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KNOWING WHAT YOU DON’T KNOW: PREDICTING BLACK SWAN EVENTS

Jacopo Credi, VP of AI at Axyon AI

Analysing market trends is fundamental to making effective investment decisions, so it is no surprise that technology has become integral in helping businesses make the right choices. However, advanced data analysis is constantly evolving and there is still some way to go before it becomes knitted into the fabric of every business.

The next challenge for investment analytics is predicting so-called ‘black swan’ events, which tend to catch businesses, markets, and governments by surprise. Fortunately, this is an area in which Artificial Intelligence (AI) is already making major inroads.

Sophisticated AI algorithms currently use data from past events as building blocks to predict industry trends and market shifts. As a result, this technology enables businesses to take investment analysis to a whole new level, since the more historical information the machine has access to, the better the analysis produced.

While this innovation does not eliminate the impact of a black swan event on the investment landscape, increased understanding of the marketplace can be vital for gaining fresh insights and predicting how different sectors will respond to different situations. When used in this way, AI can therefore help to limit the shock of a major incident dramatically.

Jacopo Credi

A new hope

Despite the perception that black swan events are seemingly impossible to anticipate, incidents ranging from political unrest to revolutions in technology typically have a number of trends in common. As a result, the outcome of previous events can be used to piece together a more accurate image of what the market’s reaction would be if something equally unique, but with similarities to previous events, were to happen in the future.

New AI practices such as Generative Adversarial Networks (GANs) are well placed to analyse events like these. GANs can be used to repeatedly stress test the market by having two separate AIs work against one other. While one AI creates different scenarios, the other decides which information is real and which is false. This way, the AIs continually learn from one another over time, with one developing more complex data sets while the other improves its analysis techniques.

As such, GANs have the potential for businesses to evolve their processes and respond to shock market changes far more effectively. Not only can potential black swan events be tested with this model, but through this self-learning process, GANs can also develop their own hypothetical scenarios beyond human imagination.

With this level of predictive power, it is no surprise that GANs are seen by AI pioneers like Yann LeCun, the current Director of AI Research at Facebook, as the most interesting idea about machine learning to emerge in the last 10 years.

People power

However, despite these advancements, humans still have a crucial role to play in the data management process. Manual oversight is needed to review results, ensure they are accurate, and remove any inconsistences or outliers. By following this process, the business can refine its AI algorithms over time to provide a more accurate image of the market and how it will respond to different events.

To support this, however, firms will need to democratise their data. Traditionally, a great deal of company information has only been available to a select few, but in order to utilise the potential of AI and GANs, this will need to change. Employees will need to have sight of data including trade history, investment yields and outcomes to better understand the AI’s decisions and amend it correctly. This will be especially important when it comes to managing a black swan event, since employees will need to have the knowledge, tools and ability to react in the right manner.

Despite AI’s advanced nature, this level of human involvement in the data management process is crucial. In every company, employees must have a solid understanding of how to sense check AI’s findings and ensure that data is consistent. This technology can act as the guide for workers and empower them to learn more about the business and the potential investment risks, but AI will ultimately deliver the greatest benefits through the combined efforts of both man and machine.

The global market is still very volatile, which means that black swan events will continue to cause assets and industries to shift in completely different directions. While black swans cannot be avoided completely, technology like AI can help businesses better prepare for these events by giving enhanced risk estimates of what may happen.  

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RISK VS REWARD: IS AI TAKING OVER?

Xavier Fernandes, Analytics Director at Metapraxis

A study by Oxford University academics into “The Future of Employment” in 2013 prompted apocalyptic headlines which stated that in the future 40% of jobs will be automated thanks to advancing technology.

The researchers subsequently claimed that the truth was in fact a little more prosaic; rather than facing complete automation, the research found that 40% of jobs faced some aspect of automation in their activity. So with new ‘AI processes a likely reality for almost half us, what does that mean for our current roles and should we be worried?

 

The fourth revolution?

The first industrial revolution saw machines replacing muscle, both human and animal. The second and third saw electrical power, mass production and computerisation revolutionise the job market. Now, with daily headlines of AI as an employment superpower, there is some concern that AI is bringing a fourth revolution, and with it, unknown circumstances.

This ‘fourth industrial revolution’ is defined by replacing brain power with machines. Our thinking capacity is what inherently sets us apart from other species, so it’s not surprising that any encroachment on it triggers some existential angst.

 

Xavier Fernandes

Evolve to reap the rewards

While many businesses still don’t fully understand the capabilities of AI, those who fear its development are, instead of embracing it, missing all the benefits that it can bring to the workplace. Businesses that utilise AI appropriately are seeing vast improvements across their entire value chain; better customer experience, reduced costs, and more insightful analysis to support management decisions.

AI is particularly useful for supporting tasks with repetitive activity, for example, performing financial checks and assessing large sets of data within financial services firms. AI performs particularly well within this context, spotting outliers before a human expert would notice them, allowing impending problems to be flagged and avoiding costly mistakes.

