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How AI can Amp Up Thematic Investment Strategies

AI

How AI can Amp Up Thematic Investment Strategies

One of the persistent criticisms facing equity investors is their short-term view. They are characterized by adding or dropping stocks as the quarterly earnings roll in. Thematic investment, on the other hand, provides one counterpoint to earnings-focused stock picking.

Thematic investing  – a strategy designed to capitalize on broad economic or social changes – has seen increasing use in recent years. In 2016, thematic funds accounted for 30% of new ETFs introduced, on topics ranging from obesity, millennial consumption habits, and health and fitness.

Yet, asking questions about anything long term can be complex and often obscure. The trends and themes themselves that will reshape economies may be easy to identify, but translating them into quality investment vehicles is another matter. Using themes like clean energy, disruptive technologies, aging populations, or emerging markets to structure portfolios comes with its own unique challenges: successfully sifting genuine long-term trends from flash-in-the-pan fads – and critically, doing so early – is no easy task. Good analysis requires a massive amount of diverse data that, once structured in a way, it would facilitate thematic analysis.

A Knowledge Graph-based framework is uniquely positioned to provide both the data and analytic framework, with the inference capabilities necessary to provide actionable insights into large data sets.

A properly built Knowledge Graph describes the interrelations between real-world entities through a multidisciplinary, multidimensional correlated structure, comparing common themes and concepts across hundreds of millions of data assets over several years of correlated data embedded into the Knowledge Graph.
Such a framework can automatically calculate thousands of strategies for any investable concept an investor can think of – ranging from sustainability themes like clean energy to disruptive technologies like 5G or cloud computing.

A functional Knowledge Graph can rapidly build new, flexible strategies for thousands of concepts, deriving insights from millions of combined sources, and in ways that a typical analyst approach cannot match. Data sets can have global coverage – with strategies tailored to and applicable to multiple regions and countries – while also being highly specialized. They’re equally capable of taking in structured and unstructured data sets; everything from news reports, SEC filings, and financial or macroeconomic reports to court opinions and clinical trial data or patents. This multidimensional approach powers a dynamic point-in-time Knowledge Graph framework to produce exposure indices with precision.

Knowledge Graphs can further offer special insights in building a thematic investing portfolio through the way they look at concepts, both – quantitative (AAPL stock prices or its fundamental indicators for example) and qualitative. This offers not only the numbers behind what makes a wise investment, but also the context behind those numbers, which is especially critical when tracking themes.

Taking that capability a step further, it can also weigh data points based on the strength of their correlation to a given data set, or screen against undesirable exposure that might at first glance appear to be on theme. This scoring can be done at the entity level, offering sourced data on every point used in the process. When the process is complete, the final index that is produced has been weighed on multiple levels, accounting for variables such as market caps and liquidity for each company, and the aggregated exposures.

This type of analysis illustrates one of the key strengths of thematic investing: its concentration. Thematic investments are typically concentrated on a smaller selection of stocks but a Knowledge Graph framework offers the opportunity to build thematic strategies based on a larger constituents basket. This pushes market analysis away from being a purely reactive prospect; through identifying anticipated changes in the world, investors can take a forward-looking approach to capitalize on opportunities as they are forming, leading to potentially greater long-term growth opportunities.

Contrast that approach with mutual funds, which are typically concentrated on 40-80 stocks in a portfolio. The emphasis is generally on diversification, which manages risk, but is not necessarily the optimal way to achieve growth.

Some funds have already begun to turn to technology to do some of this critical analysis work. The AI-powered International Equity ATF (NYSEArca: AIIQ) has been doing just this since 2018. The fund runs on the Equbot Model, a proprietary algorithm that compares and analyzes data points and international companies on a daily basis to find and optimize portfolio exposures.

With a properly designed framework, a Knowledge Graph’s AI-based exposure engine can draw inferences to understand the dynamic market trends constantly driving returns while promoting concepts investors feel strongly about. Properly deployed, AI-based thematic investment strategies can instantly create new strategies or power existing ones – and in a fraction of the cost and time that traditional analysis could yield.

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Ruggero Gramatica is founder and CEO of Yewno, innovator of the Knowledge graph that generates actionable knowledge from today’s vast informationYewno has created an extensive multi-domain knowledge graph using proprietary AI algorithms, combined with a multi-disciplinary technology platform that extracts insights and delivers products and services tailored to specific industries. Yewno generates actionable knowledge from the ever-increasing amount of information available today.

