Manchester & London Investment Trust PLC · LSE:MNL
Manchester & London Investment Trust — Investor Presentation (February 2026)
38 slides from Manchester & London Investment Trust's investor presentation, February 2026
Slide 1: Manchester & London Investment Trust Plc
Manchester & London Investment Trust Plc Investment Performance since MLCM > 17 per cent Annualized NAV Performance since inception of New Approach/Team. 1 Source: Bloomberg, MLCM
Slide 2: Manchester & London Overview
Manchester & London Overview • Incorporated & Listed in 1971 – 50 + years on the London Stock Exchange. • Growth Fund with a Rare and Attractive Dividend – Current implied dividend yield: 5%. USP’s: 1 Machine > MAN : AI is eating software – The Era of AI has begun. 2 The 4 Stages of the Era of AI as
Slide 3: History suggests technology has been the superlative route to investment returns
History suggests technology has been the superlative route to investment returns from Cromford Mill to today. Examples of technological Eras and their returns: These Eras typically provide decades of multi factor returns: The Ai Era is only just starting. 3 Source: MLCM
Slide 4: Our portfolio is positioned to benefit from the Era of AI
Our portfolio is positioned to benefit from the Era of AI. MNL AI Portfolio Exposure: Name Theme % NVIDIA Corp GPU 42.6 Broadcom Inc TPU 10.4 8.0% Ai Semiconductor TSMC Foundry 10.2 5.9% Microsoft Corp Cloud & Enterprise 4.8 Ai: Networking (Optics & 5.6% Switching) Lumentum Holdings Inc Laser 3.3 Fi
Slide 5: The AI story over the last 12 months remains encouraging
The AI story over the last 12 months remains encouraging. 1 Models are still getting smarter. & more functional: Reasoning Models, Reinforcement Learning & Memorisation. & the rate of model releases is speeding up. 5 Source: MLCM
Slide 6: Trillions of Tokens
The AI story over the last 12 months remains encouraging. 2. Continuing to see massive growth in token use => Increased Compute demand Google Monthly Tokens Processed 1400 1200 1000 Trillions of Tokens 800 600 400 200 0 A sharp increase in Dec/Jan Driven by improved Coding Agents 6 Source: MLCM, Ope
Slide 7: The Cost of Training & Inference Continues to Drop
The AI story over the last 12 months remains encouraging. 3. The Cost of Training & Inference Continues to Drop As the inference price drops => More Usage – Jevons Paradox 7 Source: Artificial Analysis, MLCM
Slide 8: Cloud Capex Spend Continues to Ramp Up
The AI story over the last 12 months remains encouraging. 4. Cloud Capex Spend Continues to Ramp Up 8 Source: Artificial Analysis, MLCM
Slide 9: Explosion of AI application use
The AI story over the last 12 months remains encouraging. 5. Explosion of AI application use. ChatGPT has 450m Daily active users OpenAI reached $10bn annual recurring revenue (ARR) & OpenAI hit $20 billion ARR – up from $10 billion in June. less than three years after the launch of ChatGPT and Anth
Slide 10: Robotics & Automation are moving fast
The AI story over the last 12 months remains encouraging. 6. Robotics & Automation are moving fast. Waymo has gone from 200k weekly trips in March to 450k in Amazon's Louisiana Warehouse December. New AI robotic systems achieved a 25% reduction in Waymo #Weekly Trips (in thousands) fulfillment costs
Slide 11: The AI story has Accelerated in the last 3 months
The AI story has Accelerated in the last 3 months. 1 Coding Agents (e.g., Claude Code) have Claude Code ARR grew in January by at least another $100M from the shown material leaps in performance. $1B announced in December. Usage & Adoption has Skyrocketed. Since the beginning of 2025 we’ve seen a 30
Slide 12: Anthropic Plug-in Marketplace and software disruption
The AI story has Accelerated in the last 3 months. 2 Anthropic Released the Plug-in Marketplace for Claude Code. Giving access to tools for : Productivity, Enterprise Search, Sales, Finance, Data, Legal, Marketing, Customer support, Product management, Biology research This led to a widespread softw
Slide 13: AI agent autonomy doubling faster
The AI story has Accelerated in the last 3 months. 3 AI agents were doubling their level of autonomy every ~7 months, it is now 4 months (Since GPT-4), unlocking step-changes in capability. More tasks → more value → expanding TAM. 13 Source: METR, MLCM
Slide 14: What excites us about AI in 2026: Nvidia Blackwell
