AURORA INV TST PLC

Investor Presentation • Jan 5, 2024

Holdings >3% on 31 December 2023	(%)
Frasers Group	21.7
Barratt Developments	15.8
Castelnau Group Ltd	13.1
Ryanair	7.4
Netflix	6.1
Lloyds Banking Group	6.0
Hotel Chocolat	4.7
RHI Magnesita	4.3
easyJet	4.1
Bellway	3.8
AO World	3.0
Others <3%	6.9
Cash & Cash Equivalents	3.1

Aurora Investment Trust – December 2023

Share Price: £2.47 Net Asset Value: £2.73 Discount: 9.5%

Market Cap: £188m

Data as of 31 December 2023

In December, the NAV was up 5.2% for the month, versus the FTSE All Share (incl. dividends), which was also up 4.5%.

For the year the NAV increased by 33.2% versus a 7.9% increase for the index. A pleasing performance but one which should be placed into context with the underperformance in 2022.

In December, the NAV made new all times highs and a performance fee was earned at the end of the year.

From an individual stock perspective, the strongest performer during the month was RHI Magnesita, which rose 23.8%. Other strong performers of note include easyJet and Bellway, rising 12.5% and 10.8% respectively.

For the year, Hotel Chocolat led the way with an 138% price increase. Other moves of note included: AO World up 89%, Netfilx up 65%, easyJet & Ryanair up 57% & 56% respectively and finally our housebuilders, Barratt & Bellway up 53% and 43% respectively.

investors: Gary will be updating Aurora investors and taking questions on a webinar on Monday 15 th January at 2.30pm. Please contact ir@frostrow.com to register for the event.

Outlook

During 2023 we passed the 25th anniversary of the launch of Phoenix. It has been an extremely interesting period in which to invest and is bookended by two profound technological innovations, the world wide web (often just called the internet) and generative AI. Looking at how the first shaped business and investing over the past 25 years has some useful lessons for how to think about the latter. There has also been a further form of innovation in business management not often discussed which we think, when combined with generative AI makes, in our opinion, what is about to come quite different from the past.

The first websites emerged in the mid-1990s. Yahoo and Amazon launched, and then later stages of a stock market bubble in the shares of technology, media and telecoms (TMT) companies. That bubble peaked in early 2000 but only after having sucked in huge amounts of capital that funded the foundational infrastructure for the internet and mobile telephony. Investors in it did terribly but society benefited. When investors are excited w and invest, it can just raise more and more capital.

Our approach to investing led us to see more threat than opportunity. Fast innovation makes forecasting the future with a degree of confidence difficult. The disruptive nature of the rise of ecommerc worthless. We don money.

difficulty from an investment perspective. For example, we believed in 2001 that smartphones would be We were invested in the company that provided the operating system for all the upcoming smartphones, used by all the leading makers of the day; Nokia, Motorola, Ericsson, Sony, etc. but there you see the problem. Smartphones did become a big thing but none of the leading mobile phone manufacturers survived and even before that Psion sold the business with the operating system in (Symbian). In investing that is called getting it wrong!

The internet has profoundly changed business but interestingly it has happened at the pace of consumer behaviour changes not at the pace the technology could handle. The rise of e-commerce has transformed retail, but it has varied depending on the consumer. Food shopping is often cited as one of the least favourite shopping experiences by consumers and yet it was very slow to shift online. It had only reached a 7% penetration rate in the UK before Covid and then as soon as Covid passed it fell back and is today only 10%.

The UK has the highest penetration of online retail in the world, it currently sits at 27% of all retail sales, and that has dramatically changed the competitive landscape, creating winners and losers. The winners in most sectors have been the incumbent operators who were able to adapt their business models. Amazon was more the exception than the rule because it turns out that supply chain and logistics are critical and physical stores can be an advantage. For example, only 1 of the top 10 fashion retailers is a pure online player (ASOS).

