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Aberdeen Standard Investments Launches Global Equity AI Fund

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ABERDEEN STANDARD INVESTMENTS LAUNCHES GLOBAL EQUITY AI FUND

Aberdeen Standard Investments has launched a new fund that utilises machine learning to identify sources of potential returns.

The Aberdeen Global (AG) Artificial Intelligence Global Equity SICAV, launched in Luxembourg, is the product of a collaboration between Aberdeen Standard Investments’ Quantitative Investment Strategies (QIS) team and Mitsubishi UFJ Trust Investment Technology Institute (MTEC)/Mitsubishi UFJ Trust and Banking Corporation (the Trust Bank) in Tokyo, Japan – a centre of excellence in robotics, artificial intelligence and financial technology.

The Fund embeds machine learning techniques within the investment process and will use a variety of quantitative techniques to time its investments.

These investments will be based on  ‘factor premia’ – those sources of risk such as value, quality, momentum, small size and low volatility that can provide investors with persistent risk-adjusted excess returns.

Martin Gilbert, Co-CEO at Standard Life Aberdeen, comments:

“For active investment management firms, the ability to use machines to read and understand vast amounts of data in order to forecast market moves more accurately has spawned innovation and a resurgence in active quantitative investment approaches. To benefit from this AI-driven innovation, and to complement our highly successful active fundamental strategies, we are proud to have collaborated with the MTEC – Japan’s leading and most prestigious financial technology think-tank – and the Trust Bank to develop this active quant Fund.

Junichi Narikawa, President of Mitsubishi UFJ Trust Investment Technology Institute (MTEC), added:

“This is the first time in MTEC’s 30-year history where we have collaborated with an entity in Europe and are pleased to work with a world-class investment firm of the calibre of Aberdeen Standard Investments. We have worked with their Quantitative Investment Strategies team in London and Edinburgh over a two-year period, and  developed a number of innovative AI-models to identify and capitalise upon patterns in global equity markets in order to dynamically time factor premia to generate alpha.”

David Wickham, Global Head of Quantitative Solutions at Aberdeen Standard Investments, comments:

“Recent innovations in AI, combined with rapid advances in computational power, have enabled us to harness machine learning techniques to dynamically time factor premia. This is an innovative AI-powered approach to factor timing, that enables us to systematically determine the weightings to each factor within the new global equity Fund and also allows us to time the relevant individual metrics used within those factors. We can now bias our portfolio towards the factors best suited to today’s market environment and continue to evolve the factor exposures as the market changes through time. 

“This new technique builds upon our existing diversified multifactor investing strategies – namely SMARTER Betaand BETTER Beta2that we have successfully employed for over a decade.  We believe this is a unique approach within the mainstream investment community. At present, most AI products are either thematically focused, investing in well-known and relatively expensive AI-related companies – or ‘big data’ focused where investment managers attempt to extract alpha from unstructured data sources using machine learning techniques. We’ve created an elegant approach with great return potential by embedding machine learning within the investment process to enhance factor timing.”

This new capability is an extension of the firm’s existing factor investing strategies, amounting to USD 49* billion in assets, including the recently launched proprietary SMARTER Beta multifactor equity indices and funds and the BETTER Beta range of enhanced indexation funds. Each of these strategies embed an ‘ESG Inside’ methodology to exclude those companies engaged in producing controversial weapons and, where applicable, companies that are deemed to be experiencing severe ESG controversies as rated by its ESG data partner Sustainalytics.

1SMARTER Beta = Systematic, Multifactor, Active Measures, Resilient, Transparent, ESG Inside and RIPE Factors
 
2BETTER Beta = Beta, Enhanced market cap, Tight tracking error, Transparent, ESG Inside and RIPE Factors

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High yield value trap: party over for high yield bonds as risk no longer rewarded

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High yield value trap: party over for high yield bonds as risk no longer rewarded 1

High yield bonds are no longer rewarding duration and credit risk correctly, argues RWC Partners’ Justin Craib-Cox, and investors should consider using convertible bonds to earn equity-like returns as volatility continues to affect markets.

