How AI Is used in the Algorithmic Trading Sector

Artificial intelligence (AI) is rapidly transforming the global financial services industry, playing a key role in everything from fraud detection and compliance to banking chatbots and robo-advisory services. It’s also changing the ever-evolving world of algorithmic trading helping to eliminate human error and streamlining decision-making processes. But, how exactly is AI utilised in this sector and what are the overall benefits? Let’s take a closer look.

What exactly is AI?

Before you can really get to grips with how AI is used in the algorithmic trading sector, you must first understand what it is. Coined in 1955 by John McCarthy, AI is a term which describes the intelligence displayed by machines, in contrast to the natural intelligence displayed by humans. AI systems will typically demonstrate at least some of the following behaviors including planning, learning, reasoning, problem-solving, knowledge representation and perception.

Important AI applications

While AI is rather broad by definition, there are specific branches that play a prominent role within the algorithmic trading sector including ‘machine learning’ (ML). Named by Arthur Samuel of IBM in 1959, ML is an AI application that focusses on the idea that machines can learn for themselves by accessing Big Data. Such systems can automatically improve based on experience, without being explicitly programmed.

‘Deep learning’ (DL) is another AI concept and a branch of ML which revolved around problem-solving. Such networks do not necessarily need structure or labels to make sense of data. You may have also across ‘neural networks.’ These have AI roots and are inspired by the way humans think. They’re becoming increasingly integrated into today’s AI-related trading world.

Algorithmic trading uses powerful computers, running complex mathematical formulas, to generate returns. This is very different from days gone by where humans used to crowd busy exchanges or pick out the best assets to buy and sell from an office.

Sophisticated algorithms now play a significant role in market transactions and while algorithmic trading isn’t necessarily new, artificial intelligence is giving algorithmic traders extra tools to enhance their performance. Indeed, feeding AI predictions into algorithms can give you a more solid overview of the market including when to enter and exit positions and the best assets to long and short.

So, how exactly does AI tie in with today’s algorithmic trading sector?

Well, algorithmic trading is all about executing orders using automated and pre-programmed trading instructions, accounting for numerous variables such as volume, price and time. Algorithmic trading nowadays involves the use of complex AI systems with computers generating 50-70% of equity market trades, 60% of futures trades and 50% of treasuries. The benefits of AI in algorithmic trading.

Fast trading speeds and improved accuracy

When it comes to algorithmic trading, large numbers of orders are executed within seconds adding liquidity to the market. High-Frequency Trading (HFT) of this kind happens in a fraction of a second and simply can’t be done by humans alone – that’s why algorithms are needed to execute and place bids before the market changes.

Automation streamlines the entire process with AI and machine learning adding an extra clever twist. Essentially ML computer systems are trained to recognise market movements with impressive accuracy, helping algorithms to bid accordingly. By accessing and understanding large data sets, ML systems can predict future outcomes, enhance trading strategies and tweak portfolios accordingly.

AI-enhanced algorithmic trading therefore helps to improve the performance and meet the demands of target clientele including hedge funds, propriety trading houses, corporates, bank propriety trading desks and next-generation marketing makers.

Elimination of human error

Algorithmic trading also helps to reduce errors based on emotional and psychological factors. Often, traders let past trades, FOMO or market pressures affect their judgement and this can lead to poor decision making.

But with algorithmic trading, algorithms are used to ensure trader order placement is instance and accurate – based on pre-defined sets of instructions.

With the help of AI, it’s also possible for computer systems to check multiple market conditions and adjust trades instantly depending on the market environment. Of course, if this were to be done manually, it would take hours and hours of physical labour, research and fact-checking. And even then, errors might occur. Opportunities are likely to be missed too which is why AI is rapidly being integrated into financial institutions and shaping the sector significantly.

AI and algorithmic trading in the real world

AI is not just something that’s being talked about. It’s already here and changing the financial world significantly, especially when it comes to trading practices. Top financial institutions including UBS and JP Morgan have already introduced AI into their trading tools with the former using AI techniques to trade volatility (which is notoriously difficult to navigate) and the latter using AI algorithms to execute equity trades. Algorithms enhanced by AI are also being used to guide venture capitalist investments.

So, as you can see, AI is being increasingly utilised in the algorithmic trading sector and offers many benefits. As 80% of all data is completely unstructured, AI and its complexed applications including ML and DL aims to deliver a more structured, organised and data-fuelled approach to the trading world, helping to make the whole process efficient, while providing split-second insights.