The emergence of online searching and social media radically transformed advertising as a more targeted and measurable means of reaching customers. This caused ad spending to switch away from traditional media and completely reshaped the advertising industry, which is now dominated by Google, Meta (Facebook), Amazon, Alibaba and ByteDance (TikTok). This happened at the pace at which consumers moved online, which was quicker than their adoption of ecommerce. The internet and then social media have become the way consumers often begin their journey towards an act of consumption, and therefore, the gatekeepers to those audiences have built highly valuable franchises.

Investment discussion is dominated by the sort of macro factors that are largely cyclical and cause oscillations in economic progress. This is very relevant to the near term but becomes much less important as your time horizon increases to the point of irrelevance UK over the past 25 years or even when they happened. We know they will keep happening. What is much more important for investors are secular trends, i.e. those changes that occur over the long term that are not cyclical in nature. The most important

ones during our history of investing have been those related to the rise of the internet and the changes that had on commerce.

discussion, but which could cause even bigger changes in the coming decade, when business, a culture, that gives a big competitive advantage versus the traditional way. Because this new way of working emerged in what were mainly technology companies it was easy to miss, their success has been attributed to the specifics of what they did rather than explained by a way of operating, a culture-based edge. It took us 2 decades to figure it out and pretty much all we do is watch businesses.

There are a few key ingredients to this new way of working that are key: they develop through trial and error, they empower deep into the organisation which devolves and multiplies decision making, they execute at speed by breaking projects into small releasable iterations, they use data and science to make decisions and they foster a culture in which this can happen.

The two most studied companies at Phoenix in the past 25 years have probably been Amazon and Google because they touch just about every area of commerce. Following what they do and trying to interpret it misses the point though, they have evolved not through grand strategy from the top but as a result of the interaction between innovation through trial and error and the results of those iterations.

At the heart of this new model is a better understanding of human motivation which originally came from Maslow. When you are trying to get the best out of people who are doing complex, creative and innovative tasks then the traditional management tools of reward and punishment, carrot and stick, do not work; what works, in the words of Daniel Pink, who has written well on the subject, is Autonomy, Mastery and Purpose. (He summarises his work well in a TED Talk called The Puzzle of Motivation. His book on the topic is Drive: The Surprising Truth About What Motivates Us). The businesses that have developed this new way of working have built cultures that tap into this.

It's not easy to do and has been a continually evolving affair but it links a whole group of companies, with a North California connection whose combined market capitalisation is now greater than that of all the stock markets in Europe. These companies, although defending their intellectual property, have been very open about this aspect of their business. The Netflix culture deck was shared with the world in 2009 and has been downloaded millions of times and has influenced lots of businesses. Google has shared lots of its practices and its whole OKR (objective and key results) framework and toolkits openly which again have influenced many other businesses. Amazon also has been open about the way it operates and innovates. The closer you get to this topic the more you see how the cross influences have occurred. Andrew McAfee, a professor previously at Harvard and now at MIT Sloan, has spent his career around these businesses and has written a very good book on the subject called The Geek Way.

All of those companies talk about culture as something they have to keep working hard to maintain. Microsoft turned into a hierarchical bureaucracy, stagnated and was overtaken by its competitors and was missing out on innovation until Satya Nadella took over as CEO in since Phoenix launched but it has increased 10-fold since he took over. What did he do? He changed the culture, tapping into all the best of what he saw amongst their

competitors. He embraced empowerment and a goal-driven approach to leadership (like OKRs as used by Google) rather than decision by what are referred to in these new fostering empathy, an understanding of human beings and from the top he changed the culture at Microsoft in what has to be one of the biggest and probably most valuable cultural transformations in corporate history.

It may be no accident that Microsoft has gone from an innovation laggard to being the owner of OpenAI and at the cutting edge of the generative AI revolution.

As we take the lessons from investing in the past 25 years and apply them to thinking about how AI will impact the future, one of the biggest differences we see is that whereas the changes brought about by the internet were very influenced by the pace of consumer adoption, a lot of the benefits of AI are internal to businesses and can therefore be deployed at the pace businesses can handle. Change therefore is likely to be quicker and more impactful, both positive and negative.

