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A vast array of investment options are available to investors, yet there can be no doubt that stocks are the best asset-class for long-term wealth creation. Whilst it is true that other asset-classes have their merits, history has shown that over the past century, stocks have significantly outperformed cash, corporate bonds, government bonds and gold.

Stocks represent part ownership stakes in real-world businesses (productive assets) and over the past century, thousands of world-changing businesses have invented invaluable products and/or services which have changed the way humans work, live and play. By enriching their customers’ lives, these businesses have not only benefited humanity, they have also created immense wealth for their owners or shareholders.

As businesses keep capturing new markets, introducing new innovative products and services, they will continue to generate ever increasing revenues, profits and free cash flows which will in turn make them more valuable over time.

As you can see from Figure 1, over the past 200+ years, US stocks have significantly outperformed other major asset-classes and given the pace of ongoing innovation, expansion of the middle-class in the developing world and population growth, American businesses are likely to continue to prosper over the long-term.

Figure 1: US stocks’ outperformance is staggering!

A graph showing the stock market

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Source: Stocks for the long run, Jeremy Siegel

Although US stocks have done well at an index-level, many dominant and disruptive businesses have done exceedingly well and compounded their revenues, profits and free cash flows at very high rates for very long periods of time! Consequently, the market capitalisations of such enterprises have grown at unbelievable rates; and handsomely rewarded their shareholders.

Before the advent of the internet, several businesses such as Adidas, American Express, Burger King, Coca-Cola, Colgate, Domino’s Pizza, IBM, KFC, Levi’s Strauss, McDonald’s, Mastercard, Nike, Philip Morris, Procter & Gamble, Unilever and Visa became household names and took over the world.

In the internet era, many disruptive businesses such as Airbnb, Amazon, Apple, Expedia, Facebook (now Meta), Priceline (now Booking.com), Google (now Alphabet), Netflix, Nvidia, Spotify, Tesla and Uber have captured the hearts and minds of billions of people.

Although the above businesses operate in different fields, they demonstrate the power of human ingenuity; and prove that if the sharpest minds in the world get together and there is no dearth of capital, the outcomes can be truly spectacular!

Since the start of the new millennium, many dominant businesses in enterprise software, online advertising, online gaming, online retail, online travel, payments, music and video streaming have done very well.

Turning to investment performance, although US stocks at the index-level (S&P 500 Index) have compounded at 10% per annum over several decades, the market capitalisations of the disruptive, dominant, rapidly growing businesses have compounded at very high rates (15/20/30% per annum)!

The bottom-line is that although investing in stocks via index investing is a lucrative endeavour over the long run, investing in disruptive, rapidly growing businesses with unique advantages has the potential to produce truly life changing returns.

At AlphaTarget, our team conducts in-depth research and invests its own capital in such disruptive businesses which are characterised by recurring revenues or frequent/repeat purchases by their customers, high gross margins, free cash flows and strong returns on invested capital (ROIC) at maturity.

Rationale for investing in disruptive companies

Innovation

Investing in disruptive businesses allows one to tap into the transformative power of innovation. Such companies challenge traditional norms, introduce ground-breaking products and services, or technologies that revolutionise entire industries. By identifying and investing in disruptive businesses early on, we seek to participate in the significant growth opportunities as these companies reshape markets and capture existing demand from competitors.

Rapid growth

Rapidly growing businesses possess the capacity to generate substantial returns over the long term. Disruptive companies either operate in nascent industries or have unique business models that enable them to expand quickly. By investing in such companies, investors can position themselves to ride the wave of growth and benefit from the compounding effect that can significantly enhance their investment returns over time.

High margins and scalability

At AlphaTarget, we primarily focus on the disruptive, online businesses because these enterprises tend to have high gross margins and also high net profit margins at scale. When it comes to the online economy, the cost of producing digital services is usually low (operating expenses are much lower than brick-and-mortar businesses).

Once they have established their infrastructure and systems, online businesses can serve a large number of customers without significant incremental costs. This allows them to generate higher revenue without a proportional increase in costs, resulting in higher margins.

Online businesses can often scale their operations more efficiently than traditional offline businesses. Digital products and services can be replicated and distributed at minimal or zero marginal cost, allowing online companies to reach a broader audience without incurring substantial expenses for each additional customer.