What excites us about Ai in 2026. 1. The first Nvidia Blackwell Trained Models will result in an Agentic Leap. From Retrieval to Autonomy (Memory): Massive memory enables agents to "know" instead of “guess”. 2.4 x Memory (vs H200) The "Thinking" Premium (Inference Scaling): Enables reasoning agents
Slide 15: Expected model release timetable
What excites us about Ai in 2026. 1. The first Nvidia Blackwell Trained Models will result in an Agentic Leap. Expected Model release timetable & its importance: 15 Source: MLCM
Slide 16: Consequential financial outcomes: revenue scales with compute
What excites us about Ai in 2026. 2. Which will result in Consequential financial Outcomes. Revenue has continued to scale with Compute. As compute continues to scale with the introduction of Blackwell, the ROI becomes harder to deny. 16 Source: Open AI, MLCM
Slide 17: The software TAM will continue to grow
What excites us about Ai in 2026. 2. Which will result in Consequential financial Outcomes. The software TAM will continue to grow. But only due to Coding Agents & Other Agents. From Software 1.0 To Software 2.0 We are not selling software tools to humans anymore; we are selling digital workers that
Slide 18: AI adoption will continue to accelerate
What excites us about Ai in 2026. 3. AI adoption will continue to accelerate. Ai Adoption Rate among large businesses: At the start of 2025, 6% of firms reported having used Ai in the last 2 weeks. It is now 18%. We expect this will rise throughout 2026. 18 Source: Bloomberg, MLCM
Slide 19: What do we hope drives Alpha in 2026: Inflation Subsiding
What do we hope drives Alpha in 2026. 1. Inflation Subsiding Pantheon Macroeconomics expect core and headline CPI inflation to settle near 2% by year-end. This could lead to a faster rate-cutting cycle than expected. If inflation stabilises money can get back to work in the Growth Equities Market. 1
Slide 20: S&P Forward EPS has rapidly risen
What do we hope drives Alpha in 2026. 2. S&P 500 Forward EPS has rapidly risen, diverging from Lower Cap. 20 Source: LSEG, MLCM
Slide 21: The beginnings of real Productivity Gains
What do we hope drives Alpha in 2026. 3. The beginnings of real Productivity Gains In Q3, US Non-Farm Business Sector labour productivity was up 4.9%. Output increased 5.4%, while hours worked barely budged at 0.5% and unit labour costs fell 1.9%. As H2 2026 & H1 2027 progresses we expect Ai’s impac
Slide 22: Revenue per employee up for AI/software companies
What do we hope drives Alpha in 2026. 3. The beginnings of real Productivity Gains Revenue per employee is up 75% for the top decile of Ai/software companies in 2025. This data predates the major coding agent breakthroughs in December (like Anthropic’s Claude Cowork, which was written 100% by Claude
Slide 23: Beyond 2026… $22T
Beyond 2026… We are excited about the potential TAM expansion that will occur. Something Software 1.0 Not Just Software 2.0 Software 2.0 & Labour Bigger Traditional programming & applications. AI-powered intelligent systems. Direct substitution of human work. 1 Operators & Functional agents. We esti
Slide 24: Beyond 2026… Software 2.0 & Labour Substitution
Beyond 2026… Software 2.0 & Labour Substitution The ROI of the Direct substitution of human work will be undeniable. The cost of Claude Pro or ChatGPT is $20 dollars a month, while a Max subscription is $200 dollars respectively. The median US knowledge worker costs ~350- 500 dollars a day fully loa
Slide 25: Why you should hold MNL
Why you should hold MNL. 3 year Tech Trust Performance: 25 Source: Bloomberg, MLCM
Slide 26: Investment Process: Data Framework – Removing Human Emotion
Investment Process: Data Framework – Removing Human Emotion. Step 1: Quantitative Data Filter Known as IGOR – Stock Universe Filter based on Quantitative Data. Step 2: Qualitative AI Filter Step 6: Risk Management AI model that further filters the Universe based on evaluation Risk based hedging over
Slide 27: Investment Methodology Pillars: Quantitative Data Filter
M&L Investment Methodology Pillars: Step 1 Quantitative Pillar 1 : Quantitative Data Filter • Universe Note: o ~90,000 global equities in Bloomberg This is not ALL the filters. o Remove poor corporate governance markets & un-interesting sectors. • Liquidity o Size: Market cap > $2.5bn Universe o Av.