Much has been written about the seeming lack of productivity growth that has followed from the internet and we have written on this before. We believe it is due to the nature of change, and the measurement of productivity which is generally GDP per person. Ecommerce takes an activity that was not part of GDP, like going to the shop to buy something, and replaces it with something that is, a low paid delivery driver brings your shopping or meal to you for a small cost. This adds lots of low value, low productivity number of people in logistics in the UK has trebled at a time when the total workforce has grown 28% (ONS Labour force data). This growth has exceeded that in computer programming or information services. In fact, the only category with higher growth has been what the ONS calls activities at Head Office and Management Consultancy. Lots of the other benefits of the internet are quality of life, greater information and knowledge and do not show up in productivity data.

AI looks to be different, very different. Generative AI is going to be able to replace a lot of current roles in the workforce. For example, the UK has 800,000 call centre workers, most of those jobs are likely to be done more efficiently and cost effectively by tools utilising generative AI. The change will happen as pioneering companies figure out how to do it and the rest will then follow or go out of business. Paying attention to how management teams are thinking and acting on this is going to be very crucial work for us. Many of these improvements will not give a permanent competitive advantage and so the value is most likely to flow to consumers, but for businesses with strong economic moats and pricing power these improvements will flow to shareholders.

Whereas the rise of ecommerce required a judgement about consumer behaviour and he willingness and capability of organisations to adopt innovations. This is where the cultural advantage discussed above comes into play. Those companies that are already set up to continuously improve through innovative trial and error have a distinct advantage.

In evolutionary biology, the rate at which a species evolves is impacted by how much mutation (or variation) there is and how quickly replication happens. Humans evolve at the pace we reproduce at, which is over 20 years, whereas for some bacteria it is minutes. We think this is a useful model for thinking about how competitive landscapes

develop where those companies who are trying the newest things the fastest, evolve and adapt more quickly than those who are more traditional. The culture of the likes of Netflix, Google or Amazon is highly suited to tying lots of permutations of how AI can help their business and as they find things that work, they can execute quickly. Because they are not waiting on consumer adoption for the effects, then the pace at which they get ahead of competitors who are not set up in the same way is greater.

All the above is learnable and can be copied. Business management innovation is happening everywhere and what you want most in a business is that hunger and curiosity important in the future than it has been in the past.

In the past 25 years we have navigated a huge change in the way commerce happens investment philosophy, focusing on a small number of businesses we could understand well enough to value. We have devoted most of our time to monitoring these businesses, their customers and their competitive landscapes and using our findings to update our assessments and judgements.

believe we are a much more competent organisation than we were 25 years ago, and we need to be because we are working with a bigger pool of capital (£1.5bn vs £6m). AI is improving our productivity too. For example, one of the monitoring programmes we have been running for Barratt Developments since 2008 which involves stripping their individual construction site websites periodically and comparing the change in order to estimate sales rates, used to take up a considerable amount of time for the analyst who did it but now one analyst has written a tool assisted by ChatGPT that runs it automatically. In this way we are able to capture more data, more frequently and with only minimal work from the analyst. By itself it is not an edge because anyone else could do the same but, combined with the way we work, it is.

We have a portfolio shaped by all of the above and believe that the business we are invested in are either set to benefit or at least not be hurt by what is coming. Frasers is an example of the former, a business built by trial and error, it is not the result of a grand vision by Mike Ashley of what a retailer should be but rather as the result of a way of operating that combines trial and error with analysis of the results, (the analytical team also designed to have limited or protected downside, so fail accepted part of business, and successes are backed and multiplied. Applying AI should be a great advantage for Frasers but first they have to figure out the how. They have a culture and mindset that should lead them to do that. Barratt is an example of the latter, i.e. not likely to be hurt by AI. This is because the essence of the business is the ability to source and build on land to the UK regulatory standard at a price that makes sense at secondary market prices. AI may improve productivity in some areas but not in a way at the moment that seems to threaten to disrupt the competitive landscape.