There is also an increasing focus on maximising customer lifetime value through the use of AI. Being able to predict existing customers’ needs as well as track trends in their financial circumstances is supercharging the old cross-selling approach with testable, predictable outcomes.

With potential benefits like these on offer, management teams of innovative financial services are increasingly relying on AI to help them with some of the heavy-lifting of analysis. Using advanced data capabilities and learned behaviours, AI analyses market trends to provide predictions of future performance. This insight is invaluable and allows management teams to change direction and  correct any problems accordingly. This offers a huge advantage over those that have not adopted such tools.

 

Supporting the workplace

Algorithms and AI are typically ‘smart’ at doing one, tightly-constrained task, but they can be less helpful with many of the activities that humans find straightforward. In most white-collar jobs, automation tends to replace certain tasks in the job, rather than the role in its entirety, as the need for human intelligence is still highly necessary. In particular, we still need human input to first challenge, and then synthesise, this information before taking action. Employees should therefore work with the business to proactively identify what areas of their role could be automated, so that they can focus on the areas that add real value to the business’ commercial goals.

Challenging AI is certainly still important. We know that algorithms can be much better than humans on certain, bounded tasks. However, many algorithms rely on existing data sets to build their understanding. As a result, when a business unit has ‘symptoms’ that fall outside of that body of knowledge, the algorithm may suggest the wrong course of action with costly results.

Indeed, even with plenty of data, algorithms will reflect any biases the data set contains. We’re seeing this with some legal sentencing algorithms where there is evidence that they are treating disadvantaged people more harshly. Getting the answers to why and how far we should trust our algorithms should therefore become an everyday part of any job affected by AI.

Rather than depending entirely on AI for all decisions, workers should be taking all these new, AI-generated insights and using them to complement the human decision-making process. No manager of a complex business ever has enough time to sieve through all the analysis available, but with AI driven algorithms able to flag up any issues and indicate where action needs to be taken, we may find that we have some AI ’colleagues’ who will cover our backs and suggest innovative options. Yes, there will be times when the algorithms get it wrong, but as long as we’re watching out for those, the future is bright.

 

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HOW TECHNOLOGY IS FUTUREPROOFING STOCK MARKET TRADING

stock market

Tony Shaw, Executive Director, London Office and Head Sales UK & Ireland at the Swiss Stock Exchange

 

Markets are shifting, there’s no doubt. Amid all the disruption and volatility from the past year, the Swiss Stock Exchange asked traders about what they expected in 2020 and beyond in our industry survey. The findings point to a rise in digital to help traders content with external forces.

 

First and foremost, traders are enthusiastic about what digital assets can offer.

Two thirds of traders polled said they’d had a marked rise in interest from their clients for digital assets and crypto-products. Given the interest, traders are increasingly bullish about the potential of these products – so much so that 80% have predicted an increase in overall demand in the long term. Market users believe these assets will help generate cost synergies and streamlining trading and settlement processes by creating efficiencies and ultimately reducing costs.

Our 2019 results reflect what traders have told us when it comes to digital assets and products. Last year, we saw significantly higher trading volumes from products with crypto currencies as underlyings. Overall volumes grew by +8.5% over 2018, but the increase in crypto products alone was +17%, reaching CHF 518.2 million ($534.54 m). There was a year-on-year increase in the number of transactions, as well (+21%): 19,636 trades in total.

The potential digital assets hold is clear – evidenced by the building of the SIX Digital Exchange (SDX), a fully integrated issuance, trading, settlement and custody infrastructure for digital assets.

According to traders, artificial intelligence (AI) is expected to bring further benefits to market operations.

Two thirds of our survey respondents anticipate AI will create more opportunities for the traditional equities business, while a similar number expect it to reduce the cost of trading. Innovation in AI is already – and will continue to be – a key driver in making our industry more effective at withstanding future risks and challenges both within and beyond the market itself.

In Europe, there is growing momentum behind calls for shorter trading hours – this trend was reflected in our survey as well.

Industry groups such as the Investment Association are advocating for stock market trading hours to be cut from 8.5 to 6.5 hours to open the industry to working parents and women who cannot commit to such long workdays. We found traders were largely supportive of this, with many saying that it could even facilitate operational benefits. The roll of AI is clear here in improving efficiency while minimising time wastage: 36% of traders said the introduction of shorter trading hours would prompt greater market liquidity.

Beyond the market itself, geopolitics continue to shape wider market sentiment.

It comes as no surprise that four fifths of traders said their strategies have been – to some extent – influenced by Donald Trump’s tweets. Interestingly, only 39% of those polled viewed Brexit as an influencing factor in trading activity, while three quarters believe the US election will drive trading activity in 2020 and 65% acknowledged trade wars would also have an impact.

More broadly, traders are split on the state of the global economy – 58% are bracing for a global recession while 42% predict stable macro-economic conditions over the next three years. What seems clear is that whatever happens in the wider economy, traders are making headway with new technologies that can improve their strategy, efficiency, and overall market health.

 

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