Alternative data and artificial intelligence - the future fuel for investors

Tomas Franczyk, Managing Director, Head of Global Information Services, Asia Pacific, Nasdaq. This is the undiscovered data from non-traditional data sources that give investors information and unique insights to help them evaluate investment opportunities.

The alternative data market, expected to become a $1.7 billion industry in the next few years, can encompass a range of sources.

These include natively digital information like web traffic, online buying habits, and social media activity, as well as more granular indicators of financial performance, such as ocean cargo and in the capital markets space, alternative data is viewed as increasingly important.

According to a 2019 survey by Greenwich Associates, 95% of trading professionals believe alternative data will become more valuable to the trading process, and 85% of banks, investors, and capital markets service providers plan to increase spending on data management.

As this new data becomes a powerful differentiator in the search for alpha, a rapidly growing community of buy-side firms have started using it to add power to quantitative and fundamental investment models with the aim of outperforming the market.

For example, Nasdaq's platform Quandl, which identifies datasets from local firms to build investment models, has partnered with large insurance companies in the United States to access insurance policies on this enables users to accurately measure car sales before automotive manufacturers report them.

This data would be extremely important, say, to hedge fund investors who need investment insights into the automotive sector.

Meanwhile, in Asia, Nasdaq is building regional-specific data products and has partnered with local fintechs and other innovative local vendors to migrate their core data and alternative data to the more sophisticated technologies mean organisations can create datasets that support managers with short-term trading strategies as well as those with a long-term approach, such as institutional investors.

Another report by Greenwich Associates last year found that 74% of firms surveyed agreed that alternative data has started to have a big impact on institutional investing, while nearly 30% of quantitative funds attribute at least 20% of their alpha to alternative data.

It can only work if it is properly interpreted and analysed.

By its nature, alternative data is harder to consume than financial data; it is often unstructured, does not follow patterns, and is created at a very fast rate.

Hence, investors now have a growing need for talent and technology, including analytics platforms, testing tools, fluid data architecture, and data science teams, to help them with their data management.

Advanced analytics and artificial intelligence (AI), such as machine learning and natural language processing, can be crucial to analysing data.

Machines can process events at roughly 2,000 times the speed of humans, digest vast datasets, and work around the clock.

During the investment process, AI-enabled data processing can increase the volume and quality of idea generation; this increase in data, including alternative data, when combined with computing power can help investment managers develop a long-lasting competitive advantage.

While some organisations are well on their way to introducing AI-based models, the industry is still understanding and identifying the operational, regulatory, and technological risks that come with the race effective risk management practices will be key for the successful adoption of AI.

Data providers have an opportunity to assist the asset management industry by making alternative data and AI the drivers of future investment research.

In fact, we may see active portfolio managers look less to the sell-side for their research needs and instead develop their own research, invest in data experts and technology, and partner with vendors to supply the information and analytical tools they need. Nasdaq offers comprehensive, bespoke, and timely data and insights to help clients build and protect assets.

Temptations - Artificial Intelligence Technology And The Price Of Admission

If your work puts you in regular contact with technology vendors, you'll have heard terms such as artificial intelligence (AI), machine learning (ML), natural language processing and computer vision before.

You'll have heard that AI/ML is the future, that the boundaries of these technologies are constantly being pushed and broadened, and that AI/ML will play an integral role in shaping this tech-forward era's most successful business models.

As a technology leader, I've heard all these claims and more. To say that AI/ML will play an increasingly impactful role in business is no overstatement. According to a recent Forbes article, the machine learning market is poised to more than quadruple in the coming years.

Many industry watchers agree that AI/ML solutions, when used to good effect, can equip your organization with a significant competitive advantage. And that makes it tempting to dive right in and start implementing these technologies without first gaining a comprehensive understanding of how they work. Accessibility to myriad options is not a barrier; almost every technology vendor now offers AI/ML services.

If anything, we are often inundated with choices in this domain. But how do we know we're making the right choices and using these services to good effect? This is where a genuine, comprehensive understanding of technology becomes critically important. For many of us, the world of AI/ML is a relatively uncharted terrain.

