do). This is just an awful job for humans and outsourcing to developing nations has not solved it. Chatbots offer an exponentially better more scalable solution to better customer service. The volume of queries, the routineness of such and the current level of semantic … 2017-12-10 14:05:55-05:00 CloudQuant Thoughts: Fintek News interviewed our CEO prior to chatting with Dr. Wise. You can find and compare answers from Dr. Wise with Morgan Slade’s answers by reviewing our earlier inteview at

Hedge fund managers embrace innovation amid industry challenges and increased competition

…gin pressures by investing in technology. Forty per cent say they plan to invest in automating manual processes and more than a quarter of managers (27 per cent) have or will be making investments in artificial intelligence and robotics to strengthen their middle and back office. Zeynep Meric-Smith, EMEIA Leader, Hedge Fund Services, Ernst & Youn, says: “Managers with growing businesses will often need to add to their headcount to support the business, but modern advances in technology provide helpful solutions in supporting operating models that add to the bottom line, rather than reduce it.” The need for tec… 2017-12-08 00:00:00 CloudQuant Thoughts: In this article it says “Investors are looking for managers who can effectively implement next generation data to gain an advantage, according to the survey. Managers are beginning to notice that effective use of data is a key advantage,” CloudQuant firmly believes this. Our crowd researchers are finding alpha in new ways, using new data sets. We believe that our experience is indicative for the future of most investment managers and traders.

Big data solutions to take a bite out of fraud

…nd harnessing the massive quantities of data produced each day, companies hope to uncover potential fraud as it occurs. The most optimistic believe that the predictive capabilities of big data-driven artificial intelligence may someday end online crime altogether. That may well come to pass, but it will be an uphill climb. The current state of affairs The internet represents an ever-larger portion of global retail sales each year. Estimates indicate that e-commerce transactions alone will reach $2.3 trillion dollars this year. Digital platforms also generate enormous amounts of advertising revenue and related busi… 2017-12-08 11:00:34+00:00 CloudQuant Thoughts: This is another article in the trend of articles talking about using AI, ML, and evolving computer tools and techniques to detect fraud. We recently posted on our blog about these tools and techniques related to Algos and Ethics.  The FINTECH & REGTECH industries have been rather busy in applying AI/ML to fraud. Here are some actions and innovations that we have seen in the world of electronic trading covering regulators and vendors. AI, Algo Trading and the Regulators and Watchdogs AI, Algo Trading, and the Innovative Firms
  • Vertex Analytics with their amazing ability to see patterns in the market data and highlight cheaters.
  • Trading Technologies’ Neurensic product that uses machine learning to catch spoofers, front-runners, layering, pump and dump, and more forms of illegal trading.
  • Edge Financial Technologies and their KillSwitchPlus tool that catches run away algos and limit breaches at the time of the order.
  • Catelas with its surveillance ability to catch collusion between traders or inappropriate use of insider data.

5 Scary Things That Won’t Crash the Market in Next 5 Years

…o the CFA Institute highlighted 5 disruptive forces influencing the future of global investing. I think these forces are vitally important, but will not “crash” the market in the next five years: 1. Artificial intelligence, big data and machine learning will be disruptive forces, but humans will still play an important role in providing investment management and financial advice. Quantitative algorithms are increasingly used to identify past patterns and subtle trends in large sets of data. Quantitative models may be superior to humans in looking through the rearview mirror, but humans still may be better equipped … 2017-12-04 00:00:00 CloudQuant Thoughts: We don’t consider big data, AI, or machine learning to be scary. We also agree that we don’t believe that this will be the direct cause of any future market crash.

The Computer That Saved a Vineyard

… fire. He hosed down embers as they flew off the frame. Yet the winery survived the worst disaster in the history of California’s wine country unscathed, because Palmaz wasn’t alone, exactly. He had artificial intelligence on his side. Palmaz Vineyards’ winemaking takes place in an engineered maze of tunnels and domes carved into rock at the base of Napa’s Mount George. Source: Palmaz Vineyards Felix is the nickname for the Fermentation Intelligence Logic Control System (Filcs), software Palmaz engineered to analyze and, eventually, help micromanage the vineyard’s 36 winemaking tanks. Using technology developed b… 2017-12-06 00:00:00 CloudQuant Thoughts: We will drink to that! We may need to order a case or two for our Holiday party. You can find the vineyard at

Microsoft doubles down on its ‘AI for Earth’ initiative, pledging $50M at Paris climate event

…Microsoft today pledged $50 million over five years for an initiative to use artificial intelligence to tackle the world’s most pressing environmental issues. Microsoft President and Chief Legal Officer Brad Smith will detail the company’s commitment to the program, known as AI for Earth, at the One Planet Summit in Paris later today. Started earlier this year, AI for Earth aims to put Microsoft’s vast AI resources in the hands of universities, non-governmental organizations and other groups to… 2017-12-11 11:01:28+00:00 CloudQuant Thoughts: Private industry is taking initiative and leadership using AI to solve an issue that many are concerned with globally. Nice move Microsoft.

