Polar Capital Technology Trust PLC · LSE:PCT
Polar Capital Technology Trust — H1 2024 Earnings Presentation
53 slides from Polar Capital Technology Trust's earnings presentation, Dec 11, 2023
Slide 1: Polar Capital Technology Trust Half Year Results To 31 October 2023
Polar Capital Technology Trust Half Year Results To 31 October 2023 polarcapitaltechnologytrust.co.uk This is a marketing communication This presentation is for use with non-US investors only. 1
Slide 2: Results As At 31 October 2023
Results As At 31 October 2023 Year ended As at Change 30/04/23 31/10/23 (y/y) Net Assets £2,828,141,000 £3,093,037,000 +9.4% NAV per ordinary share 2239.48p 2509.58p +12.1% Price per ordinary share 1940.00p 2145.00p +10.6% Benchmark change1 - - +12.8% Ordinary shares in issue2 126,285,544 123,249,25
Slide 3: PCT As At 30 November 2023
PCT As At 30 November 2023 Year ended As at Change As at 30/04/23 31/10/23 (y/y) 30/11/23 Net Assets £2,828,141,000 £3,093,037,000 +9.4% £3,381,635,000 NAV per ordinary share 2239.48p 2509.58p +12.1% 2754.50p Price per ordinary share 1940.00p 2145.00p +10.6% 2395.00p Benchmark change1 - - +12.8% - O
Slide 4: Discrete Annual Performance (%)
Discrete Annual Performance (%) Financial 31.10.22 29.10.21 30.10.20 31.10.19 31.10.18 YTD 31.10.23 31.10.22 29.10.21 30.10.20 31.10.19 Ordinary Share Price (TR) 10.57 13.25 -24.66 20.00 47.95 20.41 NAV per share 12.03 19.75 -24.73 26.65 49.01 17.29 Benchmark1 12.77 27.28 -20.30 33.94 39.67 18.87 Pa
Slide 5: Half Year Review
Half Year Review DJ World Technology vs FTSE World TR since April 2023 • Global equities (FTSE World +2% in Sterling terms) continued to rebound, almost recovering their December 2021 highs as earlier 16% banking crises were contained, and economic growth remained 14% robust. However, the market gav
Slide 6: Half Year Review
Half Year Review • US technology outperformance vs RoW technology: W1TECN +12.6% vs W2TEC +1.7%. US large-caps +16.1% vs small-caps +3.8% • Most sub-sectors performed well: Internet +10.6%, Semis +11.9%, Software +11.3% • Relative technology valuations expanded from 1.21x 1.36x during the period •
Slide 7: The Polar Capital Technology Team
The Polar Capital Technology Team • Technology is at the core of the Polar Capital business • One of the largest technology franchises in Europe with cUS$10.1bn under management • Ten dedicated technology specialists – strong multi-cycle track record Global Technology Polar Capital Technology Artifi
Slide 8: 2024: Macroeconomic Outlook – Supportive Backdrop
2024: Macroeconomic Outlook – Supportive Backdrop • Base case for 2024? Moderate US growth, US recession risk recedes (consensus too high %) BUT rates stay higher for longer • Why? Inflation trending down, Unemployment rate low, Strong balance sheets (US economy less sensitive to energy and rates th
Slide 9: 2024: Technology Outlook – AI Tailwinds
2024: Technology Outlook – AI Tailwinds • Moderate US growth in 2024 supportive for tech: Implies rates peaked and scarcity of growth continues (supportive of valuations) • AI could unlock a sustained period of higher growth without inflationary pressures: Potential impact remains underappreciated •
Slide 10: 2024: Technology Outlook – IT Spending
2024: Technology Outlook – IT Spending • IT spending steady: Gartner 2023 global IT spending est. US$4.7trn (+4.3% y/y) vs 2.7% y/y in ‘221, software (+14% y/y) vs devices (-6% y/y)1 • 2024 rebound: consensus 2024 expect technology revenue/earnings growth of 8.8%/15.8% vs S&P 500 est. 5.5%/11.9%2 •
Slide 11: Artificial Intelligence
Artificial Intelligence The Age of AI has Begun AI is one of the most profound things we are working on as a humanity. It is more profound than fire or electricity. - Sundar Pichai, Alphabet CEO This presentation is for use with non-US investors only. Please refer to the Important Information at the
Slide 12: AI: Fund Exposure
AI: Fund Exposure Indicative percentage of portfolio exposed to Artificial Intelligence (100% stock weights) Narrower “Polar” Methodology Broader Methodology (enablers/‘beneficiaries’ only) (also includes ‘adopters’) 4.7% 79.5% 4.7% 95.3% 15.7% 15.7% 30.7% 30.7% 19.1% 19.1% 28.8% 28.8% AI Enabler –
Slide 13: The Summer Of 1956: Two Important Births
The Summer Of 1956: Two Important Births 1956: Creation of the US interstate (highway) system 1956: The Dartmouth conference on AI Source: Indiaai, https://indiaai.gov.in/article/exploring-the-significance-of-the-dartmouth-workshop, 28 April 2022. All opinions and estimates constitute the best judgm
