Forex Basics

Can Artificial Intelligence (AI) Successfully Trade Forex?

Artificial intelligence can do a lot of things. It has machine learning, meaning it is able to learn from mistakes and to adapt. It is able to kind of think for itself, to make complex decisions based on pre-programmed data as well as the learning that it has done from the past. It can calculate things far quicker and far more accurately than a human, but it certainly has its limitations. It can’t exactly think like a human and it can’t really work things out based on a hunch or by looking at external factors such as news and sentiment. So the big question is whether or not you can use artificial intelligence to trade forex.

Let’s kick things off by saying that computers and AI can be incredibly helpful when it comes to trading. It is able to do things that no human can. It can look at huge amounts of data in a very short time, something that would be next to impossible for a human to do, yet it only takes seconds for an AI system to do. With all of that information it is able to make predictions or to find any anomalies that may be in the data, something that can help us to avoid certain things. It is also able to use that data to look for trends, trends that could be repeating themselves, and ones that could be profitable. 

AI systems are fantastic at sticking to the plan, something that we as humans often fail to do. When a plan is created, the points and data are put into the system and the AI will then trade along with those guidelines. Us as humans get emotional. We think outside of those rules and so can put on trades outside of them, which usually leads to bad trades being made. This is not something that an AI system needs to think about. It will stick to the plan and any risk management plans that you have put in place, making it a little safer and potentially more consistent than a human trader, certainly an emotional one.

Speaking of emotions, the AI does not have any, at least we hope they don’t! The AI will work to a system, it won’t get stressed by a loss, it won’t get overconfident and greedy when it is doing well or not, it will simply stick to its plan, something that we often fail to do when our emotions and stresses get too much for us to handle.

Another great feature of an AI system is that it is automated. It doesn’t need to eat, it doesn’t need to sleep, it doesn’t need to work, and it doesn’t need any breaks. As human traders, we need to do other things with our life. It is not all trading and nothing else. Some of us have jobs, some family, and others just like doing other things. These all take us away from trading. When it comes to an AI system, there are no other distractions, it is there to trade and only trade, so it can be there 24 hours a day, taking all the trades that it needs to and never missing a single one.

Now, there are of course some problems when it comes to AI systems. Have you ever been trading and looked at the markets and something in the back of your mind has told you to trade something? You do not know why but it just feels right. You put the trade on and it wins. Or the opposite, something is telling you not to, a little feeling telling you that it is a bad trade, so you decide not to. The markets then react in the way your hunch told you that it would, you have either just made or saved yourself quite a lot of money. This is a human emotion, a feeling that we get and something that an AI will not. It will simply follow the set algorithms that have been built into it, not feeling this and eventually putting on trades that are good trades, but not correct trades.

There is a huge downside to trading with an AI, but this again comes down to human error. You would have created the algorithm for it to follow, but what if you put something in slightly wrong? A one when it should be a zero? Just a little mistake could potentially cause disastrous consequences. We aren’t talking about the robots revolting against the humans, but it could mean that the AI thinks it should buy instead of sell when a certain condition is met. This will lead to a loss and a loss every time that this scene takes place. So while it is not the AIs fault, it will continuously make the error when a human would not.

The AI is also dependant on the hardware and software that it is built on. We have all had computers fail in the past. If this happens to the AI, not only will it potentially lead to open trades being stuck open, but it will also give you quite a long downtime, time where no trades are being made and so profits are being lost. If parts aren’t available then it can take days, weeks, or even months to fix which is a long time when it comes to trading. There is also a cost to AI trading. You need to buy the equipment, the software, and any other components when things break. This added cost is on top of your trading balance and for some it may simply be too much.

The final disadvantage that we are going to look at is the fact that an AI system will take in all the information that it finds. Sometimes this can be a little too much information, some relevant and some not so relevant. The problem is that the AI will not be able to work out what information is good and what is bad so it will most likely use it all. This can make its predictions go a little off track. Using too much information can change a buy to a sell or to no trade at all. With a human mind, we are able to discard info that we don’t want to use. An AI system cannot do that, at least not very well.

So those are the advantages and disadvantages of using an AI system with trading. It certainly has its uses, but using it solely for trading could lead to some negatives. However, using it along with your own analysis and trading, as a tool to help you analyse and to gather more data is certainly a good thing to try. It can give you more information than you would otherwise have and can do calculations far quicker and more accurately than you can.

Blockchain and DLT Cryptocurrencies

Introducing Fetch.AI (FET): What’s Is It

Blockchain has been touted as a solution to countless modern-day problems. But what if it could be seen as a catalyst for innovation? You know, innovation that brings us products and services that we simply hadn’t fathomed about before. is an intelligence lab that wants to harness blockchain to power a decentralized digital economy. The platform will enable the sharing and connection of data globally and driven by machine learning and artificial intelligence. will be open-source, allowing anyone from anywhere to connect to the network and carry out safe and secure tasks in a modern economy. 

