The Future is Near: Blockchain, AI & Data Science Synergy

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AI-blockchain-and-data-science

So, what is Blockchain?

A blockchain is a digitized, decentralized, public ledger of all cryptocurrency transactions. It is distributed ledger technology maintaining a continuously growing list of data records. It creates digitized blocks of transactions without the need for centralized control.

Let’s explain simply the concept of Blockchain technology. It enables moving digital coins or assets from one individual to another one. The first thing what Blockchain is attempting to solve is to do the transfer money without the trusted entity, the third party. The second, to do it faster, immediately. And the third one, to do it cheaper than the fee that the third party collects.

Blockchain technology has enormous potential in terms of simplification and efficiency due to the creation of a fundamentally new infrastructure of financial services. This technology can be successfully used by banks for internal settlements and interbank transactions, as well as for individual micro-payments.

At the same time, it can greatly simplify the tracking of suspicious transactions and in general increase transactions’ transparency. Basically, this is a technology of distributed transactions, which is a huge distributed database. At the same time, the verification of the transactions’ authenticity is undertaken by the participants themselves. They confirm their verification and form blocks of records.

There is no need for intermediaries and payment systems processing transactions. Consequently, this approach increases the transaction speed and reduces the cost for users.

Over the past three years, major firms across the financial services landscape have made investments in bitcoin and blockchain startups. According to CBInsights charts, in total, over 50 financial services firms or their strategic investment arms have invested in a bitcoin or blockchain-specific startup since the start of 2014.

CBinsights-charts

Artificial Intelligence and Blockchain synergy

Artificial intelligence and blockchains are the two closed components of the digital business. While blockchains can help us verify, execute and record, AI helps in decision making, assessment, understanding and recognizing. While the machine learning methods that are a part of AI help us find opportunity and improve decision making, smart contracts and blockchains can automate verification of the transactional parts of the process.

Blockchains are much more than the already extraordinary scope of potential activity that has been envisioned for their deployment in reinventing currency, finance, economics, government, legal services, science, and health – blockchains are a basic substrate for computing itself.

Blockchains could be employed as a secure large-scale data management mechanism to coordinate the information of millions and billions of individuals.

AI from the point of view of Blockchain and vice versa

From the point of view of artificial intelligence and machine learning, the blockchain has a certain value allowing some AI objects to become economic agents. We can talk about drones, machines that have a certain degree of autonomy and are controlled by artificial intelligence, working on the basis of smart contracts.

For example, you want to hire a vehicle. You paid money via Ethereum system to get a smart contract due to which the car delivers you to the appointed address. Now the car is an economic agent.

In the future, AI will reproduce a large amount of data, from simple algorithms, as components of the Internet of things, to how highly developed artificial intelligence works. All this can be stored in the blockchain. AI will be probably able to mine cryptocurrency due to the fact that it performs cognitive work.

artificial-intelligence-blockchain-synergy  artificial-intelligence-blockchain-synergy2

What Blockchain data can be provided to AI?

DLTs-open-data-for-ai

 

Nowadays we can talk about financial transactions. There are huge volumes of transaction activity in the networks Bitcoin, Ripple, Dash and so on. You can analyze, determine credit risks, create new fintech models without any payments.

In the future, it will be some data on energy consumption, food and goods transportation, legal records, smart city, autonomous vehicles etc. Eventually, sooner or later, we will get a digital picture of the world in the distributed ledger.

NO Data Oligopoly

AI process needs data availability. Today we have such a concept like data oligopoly. Those companies that have access to significant amounts of data, f.e. Google, Facebook, Microsoft, IBM, Amazon, have an ability to build the most effective algorithms for machine learning. These data are not traded on the market. They are closed. The blockchain is a distributed registry, accessible to everybody. Thus, we are destroying data oligopoly making open and free data science.

no-data-oligopoly

AI cognitive mash with Blockchain

Blockchain will give to multi-agent Artificial Intelligence the same thing that written language gave to humans. It called means of cognitive evolution. The information transfer requires:

  • consensus. Each agent gives the same sense of a signal as others.
  • persistence. The sense of the signal does not diminish with time.