Following an initial widening, high yield bond spreads quickly tightened in the wake of the initial coronavirus crisis, despite signs that economies have a long way to go and there may be more stress to follow.

With high yield bonds offering under-appreciated risks in the current environment, investors should look elsewhere for debt that has equity-like returns according to Craib-Cox.

“Bond markets are at a turning point, where taking credit and duration risk will not be rewarded as it was in the past,” says Craib-Cox.

“High yield bonds have enjoyed very strong risk-adjusted returns in recent years. That is because the environment has been broadly supportive, thanks to low rates, minimal interest burdens and muted volatility of outcomes. And with investors in need of income and having to allocate more to high yield, it becomes a sort of circular arrangement.

“So why was this period so good for high yield? Simply put, massive monetary support from central banks pushed interest rates lower and dampened volatility, and those conditions helped to limit defaults in high yields while pushing bond prices higher.

“Plus, risk preferences and an aging global demographic created more demand for bonds, providing a steady bid for more speculative credit. In other words, the bet of loaning money to shaky companies worked fine in this period, given that high yield issuers were largely able to repay or refinance their debts.”

But where the market stands today in the ‘New Normal’ is clearly different, Craib-Cox believes.

“Asset price volatility has increased with the more uncertain future following the Covid-19 pandemic, even with rates staying low and governments pledging fiscal support. Corporate defaults, particularly in the US, have crept up even before the coronavirus crisis began.”

Speculative-grade corporate default rates

Source: Moody’s Investors Services, 31st August 2020.

Source: Moody’s Investors Services, 31st August 2020.

“The rapid spread of the pandemic caused a massive widening in credit spreads in March and April 2020, and a subsequent loss of capital for the sub-investment-grade bond market. As such, high yield does not look like a bargain anymore, with spreads recovering to pre-lockdown levels while the probability of defaults has plainly increased.”

“In a world of low rates and low volatility, issuers used the high yield markets with carefree abandon and no concern for extra leverage. Now that volatility and uncertainty have returned, simply adding another layer of debt to get through a rough patch doesn’t make as much sense.

“Overleveraged issuers are facing conditions vastly different to those they assumed when taking on debt, and investors accustomed to low defaults from this market are thinking again about exposure to this asset class.”

Craib-Cox argues investors in high yield bonds that have the flexibility to earn return through embedded equity options should consider convertibles, which have outperformed high yield this year.

Convertibles vs High Yield

1-year performance

Source: RWC Partners, 30th September 2020.

Source: RWC Partners, 30th September 2020.

“While high-yield bonds are a one-way bet that a speculative issuer will not default, the embedded option to convert gives positive returns if stocks rally, but limited downside thanks to a bond floor.

“These structural features helped convertibles to outperform high yield, both when markets sold off in early 2020, and during the rally that began in April 2020.”

“In fact, from the year’s lows, convertibles recovered to pre-lockdown levels more quickly than high yield, and as of the end of September, convertibles are positive for the year while high yield remains negative.

“Issuers too are now choosing to use convertibles, with a record amount of issuance in 2020. Convertibles are being issued by companies that may be the stronger operators in a temporarily challenged sector, or looking to finance growth prospects, particularly in sectors such as IT where the pandemic has created opportunities in areas such as distance working and learning.

“With less representation from highly leveraged or cyclical sectors, many investment grade or equivalent convertible bonds, and a growth aspect to many issuers, the sector composition of the convertible market is also quite different to high yield, with potential diversification for credit.”

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Investing for Infrastructural Resilience

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Investing for Infrastructural Resilience 2

Today, the concept of resilience is applied in a range of contexts from ecology and disaster management to cyber security and engineering. The notion of resilience has been at the forefront of discussions around the global post-Covid-19 recovery and our collective efforts to build back better.