Slide 14: 1956-1986: Highways – Not AI – Transform America
1956-1986: Highways – Not AI – Transform America 1956-1986: Construction of the US interstate system1 Parameter Count of Significant Machine Learning Systems2 45000 40000 35000 30000 25000 Miles 20000 15000 10000 5000 0 Source: 1. Highway History, https://www.fhwa.dot.gov/infrastructure/50interstate
Slide 15: 2011-2015: Emergence Of General Learning Systems
2011-2015: Emergence Of General Learning Systems 2011: IBM Watson wins Jeopardy!1 DeepMind ‘solves’ Atari Breakout2 ...the first significant rung on the ladder to proving general learning systems can work Demis Hassabis, 20153 Sources: 1. Techrepublic, Business Insider. 2. Deep Mind and New Scientis
Slide 16: 2016-2019: Superhuman (But Narrow) AI
2016-2019: Superhuman (But Narrow) AI 2016 2017 2018 2019 AlphaGo AlphaZero AlphaStar Pluribus defeats Go world champion crushes chess engine beats 99.8% of StarCraft defeats professional Lee Sedol Stockfish II players poker players • 1920 general purpose core • Reinforcement learning and • A deep n
Slide 17: 2018-2020: Early Content Creation
2018-2020: Early Content Creation GameGAN by NVIDIA1 Portrait of Edmond Belamy, 20182 AI generated article, 20203 I am not a human. I am a robot. A thinking robot. I use only 0.12% of my cognitive capacity. I am a micro-robot in that respect. I know that my brain is not a “feeling brain”. But it is
Slide 18: 2017: Technology Inflection – Transformer Models
2017: Technology Inflection – Transformer Models Change in computational requirements for training AI models1 10,000,000,000 Megatron-Turing Scalability Self-Attention NLG 530B 1,000,000,000 Training Compute (petaFLOPS) • Model performance • Can weight GPT-3 scales with increased importance of diffe
Slide 19: 2017: Technology Inflection – Transformer Models
2017: Technology Inflection – Transformer Models Parameter Count of Significant Machine Learning Systems1 Threshold for modelling the Scalability Self-Attention content of the Internet • Model performance • Can weight scales with increased importance of different data and compute words in a sentence
Slide 20: 2017: Technology Inflection – Transformer Models
2017: Technology Inflection – Transformer Models Model training (floating point operations)1 Threshold for modelling the Scalability Self-Attention content of the Internet • Model performance • Can weight scales with increased importance of different data and compute words in a sentence • Performanc
Slide 21: Transformer Models: Emergent Capabilities
Transformer Models: Emergent Capabilities Generative capabilities Ability to generate coherent and contextually-relevant natural language Multimodality Applicable to many data modalities – natural language, images, audio, video, code Versatility Models can be fine-tuned on smaller datasets for speci
Slide 22: AI: “Sparks” Of Artificial General Intelligence (AGI)
AI: “Sparks” Of Artificial General Intelligence (AGI) GPT-4 passes technical interviews on LeetCode A question that might be Polar Capital Technology Trust plc lingering…is whether GPT-4 Artificial Intelligence sparks into life truly understands all these concepts, or whether it just became much bet
Slide 23: AI: “Sparks” Of Artificial General Intelligence (AGI)
AI: “Sparks” Of Artificial General Intelligence (AGI) GPT-4 outperforms GPT-3.5 across multiple exams1 A question that might be Polar Capital Technology Trust plc lingering…is whether GPT-4 Artificial Intelligence sparks into life truly understands all these concepts, or whether it just became much
Slide 24: AI: “Sparks” Of Artificial General Intelligence (AGI)
AI: “Sparks” Of Artificial General Intelligence (AGI) What breed of dog? What am I eating? What opening bid? Source: OpenAI GPT4, November 2023, some answers shown are abridged. Some information contained herein has been obtained from third party sources and has not been independently verified by Po
Slide 25: AI: A New Interface For Humans To Interact With Computers
AI: A New Interface For Humans To Interact With Computers PC: Text Graphical User Interface1 1980 1990 1980 c10m 1990 c100m users 2000 c500m users Smartphone: Keyboard Touch2 1998 2007 1998 <1m 2007 c330m users 2017 c2.4bn users Source: Google images, 18 August 2023. 1. Areppim, https://stats.ar
Slide 26: AI: Technology Transitions Drive Huge New Markets