The blockchain is perfect for both consensus and persistence rendering multi-agent AI as an evolving self-organized system. Consensus is a mechanism for building trust in a trustless environment. If such rules of the game are followed, the participant gains economic benefit.

What about persistence in blockchain? This is conditionally the money on your wallet or those calculations that are performed by a smart contract, or any data records that you want to store in the Blockchain. Due to transactions, the distributed ledger combines the persistency of data and the storage of all data history with their changes.

Blockchain technology progress in big data

what-is-blockchain-technology

The blockchain is a trustworthy system where mass collaboration and smart contracts are the key guarantees of trust excluding intermediaries like banks, governments, and technology companies. This helps to extremely save time during transactions and to reduce payments. Powerful encryption algorithms in the distributed ledger are replicated on thousands of computers around the world. This technology is so disruptive that big companies, giant techs, and banks are spurring in this new data shift. In the future, almost every transaction could be running on blockchain technology.

IBM and Microsoft: two blockchain giants

We have already started seeing major industries leaning into the distributed ledger technology. For example, companies such as Microsoft and IBM are using their cloud infrastructure to build custom blockchains for customers and experiment with their own use cases, like building a worldwide food safety network of manufacturers and retailers. This blockchain is called Blockchain as a service.

IBM has launched a blockchain service based on Hyperledger Fabric technology.  A new product called IBM Blockchain is an open, distributed ledger framework and code base, multifunctional for creating commercial applications, and is capable of processing more than 1000 transactions per second. There are other tech companies in Hyperledger as Cisco, Intel, and VMware, but Microsoft is not among them.

The big difference with Hyperledger in relation to the blockchain technology used in Bitcoin (and even Ethereum) is open governance. Ethereum is an open source but it’s governed by the board of the Ethereum Foundation, not an open technical committee.

hyperledger

IBM is working with clients and developers throughout the world to implement the blockchain idea to explore how blockchain can transform, how business is done in such areas as banking and financial services, supply chain, healthcare, travel and transportation, media and entertainment, energy and utilities.

According to the opinion of IBM representatives, the market for technology solutions based on the blockchain may be a new growth point for the company. Blockchain-based solutions can be widely demanded in the financial sector, as they contribute to efficiency improvement of some labor-intensive processes.

In general, IBM has the intention to become a leader in the implementation of various application solutions based on this technology. By the end of this year, IBM, along with the Chinese company Energy-Blockchain Labs, will launch a blockchain-based platform for asset tracking solutions. In collaboration with SecureKey Technologies, IBM is creating digital identifiers network for banks. At the end of 2017, a new blockchain service will be used by several Canadian banks for users identification when using bank accounts, paying utility bills etc. Moreover, IT giant, in partnership with Invictus, Singapore company, is working on launching a new Blockchain that will allow business structures to reduce costs and expand access to financial resources.

Microsoft: revolutionary way to do business

In October 2015 Microsoft launched its first version of Azure Blockchain-as-a-Service which was built on the Ethereum platform. In summer this year Microsoft has launched its own BaaS Project Bletchley, its own modular blockchain standard for smart contracts and financial transactions. In order to make it easier for enterprises to use this service, Microsoft is evolving its strategy by the introduction of Enterprise Smart Contracts.

According to the framework of Enterprise Smart Contracts, the goal is to provide a secure, confidential, distributed, multi-party application platform for running shared business logic, with a cryptographic proof system that natively integrates with multiple blockchains. Enterprise Smart Contracts and Azure platform provide this platform that will allow the distribution of costs, risk, identity and more for building next generation distributed applications. This also creates a multi-trust model where Enterprise Smart Contracts can implement different privacy measures based on the blockchain underneath, utilizing privacy features that may be available for certain blockchains. Without Enterprise Smart Contracts, enterprises are limited to the trust model of the blockchain platform only.

blockchain-cloud

Microsoft has announced a new blockchain for corporate systems, the Coco Framework to improve performance, confidentiality and governance characteristics of enterprise blockchain networks. The main advantage of CoCo is that it can process more than 1,600 transactions per second, which can not be done at the moment in Bitcoin or Ethereum.