The answers to these fundamental questions are the keys to unlocking the true potential of AI/ML as business solutions. Current machine learning is a statistical process that employs a model/algorithm to explain a set of data and predict future outcomes. Many of these are "big data" algorithms that analyze huge quantities of data to generate predictions that are as accurate as possible.

Once we understand this, we start to see what is required to effectively use ML as a business solution. We need a lot of it, and we need it to be high quality.

Poor data quality is the biggest impediment to successfully adopting and deploying AI/ML solutions, and insufficient quantities of data can be a major hindrance as well.

Take IBM's Watson for oncology as a cautionary tale. After being trained on a small number of synthetic cancer cases, the Watson supercomputer was discovered to generate "erroneous cancer treatment advice" which ranged from incorrect to outright unsafe.

The data management process, which covers everything from data creation or acquisition to transmission and storage, is therefore intrinsically linked to AI initiatives.

When considering the cost of implementing any AI/ML solution, it's vital to also consider the cost of obtaining a robust amount of high-quality data with which to feed that solution.

Considering AI/ML Solutions In The Context Of Your Needs

Now, with a better idea of what goes into deploying AI/ML solutions, we have to consider each of our options in the context of our vision.

What do we hope to achieve by implementing AI/ML strategies?

Any AI/ML technology we implement will function within a web of our existing applications, interfaces and platforms.

So, when crafting our vision, we need to take our organization's existing technology ecosystem into consideration.

Precise goals will help us ground our vision in reality, while a more ambiguous approach may lead to equally muddled (and unsatisfactory) results.

An effective machine learning model or algorithm must, of course, continuously learn.

We won't see much success with a "set it and forget it" mentality when it comes to machine learning algorithms.

If our algorithms don't rapidly adapt to changing requirements, they quickly become irrelevant and unproductive.

It's just as imperative for an algorithm to be unbiased. Cathy O'Neil, the author of Weapons of Math Destruction, spoke to NPR about the dangers of placing blind faith in the objectiveness of ML algorithms when "we really have no idea what's happening to most algorithms under the hood."

Many of the models used today across the public and private sectors certainly suffer from the prejudices and misconceptions of their designers. In 2011, a Massachusetts man was informed his driver's license had been revoked because a facial-recognition algorithm mistook him for another Massachusetts driver who was involved in criminal activity. In a similar vein, Google's hate speech detector was reported to be racially biased.

To make the most of our AI/ML solutions, we have to invest the time and attention to governing them fairly and rigorously.

You might be excited, and reasonably so, about the seemingly boundless potential of AI/ML technology. Or maybe you subscribe to Stephen Hawking's view that the development of AI could be "the worst event in the history of our civilization." In either case, there’s no question that AI/ML technology is here to stay.

Politics and history of Nepal’s Kalapani claim

The Nepali media also backed the country's historic claim to the region, but the coverage of governments in Kathmandu without much emphasis on Nepal's rightful claim to the region has been measured with much blame.

Former Director General of Nepal Topographic Survey, Punya Prasad Oli said there was a "gentleman's agreement" between Nepal and Indian authorities to publish maps after the joint issue of border / delimitation operations and strip maps of their joint border. . After India released its map in November, Nepal was no help, but released its edition.

It was only in 1981 that the two countries formed the Nepal-India Technical Level Joint Boundary Group, which decided to locate the borders, maintain the dilapidated and missing boundary columns and freeze the areas where they were built.

As clearly stated, Nepal's position in relation to Kalapani, Lipu Lekh and Limpiyadhura is based on a map of British East India, published after the Treaty of Sougouli of 1816 - especially the British map of 1857.

Deepak Gurung needs to be educated in Nepal

On the other hand, India's position is based on a map of the British Survey of India 1857–1881 and beyond. It should be remembered that Nepal's Topographic Survey published the first map of Nepal in 1976, but the artist, Lipu Lekh and Limpiyadhura were not shown. On the other hand, Nepal maps published in textbooks during the Panchayat period contain these areas. The new political map has an appendix-like piece from the northwest corner of Nepal.

There is no other treaty that Nepal has entered into with British India, claiming that Nepal has changed its western boundary due to natural causes. Although the flow of rivers has changed in some sections of Terai following the Treaty, the status of the river is taken as a boundary at the time of the Treaty, according to international boundary principles.

An Indian argument is that British cartographers continued to move the Kashi River to the east for strategic reasons, so Nepal should accept it without question.

