Hedge Funds
A hedge fund is an alternative investment fund available only to sophisticated investors, such as institutions and individuals with significant assets. These funds typically utilize a variety of investing techniques and asset classes to achieve their return on assets for the fund investors.
Artificial Intelligence, Machine learning, and crowdsourced algorithmic trading platforms are challenging professional fund managers as the tools, data, and data science techniques powerful enough to forecast market moves better are becoming more readily available to anyone with an internet connection.
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$TSLA Skyrocketed Ahead of Stock Split
BlogESG for the Short Seller with Alt Data
Blog, Industry NewsEnvironmental, Social, & Governance (ESG) Short Term Trading
BlogShort-term ESG data is showing some very interesting opportunities. Our recent whitepaper shows that 5-day and 20-day positions are profitable.
Spot checking the white paper shows the following simulated trades from last week.
The simulated trades were MOO on Monday, MOC on Friday.
$ADBE ESG Simulated Trading, 5 Day Hold

$DE ESG Simulated Trading, 5 Day Hold

$FOX ESG Simulated Trading, 5 Day Hold
Quants discuss evaluating and adapting their models – Including CloudQuant
CloudQuant Press, PressMarket Turmoil Generates Opportunity for Proprietary Traders
Blog, CareersMeet The Niche Manager – Quantitative Managers. January 26, 2018
CloudQuant Press, PressPeltz International seminar Meet the Niche Manager on January 26, 2018
Artificial Intelligence (AI) and Machine Learning (ML) STAC Conference Summary
CloudQuant Press, Industry NewsIndustry News: Machine Learning and Artificial Intelligence for December 11, 2017
Industry NewsHedge 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: https://www.economist.com/news/finance-and-economics/21732147-investing-more-artificial-intelligence-need-not-mean-less-human 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: https://www.bloomberg.com/news/articles/2017-12-06/demand-for-ai-talent-turns-once-staid-conference-into-draft-day 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 https://www.bloomberg.com/news/articles/2017-12-11/harvard-phd-s-ai-startup-aims-to-help-analysts-triple-coverage 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 http://finteknews.com/3-questions-dr-sean-wise-ryerson-futures-seed-fund/ 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 http://finteknews.com/3-questions-john-morgan-slade-cloudquant/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 http://www.hedgeweek.com/2017/12/08/259158/hedge-fund-managers-embrace-innovation-amid-industry-challenges-and-increased 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 http://bigdata-madesimple.com/big-data-solutions-to-take-a-bite-out-of-fraud/#Comment 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- Improved surveillance tools and techniques being championed and shared within the industry including the Futures Industry Association’s Market Access Risk Management Recommendations best practice white paper.
- Exchange hosted and trading system mandatory pre-trade limits and speed limits (CME Globex Credit Controls, Eurex pre-trade controls, CQG, Trading Technologies, Fidessa, and more)
- New registrations and training, (like the FINRA series 99 registration for IT and operations staff)
- Regulators working with federal policing agencies to criminalize cheaters, especially spoofing. (Reference FBI and Michael Coscia of Panther Energy)
- 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.