AI: Technology Transitions Drive Huge New Markets +10 Years +5 Years UI Visible Tech Visible Market New Markets Technology Breakthrough Market Transition Growth Created US$150bn Windows 3 GUI 100m users 500m users Packaged PC1 (1990) (1990) Home PC (2000) software market (2005) US$570bn ecom, Web Br
Slide 27: AI: Sizing/Timing The Market Opportunity
AI: Sizing/Timing The Market Opportunity • Generative AI could put 300m jobs at risk of automation and add 1.5% to annual productivity growth and 7% to global GDP (c$7trn)1 • 60% of workers are employed in occupations that did not exist in 1940; 85% of employment growth may be technology driven1 • 5
Slide 28: Transformers: AI’s Bessemer Moment
Transformers: AI’s Bessemer Moment • Early steel prohibitively expensive relative to iron – Various types of early steel: blister, crucible/cast, shear steel – But steel still 4-5x more expensive than wrought iron by mid 1850s • Only 2% of of pig iron produced was converted into steel1 – Specialty a
Slide 29: Transformers: AI’s Bessemer Moment
Transformers: AI’s Bessemer Moment Iron and steel rail price is the US • Early steel prohibitively expensive relative to iron (2022 dollars)1 – Various types of early steel: blister, crucible/cast, shear steel 3500 Steel rail – But steel still 4-5x more expensive than wrought iron by mid 1850s 3000
Slide 30: Transformers: AI’s Bessemer Moment
Transformers: AI’s Bessemer Moment Steel production in England • Early steel prohibitively expensive relative to iron (1780-1910)2 9000000 – Various types of early steel: blister, crucible/cast, shear steel – But steel still 4-5x more expensive than wrought iron by mid 1850s 8000000 • Only 2% of of
Slide 31: New Markets During The Age Of Steel
New Markets During The Age Of Steel This presentation is for use with non-US investors only. Please refer to the Important Information at the end of this presentation. 31
Slide 32: Themes
POLAR CAPITAL Themes
Slide 33: Core Thematic Exposure
Core Thematic Exposure Core thematic exposure Cloud Infrastructure/Cybersecurity Data Economy and Artificial Intelligence Digital Advertising//eCommerce/Payments Software and Digital Transformation Connectivity and 5G/IoT Mobility and EV/Energy Transition Other1 Market hedge/beta offset 0% 5% 10% 15
Slide 34: Core Investment Themes
Core Investment Themes Estimated thematic exposure 28% 27% 26% 25% 24% 23% 22% 21% 20% 19% 18% 17% 16% 15% 14% 13% 12% 11% 10% 9% 8% 7% 6% 5% 4% 3% 2% 1% 0% Jun-21 Jan-22 Jun-22 Jan-23 Jun-23 Jan-20 Jun-20 Jan-21 Jan-17 Jun-17 Jan-18 Jun-18 Jan-19 Jun-19 May-23 May-19 May-20 May-21 May-22 May-17 May
Slide 35: Core Investment Themes
Core Investment Themes Digital Software and Cloud Advertising/ Mobility and EV/ Data Economy and Connectivity and Digital Infrastructure/ eCommerce/ Energy Transition Artificial Intelligence 5G/IoT Transformation Cybersecurity Payments Source: Polar Capital, 30 November 2023. It should not be assume
Slide 36: Technology Valuations
Technology Valuations Absolute sector valuation (P/E): Relative sector valuation (P/E): At post GFC highs (1992 – present) At/around market level – with superior balance sheet Past performance is not indicative or a guarantee of future returns. Source: Ned Davis, 1 December 2023. Copyright 2018 Ned
Slide 37: 'Next Generation’ Valuations
'Next Generation’ Valuations Internet valuation (equal cap weighted): Software as a Service (SaaS) valuation: Enterprise Value (EV)/forward 2-year EV/EBITDA levels1 Enterprise Value (EV)/forward 12-month revenue multiples2 30.0x 25.0x 20.0x 15.0x 10.0x 5.0x 0.0x ML Internet Index Source: 1. Bloomber
Slide 38: 'Next Generation’ Valuations
'Next Generation’ Valuations IT security valuation: Cloud vs legacy valuation: Enterprise Value (EV)/forward 12-month revenue multiples1 Enterprise Value (EV)/trailing 12-month revenue multiples2 25x 20x EV/ trailing 12 month sales 15x 10x 5x 0x LEGACY CLOUD Source: 1. Citi Research, FactSet, Novemb
Slide 39: PCT Positioning
PCT Positioning Geographic exposure (%) Top 15 positions Sector exposure 80 74.4% Microsoft 12.1% Software 27.1% 70 Apple 7.6% Semiconductors & Semiconductor Equipment 25.3% 60 50 NVIDIA 7.1% Interactive Media & Services 11.9% 40 Alphabet 6.4% Technology Hardware, Storage & Peripherals 11.7% 30 Adva
Slide 40: PCT Positioning
