Quantitative Trading

Quantitative trading utilizes trading strategies based on quantitative analysis to systematically identify trading opportunities and to execute trades as identified. A Quant trader may work for the buy side or sell side of the trading industry. Buy side quants are looking to trade for investment purposes. These trades typically seek to make a profit from either short-term price movements (alpha) or from longer-term investment returns (beta.) Sell side quants provide quantitative trading in their brokerage activities. The sell side algos are typically accumulation type strategies (i.e. volume weighted average pricing – VWAP) that help investors get the best price for their overall order.

Quantitative trading techniques include high-frequency trading, sentiment analysis trading, and statistical arbitrage.

Quantitative trading is not synonymous with High-Frequency Trading (HFT) even though all HFT firms employ some form of algorithmic trading.

CloudQuant utilizes crowd researchers to provide the quantitative analysis that is then used by our quantitive traders.


bulls and bears

Quantitative Trading & Algos News. 20, April 2018

News clippings covering Quantitive Trading, Trade Strategy, and Quant Finance. Algo developers and traders in the crowdsourced community can see terms or phrases which drew the attention of our portfolio managers and product team.

Strategy Diversification: Combining momentum and carry strategies within a foreign exchange portfolio

…pared to the returns of two indices, the S&P500 and the BTOP50, to determine if their combination leads to an improvement in risk-adjusted returns. The strategies used are two common foreign exchange trading strategies– the momentum strategy and the carry strategy. Data from the 20-year period 1993-2013 on eight of the major currencies is used. The first trading strategy, momentum, relies on the existence of sustainable price trends. These trends are driven by an increase in liquidity demands, which can be caused by increased market risk (as greater hedged risk leads to greater demand) as well as the buildup o… 2018-04-13 13:43:58+00:00 https://www.quantnews.com/strategy-diversification-combining-momentum-carry-strategies-within-foreign-exchange-portfolio/ CloudQuant Thoughts: In everything we do, we use algorithms of some sort. Our approach to trading strategy and risk allocation is strongly influeneced by AI.

Instinet fined for algo trading and market access breaches

…ved execution priority over proprietary orders within its alternative liquidity pool, alongside general failures to maintain risk management controls and the smart order routing of its electronic and algorithmic trading systems. When deciding on the penalty, the SFC said it took into consideration that Instinet fully cooperated with the regulator and carried out independent reviews to identify problems with its systems. Instinet was also penalised in the US last week by the Financial Industry Regulatory Authority (FINRA), and major exchange operators including Nasdaq, NYSE and IEX, for market access violations… 2018-04-16 13:38:48+01:00 https://www.thetradenews.com/instinet-fined-for-algo-trading-and-market-access-breaches/

Pragma Securities commits to FX Global Code

…duct suite can play an important role in helping market participants meet their best execution, transparency and ethics obligations. Mechner adds: “In today’s fragmented and fast moving FX market, algorithmic trading and trade analytics are indispensable tools for achieving and demonstrating best execution. As an independent vendor, Pragma will continue to help our customers achieve their business objectives under the FX Global Code.” … 2018-04-19 00:00:00 http://www.hedgeweek.com/2018/04/19/263380/pragma-securities-commits-fx-global-code  

SEC Charges Advisor in $1.4 Million Fraud Scheme: Enforcement

…According to the complaint, Chahal lured investors by falsely claiming to be an experienced and successful trader who could generate above-market returns for clients through a low-risk trading strategy. In reality, Chahal had substantially no experience working in the financial or securities industry or trading securities on behalf of clients. The complaint further alleges Chahal initially invested client funds in a variety of investments, but suffered significant trading losses. According to the complaint, instead of disclosing the losses, Chahal lied to his clients about their investment ret… 2018-04-20 00:00:00 https://www.thinkadvisor.com/2018/04/20/sec-charges-advisor-in-1-4-million-fraud-scheme-en/