As a pioneer in the Knowledge Economy and the innovator of the proprietary Yewno Knowledge Graph, an artificial intelligence-based framework powered by billions of disparate data sources, Yewno provides continuously evolving inferences that uncover unexpected insights for financial services, education, life sciences, government and beyond.  By delivering more meaningful intelligence, Yewno is revolutionizing how information is processed and understood, enabling users to more quickly analyze complex problems and improve decision-making. For more information, visit https://www.yewno.com/.

production

The Countries Leading the Way in the Future of Production

The First Industrial Revolution dates back to the 18th century, with the manufacturing and production process evolving significantly to improve efficiency. Since then, the world has gone through a series of changes with the present-day seeing us in full swing of the world’s Fourth Industrial Revolution. 

Using data from the World Economic Forum’s ‘Readiness for the Future of Production’ report, RS Components have taken a look at the countries that are leading the way when it comes to driving production forward. The six main drivers are ‘Technology & Innovation’, ‘Human Capital’, ‘Global Trade & Investment’, ‘Institutional Framework’, ‘Sustainable Resources’, and ‘Demand Environment’. See how each country compares when it comes to being ready to produce more products, technologies, and goods here.

The 21st century is a truly digital age, with technology now intertwined and cemented into both our personal and professional lives. Over the last two decades, in particular, technology has become increasingly advanced and has seen the emergence of the Fourth Industrial Revolution. Complicated and impressive technologies such as artificial intelligence (AI), robotics, the Internet of Things (IoT), 3D printing, genetic engineering, and quantum computing have all emerged and are being used across the globe in a variety of industries, businesses and processes.

As a result of the new technological age, the speed, efficiency, and accuracy of production levels have improved astronomically, with less room for human error as machinery takes over, making production levels much faster and hassle-free.  

With the rise of these advancements, it is important for countries and businesses across all industries to be tapping into these changes to keep up with the future of production. But which countries are leading the way?

RS Components have produced a graphic analyzing data from the World Economic Forum’s Readiness for the Future of Production report, to reveal the countries leading the way when it comes to driving production forward. With each country analyzed by a series of metrics including global trade and investment, institutional framework, sustainable resources, demand environment, and emerging technologies, the top 10 countries leading production levels forward have been scored out of 10.

The top 10 countries driving the future of production include:

The US takes the crown as the leading country in the world driving the future of production forward. Scoring at the top of the leaderboard across all metrics excluding Sustainable Resources and Institutional Framework, the US holds an overall score of 8.16 out of 10. The US is renowned for its innovation and holds an advanced, connected and secure technological platform that allows production to drive forward in the most efficient way possible.

Singapore ranks as the second country driving the future of production and the UK sits at fourth place with a score of 7.84. Singapore sits as one of the world’s leading chemical manufacturing sites, with over 100 global petroleum, petrochemical and specialty chemical companies situated on 12 square miles of land. Singapore today sits as the world’s fifth-largest refinery export hub and amongst the top 10 global chemical hubs by export volume. Involved in these systems includes advancements in manufacturing from robots, to predictive analytics and artificial intelligence. Singapore, like the US, is a key driver in testing, experimenting and trialing the latest technologies. In addition, manufacturing continues to contribute around 20% to Singapore’s GDP.

The importance of having the right technological foundations 

In order for production levels to thrive, it is crucial that technological foundations are cemented in supply chains across the globe. For example, in a warehouse, the speed and availability of the internet is crucial when the Internet of Things is being adopted on the factory floor. In addition, it is also greatly important for businesses and industries to have strong, connected cybersecurity systems to ensure digital security is maintained to a high standard. Having the technological foundations of this, like the US, allows the nation to drive forward technologies to increase production levels.

In addition, in order to ensure these new innovations are implemented effectively, it is crucial that employees have a good understanding of the technology they are interacting with on a daily basis, as the skills required of workers will evolve with the new advancements.

Combined, industries and countries will be able to adapt rapidly emerging technologies into their production lives, which will have a global impact on both businesses and consumers across the world.

supply chains

Trade Wars and Warehousing: Repositioning Supply Chains for Success

It’s almost impossible to keep up with trade war news today – whether it’s U.S.-China, UK’s Brexit, EU vs Tech Giants, or anyone of the 101 international trade dispute cases filed with the WTO since 2015. The fact is, the news changes almost daily. What we do know is that the pace of change in tariffs, regulations, and subsidies has enormous impacts on global businesses and their supply chains, dramatically impacting sourcing decisions, market opportunities, competitiveness, and profitability. In the view of many analysts, this state of constant flux has become the new normal. It also means that businesses will need to find a way to cope.