Blockchain is a transformational technology with the ability to significantly reduce the friction of doing business,” said Mark Russinovich, chief technology officer of Azure at Microsoft.

CoCo Framework will use the unique TEE technology (Trusted Execution Environment). This technology will allow storing the blockchain code in a secure environment like Intel’s Software Guard Extensions (SGX) or Windows Virtual Secure Mode (VSM). CoCo technology will also be available through the Microsoft Azure cloud service, which is already used by such blockchain platforms as Waves, Corda, Stratis and others.

Advantages of Blockchain technology in various industries

blockchain-participants

Blockchain has the ability to increase secure data exchange in other industries as well. It also has the ability to make that data transfer simpler and easier between entities.

Originally developed for a public network, companies in several industries are developing their own blockchains for private use. What are the benefits of Blockchain across industries? First, having a Blockchain eliminates the need for a third party transactions clearinghouse, saving both time and money. Second, it increases the accountability and security of the network, as all participants are known and trusted.

According to Fortune, about 40 of the top financial companies in the world are currently experimenting with blockchain, with more expected to get on board in the next few years.  

blockchain-in-industries

Let’s review some industries using blockchain technology more profoundly:

  • Healthcare

Security is the most important benefit that Blockchain can offer healthcare. Many fields in medical data can be benefited by the implementation of blockchain technology. Blockchain could benefit healthcare in many ways. It could provide a fast, accurate and secure diagnosis. Moreover, the possibility to store clinical data will allow hospitals and the patients to have an access to the healthcare records. In addition, hospitals, doctors, patients, and insurance companies, could be part of the overall blockchain, reducing fraud in healthcare payments.

To that end,  IBM Watson Health has signed a research initiative with the U.S. Food and Drug Administration (FDA) aimed at defining a secure, efficient and scalable exchange of health data using blockchain technology.

“The healthcare industry is undergoing significant changes due to the vast amounts of disparate data being generated. Blockchain technology provides a highly secure, decentralized framework for data sharing that will accelerate innovation throughout the industry,” said Shahram Ebadollahi, Vice President for Innovations and Chief Science Officer, IBM Watson Health.

 

Gem is another blockchain startup, launched Gem Health, a network for developing applications and shared infrastructure for healthcare powered by the Ethereum blockchain. Gem Health is a blockchain network for the global community of companies that take part in the continuum of healthcare.

  • Food and agriculture security

The Blockchain evolving in agriculture sphere will enhance food supply chain transparency and traceability, the food origin and will verify the accuracy of food provenance data. The supply chain cannot tamper with the tracking information about food supply and the participants, while Blockchain can solve this issue.

Blockchain can improve real-time management of supply chain transactions between farmers, buyers, and financiers. Blockchain can enable real-time payment on delivery. As a result, farmers get paid immediately, industry competition increases and keeps prices higher, and buyers save time and money. Also, adding transparency, trust, and efficiency to settlements can decrease risk and unlock new financing mechanisms for banks.

To reduce food safety risk, in March Alibaba, China top online shopping company, announced its experimenting with blockchain to track genuine food products through the supply chain. Due to the growing problem of fraud, there is a sharp need to take measures of fraud prevention. Thus, Blockchain is a good solution to complete transparent transactions.

In order to provide trusted information on the food origin and state, IBM started its collaboration with food producers and distributors in blockchain sphere. Blockchain technology could enhance the traceability and transparency of food supply chain.

  • Energy

Blockchain technology in the energy sector is at a very similar early stage.