There are no records in Nepal to suggest that these boundaries were jointly made between the British East India Company and Nepal. There is no water on the international border crossing due to a change in the route of the mountain river. Although these changes along the river route are described in maps published by the Survey of India under British rule, they cannot be used as a reference for determining international boundaries.

Two Nepal-India allies face Alisha Sizapati

Perhaps Indian Army Chief General M.N. Narvana made a very serious statement last week, which suggested that Nepal was influenced by the 'Third Party' in bringing about the issue of artisans. It is not only in Nepal but also in India where the former Indian Ambassador to Nepal is. A-Salah said, creating a ruckus.

According to Biswabandhu Thapa, who was the Home Minister in the reign of King Mahendra in Nepal in 1962, Prime Minister Jawaharlal Nehru wrote a personal letter to King Mahendra. Ask for the Indian War.

Two American astronauts enter the International Space Station (ISS)

American astronauts Doug Hurley and Bob Benken have entered the International Space Station (ISS). 

Their Dragon Capsule, operated and provided by a private SpaceX company, was attached to the space station at a distance of 422 kilometers from China. After waiting a while to check for leaks, pressure and temperature, they landed at the station to join the Russian and American teams already on the ISS.

Hurley and Benken were launched from Florida on Saturday. This is the first time astronauts have been sent from American soil since NASA's shuttle system shut down nine years ago.

NASA has been using Russian rockets for manned space travel since the shuttles ceased operations in 2011. Through this mission, NASA has signaled the beginning of a new era of commercial leasing, not its own spacecraft. NASA will no longer buy or operate US spacecraft to and from the space center.

Only California-based companies like SpaceX of Heathron, led by billionaire Elon Musk, do such work. The connection to the Dragon ISS was confirmed on Sunday at 14:16 GMT. The SpaceX Falcon reached the space center 19 hours after it was launched from the Kennedy Space Center.

The process of connecting two vehicles is fully automated; Hurley and Bencon didn't have to be involved - but they did practice. The door between Dragon and ISS opened at 17:02 GMT. Hurley and Benken floated to meet ISS commanders and NASA astronauts, as well as Russian astronauts.

"We're happy to be here and now the commander here will put us to work. And, hopefully we'll get used to it and not spoil a lot," said Doug Hurley.

Another astronaut, Bob Banksy, said they had rested well and were ready for more work. "We slept well for seven hours or so," he said in a radio contact with Texas-based Mission Control.

"The first night is always a little challenging, but the dragon was Kaida's vehicle, and the air flow was good and the night was great. We're eager to be in Earth orbit again."

Earlier, the space trip was scheduled for Wednesday but was postponed due to bad weather. NASA Administrator Jim Bridenstein congratulated them both on their good work: "The whole world has seen this mission and we are very proud of what you have done for our country and especially for inspiring the whole world."

The SpaceX company last year launched an unmanned spacecraft in an automated process, but this is the first manned spaceflight.

During the mission, Hurley and Benken's job is to inspect the entire system and inform the engineers about it. It is unknown at this time what he will do after leaving the post.

During that time, he became a member of the current ISS Expedition 63 team and participated in daily activities there. Hurley and Benken were selected in 2000 and have been to space twice before.

ISS commander Chris Cassidy joked that they had missed the opportunity to clean up on Saturday as they arrived on Sunday.

The spacecraft Dragon Capsule carrying two American astronauts has entered the space station.

The spacecraft, including US astronauts Doug Hurley and Bob Banks, has entered the International Space Station (ISS), according to US media reports.

The US space agency NASA has launched the spacecraft in collaboration with the private company SpaceX.

Dragon Capsule is provided by SpaceX and is being operated by him. The spacecraft entered the space station 422 kilometers above China.

After waiting a while to check for leaks, pressure and temperature, passengers in the Dragon capsule entered the station to join the Russian and US teams already on the ISS.

The Dragon Capsule spacecraft, including Hurley and Benken, was launched from Florida, USA last Saturday night.

NASA shut down its space shuttle system nine years ago. This is the first time an astronaut has been sent from American soil since then.

Through this mission, NASA has ushered in a new era of renting spacecraft from the commercial sector, not its own spacecraft.