Supply Chains in the Crosshairs

Trade disputes cause havoc with global supply networks, affecting both supply and demand, as well as logistics providers who move the goods. As we know, changes in tariffs and regulations can throw a wrench into even the best of supply chains. By quickly changing market signals, they can completely alter the economics of a business and leave companies struggling with sub-optimal networks and trading partners. It puts enormous pressure on margins and makes companies more vulnerable to disruptions, market fluctuations, and changes the competitive landscape at home and abroad.

Reconfiguring the links in the supply chain can be a monumental task. In fact, in this Wall Street Journal article Jacob Parker, vice president of China Operations for the U.S.-China Business Council, said, “Businesses are making arrangements to diversify their supply chain investments away from the China market and enacting other structural changes to account for that. It could take about three to five years to build up the supply chain elsewhere.”

While that may be true for some, for others changes in supply and manufacturing will occur much faster, and in many cases are already occurring. Whatever the timescale, in the near term these disputes can leave executives paralyzed by uncertainty and their businesses idling, hoping for global trade issues to subside. That may happen, but at this point, it looks just as likely for the uncertainty to continue. For many, waiting is not an option.

Pressures for Warehousing and Distribution

For warehouses and distribution networks, changes in cost signals brought about by tariffs manifest themselves on two timescales.

Near term: For an importing country facing higher tariffs on imported goods, the business response is as obvious as “Sale Ends Sunday” signage. Businesses will stockpile imports from their traditional suppliers to the greatest extent possible in the months and weeks prior to the imposition of tariffs – before prices go up. Ports and warehouses will operate at max capacity, and nimble businesses will look to move materials into their downstream warehouses and distribution network as quickly and efficiently as possible. For the supplier nation, manufacturers and logistics providers will be stretched in their supply chains as well, looking to match this spike in demand.

Longer term: Because of changing economics, importing businesses will ultimately look for new international sourcing options, new manufacturing capacity, overseas warehouse capacity and possibly new logistics providers. Here the advantage will go to those businesses that can adapt to change most quickly and bring new business partners into their supply network most efficiently. They will need to establish a trading collaboration with shared work processes, communication, business rules for exception handling, and master data management – so all parties are working from a single version of the truth in the trading relationship. Even the domestic supply chain structure may need to change in response to shifting entry points, volumes, and lead times.

A Fundamental Shift: Optimizing for Uncertainty

What businesses need to do is plan and prepare for uncertainty and constant change, which will make their business operations and network more resilient. To minimize the existing uncertainty in the supply chain, while increasing its agility, many are looking at their existing infrastructure and are seeking new ways to make them more adaptable to rapidly changing conditions in demand, supply and logistics.

Because most companies run their businesses and global supply chains with many different enterprise systems, they lack end-to-end connectivity and real-time visibility and collaboration capabilities. Traditional systems, such as ERP, MRP, WMS, and TMS, provide vital functionality, but it is primarily enterprise-focused. B2B networks often suffer from a similar problem, as they evolved from acquisitions and the integration of enterprise systems. While giving the illusion of a unified system, at the core they have multiple data models and databases that must be integrated and synchronized.

These systems introduce latency through batch processing to synchronize the various systems; both internal systems and those of trading partners. They contribute a huge amount of friction and uncertainty to the supply chain, increasing the variability and the need for safety stocks. They create rigid, hardwired connections between systems and trading partners, which make it difficult for companies to adapt systems to new partners, business opportunities, and workflows. They are costly to maintain, and an upgrade is virtually a new implementation, with all the cost, time and risk that that entails. The combination of poor visibility and collaboration, rigid architecture, and untrustworthy data makes it difficult to make effective decisions and identify opportunities and threats in a timely manner.

Removing the Guesswork with Real Time Business Networks

Enterprise systems certainly have a role to play, but to effectively manage global supply chains, trading partners need to share data and work together in real-time, to resolve supply chain issues and exploit business opportunities in a rapidly changing trade environment. Multi-party supply chain networks connect all parties to a single network so they can share data in real-time. This provides a cohesive, connected and transparent supply network, that eliminates delays and minimizes uncertainty and variability. With a permissions framework to control who can see what, companies can quickly enable access for various supply chain roles at each trading partner. All relevant parties can have visibility to demand, inventory, orders, shipments, capacity, and constraints. They can plan collaboratively and work together to resolve issues as they arise during execution, eliminating huge amounts of uncertainty while enabling companies to reduce safety stocks and other buffers against variability.