Video: When Analyzing General Electric, Take Stock of Your Cost Basis

…day, following better than expected earnings. When analyzing the stock, it’s important to take stock of your cost basis, or the price you paid to enter the stock, according to Shawn Cruz, manager of trading strategy at TD Ameritrade. GE shares are down 50% over the past year. For exclusive investing insight from Jim Cramer, get 24/7 access to Jim’s charitable trust portfolio with a free trial to Action Alerts PLUS! Subscribe to our Youtube Channel for extended interviews, Cramer Replays, feature content, and more!… 2018-04-20 11:01:12-04:00 https://www.thestreet.com/video/when-analyzing-general-electric-take-stock-of-your-cost-basis-14562929

Manipulation of the CFD market in Australia? Eat porridge for two years

… are potentially damaging to CFD issuers if followed assiduously. CySec’s rules effectively prohibit negative slippage. Over a prolonged period of time and in a market full of scalpers (clients whose trading strategy is to ‘hit’ brokers off-market) this could result in the bankruptcy of brokers. The author commends the NFA and FCA for their rules on fair market pricing. Though, different in their approach, both operate to ensure that brokers can operate within the general market while prohibiting nefarious behaviour when it comes to pricing of the financial instruments. – James O’Neill, Director, ILQ Australi… 2018-04-10 12:14:50+03:00 https://financefeeds.com/manipulation-cfd-market-australia-eat-porridge-two-years/

Alphabet Stock May Complete Long-Term Top

… deal because the March decline tested four-year wedge support, raising the odds for an eventual breakdown that drops the stock into a primary downtrend. [Learn to analyze stock charts and develop a trading strategy in the Technical Analysis course on the Investopedia Academy] GOOGL Short-Term Chart (2016 – 2018) Volatile price action since October 2017 has carved a potential double-headed head and shoulders top that requires a steep descent from current levels to complete the right shoulder. A breakdown would generate a 200-point measured move target, dropping the stock below $800. The 200-week exponentia… 2018-04-20 08:23:00-06:00 https://www.investopedia.com/news/alphabet-stock-may-complete-longterm-top/

3M Company Reports Oversold, Below Key Levels

…t $76.2 during the week of Oct. 14, 2011. The 12x3x3 weekly slow stochastic reading is projected to end this week at 17.13, below the oversold threshold of 20.00. Given these charts and analysis, my trading strategy is to buy weakness to the April 2 low of $209.47 and reduce holdings on strength to my semiannual risky level of $225.33. (For more, see: How 3M Makes Its Money.)… 2018-04-20 07:28:00-06:00 https://www.investopedia.com/news/3m-company-reports-oversold-below-key-levels/

JPM launches ESG bond index, hires PM for quant team

…alternative beta and quantitative equity portfolio managers. Based in New York, he will report to Yazann Romahi, chief investment officer of the QBS team. JP Morgan said the QBS team, which conducts quantitative research in factor-based investing, launched 16 new products and doubled assets under management in 2017. Prior to joining JP Morgan, Lowe was an independent consultant advising asset managers and RIAs in asset allocation and portfolio construction. He also worked as a senior advisor at AlphaSimplex. Previously, Lowe served as the chief investment officer for State Street Global Advisors’ global equitie… 2018-04-19 12:39:00 http://citywireusa.com/news/jpm-launches-esg-bond-index-hires-pm-for-quant-team/a1111869

Want to know what Tier 1 banks teach their FX desks? Look no further

…iled in a bankruptcy auction on December 23, 2008. Creditors of Lehman Brothers Holdings Inc. retain a 49% common equity interest in the firm, now known as Neuberger Berman Group LLC. In Europe, the Quantitative Asset Management Business has been acquired back by its employees on November 13, 2008 and has been renamed back to TOBAM. Barclays acquisition On September 16, 2008, Barclays PLC announced that they would acquire a “stripped clean” portion of Lehman for $1.75 billion, including most of Lehman’s North America operations. On September 20, 2008, a revised version of the deal, a $1.35 billion (£700 million) plan … 2018-04-10 14:49:56+03:00 https://financefeeds.com/exposed-lehman-brothers-internal-fx-training-manual-want-know-tier-1-banks-teach-fx-desks-look-no/