Overview Of Azure Kinect

Pre-requisite Knowledge

 Before we start with the understanding of what is Azure Kinect, we should know,

Background I would like to explain the short information about ‘Artificial Intelligence and Kinect’ before jumping in to ‘Azure Kinect’. 

What is Artificial Intelligence

 In simple words ‘Artificial Intelligence (AI)’ is the artificial creation of the system like a human who can observe, react, learn, plan and process the instructions, virtual reality and provide intelligence on it. It is rapidly emerging technology and internet enable technology. Sometimes AI is also called as Machine Learning. 

What is Kinect and its background

 Kinect is the motion sensor device using in Xbox 360 gaming console. This device provides natural user interface to interact with it without any intermediate device. This device has capability of face detection as well as the voice recognition. This device has 3D camera which creates the virtual images and with the help of motion sensor it detects the movements of the images. The first-generation Kinect for Xbox 360 was introduced in November 2010. This device was originally created for gaming purpose, but now a days this technology is applying to real worlds applications in the virtual shopping, education, healthcare industries, digital signage etc. This product is developed by Microsoft. 

Introduction of Azure Kinect

 As I explained above Kinect is the motion sensor device. Azure Kinect device has,

  1. DK camera system
  2. 1MP depth camera
  3. 360-degree microphone
  4. 12MP RGB camera
  5. Orientation senor
  6. Size and weight – 103 x 39 x 126 mm and weighs only 440g
Overview Of Azure Kinect

Image Source – Microsoft Docs Azure Kinect has ability to create platform for developers with Artificial tools and plug this in to the Azure cloud for cloud-based service, computer vision and speech models. Azure Kinect has its own developer kit (DK) by Microsoft which is available in the portal site here. Microsoft Azure Kinect SDK has new sensor SDK, body tracking SDK, vision APIs, speech service SDK for Azure Kinect DK. This is the latest released feature by Microsoft for Azure cloud. Please note that Azure Kinect DK is not designed for use with Xbox. By using Azure Kinect, now we can build the applications like cashier less stores, manage inventory of the products, track the patient movements integrate these motions with the AI in hospital, enhance physical therapy, improve and monitor athletic performance, computer vision and speech models etc. We can enhance feature of Azure Kinect application with Azure cognitive services. Transcribe and translate speech in real time using Speech Services. Add object, scene, and activity detection or optical character recognition using Computer Vision or use Azure IoT Edge to manage PCs connected to your Azure Kinect DK device. 

Overview Of Azure Kinect

Image Source – Microsoft Docs Azure Kinect device price is $399.00 and can be purchased from Microsoft’s store here. As of now (12th August 2019) this product is only available in the US and China. 

Inside of Azure Kinect DK

Overview Of Azure Kinect

 Image Source – Microsoft Docs

  1. 1MP depth sensor with FOV option
  2. 7-microphone array for speech and sound capture
  3. 12-MP RGB video camera for an additional color stream
  4. Accelerometer and gyroscope (IMU) for sensor orientation and spatial tracking
  5. External sync pins to easily synchronize sensor streams from multiple Kinect devices
  6. Azure Kinect Developer Kit
  7. Purchase Azure Kinect from Microsoft Store

7 Benefits of Artificial Intelligence for Business

Artificial Intelligence can have a very positive impact on a business. Here’s how…

One of the newest benefits of cloud computing is that it enables businesses to take advantage of artificial intelligence (AI). This rapidly developing technology offers significant development opportunities that many companies have already been quick to seize upon. In this post, we’ll look at some of the ways your company can benefit from cloud-based AI.

1. Improving personalised shopping experiences

Providing customers with personalised marketing increases engagement, helps generate customer loyalty and improves sales. This is why companies are putting so much effort into it. One of the advantages of using AI is that it is able to identify patterns in customers’ browsing habits and purchasing behaviour. Using the millions of transactions stored and analysed in the cloud, AI is able to provide highly accurate offers to individual customers.

2. Automating customer interactions

Most customer interactions, such as emails, online chat, social media conversations and telephone calls, currently require human involvement. AI, however, is enabling companies to automate these communications. By analysing data collected from previous communications it is possible to program computers to respond accurately to customers and deal with their enquiries. What’s more, when AI is combined with machine learning, the more the AI platforms interact, the better they become.

One example of this is AI Chatbots which, unlike humans, can interact with unlimited customers at the same time and can both respond and initiate communication – whether on a website or an app.

It is estimated, that by 2020, 85 percent of all customer interactions will be taken care of by intelligent machines that are able to replicate human functions. The days of using a call centre look like they are coming to a close.