Because all business partners are on the same network, with planning and execution on the same platform, processes like creating documentation for trade compliance can be automated, streamlining many labor-intensive import and export administrative tasks. These processes can also be preconfigured so that intelligent agents can monitor and alert users to missing customs documentation and other issues to ensure compliance.

With unified solutions like inventory management, warehouse management, yard management, and transportation management all running on the same network, businesses are better positioned to understand actual demand and their various supply and logistics options so they can meet the demand at the lowest costs. Companies can also leverage the network to make better decisions about where and when to move inventory. For example, they can choose to move their goods to new markets where demand is higher, rather than incur tariffs on products where demand is low. And if stockpiling is strategically necessary in order to take advantage of market fluctuations or impending changes to tariffs and regulations, companies can leverage the network for storage, distribution and logistics services.

Digital Transformation is Important and Urgent

Lower inventory levels are one of the major benefits of real-time business networks, with companies typically reducing inventory levels by 10 to 30 percent. This relieves pressure on warehouses, where inventory is frequently stockpiled to provide a buffer against variability and uncertainty. Inventory reduction frees up a lot of capital, reduces storage costs, and significantly reduces the risk of product going unsold or obsolete.

Having access to an unlimited number of potential partners is another powerful advantage of a multi-party network. Whether it’s the need to expand in new markets, or withdraw from others, find new suppliers or new logistics partners, a multi-party digital network also means you are already potentially connected to thousands of new customers and partners. Companies who are not already on the network need only onboard once, as connections are then made virtually as opposed to physically with clicks as opposed to point-to-point hardwired connections. This makes for extremely flexible and agile business ecosystems that are controlled by the business analysts charged with managing supply and demand rather than involving scarce IT resources.

Regardless of the changes imposed by political and regulatory agencies, a real-time business network mitigates risk. They are easy to configure, rapid to adapt, extensive and inclusive, rich with alternatives, and infused with intelligence. Although the financial costs can’t be eliminated entirely, much of the administrative overhead can be, and significant savings can be made through a frictionless transaction platform that removes uncertainty, provides transparency, reduces waste and optimizes the utilization of resources.

Most importantly, for businesses facing the uncertainty of ongoing trade wars and other factors that drive volatility, real-time, multi-party networks provide a digital platform for agile business that can respond to risk and quickly exploit new opportunities. They enable companies to leverage new markets, suppliers, logistics services and other trading partners, to respond to changing conditions and to innovate new business models that keep them profitable and competitive whatever the market throws at them.

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Nigel Duckworth is a senior strategist at One Network Enterprises, provider of an AI-enabled business network platform that enables all trading partners to manage, optimize and automate complex business processes in real time. To learn more, visit www.onenetwork.com or follow ONE at https://twitter.com/onenetwork.

FinTech

FinTech: 5 Automation Trends That Are Impacting the Industry Right Now

The FinTech industry is rapidly moving toward automation as a source of efficiency. The move to specific tools and software programs increases speed and accuracy of processes. It also keeps employers on their toes as they need to quickly evolve and learn. Many of these programs previously required specialized training and adaptability.
Automation helps with repetitive procedures and simplifies complicated tasks. It increases accuracy and safety measures, while minimizing human error. Expectations indicate that the FinTech industry will extend its tech integration significantly over the next four years.


Here are 5 automation trends that are impacting the Fintech industry right now:

1. Human Resources Management: This used to be one of the least automated components, but now software like Workday and 15Five are building platforms to assist workflow with related systems that support employee management. Finance companies increasingly recognize that their people are the most valuable resource and need to be managed more thoughtfully as well as efficiently.

2. Mobile: Finance companies now consider mobile oriented tech as part of the core work-flow. The industry relies heavily on its ability to get work done efficiently. FinTech continues to utilize software which speeds up communication and productivity. Mobile used to be considered a security risk by the financial industry. Now it is considered a way to enhance productivity as well as provide more flexible workflow for employees.

3. Customer Support: More automation is taking over customer service. This support has advanced tremendously with certain software programs that include internal systems to support customers. Software systems such as Fresh Desk and Zen Desk are cutting down on the head count needed for customer service departments in some companies. But more importantly these new systems are improving the customer experience and the lives of the people working in those departments.

4. Billing/Invoicing: Payments systems like Stripe, invoicing and billing systems like Freshbooks, and more advanced ERP systems Netsuite are examples of programs that continue to reinvent the way FinTech is automating business functions. Although many companies are still at least partially stuck in the past of creating manual invoices and payments, these automated systems are increasingly taking over. Both the customer and the vendor win with greater automation in this area. Vendors cut costs and get paid faster. Customers benefit from this greater efficiency of vendors with lower prices or higher value delivered for their purchases.