This technology will help to track energy flows and value while allowing multiple parties to transact. There are different possibilities to use blockchain technology in the area of business transactions and smart contracts:

  • Solutions for e-mobility (charging and car sharing)
  • The buying and selling of electricity from your own systems
  • Stopping the delivery of electricity
  • Battery management, building a pool of saved electricity and supporting community energy models.
  • Connecting energy buyers with operators of renewable energy systems

The most discussed blockchain pilots demonstrate this basic functionality, with small-scale rooftop solar customers exchanging green attributes of power in places like New York City and Australia. RMI and Grid Singularity, an Austria-based blockchain technology developer, formed the Energy Web Foundation (EWF). On October 3, 2017, it has launched a test network of the EWF blockchain and application layer, constructed as a public network with permission validators.

The Energy Web Foundation (EWF) is a global non-profit organization focused on accelerating blockchain technology across the energy sector. The intent of EWF, through its Energy Web Platform, is to develop a market standard that ensures interoperability, reduces costs and complexity, aligns currently dispersed blockchain initiatives, and facilitates technology deployment through easy-to-implement applications.

One more startup in the energy field is TransactiveGrid energy market enabled by blockchain technology. It allows customers to make peer-to-peer energy transactions and to control distributed energy resource.

Innogy SE, a subsidiary of RWE, Germany’s biggest energy and gas provider, has launched hundreds of electric vehicles charging stations across Germany connected to Ethereum blockchain. The owners of electric cars will have the possibility to charge their vehicles at any stations using the Share$Charge app, the world’s first e-mobility community.

  • Law/Legal

The potential impact of blockchain on the legal industry is the use of smart contracts hosted on a blockchain based platform, such as the Ethereum network. While a standard contract outlines the terms of a relationship (usually one enforceable by law), a smart contract enforces a relationship with cryptographic code. Smart contracts help you exchange money, property, shares, or anything of value in a transparent, conflict-free way while avoiding the services of a middleman.

Due to their immutable and autonomous nature, smart contracts provide an alluring alternative to traditional legal contracts, and law firms are taking notice. In August of 2017, ten law firms and four legal institutions joined the Ethereum Enterprise Alliance. Among these is Hogan Lovells, the 14th largest law firm by revenue in the United States.

smart-contracts

Smart contracts can streamline and enforce legal contracts, but they aren’t going to be replacing attorneys. In fact, smart contracts need attorneys to help lay out their terms and conditions. It’s more likely that smart contracts will bring developers and attorneys together to collaborate and provide progressive solutions for the legal industry.

Forensics of the Blockchain

The use of blockchain technology supersedes the traditional transactions. And this, in turn, presents a great promise for the forensic implications due to the blockchain ability of decentralized trust.

Blockchain can bring substantial benefits to forensic applications, where establishing integrity is crucial to achieving the desired end. Collecting, preserving and validating evidence can be strengthened through the use of blockchain. The provenance of any transaction can then be traced back to where it originally entered the process in question. Leveraging these closed-loop systems provides significant evidentiary benefits and allows for the reduction of spending in areas that typically consume significant resources in forensic investigations.

The forensic implications of this powerful technology also include improved transactional efficiency, the reduction of fraud and the reduced costs of certain kinds of transactions.

The transparency of blockchain will make it easy for forensic accountants to access and examine the material related-party transactions (Dai and Vasarhelyi 2017). Furthermore, the risk of receiving checks without sufficient funds could be avoided. Therefore, blockchains not only increase the chance of detecting fraud but also pressure management to reduce earnings manipulation.

Forensic relevance

Let’s go to Bitcoin. Cyber criminals almost always demand a ransom for data held captive with ransomware or data that has been exfiltrated, and they often demand it in Bitcoin. Fraud examiners should understand blockchain transactional analysis and Bitcoin mixing services so that they’re better equipped to trace laundered currencies and track down hidden assets, and forensic investigators should understand Bitcoin as it relates to selling or purchasing contraband items and services.

There are many reasons why an examiner might be required to examine Bitcoin forensic artifacts. Bitcoin has a legitimate purpose; however, it will always be associated with nefarious deeds. Bitcoin has been used for money laundering and purchasing black market goods among others. There are a few reasons Bitcoin is ideal for these illegal purposes.