Hedge fund assets reach new record high, says HFR

…al ED hedge fund capital to USD835 billion. Special Situations led ED sub-strategy inflows, receiving USD1.6 billion in new capital and raising ED: SS capital to over USD380 billion. Activist and ED: Multi-Strategy funds received USD814 million and USD920 million in inflows, respectively. The HFRI Event-Driven (Total) Index returned +0.15 per cent in Q1 2018, while the HFRI Event-Driven Index (Asset Weighted) Index gained 0.73 per cent. Fixed income-based Relative Value Arbitrage strategies also experienced inflows in Q1 2018, attracting USD2.3 billion of new capital and increasing total RVA assets to US… 2018-04-20 00:00:00 http://www.hedgeweek.com/2018/04/20/263410/hedge-fund-assets-reach-new-record-high-says-hfr

Tesla’s Testing a Key Price Floor: Chart

…are still out there in force. Longer term, for Tesla to turn fully bullish again, shares need to muster the strength to push through the $350 to $380 range, the price ceilings that represent Tesla’s trendline resistance level and the top of the rectangle pattern, respectively. The good news for Tesla bulls is that there are an abundance of potential catalysts on the horizon between now and the end of 2018 that could trigger buying. That said, patience is a virtue in this stock right now – and the price action is king…. 2018-04-20 12:43:41-04:00 https://www.thestreet.com/investing/tesla-testing-a-key-price-floor-14562912

Does Great-West Lifeco Inc. Offer Investors the Best Value Today Among Canada’s Life Insurers?

… or near their 52-week lows are generally a good idea to begin with, what’s more in the case of Great-West stock is that the shares now find themselves resting just atop the company’s 200-week and 50-month moving averages. Moving averages are technical indicators that can help traders and investors identify if a particular stock is showing signs of strength or weakness. Stocks that remain above their moving averages indicate a “bullish” sentiment — that investors are still firmly behind a stock. Some say that cases like Great-West stock, where the shares are just above their moving average, present the best bu… 2018-04-20 00:00:00 https://www.fool.ca/2018/04/20/does-great-west-lifeco-inc-offer-investors-the-best-value-today-among-canadas-life-insurers/

EUR/USD Advances for a Third Consecutive Session

…EUR/USD Advances for a Third Consecutive Session EUR/USD advanced in European trading on Tuesday to climb above its 20-day moving average, on pace to post a third consecutive day of gains. Although there is some momentum behind the recent rally, the pair remains within a broader range that has been playing out for most of the year. Friday’s reversal from important technical support followed an underwhelming U.S. jobs report. The dollar has traded broadly weaker since. EUR/USD was lingering around a rising trendline that connects a… 2018-04-10 10:45:00-06:00 https://www.investopedia.com/news/eurusd-advances-third-consecutive-session/    
This news clip post is produced algorithmically based upon CloudQuant’s list of sites and focus items we find interesting. If you would like to add your blog or website to our search crawler, please email customer_success@cloudquant.com. We welcome all contributors. This news clip and any CloudQuant comment is for information and illustrative purposes only. It is not, and should not be regarded as “investment advice” or as a “recommendation” regarding a course of action. This information is provided with the understanding that CloudQuant is not acting in a fiduciary or advisory capacity under any contract with you, or any applicable law or regulation. You are responsible to make your own independent decision with respect to any course of action based on the content of this post.
John "Morgan" Slade

Quants discuss evaluating and adapting their models – Including CloudQuant

In a world where robots, voice recognition and artificial intelligence are growing in importance, Peltz International’s Meet the Quantitative Manager … In January, Morgan Slade participated in a Panel Discussion for Quantitative Fund Managers and how they are adapting their model. This link to the article published by Peltz International after the conference requires registration and a user ID on their web site.

Market Turmoil Generates Opportunity for Proprietary Traders

In these times of market turmoil and volatility, the Kershner Trading Group stands ready to provide traders with a firm built on a strong foundation of significant capital investment, innovation-focused trading technology and decades of experience in the active and proprietary trading space. Kershner Trading is actively seeking experienced US Equities Traders
New York