5. Accounting: Xendoo, Zoho, Quicken online and other systems automate are automating the accounting, bookkeeping, and tax filing functions of businesses. Traditional accounting software, and human bookkeepers and accountants, still have an important role to play in this area, but the accounting business is rapidly changing as well due to technology. The number of people involved with these activities is likely to shrink dramatically as automation takes over more of these functions. Ultimately businesses and their customers will benefit from this via lower operating costs that allow for better value to be delivered rather than spent on administrative functions like accounting.

It is crucial for companies of all sizes to be knowledgeable about this trend and keep their business updated as automation continues to reinvent Fintech industry jobs. You have to be able to adapt quickly to these changes. Our previous ideas and habits of doing business are changing, and we have to keep up with those changes or be left behind by competitors who will adapt more quickly

Automation is impacting Fintech employees in a variety of complex ways so it’s critical for employees to have a greater understanding of and training on different software systems to ensure they keep up with the automation and benefit from it rather than viewing it as a potential threat to their jobs. There is no way to stop technology. All of us need to work hard to stay on the right side of its inevitable progress.

farmers

Yield Guarantee Program Supports Farmers While Mitigating Financial Risk

Farmers and enhancement opportunities are the primary focus of the latest partnership announced this week between Growers Edge Financial, Inc. and GROWMARK, Inc.

While some might associate the agriculture sector with outdated operations, the two companies will offer farmers an opportunity for enhancing efficiencies while maximizing profits through the Yield Guarantee Program from Grower’s Edge.

“In today’s stressed farm economy, farmers are incredibly wary of taking on more financial risk – even when taking that leap could boost profitability. They need guarantees,” said Joe Young, president and chief operating officer, Growers Edge. “Working with strategic partners like GROWMARK, we are providing the financial incentives farmers need to confidently adopt the new technologies that can ultimately drive their long-term sustainability and business success.”

Through carefully and strategically combining AI from Growers Edge’s Growers Analytic Prediction System (GAPS) and information gathered from GROWMARK’s Product Yield Trials, farmers can now rely on the predictive performance and exactly how to benefit from the technology, minus the increased risk for wasted resources and costs.

GROWMARK is committed to helping our customers grow their bottom line with new ag technologies, which makes Growers Edge an ideal partner for us,” added Lance Ruppert, director of agronomy marketing technology, GROWMARK. “The Growers Edge team is removing some of the risk and creating a new value stream for both the farmer and our technology providers. We think the yield guarantee program will help customers deploy the technologies needed to improve profitability, and we are eager to see it in action.”

To read more about how this is changing farming strategies, please visit: Growers Edge Financial or GROWMARK.

machine learning

How Machine Learning Is Transforming Supply Chain Management

Supply chain management is a complicated business. A lack of synchronization or one missing entity can interrupt the entire chain and result in millions in losses.

In a market environment where businesses are continually striving to cut costs, increase profits, and enhance customer experience, disruptive technologies like machine learning offer a window of opportunity. By exploiting the enormous amount of real-time data and leveraging the cloud power, it improves decision making, process automation, and optimization. It can create an entire machine intelligence-powered supply chain model. It also helps companies improve insights, mitigate risks, and enhance performance, all of which are crucial as the global supply chain war wages on.

Gartner recently announced that innovative technologies like blockchain and Artificial Intelligence (AI)/machine learning would significantly disrupt existing supply chain operating models. In addition to advanced analytics and Internet of Things (IoT), machine learning is considered one of the high-benefit technologies. This is because it allows dynamic shifts across industries and enables efficient processes that result in significant revenue gains or cost savings. 

So, it is no surprise then that, in another industry update, Gartner predicted that at least 50% of global companies would be using AI-related transformational technologies in supply chain operations by 2023.

There are three key ways in which these transformational technologies empower businesses:

Monitoring: By connecting equipment, products, and vehicles with IoT sensors, companies can monitor goods and operations in real time.

Analyzing: Advanced analytics convert data into actionable insights and help businesses understand the reason behind specific incidents and how they impact the business.

Acting: Valuable insights as a result of data crunching help businesses address planning challenges and automate processes to improve efficiency.

So, adopting machine learning in supply chains is critical for companies to stay competitive in the long run. However, what aspects of the supply chain will be impacted by machine learning? Let us find out.