Slide 28: Investment Methodology Pillars: Qualitative
M&L Investment Methodology Pillars: Step 2 Qualitative We use an AI model to further filter the Universe based on our methodology Pillars which we have determined to be key based on secular trends. 2 3 Historic Shift from Man to Machine Management Who “Play to Win” Screens for Machine centric busine
Slide 29: Investment Methodology Pillars: Macro & Momo
M&L Investment Methodology Pillars: Step 3 Macro & Momo Model: Scamper. Covers these key areas: 1 2 The Flow of Money Market Earnings Growth & Revisions This includes flows into & out of SPY ETF and Money Market This pillar looks at Forward EPS growth of indices, and % of Funds. Also changes in the
Slide 30: Investment Methodology: Results
M&L Investment Methodology: Results Our process has yielded many successful investments. Return on our initial entry : 8.5 x 130 x 4x 2.5 X MSFT NVDA AVGO HOOD Note: This book happens to map closely to the thought process behind our investment methodology. 30 Source: Bloomberg, MLCM
Slide 31: Thank You
Manchester & London Investment Trust Thank You Subscribe to our Newsletters: https://mlcapman.com/subscribe Follow our Tweets for AI News: https://x.com/MLCapMan Visit our website: https://mlcapman.com/about/ Follow our LinkedIn for fund news: https://www.linkedin.com/company/m-&-l-capital-managemen
Slide 32: Important information
Important information This document has been prepared by M&L Capital Management Limited, (“MLCM”) 12a Princes Gate Mews, London, SW7 1JS, which is authorised and regulated by the Financial Conduct Authority (“FCA”). This document is provided to you for information purposes only and should not be use
Slide 33: Why you should hold MNL: correlation with MSCI World
Why you should hold MNL. Our Correlation with MSCI world Equity Index shows a differentiated approach Rolling 3-Year NAV Correlation (n=150 weeks) (source Bloomberg): This is significantly lower than other tech focused trusts like PCT which sits at 0.74. 33 Source: Bloomberg, MLCM
Slide 34: Investment team
Investment team We use experience and expertise to validate ideas, manage risk and assess the 5 year outlook. Mark Sheppard Richard Morgan Orlando Morris • Co-Fund Manager. • Co-Fund Manager. • Analyst • Qualified Chartered Accountant • CFA ® charterholder. • CFA Exam Level III Candidate (Deloitte).
Slide 35: Key Risks for MNL right now
Key Risks for MNL right now. 35 Source: MLCM
Slide 36: Key Risks: The New Cold War - USA v China Tech
Key Risks for MNL: The New Cold War - the USA v China Tech War for Supremacy. "AI is the essential omni-purpose technology of the U.S.-China arms race, like steel in medieval warfare." - Jacob Helberg, nominated Under Secretary of State for Economic Growth. Note: This is why we filter out this risk
Slide 37: Key Risks: Inflation, Debt => Higher Yields
Key Risks for MNL: Inflation, Debt => Higher Yields (Duration Risk). 37 Source: Bloomberg, MLCM
Slide 38: Key Risks: Luddites do not adopt AI
Key Risks for MNL: Luddites do not adopt AI. There is a slim chance that the average person or business does not adopt Ai as quickly as we expect. Current metrics do not indicate this, however we are watching them carefully. Annual Searches by Year Since launch ChatGPT hit 365B annual searches/promp
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