This article explores the network in-depth, from how it works to use cases, right down to its native token and where to purchase it. 

Understanding is an artificial lab that wants to bring together tools and develop an infrastructure to power a decentralized digital economy. Based in Cambridge, intends to create a distributed ledger platform to facilitate secure and safe sharing connection and data transfer on a global scale. 

Fetch wants to automate countless markets that currently require a lot of manual intervention. The goal is to have frictionless transactions at digital speeds. The team imagines an evolved world where everybody has numerous economic agents on the platform, each operating to provide solutions for some of the most challenging today and tomorrow’s problems. 

Some of the highlights of the platform include: 

  • A near-autonomous integration for various components of complex systems
  • Frictionless integration and the deployment of machine learning (ML) and artificial intelligence (AI) in decision making without necessarily understanding how the two technologies work
  • Combining machine intelligence and human intelligence model to optimize decision-making processes

Key Features of

Some of the notable features of include: 

  • A digital infrastructure optimized for multi-agent systems.
  • A scalable ledger to power massive transaction volumes 
  • Synergetic computing to support ‘intelligent’ smart contract contracts 
  • An economic infrastructure to support dynamic market places
  • Navigation based on semantics and geography, and through which autonomous agents can oversee the smooth solving of problems

Key Products of

#1. Consensus Mechanism: utilizes a combination of proof of stake consensus and other protocols that oversee the delivery of the consensus. New blocks are produced via the PoS protocol, with the transaction verified through the work put in between every two blocks. The work is then recorded on a directed acyclic graph (DAG) created between the two blocks. The DAG is ‘stamped’ by the blockchain, removing the need for a supervisor. 

#2. Fees and Rewards runs a fees and rewards program, whereby processing nodes are incentivized with system incentives. Processing nodes are also in charge of data mining – the process through which transactions are produced and confirmed. 

Performance of the Network

The ledger is designed to scale, and its performance will differ depending on the current configured resources at the given moment. However, the network claims to have achieved speeds of up to 30,000+ transactions per second (TPS). The network is expected to increase configured resources as demand balloons. 

Open Economic Framework

The Open Economic Framework (OEF) is a second-layer protocol that provides services to participants (agents). Agents connect to the framework to connect with other agents to do business together. OEF is created to show the semantic, geographic, and economic views of that time to participants. 

Network nodes can either be just blockchain nodes or be both blockchain/OEF nodes. Initially, the OEF nodes will be either “trusted” or “trustless.” The “trustless” nodes can support the network anonymously, as can the pure blockchain nodes. However, the “trusted” nodes are eligible for access to agents’ information so they can render their intelligence and discovery capabilities to the network. Operators of trusted nodes must submit a legitimate public and legal identity and be accredited by the Foundation.

Example Use Cases of could potentially revolutionize a lot of industries, helping to improve efficiency and optimize processes. The project wants to increase efficiency and enhance solutions to daily problems via intelligent data sharing, ML, and AI. 

#1. Decentralized marketplace and decentralized finance will be used for decentralized commodity exchange, an innovative platform that will support improved liquidity in the trading of base metals and other commodities. will assist market participants in circumventing barriers to entry via innovative technology. It will facilitate the digitalized trading of various materials, enabling market players to have at their disposal new risk management tools. 

#2. Transportation

Current transportation systems are mainly self-service, with commuters having to do so much just to move from one point to another. will feature Autonomous Economic Agents who will do the heavy lifting on behalf of individuals. The Autonomous Economic Agents will be able to adjust to individuals’ preferences as they go, and they’ll be able to react in real-time to any unforeseen scenarios. 

#3. Smart parking and congestion solution’s autonomous agents can search and inform you about the available parking space and book it for you in advance. When you come back to your car, the system calculates the bill for you and completes the payment. This not only saves time, but it also removes the hassle of a manual process. And it can greatly help reduce congestion in cities. 

#4. Powering electric cars wants to be at the forefront of powering the next generation of cars, which are likely to take on in the near future like never before. For the technology to advance, major changes will have to be made.’s intelligent ecosystem will enable the autonomous agent in your car to scour for the nearest charging system, book a space and direct you there, instead of having to go and wait at a filling station. As smart vehicles become more popular, more users will be flocking at recharge points. Smart optimization tech powered by will ensure that increased demand is met by the nearest possible charging point. The system will also guide users to charging points near a coffee shop or playground, making their charging stop more enjoyable. 