Bitcoin offers “mixers” that exist for the express purpose of exchanging your currency with other users. Bitcoin is only pseudo-anonymous after all and by using these mixers, if properly configured, one can throw investigators off the proverbial money trail. Bitcoin is often thought of as digital cash which naturally makes it an ideal candidate for purchasing illicit goods online. The most notorious example of this is using Bitcoin to purchase illegal goods from silkroad on the darknet. Silkroad and its successors, which have been already shut down, was an online black market that sold guns, drugs, illegal services, and more with Bitcoin as the medium of exchange.

Beyond Bitcoin as a currency, some see Bitcoin as an opportunity to make money. Beyond the traditional type of investment, mining is a process that allows users to “mint” new Bitcoins and get rewarded for doing so. As a profit is at stake, it is not unheard of for bad actors to make use of a botnet to mine bitcoins.

Artificial Intelligence in trading

ML and AI systems can be considerably useful to humans during the decision-making process. ML has been evolving in the last 15 years, and deep learning is definitely a new breakthrough technology. It helps people to manage lots of data sources and come up with new patterns to help estimate trading, ideas, and make better investing decisions.

According to interview on AI in stock trading and finance, by Alex Lu, CEO and Co-founder of Kavout, with Machine Learning and deep learning we can mine information and lots of trading insights from unstructured data sets which could not be done before. This technology enhances the ability to scan every single stock and find all the tradable classical chart patterns. You don’t have to do it by using human eyes. That will save you lots of time and help you capture more trading opportunities.

Artificial Intelligence (AI) allows replacing humans with machines. In the 1980s, AI research focused primarily on expert systems and fuzzy logic. With computational power becoming cheaper, using machines to solve large-scale optimization problems became economically feasible. As a result of the advances in hardware and software, nowadays AI focuses on the use of neural networks and other learning methods for identifying and analyzing predictors, also known as features, or factors, that have economic value and can be used with classifiers to develop profitable models. This particular application of AI often goes by the name of Machine Learning (ML).

The application of methods for developing trading strategies based on AI, both in short-term time frames and for longer-term investing, is gaining popularity and there are a few hedge funds that are very active in this field.

ML in Fundamental and Technical Analysis

fundamental-and-technical-analysis

Forecasting the direction of future stock prices is a widely studied topic in many fields including trading, finance, statistics and computer science. The motivation for which is naturally to predict the direction of future prices, so that stocks can be bought and sold at profitable positions. Professional traders typically use fundamental and/or technical analysis to analyze stocks and make investment decisions. Fundamental analysis is the traditional approach involving a study of company fundamentals such as revenues and expenses, market position, annual growth rates, and so on (Murphy, 1999). Technical analysis, on the other hand, is solely based on the study of historical price fluctuations. Practitioners of technical analysis study price charts for price patterns and use price data in different calculations to forecast future price movements (Turner, 2007). The technical analysis paradigm is thus that there is an inherent correlation between price and company that can be used to determine when to enter and exit the market.

In finance, statistics and computer science, most traditional models of stock price prediction use statistical models and/or neural network models derived from price data (Park and Irwin, 2007). Moreover, the dominant strategy in computer science seems to be using evolutionary algorithms, neural networks, or a combination of the two.

With the increasing access to computational power the use of artificial intelligence, particularly machine learning has become an important aspect of market prediction. Machine learning is successfully used for time-series financial forecasting. Support vector machines (SVM) and artificial neural networks (ANN) are widely used to predict financial data.

Due to automated trading, it is easy to predict the direction of a succeeding price change as buy or sell signals. ANN is by far the most applied machine learning technology within the automatic stock analysis. “Neural networks have been one of the most important techniques for forecasting stock prices” (Raei (2011). ANN has successfully been used to effectively find the non-linear relationships existing in the stock market. When executing automatic trading, the essence is to formulate trading decisions: buy cheap, sell expensive and to do that often. One way to automatically find trading strategies is to apply genetic algorithms (GA) to breed algorithms in several generations, selecting the most successful individuals for further breeding (Raei et al., 2011).