A Myriad of Benefits to Supply Chains

If you get the algorithms right, the benefits of using machine learning are innumerable. The algorithms can predict supply trends based on human behavior, resulting in personalized customer service with lower inventories and better utilization of resources. We take a look at several such benefits of machine learning below.

Brings Real-Time Visibility Which Improves Customer Experience

According to a Statista survey, visibility is a significant organizational challenge for 21% of supply chain professionals. Visibility has been a buzzword in supply chain circles for more than a decade now and every technology so far has promised to improve visibility in some way. But, is machine learning contributing anything here? 

The combination of IoT, deep analytics, and real-time monitoring is improving supply chain visibility, helping businesses achieve delivery commitments and transforming the customer experience. By examining historical data from various sources, machine learning workflows discover complex interconnections between various processes along the value chain.

Amazon is a prime example as it is using machine learning to enhance its customer experience by gaining an understanding of how product recommendations influence customers’ store visits.

Cuts Costs and Reduces Response Times

As per Amazon’s regulatory filing in 2017, their shipping costs increased from $11.5 billion in 2015 to $21.7 billion in 2017. And, it’s not just Amazon. Many other players are struggling because of rising shipping costs. In fact, in one survey, more than 24% of supply chain professionals expressed that delivery costs are the biggest challenge for B2C companies.

By applying machine learning to handle demand-to-supply imbalances and trigger automated responses, businesses can improve the customer experience, while minimizing costs. Operational and administrative costs can also be reduced by integrating freight and warehousing processes and improving connectivity with logistics service providers.

Machine learning algorithms’ ability to analyze and self-learn from historic delivery records and real-time data helps managers and dispatchers optimize the route for each vehicle. This allows them to save costs, reduce driving time, and increase productivity. 

Machine learning can also be used to detect issues in the supply chain before they disrupt the business. Having an effective supply chain forecasting system means a business has the intelligence to respond to emerging threats. And, the faster a business can respond to problems, the more effective the response will be.

Streamlines Production Planning and Identifies Demand Patterns

When it comes to machine learning’s role in optimizing complex supply chains, production planning is just the tip of the iceberg.

Sophisticated algorithms are trained on existing production data in such a way that they start identifying future buying, customers’ ordering behavior, and possible areas of waste. This helps businesses tailor production and transport processes to actual demand as well as improve their relationships with specific customers.

For example, by anticipating and acting on the specific needs of your customers before they even arise, businesses can establish themselves as reputed brands capable of recognizing customer needs. 

There is so much volatility in global supply chains that it will be challenging to forecast demand accurately, without technologies like machine learning. However, reaping the full benefits of machine learning might take years. So, businesses should plan for the future and start taking advantage of the machine learning solutions available today.

Investing in machine learning and the related technologies today means increased profitability and more resources for your business tomorrow. Businesses that can use machine learning in their supply chains will have better plans, resulting in less “firefighting” and fewer inefficiencies.

 

Tech Mahindra Ltd. Opens O’Fallon, MO Location

M Property Services officially announced the addition of Tech Mahindra Ltd. to its WingHaven Development earlier this week. The technology-focused global company – which is specialized in areas pertaining to digital transformation, consulting, business reengineering and software solutions, now boasts an address on Technology Drive in the O’Fallon, Missouri region.

“Due to the many amenities throughout O’Fallon and the WingHaven development, we were able to invite a world-class tech company to open a facility within the city’s boundaries which would allow it to continue supporting world-class companies in O’Fallon, MO and numerous other large companies outside of the O’Fallon area,” said MPS Chairman Paul McKee, Jr. “So many of Tech Mahindra’s employees currently live in O’Fallon and WingHaven, so the location for the new technology center was ideal.”

As innovative solutions for micro services, automation, artificial intelligence, security, machine learning, cloud computing, big data, data and analytics, and blockchain serve as primary drivers behind the expansion, Tech Mahindra’s new 14,000-square-foot Technology Center also supports efforts in addressing the needs of customers.

“As part of our TechMNxt charter, we are committed to inspire our partner ecosystem, academia and employees to focus on innovation in next gen technologies and customer experience,” said CP Gurnani, Managing Director and Chief Executive Officer at Tech Mahindra.

“We believe it is our responsibility to invest in the local communities we operate in, and this is a step towards supporting increase in employability of future technologists, and delivering enhanced experience to our customers globally. We look forward to seeing the innovations that come out of this center as we develop real-world solutions for a digital future,” Gurnami concluded.