Summary

which has taken the NAV to a new all-time high. The upside to IV is around 130% which is attractive in historical terms.

We expect to continue to be able to deliver you long-term investment returns that significantly exceed those of the market and most of our peers. Our edge remains the

ability to focus effort, think clearly, do nothing for long periods of time, act occasionally when it makes sense and with a longer time horizon than most market participants. That ability is because of the investors and we work for, and we thank you for that.

Aurora Track Record

Performance	NAV Return %	Share Price Total Return** %	FTSE All-Share Total Return Index %**	Relative NAV to ASX %
2023 (to 31 December)	33.2	28.8	7.9	25.3
2022	-17.4	-16.3	0.3	-17.7
2021	19.1	13.5	18.3	0.8
2020	-5.5	-10.0	-9.7	4.2
2019	29.7	31.9	19.1	10.6
2018	-10.3	-10.9	-9.5	-0.9
Cumulative*	85.3	75.4	64.6	20.7

* Since 1 January 2016

**Share price return with dividends reinvested; FTSE All Share Total Return Index with dividends reinvested.

Past performance is not a reliable indicator of future performance.

Aurora Share Price & NAV per Share – 31 December 2023

Past performance is not a reliable indicator of future performance.

Aurora Premium / (Discount) – 31 December 2023

Past performance is not a reliable indicator of future performance.

Aurora shares are eligible to be invested in an ISA or SIPP. Neither the Aurora Investment Trust nor Phoenix Asset Management Partners run such a scheme. You should consult a financial adviser regarding a suitable self-select ISA or SIPP provider.

Investment Objective

We seek to achieve long-term returns by investing in UK-listed equities using a value-based philosophy inspired by the teachings of Warren Buffett, Charlie Munger, Benjamin Graham and Phillip Fisher. Our approach, combined with thorough research, invests in high quality businesses run by honest and competent management purchased at prices that, even with low expectations, will deliver excellent returns.

Target Market

The Aurora Investment Trust is a long-term investment vehicle, appropriate for those making investments with at least a three year time horizon. It is aimed at investors looking for a manager with a business and value orientated approach, achieved through investments in predominantly UK companies demonstrating a high return on capital and control over their profitability through the strength of their business franchise. portfolio is typically concentrated in a small number of deeply researched stocks, which can result in above average volatility. An investment in Aurora may be best suited to investors with at least an underlying knowledge of equity investments. The Trust is measured against a benchmark but does not follow the benchmark in its portfolio construction. It is intended for investors looking for capital appreciation rather than income, and while it does distribute a dividend, this is not the strategic aim of its investment approach.

Contact

Phoenix Asset Management Partners Ltd 64 66 Glentham Road London SW13 9JJ Tel: +44 (0) 208 600 0100 Fund Manager since 28 January 2016

Portfolio Manager: Gary Channon Listing: London Stock Exchange Inception Date: 13 March 1997 ISIN: GB0000633262 Bloomberg: ARR

Fees

Management: None Performance: One third of returns in excess of the market

Regulatory Notice:

This advertisement is issued by Phoenix Asset Management Partners Limited (PAMP), registered office 64-66 Glentham Road London SW13 9JJ. PAMP is authorised and regulated in the UK by the Financial Conduct Authority. Trust Stock Exchange. Shares in an investment trust are traded on a stock market and the share price will fluctuate in accordance with supply and demand and may not reflect the underlying net asset value of the shares. An investment trust may not be suitable for retail investors with only basic knowledge of investments. The value of investments and any income from them may go down as well as up and investors may not get back the amount invested. There can be no as objective will be achieved, and investment results may vary substantially over time. Past performance is not a reliable indicator of future performance. Prospective investors should consult their own advisors prior to making any investment. The Prospectus and other regulatory documents can be found at can be found at: www.aurorainvestmenttrust.com