What Does Your Cloud Data Look Like? QuantHouse Is Moving Historical Data On-demand To The Cloud

… also looking at the metadata space. Firms can now take their own trading information and identify better performance strategies for traders, or weed out problems with a particular strategy. Layer in artificial intelligence and machine learning tools and you can see the potential for firms and another phase of competition. QuantHouse moved to bolster its overall service offering with the acquisition of Victory Networks in September, giving it further reach in the high speed network space, especially for hedge funds and asset managers. Feligioni believes his firm is now well positioned for that client base which is … 2017-12-08 00:48:00+00:00 CloudQuant Thoughts: Nice move QuantHouse. We like what you are doing. We also find that the cloud’s power for computing cycles provides a major opportunity for the industy.

Nasa to hold major announcement after artificial intelligence makes major planet-hunting breakthrough

…ly relate to exoplanets – Earth-sized worlds that orbit around their own stars, and are our best hope of finding alien life. The space agency said that the discovery was made with the help of Google artificial intelligence, which is being used to analyse the data sent down by the telescope. By using machine learning provided by the tech giant, Nasa hopes that it can pick through the possible planets more quickly and hopefully find life-supporting planets sooner. Nasa said that four engineers and scientists would take part in the session. They include Paul Hertz, who leads Nasa’s astrophysics division, a senior Goo… 2017-12-11 08:53:56+00:00 CloudQuant Thoughts: We already knew that machine learning is “Out of this world” but this just proves the point.

Apple’s AI Chief Reveals Fresh Details About The Car Project

…researchers to share their work – primarily related to the car project – with the wider scientific community. Apple car project: It can detect objects hidden behind parked cars Speaking at the NIPS machine learning conference (via Wired), Apple’s AI director Ruslan Salakhutdinov provided some previously unpublicized details about the self-driving car technology. He offered a sneak peek into how Apple is using artificial intelligence and machine learning to detect pedestrians and make autonomous driving safer. More than 8,000 people attended the NIPS conference. He demonstrated a system that can identify ob… 2017-12-11 06:43:07-05:00 CloudQuant Thoughts: The trend is to be more open with technology. We see it in open source and crowdsourcing. Apple, with a very loyal community of users, always has a great opportunity to be a thought leader and not just an innovation leader. We like seeing them be more open.

Quantitative Brokers Appoints Ralf Roth as CEO

…ch he will join. Roth will begin as CEO effective December 18th. “After a comprehensive search process, we are thrilled to appoint Ralf Roth as CEO. Ralf brings strong leadership and experience with machine learning and cloud computing that will help us scale and expand on the innovation that defines QB in the market,” said Christian Hauff, Co-Founder and outgoing CEO of Quantitative Brokers. Hauff will continue on as a member of QB’s Board and Executive Committee and will oversee the firm’s client and industry relationships. “Ralf is very well placed to succeed me in the role of CEO and I look forward to as… 2017-12-08 00:00:00

Google’s AI teaches itself chess in 4 hours, then convincingly defeats Stockfish

…There has just been a revolutionary development in the world of AI, and in the world of chess. Google’s Artificial Intelligence project, DeepMind explains they’re on a scientific mission to push the boundaries of AI, developing programs that can learn to solve any complex problem without needing to be taught how. A little over a year ago, DeepMind released AlphaGo, which sensationally defeated the world champion of the famously CPU unfriendly ancient Chinese game, GO. Now their AlphaZero program has kicked up a storm in … 2017-12-09 17:16:47+00:00 CloudQuant Thoughts: Why does everyone want to play chess with AI and Machine Learning? We want to see some Machine Learning project team take on Settler Of Catan!

CityBldr raises cash, prepares to expand to California with software that reveals hidden real estate value – GeekWire

…icer at Touchstone earlier this year. Initially, CityBldr was focused on residential properties but now has expanded its service to cover nearly all types of real estate. “What we’ve learned is our machine learning algorithm doesn’t care if its a house, or an apartment, or a gas station, or a vacant parcel of land, or a commercial building, or an office building … it doesn’t care at all,” Copley said. “It just sees that there’s opportunity in that land and it predicts the highest and best use of that land.” CityBldr is hoping to hire a team of about seven in Los Angeles and bring on an additional 15 to 20 … 2017-12-07 23:47:18+00:00 CloudQuant Thoughts: In Chicago, there is the unused old post office. The building is huge and spans a highway that most people in the western suburbs use. We wonder what CityBldr would recommend to the Chicago mayor about this building?
Quantamental alternative data

The Rise of Quants in Trading and Financial Markets

Cloud computing and access to industrial grade investment and data science tools are changing the playing field for quantitative trading firms. CloudQuant’s CEO Morgan Slade participated in a panel at Stocktoberfest West in October 2017. This has raised the discussion of quantamental investment and data science techniques. This is the merger of technology, investment management, and data science.
Quantitative Strategy, Trading, and Algo Development Industry News

Industry News: Machine Learning and Artificial Intelligence News November 6, 2017

AI and ML for investing, ETFs, Cliff Asness, BofE, Manifold Partners, Japan’s bank, SoftBank, lack of skilled AI teammates, Uber, MarketX, fake news, …
Machine Learning, Quantitative Investing News

Industry News: Machine Learning and Artificial Intelligence News 10/30/2017

AI and ML for CloudQuant, ArcaEx, Corporate earnings reports, Hedge Funds, Microsoft, Alexa, Saturday Night Live, the apocalypse, Elon Musk, and more …
Stock Market, Quantitative Strategy, Trading, and Algo Development Industry News

Industry News: Machine Learning and Artificial Intelligence News

ML for Banking, New York, Google/Deepmind,, God & Dan Brown, Natural Language Processing (NLP), IoT, and more…