TeleSense Addresses Global Grain Ecosystem Challenges

Grain spoilage may soon be a thing of the past for global grain operators and transporters. IoT tech innovator TeleSense recently announced its acquisition of Danish wireless sensor technology company, Webstech. Through this acquisition, TeleSense announced it will amp up IoT efforts as it now has access to the largest global remote-sensed dataset and plans on integrating Webstech’s industrial automation capabilities, solar/battery power functionality and sensor spears to its current solution.

“Spoilage and energy optimization in drying grain continue to be multi-billion dollar issues; TeleSense provides the data insights needed for players throughout the global grain ecosystem to improve safety and profitability,” TeleSense CEO Naeem Zafar said. “The acquisition of Webstech greatly accelerates our entry into the European market and provides millions of additional historical data points to further refine our machine learning technology and predictive algorithms.” 

The TeleSense GrainSafe™ AI platform serves the grain supply chain as a scalable solution through monitoring temperature and humidity levels and providing real-time view of the stored grain to ensure quality conditions are maintained. With this innovative, portable, and wireless solution, the company is ready to expand its presence beyond the U.S. and Australia and make its entry in the European regions.

“How grain is stored, handled and traded in the years to come will change as new IoT-enabled technologies take hold throughout the supply chain,” added Peter Votkjaer Jorgensen of Maersk Growth Ventures. “We think that this acquisition by TeleSense will accelerate the mission of higher sustainability and efficiency in the grain supply chain.”

The company also confirmed it will expand with a new Denmark office and onboard two new additions to the team. Maersk Growth Ventures’ Peter Votkjaer Jorgensen will serve on the Board of Directors of the newly created TeleSense Europe ApS subsidiary and Webstech’s CEO Thomas Kylling will serve as managing director for TeleSense’s European team.

“After operating in the European remote sensing space for almost a decade, I was absolutely blown away by TeleSense’s integration of data science with an IoT solution for grain,” noted Kylling. “I think that TeleSense will help drive the automation of the grain supply chain, and I’m excited to help lead the effort in Europe.” 

forex

How to Analyze Data for More Profitable Forex Trading

Successful forex trading is the art of being able to predict when currencies are going to shift in value in relation to each other, and what direction that shift is going to be in. The good news is that those fundamentals are relatively simple; is the dollar going to weaken against the yen? Will the pound pick up against the euro? Another piece of good news is that there are huge swathes of data available to the average retail trader to enable them to make these decisions. Of course, you may opt to rely on your instincts and make decisions as the situation in the various currency exchanges unfolds before you.

While there is a place for this kind of fast thinking and quick decision making in forex trading, it will only ever form the basis of a stable and successful long term strategy – one which delivers consistent levels of profit – if the quick decisions are built upon the foundations of a clear and thought through long term plan. And this kind of planning is only possible if you know exactly what kind of data to be on the lookout for, and about the tools which are available aid in your analysis. 

The complexities of big data in the age of seamless digital communication are such that it would be impossible to summarise every possible metric or analytical approach accessible to the retail trader in the space available. What is possible, however, is an overview of the main planks of data analysis a trader needs to bear in mind, and a look at a few of the types of tool which can make that analysis easier and more accurate.             

Forex Fundamentals 

When a trader buys and sells shares the analysis required is focused, in the main, on the good health of otherwise of the company in question, and whether the various indicators predict that the shares are likely to rise or fall in value. Wider market conditions have an impact as well, of course, but these conditions would be the same for any stock being traded, which places the emphasis firmly on the choice of stock.

Where forex trading is concerned, however, the fundamental issue is always going to be the relative strength and weakness of a pair of currencies. Looking ahead in an effort to take advantage of shifts in value means analysing macro-economic figures such as interest rates, unemployment rates and GDP (gross domestic product). Many of these figures are firmly fixed in the economic news cycle, meaning it’s simple for a trader to see in advance when a country or bloc such as the EU is likely to announce figures which might impact on currency fluctuations (predicting what this impact will be is a more complex matter altogether, of course).

Requiring more vigilance to spot, on the other hand, are the sudden shifts which might be triggered by an event such as a comment in a ministerial press conference which is assumed to increase the chances of a no-deal Brexit and so sends the value of the pound dropping. Fundamental analysis based on one-off events of this kind requires a close attention to detail, up to the minute (or even second) access to newsfeeds and the willingness to take up positions instantly.        

Technical

Technical analysis is based not on real world events beyond the confines of the currency exchanges, but on in-depth analysis of the way in which the price of currencies has moved in the past. By focusing on charts of price movements and analysing them with a variety of tools – both manual and automatic – a trader can identify patterns which have repeated in the past and can be expected to repeat again in the future. Past performance is no guarantee of future success, of course (some clichés become clichés because they happen to be true), but the relative stability of the major currencies, over the long term, means that patterns of movement can become relatively predictable. 