For impact investors, this means directing our capital allocation and stewardship activities towards solutions that can drive systems change and transformation. At Tribe, we divide our range of resilience-based investment opportunities into three categories: infrastructural, planetary and human resilience.

In this article, we focus on Infrastructural Resilience. The investments are designed to strengthen our man-made environment and improve its capacity to withstand the various potential social-ecological disruptions on the horizon.

DIGITAL INNOVATION

Digital technology and software has the unique ability to support the delivery of all 17 UN Sustainable Development Goals (SDGs). Digital technologies increase our capacity to connect and communicate, supporting engagement with political, educational, healthcare, and other welfare-based systems.

Moreover, digital innovations like Artificial Intelligence (AI) enable us to monitor and understand with greater clarity the changes unfolding in the world around us, so that our responses can be more targeted and precise. The rise of smart, connected devices and big data capabilities allow us to analyse and optimise our resource use, bringing significant efficiency benefits. Digital technology and software are also a critical element of crisis management, as we have witnessed during the Covid-19 pandemic with the successful shift to remote working for many.

SUSTAINABLE CONSTRUCTION

Our conventional modes of construction are set for reimagination as buildings currently account for roughly 39% of global energy-related carbon emissions as well as significant volumes of water and material consumption. Numerous initiatives have been developed to promote the delivery of resource efficient buildings and refurbishments.

Technologies like high performance insulation, natural ventilation and heat recovery systems, natural daylighting systems, greywater recycling and onsite renewable power generation, can be used to significantly reduce the operational resource footprint of buildings. Digital innovation also has a role to play in smart energy and water management systems which can drastically improve resource efficiency.

Buildings made from conventional building materials, like cement and concrete, also account for significant amounts of embodied carbon. A wide range of bio-based, renewable and recyclable materials show promise as alternative building materials, from bamboo to seaweed. These alternative materials are effective at locking in sequestered carbon and supporting biodiversity during their growth.

CLEAN AND RENEWABLE ENERGY & TRANSPORT

There are infrastructural shifts in support of renewable energy generation and low-carbon transportation which will be critical enablers of cross-sectoral decarbonisation, to bring us in line with the 1.5°C warming goal outlined in the Paris Climate Agreement.

Renewable energy generation allows us to move away from pollutive fossil fuels and instead power our lives and economies in a cleaner, more affordable way. Renewable energy sources continue to prove increasingly cost-effective and efficient across a range of technologies, including solar PV, onshore and offshore wind and geothermal power. Moreover, advances in battery energy storage and smart grid technologies show promise for improving efficiency and balancing out the intermittency issues inherent in harnessing natural elements like sunshine and wind.

The electrification of the transport sector is another essential infrastructural shift, and one that relies on affordable and reliable access to renewable power in order to deliver decarbonisation benefits alongside reductions in ambient air pollution. Innovations in vehicle-to-grid technology highlight the potential for electric vehicle batteries to help balance out power supply and demand while charging, which will enable the integration of more renewable power into the electricity grid. In addition to electrification, innovative fuels like green hydrogen could become feasible solutions for the decarbonisation of harder to abate transport sectors like shipping and aviation. Meanwhile, connected and autonomous vehicles could help to shift us towards a more efficient ride-sharing economy, while improving road safety and reducing air pollution.

This range of opportunities demonstrates the scope we have to truly build back better. Sourcing investments which drive change and improve efficiencies in our man-made environment is at the heart of our focus on Investing for Infrastructural Resilience

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Humans vs Robots: Which Is Better for Managing Investments?

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Humans vs Robots: Which Is Better for Managing Investments? 3

By Anton Altement, CEO of Polybius and OSOM Finance,

In an era of technological advancement, innovation, and fear-mongering sci-fi programs, fears over a robot uprising and artificial intelligence coup are rife. While these two hyperbolic scenarios are likely a while off, trading bots used within financial dealing are starting to supersede their human researcher counterparts. On Wall Street, these infallible and emotionally-neutral trading automatons are gathering acclaim. And some propose that they’re going to change the face of finance forever.