3. Real-time Assistance

AI is also useful for businesses that need to constantly communicate with high volumes of customers throughout each day. For example, in the transport industry, bus, train and airlines companies, which can have millions of passengers a day, can use AI to interact, in real-time, to send personalised travel information, such as notice of delays. Some bus companies, for example, are already tracking the location of their buses and using AI to provide travellers with real-time updates about where the bus is along its route and its estimated time of arrival. Customers receive this information on the bus company’s app.

4. Data mining

One of the biggest advantages of using cloud-based AI is that artificial intelligence apps are able to quickly discover important and relevant findings during the processing of big data. This can provide businesses with previously undiscovered insights that can help give it an advantage in the marketplace.

5.Operational automation

AI is able to operate other technologies that increase automation in business. For example, AI can be used to control robots in factories or maintain ideal temperatures through intelligent heating. In Japan, human-looking robots now serve as receptionists in some of the countries’ hotels automating check-ins, booking services and dealing (in four languages) with customer enquiries. In retail, AI is also being linked with RFID and cloud technology to track inventory. In China, police forces use AI to catch criminals. The country has a vast CCTV network and AI uses facial recognition to spot and track suspects so that they can be apprehended.

6.Predicting outcomes

Another advantage of AI is that it is able to predict outcomes based on data analysis. For example, it sees patterns in customer data that can show whether the products currently on sale are likely to sell and in what volumes. It will also predict when the demand will tail off. This can be very useful in helping a company purchase the correct stock and in the correct volumes. It is predicted that, within 10 years, the days of seasonal sales will be over as AI will mean there is too little leftover stock to sell off.

This ability to predict is not just useful in retail. AI is also being used in many other areas, for example, in banking where it can predict currency and stock price fluctuations or in healthcare where, remarkably, it can predict outbreaks of infections by analysing social media posts.

7.Improve the recruitment process

It may be bad news for recruitment companies, but AI is now helping businesses automate the recruitment of new employees. It is able to quickly sift through applications, automatically rejecting those which do not meet the company’s personal specification. This not only saves time (or money spent on a recruitment agency), but it also ensures that there is no discrimination or bias in the shortlisting process. The AI programs available can even take care of the many administrative tasks of recruitment.

Conclusion

As you can see, AI systems provide businesses with a wide range of benefits, including personalised marketing, customer service, operational automation, inventory management and recruitment. And these are just a few of the many ways AI can be used. What’s remarkable, however, is that many of the AI apps, which are designed specifically for cloud-based systems, are quickly and easily deployable. Companies whose systems are in the cloud can be benefitting from them in no time at all.

How to Create an Emotional Connection with Your Fans

There is a huge issue that many brands, sports teams, and anyone offering a service face today when it comes to building their fanbase. They do not put in the time or effort to make an emotional connection. Too many people want to skip the “real work” and go right to the part where they have engagement and a loyal fanbase. Without creating this emotional connection, this is virtually impossible. 

While it may seem like an impossible task, creating an emotional connection is not as hard as it may seem. 

Consider Your Fan’s Journey

The fan’s journey means how they find out about you and how they become a fan initially. What is the journey they have gone on to discover you and fall in love with your team? 

Usually, this is going to happen via television, online, or from personal experience. Once a potential fan gets a “whiff” of what you offer, what you stand for, and what you can do, they will want to learn more. Where will this journey go? This is what you have to consider. Take time to connect the dots to provide the best fan journey possible. 

Remember, a crucial part of any fan’s journey is likely going to be social media. They want to see what their friends say and what random people have to say. Be sure to monitor what is going on and being said to put your best foot forward. 

Build an Email List Then Use It

If you are a fan of something, you want to learn more about it, right? Your fans are going to want to hear from you. It is up to you to keep this line of communication open. While it may seem daunting at first, there are an array of methods you can use to make email marketing easier and more efficient, including automation. Take time to build an email list and then use it to your advantage. By connecting with your fans in this manner, you will be building that ever-important emotional connection. 

Take Your Fans Behind the Scenes 

One of the fastest and most effective ways to build an emotional connection with your fans is by taking them behind the scenes. Use features like Facebook Live and Instagram Live to give your fans a glimpse of something unique. When you provide an exclusive look behind the scenes, your fans will appreciate it and want to see more. Also, this helps them go on the journey with you, which is going to deepen their loyalty. 

If the process of building an emotional connection with your fan base seems daunting, do not worry. The professionals can help ensure you create the connections that mean the most and that you are able to build something that will last. By using the tips here, you will create loyal fans that stick with you for life.