Market Movements

A further method of analyzing the forex markets is by watching out for larger than usual shifts in the number of traders investing in a particular currency. As soon as a large number of traders invest in a particular currency, the future pool of people who might opt to sell that currency expands, with the result that the potential value of that currency is impacted upon. Analyzing market movements could be referred to as depending upon the wisdom of crowds. As has been shown in the past, that wisdom can often be mistaken. A stampede to buy or sell a specific currency could be triggered by knowledge of where the value of that currency is heading, but it could also be caused by a simple self-fulfilling prophecy – sometimes, if enough traders take a position, enough other traders assume there must be a good reason for doing so and follow suit, creating a pattern which feeds off itself with little or no external justification.     

It’s not a question of which of these three modes of analysis is the most effective, since the best results will always be gained by combining elements of all three. The deluge of data which is available, however, particularly where technical analysis is concerned, means that the wiser trader will make use of some of the tools which are available:

Session highlighter

One of the key attractions of forex trading is the fact that the currency markets are open somewhere in the world 24 hours a day throughout the week. The fact that different markets are open at different times of the day means that the sessions within those markets are likely to have different impacts on the pairs of currencies which a trader is working with. A session highlighter tool can be used to divide a traders charts into these various sessions, and then to highlight any movement that occurs over set periods, such as a minute, a specific number of minutes or an hour.     

Volatility Tool for Forex 

A volatility tool will show a trader how much, and in what way, a pair of currencies has moved on an hourly basis during a period such as the last thirty days. This enables the trader to build up a fuller picture of the way the currency pair behaves, and note any patterns such as recurring movements on specific days or at a specific time of the day. The more advanced versions of the tool will calculate the typical movement range and, given a time period by the trader, will display a percentage probability that the pair will stay within the set range.   

Signal service

Signal service providers offer instant information in the form of tips, delivered either by experts or AI systems, which recommend trades are made at a certain time and price on the basis of analysis. There are different types of signal services available, some based on fundamental analysis (i.e. news which might impact on the markets) and some on technical analysis. Signals shouldn’t be confused with the kind of AI that trades automatically on your behalf – they are merely providing information in a timely manner which it is up to you, as a trader, to interpret.  

Undertaking and applying analysis is a key practice of any successful trader. The degree of analysis a trader carries out will depend upon their inclination and appetite for hard number crunching, but the rule to remember is that while there really isn’t such a thing as too much analysis (as long as it’s used to eventually take a position), the concept of too little analysis is all too real.   

Resilinc: AI to Support Weather Risk Assessment & Mitigation for Suppliers

Leading provider of supply chain visibility, Resilinc, identified a major oversight in terms of weather-related risk assessment and preparation within the supply chain. The company released surprising statistics revealing how unprepared supply chain suppliers are during potentially disruptive events such as hurricanes and weather-related catastrophes, sparking the deployment of an AI and data sciences-based hurricane-preparedness solution to better prepare supply chain resilience.

Among the statistics revealed in the Resilinc supply chain database, 35 percent have poor logistics recovery, 27 percent of supplier sites lack business continuity procedures, and 37 percent have no backup power.

Unfortunately, it comes as a surprise to many supply chain managers that a large proportion of their suppliers are woefully unprepared to withstand major disruptive events like hurricanes,” said Sumit Vakil, Resilinc CTO. “This lack of transparency is especially true in the sub-tiers of a supply chain.

More than seven years of supply chain and hurricane data in conjunction with the company’s expertise was combined to create a customized, automated solution for avoiding and assessing the risk at hand in the face of hurricane-related disasters and weather-related disruptions.

The company outlined the following core capabilities of the solution to include: multi-tier supply chain mapping down to the product and part-level, supplier surveys and site readiness assessment, dashboard incorporating AI and recommendations, and ongoing monitoring throughout hurricane season featuring real time supplier impact confirmation during live events.

Taking it a step further, Resilinc’s solution will evaluate customer key metrics, supplier site vulnerabilities, regional hurricane risks, revenue risks, and more.

“Based on data, heuristics, history and other factors, Resilinc will come back with very specific recommendations, such as ‘move inventory from that site,’ or ‘evaluate your safety stock for that part,’ to provide clients specific targeted recommendations to mitigation action and protect revenue,” said Resilinc Senior Director Jon Bovit.

Source: Resilinc