Let’s face it, not many humans are cold-blooded and rational enough, which are essential qualities for long-term trading success. This means those few strong traders can ask for high fees for their services, which are often completely unpalatable for a small investor. Robo-advisors, on the other hand, do away with this hubris, epitomising financial inclusion and cost-efficiency. Moreover, they are much more scalable than a human trader, with the ability to trade multiple markets at once.

Major commercial banks are the first to see the potential in these robo researchers. In 2019, multinational investment bank Goldman Sachs announced its own robo-advisory service. While the launch is postponed until next year due to coronavirus-based disruption, the market for robo advisors is still booming, with trading bot usage has grown between 50% and 300% from December 2019 to January 2020.

Why? Because unlike human traders, robots aren’t restricted by the primal urges of the reptilian brain.

A Quantitative Solution to Irrationality

There are few triggers more powerful in electing an emotional response than money, power, and greed. Our internal struggle to satisfy any one of these desires can set us on a disastrous course for failure—particularly when it comes to trading. The fear of missing out, loss aversion, and even hubris present major obstacles for traders to overcome. And, historically, we have very little success in doing so.

There are a few techniques at a trader’s disposal when it comes to evaluating entry and exit points for a trade. For the most part, they can be categorised into two distinct approaches: qualitative and quantitative analysis.

A qualitative approach involves in-depth data analysis pertaining to subjective information, such as company management, earnings, and competitive advantage.

Quantitative analysis, meanwhile, examines the statistical attributes of an asset, including performance, liquidity, market cap, and volatility. For the data-driven cryptocurrency market, with its swathe of exchanges and bounty of information (total supply, transaction volumes, fees, and mining metrics, etc.), it’s the latter quantitative approach that is often favored.

This is reflected by the 2020 PwC–Elwood Crypto Hedge Fund Report, which details that nearly half of all crypto fund managers (48%) opt for a quantitative trading strategy. And there’s one clear reason as to why. A quantitative approach—in the main—aims to neutralise cognitive bias.

Still, try as they might, no human is capable of totally ignoring their primal instincts. And that can prove troublesome.

In a study into emotional reactivity on trading performance, researchers of the MIT Sloan School of Management found that excessive emotional responses can be extremely detrimental to trader returns, particularly during times of crisis and within high volatile markets.

But where humans fall down, the novel trading bot thrives.

The Rise of the Robo Advisor

Trading bots are much more nuanced than their all-encompassing moniker would suggest. These bots come in many different varieties. Two of the most common are the analyst and advisor bots. The latter advisors build portfolios based on the client’s risk profile. Robo analysts, meanwhile, probe data released in annual company records, as well as SEC filings, to provide buy and sell recommendations.

Despite their varying traits, both benefit from negating the cognitive biases inherent in human researchers, analysts, and traders.

As such, within volatile and high-pressure market conditions, trading bots have proven to surpass the performance of their human equivalents.

A 2019 study from Indiana University appraised over 76,000 research reports published over 15 years from various robo-analysts. Researchers found that the robo buy recommendations conferred 5% better returns than those of the human analysts.

But while bots may have the edge over humans, their results vary wildly when competing amongst themselves.

Between May 2019 and March 2020, researchers pitted 20 German B2C robo-advisors against each other, measuring their performance and calculating the differences. The variation among the bots was enormous. But most impressive of all was the bot that came in pole position. The top robo advisor managed to restrain losses to just -3.8%, beating the other bots by around 14 basis points. And decimating traditional hedge funds who were down approximately -10% across the board following March’s tumultuous marketwide crash.

As it turns out, the main difference between the top robo performer and the rest was its unique strategy. The robo advisor not only used quantitative analysis, but it leveraged the irrationality of the market to its advantage—measuring conventional risk metrics, such as loss aversion bias and recovery time, to ascertain illogical trades and position itself on the other side. In doing so, it was able to interpret the market better than both the determinedly quantitative-based bots and the human-operated hedge funds.

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