Meet The Niche Manager – Quantitative Managers. January 26, 2018


Peltz International seminar Meet the Niche Manager on January 26, 2018

CloudQuant will be participating in the Peltz International seminar Meet the Niche Manager on January 26, 2018 in New York. Investors will have an opportunity to meet managers they may not be familiar with. Investors will have an opportunity to see the manager in action, thinking on his feet, discuss critical issues relative to the specific strategy. “Niche’ is defined as an alternative investment strategy that is not used by many managers. It may relate to the methodology used and/or the markets traded. In many cases, the correlation to traditional investments will be low. 8:15-8:30     Registration 8:30-9:45     Panel discussion, critical issues relating to the strategy 9:45-10:25    Individual strategy highlights 10:25-11:00  Informal networking   Pre-registration is required. To register, call 212 689 0180 or E: General@peltzinternational.com  
Three Inside Up Technical Pattern shown on $IBM Jan 2, 2018

TA-LIB Three Inside Up Buy Signal – $IBM

IBM, the 100-year-old company, is wedging into a tight trade, but it looks like the Bulls are gearing to press a move higher. Just before year-end, the stock set a Three Inside Up Japanese candlestick pattern setting the stage for a rally. Source code using TA-LIB and Python included.
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 http://techcenter.thinkadvisor.com/2017/12/27/increasing-automation-in-offices-paying-off-for-ad 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 https://marketsmedia.com/outlook-2018-alastair-hawker-quantitative-brokers/ 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: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3015609 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 http://www.quantnews.com/2017/12/29/machine-learning-trading/ 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 https://nytimes.com/2017/12/31/technology/google-images-voters.html 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 http://www.wildml.com/2017/12/ai-and-deep-learning-in-2017-a-year-in-review/ 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 http://blog.kaggle.com/2017/12/26/your-year-on-kaggle-most-memorable-community-stats-from-2017/ 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 https://venturebeat.com/2017/12/28/ai-weekly-ai-democratization-depends-on-tech-giants/ 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 https://www.forbes.com/sites/elizabethharris/2017/12/31/meet-the-woman-behind-woebot-the-ai-therapist/ 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 https://fuse.wikichip.org/news/686/esperanto-exits-stealth-mode-aims-at-ai-with-a-4096-core-7nm-risc-v-monster/ 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 https://www.forbes.com/sites/panosmourdoukoutas/2018/01/01/the-15-minimum-wage-movement-is-winning-and-thats-bad-news-for-cashiers/ 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 https://venturebeat.com/2017/12/29/ai-operators-will-play-a-critical-role-as-bots-redefine-the-workplace/ 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 https://www.forbes.com/sites/janetwburns/2017/12/30/the-weirdest-pitches-of-2017-that-i-can-remember-ranked/ CloudQuant Thoughts: Really? I had to read this out of morbid curiosity. Ouch.

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: 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 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 http://techcenter.thinkadvisor.com/2017/12/04/5-scary-things-that-wont-crash-the-market-in-next?ref=hp-blogs 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 https://www.bloomberg.com/news/articles/2017-12-06/the-computer-that-saved-a-vineyard 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 https://www.palmazvineyards.com/

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 https://www.geekwire.com/2017/microsoft-doubles-ai-earth-initiative-pledging-50m-paris-climate-event/ 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 http://www.johnlothiannews.com/2017/12/cloud-data-look-like-quanthouse-moving-cloud/ 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 http://www.independent.co.uk/life-style/gadgets-and-tech/news/nasa-announcement-today-latest-kepler-breakthrough-google-ai-artificial-intelligence-a8102966.html 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 http://www.valuewalk.com/2017/12/apple-car-project-ruslan-salakhutdinov/#disqus_thread 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 http://www.bobsguide.com/guide/news/2017/Dec/8/quantitative-brokers-appoints-ralf-roth-as-ceo/

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 http://trove42.com/google-ai-teaches-itself-chess-defeats-stockfish/ 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 https://www.geekwire.com/2017/citybldr-raises-cash-prepares-expand-software-reveals-hidden-real-estate-value-california/ 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?
Morgan Slade, Python Data Scientist and Trader

QuantNews Interview with CEO Morgan Slade

With over 20 years of experience as a trader, portfolio manager, executive, and entrepreneur, Morgan Slade is now the CEO of CloudQuant, a cloud based quantitative strategy incubator and systematic investment fund. He has built quantitative trading businesses at some of the world’s largest hedge funds and Investment Banks …
Open, Close, High, Low

Share Ordering Demo using Market, Limit, and Midpoint Peg Orders

The CloudQuantAI github repository holds the share_ordering_demo tutorial/code that demonstrates ways to buy and sell stocks in the CloudQuant backtesting engine using Market, Limit, and Midpoint Peg Order types. There is no single “right way” to do any of these. You will have to think carefully about your algorithm, how it determines when to buy and sell, how large a trade you want to implement, and how quickly you need your orders filled. To give an example, let’s imagine a hypothetical stock XYZ, at time t0 with bid prices at 29.95 and ask prices at 30.05.