Algorithmic Trading

Algorithmic trading also referred to as algo trading and black box trading, is a trading system that utilizes advanced and complex mathematical models and formulas to make high-speed decisions and transactions in the financial markets. Algorithmic trading involves the use of fast computer programs and complex algorithms to create and determine trading strategies for optimal returns. It is the process of using computers programmed to follow a defined set of instructions for placing a trade in order to generate profits at a speed and frequency that is impossible for a human trader. The primary function of algorithmic trading is to help you manage costs and minimize risks.

How cryptocurrency trading bots work, or sleep well while your bots gain profit

ML hedge funds outperform traditional quant and hedge funds. Applying to trading strategies ML and AI can incredibly enhance the process of making a decision instead of humans who cannot be absolutely predictable and accurate due to their emotional nature.

“Technology has become better, cheaper and more efficient than any human, as it is impossible to match the high-frequency execution or decision making speed of algorithmic trading robots. Instead of simply crunching numbers, the machines are now deciding and executing trades for us in the same way they are intended to be driving us home and cook or clean for us”, – Mikael Breinholst, CEO of Tradeworks, which is an FX algo trading and automation technology company, said during the interview with FinanceFeeds.  

Trading bots are automated computer pre-programmed instructions based on a determined set of market indicators, rules, and parameters that when all align will make a buy or sell signal, telling the exchange of your choice to execute a trade. The defined sets of rules are based on timing, price, quantity or any mathematical model.

Trading systems are used for trading on global stock exchanges. There is a chain of reasons why to use trading algo bots. Their advantages over human trading are the logic, consecutive and deliberate fact-based decisions. It is worth mentioning, that we humans often follow our emotions in decision making. A rational approach will overcome emotional way of trading. Thus, such bots are helpful for newbies who are inexperienced traders on the market landscape. The aim of trading systems is not only to gain profits but to reduce losses.

You cannot be always involved in the trading process. Trading bots can. While you absent or working, traveling, or even sleeping, your bots will look for new opportunities and options analyzing efficiently the trading process. There are large unknowns when dealing with markets, any number of influences can trigger a rise or fall. Most bots will be a better strategy than a buy and hold method and as long as you believe your choice of altcoin will go up, then you will likely make a profit.

Top Bitcoin and Altcoin trading bots

  1. BTC Robot
    BTC-robotThe highlights are the following:

    • It is the world’s first commercial multi crypto-currency robot!
    • Its algorithm performs automatic pattern charting for Bitcoin markets;
    • It checks and calculates market indicators for a potential breakout;
    • It also calculates market depth;
    • The followed market trends enable it to determine the optimal time to buy or sell. It also monitors the activity of other users, holding out for potential market rallies and falls;
    • The programming aims at the highest profit and the lowest loss possible;
    • The implemented “loss-cutting” function is in charge of rectifying any potential trading error;
    • The system is perfectly capable of running 24/7.

     

  2. HaasOnline haasonlineHaasOnline Software has been around since January 2014, when it was founded by Stephan de Haas. It is automated trading software developed in accordance with the desires and needs of its users, with new features developed and introduced on a regular basis. The company’s innovative approach is reflected in the abundance of supported indicators, a variety of custom bots, and other powerful, advanced features that have won over a large number of professional traders. The company’s diversified offer is designed to accommodate the needs of even the less-experienced traders, thus allowing a wider range of users to make a profit.There are 4 different types: trade, arbitrage, order and script bots. HaasOnline supports over 50 different customizable indicators, which are designated to specific license types. Among them  MACD, PPO, Aroon, StochRSI, Regression Slope Cross, etc. There is such an opportunity for users to utilize Auto-Tuning feature for indicators and safeties to see which settings work best for a specific period of time.
  3.  Cryptotrader cryptotrader
    Cryptotrader is an algorithmic trading platform for Bitcoin and other cryptocurrencies. The goal is to provide traders with cloud-based automated trading solutions powered by cutting-edge technology.The advantage of Cryptotrader are:

    • automated trading bots in the cloud running on servers without software installation
    • All major crypto-currency exchanges are supported for both backtesting and live trading
    • The place where trading strategies can be bought and sold
    • With backtesting tool strategy you can see how the strategy would work over different market conditions
    • Instant email alerts and SMS notifications.