#5. Supply chain supply chains will allow businesses to study future patterns, which will enable them to plan for potential disruptions for months while responding appropriately to changing customer behavior. 

Both AI and blockchain tech will assist companies in achieving more efficiency. For instance, AI can use real-time info to enable a company to choose the best trading partner for their current business situation.

The FET Token

FET tokens will be the native tokens of the system and will play many roles, including the following: 

  • Connect participants and nodes to the ecosystem: agents and network nodes will have to stake in FET to demonstrate their goodwill and intention to maintain good behavior. As the cost of joining the network escalates, it will be more difficult for undesirable elements to attempt to join the network. 
  • As a value exchange mechanism: FET tokens will be required to exchange value between and among agents, no matter their location. FET will be infinitely divisible, which means it can support very low-value transactions.
  • Facilitate access to the search engine: Network users will have to stake in FET to assess search and discovery capabilities of the perform. 
  • Facilitate access to’s multi-dimensional space: Agents on will need agents to interact with its digital world geographically, semantically, and economically. 

FET Token Allocation

As of October 15, 2020, traded at $0.047499, with a market cap of $35,439,353, which placed it at #175 in the market. The token’s 24-hour volume was $4,706,418. It had a circulating supply of 746,113,681, a total and maximum supply of 1,152,997,575. FET had an all-time high of $0.0432695 (Mar 03, 2019) and an all-time high of $0.008270 (Mar 23, 2020), according to Coinmarketcap. 

Buying and Storing FET 

The FET token is currently listed on quite a variety of exchanges, including Binance, BitMax, MXC, HotBit, Bitfinex, Folgory, KuCoin, WazirX, BiKi, CoinDCX, Omgfin, IDEX, Bitsonic, Coinall, Fatbtc, Giotus, and Bitbns. 

FET tokens are compatible with the ERC-20 standard and hence can be kept in any wallet supporting Ethereum. Great options include Trust Wallet, MetaMask, Ledger, ethaddress, Parity, and more. Once migrates to its mainnet, token users will be able to “easily convert ERC20 FET into native FET tokens and back again.” 

Crypto Guides

What Should You know About Web 3.0?


World Wide Web, as we know, today has undergone a lot of changes. To dwell on Web 3.0, we need to understand what comprises Web 1.0 and Web 2.0. Web 1.0 is the first integration of the internet in the nineties. The visionary Sir Tim Berners-Lee led us to web 1.0. He wanted to decentralize the information so that there wouldn’t be any third-party intervention to access the information. Let’s look at the previous two versions briefly below:

Web 1.0

Web 1.0 comprises of mostly static information. It can be termed as a worldwide explosion of information or read the only web. Many big companies have come up with read-only websites. Many E-Commerce websites can be termed as Web 1.0 version as an example today. User interaction is very minimalistic.

Web 2.0

Web 2.0 can be termed as the web we know as of today. It is also said web of social media with many video streaming platforms. With the invention of Web 2.0, all of us got access to not only download available content but also to upload the content made by us. It has started becoming two ways, which started revolutionizing many business models. Let us look into Web 3.0 now.

Web 3.0

Web 3.0 is termed as the internet of value, and it has special significance in today’s world. We have already entered web 3.0, and it is not somewhere in the distant future. We consider it as the most advanced of all because it uses Machine Learning, Artificial Intelligence, and Blockchain technologies to offer us the best suit of experience.

One of the daily examples of Web 3.0 usage is when we shop on Amazon or any eCommerce website. Under a product we are looking to buy, there is another section which says people ‘who bought this has bought’ these items or what items people bought after buying this product. This is possible because of AI/ML. The user experience is maximized because of the suggestions.

Web 3.0 allows the acceleration of decentralized finance. We have business models available for many purposes rather than the one in the previous versions, where only big companies were used to make use of them for businesses. User privacy is hampered in a big way with the advent of so many apps and their usage.

Big multi corporations, even though they say that their laws pertaining to data privacy are simple, which prevents them from collecting data is not true in reality. With the advent of DAPPS with blockchain as the underlying technology, no user information can be collected and stored without users’ consent. Web 3.0 is a whole new experience without privacy concerns anymore.

The key technology in shaping up Web 3.0 is termed as blockchain. Blockchain provides the decentralized infrastructure for the internet, which fundamentally changes how the web operates. Blockchain allows a highly secure environment to exchange data generated by billions of IoT devices across the world. The decentralization of data allows users to control data rather than the big corporations controlling them single-handedly.


The big companies have treated us like products by collecting the information in the form of our tastes, need to target and sell their products in return to us. We lost control of our data privacy. Web 3.0 is essentially taking back the control from the corporations to our own hands using the decentralization of data using blockchain technology