Market Orders

One option is a simple market order: order_id = order.algo_buy(self.symbol, algorithm=”market”, intent=”init”, order_quantity=num_shares) This means that your order will fill at the lowest price someone is actively willing to sell it at. In real trading, you would never buy significant shares of stocks like this, because people will raise their ask price when they realize someone is buying large volumes on market. In backtesting, however, it is essentially assuming you are buying at the ask price for that time, which is reasonable. Your order will always fill immediately, and the only risk is that if the stock price shoots up, you will be paying whatever price the stock goes up to. In our example of stock XYZ, you are buying at 30.05 at t0, though if your order is placed at t0, you may be purchased at the ask price at time t1, which could be different from the ask at t0. Market orders will simply purchase at whatever that ask price is.

Limit Orders

Another way is to initiate a limit order, based on the ask price: order_id = order.algo_buy(self.symbol, algorithm=”limit”, price=md[self.symbol].L1.ask-.01, intent=”init”, order_quantity=num_shares) or order_id = order.algo_buy(self.symbol, algorithm=”limit”, price=md[self.symbol].L1.ask*.99, intent=”init”, order_quantity=num_shares) These two algorithms place an order for a stock with a limit on the price. In the first case, we set a limit one cent below the ask, and in the second our limit is 99% of the ask price. These are likely to get filled, but not guaranteed, though they will get a better deal than a simple market order. The farther below ask you go, the better a deal you might get, but the higher a chance that you won’t get filled. The lowest you can go is probably 95% ask or 5 cents less than the ask. If it’s important that you get your order filled immediately, you will want to place a more aggressive limit, such as the ask price PLUS 5 cents or 105% the ask price. This is similar to a market order but will keep a lid on how much you actually will pay for the shares. This is a critical distinction in live trading, but less important in back-testing. In our example of stock XYZ, if we, at t0, place a limit order one cent below the ask, we are essentially offering at t1 a price of 30.04. Cloudquants backtesting environment does its best to approximate whether someone would have been likely to meet our price limit or not. If the price of stock XYZ moved up at t1, there is a very high chance we would not have been filled. If, however, we set a limit of ask + 5c, we would have placed a limit at $30.10, and we would have likely been filled unless the stock shot up more than that.

Midpoint Peg Orders

Finally, we have a slightly more complex way of computing our trade price, using a “midpoint peg.” This algorithm is only available in the elite version. order_id = order.algo_buy(self.symbol, algorithm=lime_midpoint_limit_buy, price=md[self.symbol].L1.ask*1.05, intent=”init”, order_quantity=num_shares) order_id = order.algo_buy(self.symbol, algorithm=lime_midpoint_limit_buy, price=md[self.symbol].L1.ask+.05, intent=”init”, order_quantity=num_shares) You will also, earlier in the code, need the lines: lime_midpoint_limit_buy = “4e69745f-5410-446c-9f46-95ec77050aa5” lime_midpoint_limit_sell = “23d56e4a-ca4e-47d0-bf60-7d07da2038b7” Though the exact algorithm is only available in the Elite CloudQuant version, you could approximate it in lite by using the mean of the ask and bid prices. This is similar to what the “Lime” midpoint peg does, but the real version should include elements such as the volume of the shares to more accurately estimate where the price would have been. If your trade doesn’t need to urgently fill, the lime midpoint peg is a good way to go, however, if your trade requires an immediate fill, this may give you unrealistic purchase prices, and make your algorithm seem better than it really is. In our XYZ example, this essentially assumes we would always be purchasing shares of XYZ for $30.00 at t0, and then the average between bid and ask at t1, and so on. The public scripts with these examples are available for your copy and re-use.