     

  4. Gekko gekko

Gekko is a free and open source Bitcoin TA trading and backtesting platform that connects to popular Bitcoin exchanges. It is written in JavaScript and runs on Node.js.

The main features are:

  • Gekko supports 18 different exchanges (including Bitfinex, Bitstamp and Poloniex). There is the possibility to create your own trading strategies using TA indicators.
  • Using plugins Gekko is able to update you wherever you are! Plugins are available for IRC, Telegram, email and a lot of other platforms.
  • Gekko comes with a web interface (written from scratch) that lets you monitor your local data, strategies and can run backtests and visualize the results.
  • Gekko runs flawlessly on all major operating systems (Windows, Linux, macOS).

trading-bot

 

 

References:

  1. What is Blockchain. Youtube video. https://www.youtube.com/watch?v=93E_GzvpMA0
  2. Data Driven #5: Blockchain and Big Data https://www.youtube.com/watch?v=Wz_PT3W29Lo
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  7. iForum-2017: Maxym Orlovskyi – how to connect AI and Blockchain https://ain.ua/2017/06/09/iforum-2017-maksim-orlovskij-kak-sovmestit-iskusstvennyj-intellekt-i-blokchejn
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  12. Microsoft announces the Coco Framework to improve performance, confidentiality and governance characteristics of enterprise blockchain networks https://news.microsoft.com/2017/08/10/microsoft-announces-the-coco-framework/
  13. IBM, Microsoft Are Building Our Blockchain Future—and They’re Not Afraid to Butt Heads https://www.pcmag.com/article/346729/ibm-microsoft-are-building-our-blockchain-future-and-theyr
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  35. Artificial Intelligence in Stock Trading – Future Trends and Applications https://www.techemergence.com/artificial-intelligence-in-stock-trading-future-trends-and-applications/
  36. Revolutionizing retail FX – We go into great detail on algo trading, AI and bots as brokers and traders need to turn a new page https://financefeeds.com/revolutionizing-retail-fx-go-great-detail-algo-trading-ai-bots-brokers-traders-need-turn-new-page/
  37. What I should know about trading bots? https://cryptotrader.org/topics/540172/what-i-should-know-about-trading-bots
  38. Great list of trading bots | Up to date 9/10/2017 | Automate your profit! https://bitcointalk.org/index.php?topic=1944274.0
  39. Top 6 Bitcoin Trading Bots https://themerkle.com/top-6-bitcoin-trading-bots/
  40. Best Trading Bots https://www.virtualbanking.com/rankings/best-trading-bots/
  41. Best Bitcoin Trading Bots – Top Cryptocurrency Earning Software? https://bitcoinexchangeguide.com/best-bitcoin-trading-bots/
  42. The ultimate beginner’s guide to trading online https://thenextweb.com/investing-2-0/2017/09/22/the-ultimate-beginners-guide-to-trading-online/
  43. Algorithmic Trading http://www.investopedia.com/terms/a/algorithmictrading.asp
  44. Algorithmic Trading https://en.wikipedia.org/wiki/Algorithmic_trading
  45. Machine Learning for Technical Stock Analysis https://www.nada.kth.se/utbildning/grukth/exjobb/rapportlistor/2012/rapporter12/cedervall_fredrik_12088.pdf
  46. Predicting Stock Prices Using Technical Analysis and Machine Learning http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.174.8858&rep=rep1&type=pdf
  47. Technical Analysis inspired Machine Learning for Stock Market Data http://www.diva-portal.se/smash/get/diva2:928205/FULLTEXT01.pdf
  48. Impact Of Artificial Intelligence And Machine Learning on Trading And Investing https://medium.com/towards-data-science/impact-of-artificial-intelligence-and-machine-learning-on-trading-and-investing-7175ef2ad64e
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