PCT Positioning Largest overweights Largest underweights PCT relative market cap exposures vs benchmark1 Advanced Micro Devices Adobe Systems 20% Amazon Alphabet Arista Networks Analog Devices 15% Crowdstrike Holdings Apple 10% CyberArk Software Applied Materials Datadog Broadcom 5% Disco Cisco Syst
Slide 41: Portfolio Structure – Active Positions And Valuation
Portfolio Structure – Active Positions And Valuation A diversified portfolio, capturing secular growth potential of key themes Fund Index Active Fund Index Active Valuation Snapshot Technology Index Difference (6 December 2023)1 Trust1 Top 1001 Advanced Micro Devices 3.74% 1.13% 2.61% Apple 7.57% 16
Slide 42: Appendix
Appendix This presentation is for use with non-US investors only. Please refer to the Important Information at the end of this presentation. 42
Slide 43: Digital Advertising
Digital Advertising • Digital advertising: US$602bn ‘23E +8.5% y/y, c67% of total worldwide ad spend, entering a more • AI impacts: mature (cyclical) phase1 – AI-generated digital ad • New markets growing in Connected TV (CTV) (US$20bn 2023E market) and retail media (US$45bn)2 creative, copy and cam
Slide 44: eCommerce
eCommerce • eCommerce penetration recovered in 2022 and is forecast to gain 1-2% share of core retail sales over • AI impacts: next few years1 – Product discovery: Better • Larger platforms have consolidated share: Amazon, Shopify and Walmart captured >60% of US matching of buyers and eCommerce grow
Slide 45: Software/Digital Transformation
Software/Digital Transformation • Digital transformation was a $595bn market in 2022 and projected to grow at a 21% CAGR to 2027 to • AI impacts: >$1.5trn. Software continues to grow as a share of GDP1 – Premium AI-powered SKUs • Software sector EV/NTM sales multiple compressed by -63% during 2022 a
Slide 46: Cloud Infrastructure/Cybersecurity
Cloud Infrastructure/Cybersecurity • Strong Covid demand has given way to cloud spend optimisation: >US$180bn public cloud revenue • AI impacts: run-rate has slowed from c40% y/y to c20% y/y growth but appears to be stabilising1 – Increased demand from AI • Only c29% of workloads running in cloud to
Slide 47: Data Economy And Artificial Intelligence
Data Economy And Artificial Intelligence • Exponential growth in data/compute: Machine learning (ML) compute doubles every 3.4 months1. • AI impacts: Datasphere doubles every 3 years2 – Requires a new high- • >1/3 of organisations already using generative AI regularly in at least one business functi
Slide 48: Mobility And EV / Energy Transition
Mobility And EV / Energy Transition • Battery Electric Vehicles (BEVs) expected to be ~22% of global auto production in 2025 from ~11% in • AI impacts: 2022 (33% CAGR)1 – Generative-AI could • BEVs have >70% more semiconductor content vs Internal Combustion Engine (ICE). BEV semi content accelerate
Slide 49: Portfolio Structure – Liquidity Profile
Portfolio Structure – Liquidity Profile Liquidity horizon evaluation 16,000 6 14,000 5 12,000 4 10,000 Days to liquidate 8,000 3 AUM (USDM) 6,000 2 4,000 1 2,000 0 - Dec-17 Aug-18 Sep-18 Nov-18 Dec-18 Aug-19 Sep-19 Nov-19 Dec-19 Aug-20 Sep-20 Nov-20 Dec-20 Jan-18 Aug-21 Sep-21 Nov-21 Dec-21 Jun-18 J
Slide 50: Team Biographies
Team Biographies • BA (Hons) Modern History, University of Oxford Ben Rogoff • 28 years’ experience Partner • CMI, Aberdeen Fund managers • BA (Hons) History, University of Cambridge Alastair Unwin • CFA charterholder Deputy Fund Manager • 12 years’ experience • Arbrook Investors, Herald Investment
Slide 51: Team Biographies
Team Biographies • BA in History and Politics, Keele University Paul Johnson • MA in History, Keele University Analyst • CFA Charterholder • 11 years’ experience • Mchem in Chemistry, University of Oxford Nick Williams • CFA level 1 Analyst • 8 years’ experience • Neptune Investment Management • BSc
Slide 52: Important Information
Important Information Polar Capital 16 Palace Street Polar Capital Technology Trust plc (the "Company” London SW1E 5JD The Company is an investment company with investment trust status and its shares are excluded from the Financial Conduct Authority’s (“FCA”) restrictions on the promotion of non-mai
Slide 53: Important Information
Important Information Polar Capital 16 Palace Street Not Investment Advice: London SW1E 5JD This document does not contain information material to the investment objectives or financial needs of the recipient. This document is not advice on legal, taxation or investment matters. Prospective investor
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