Free cash flows and high ROIC

Disruptive companies often have high free cash flow margins and return on invested capital (ROIC) due to their innovative business models. They operate with streamlined processes, lower costs, and efficient supply chains, allowing them to generate significant cash flows. In the online world, the nature of the offerings of the dominant businesses enables rapid cash flow generation without proportionate increases in capital spending, resulting in high free cash flows and high ROIC.

Outperforming index investing

Investing in innovative businesses provides the potential to outperform index investing. These companies are able to rapidly grow their business for long periods of time, which enables them to outpace broader market indices over the long-term. By carefully evaluating and selecting disruptive businesses, investors can seek to outperform passive index strategies and potentially achieve superior returns.

Investing with the secular trends

Disruptive businesses usually operate at the forefront of new industries. At AlphaTarget, we observe the secular trends in the business world, study the dominant businesses and invest our capital in the most promising companies.

Over the past two decades, the below secular trends have transformed the business world:

E-commerce

E-commerce has witnessed extraordinary growth, transforming the retail landscape and creating immense investment opportunities. Companies like Amazon, Alibaba, Mercadolibre and Shopify have demonstrated unprecedented growth, reshaping consumer behaviour and capturing significant wealth for shareholders.

Dominant online travel agencies such as Expedia and Priceline (now Booking.com) have totally disrupted the industry, upended millions of traditional online agents and created immense value for their shareholders.

E-commerce penetration is still fairly low in many parts of the world, so the leading
businesses in this space are likely to continue to do well over the next few years.

Online payments

The rapid proliferation of online payments has revolutionised the financial industry, offering convenience, security, and efficiency. Companies like Adyen, PayPal, Mercadolibre, Square and Stripe have thrived in this space, providing seamless payment solutions that enable individuals and businesses to transact online. As digital payments become increasingly ubiquitous, investing in the leading online payment providers allows investors the opportunity to capitalise on the growth of cashless transactions and the expanding e-commerce ecosystem.

Music and video streaming

The advent of streaming services has disrupted traditional media consumption patterns, providing consumers with on-demand access to a vast array of content. Companies like Netflix and Spotify have emerged as pioneers in this space, experiencing exponential growth and reshaping the entertainment industry. Investing in the streaming sector has allowed investors to tap into the evolving consumer preferences and the shift towards digital content consumption.

Enterprise software

Enterprise software solutions have become integral to modern businesses, driving efficiency, productivity, and digital transformation. Due to cloud computing and “Software as a Service” (SaaS), enterprise software vendors now have sticky recurring revenues and they have become modern-day utilities.

The public hyperscalers have also spawned a new generation of software businesses which have experienced remarkable growth by providing cloud-based infrastructure services. Investing in leading enterprise software providers has offered investors exposure to the ongoing digitisation of businesses and the growth runway appears to be long.

Looking ahead

Long-term projections of any kind should be made with humility but at AlphaTarget, we have high conviction that the e-commerce, fintech/online payments, music/video streaming and software industries will continue to grow. Additionally, we believe that nascent industries such as autonomous driving, gene editing, robotics and space exploration will also transform the way humans live, work and play.

If our world-view is correct, the biggest transformation will be in Artificial Intelligence (AI). According to our research, AI is a major technological revolution and over the next decade, it will transform every industry.

Investing in AI-focused businesses will allow investors to participate in the next wave of technological advancements and potentially benefit from the transformative power of AI across various sectors, including education, finance, healthcare, professional services, robotics, transportation, and more.

Since the launch of ChatGPT (autumn 2022), due to the AI infrastructure (datacentres) build up, dominant “picks and shovels” plays in AI such as NVIDIA and Super Micro Computer have already made a small fortune and rewarded their shareholders.

Going forward, as businesses begin to monetise AI, we expect some companies at the application layer to prosper. Additionally, enterprise software companies which successfully deploy AI agents on top of their software platforms should also reward their shareholders.

At AlphaTarget, we invest our capital in some of the most promising disruptive businesses at the forefront of secular trends; and utilise stage analysis and other technical tools to continuously monitor our holdings and manage our investment portfolio. AlphaTarget produces cutting-edge research and those who subscribe to our research service gain exclusive access to information such as the holdings in our investment portfolio, our in-depth fundamental and technical analysis of each company, our portfolio management moves and details of our proprietary systematic trend following hedging strategy to reduce portfolio drawdowns. To learn more about our research service, please visit subscriptions.

In the dynamic and ever-changing world of financial markets, investors and traders are constantly seeking strategies to gain an edge and generate consistent returns. One popular approach that has gained significant attention is trend following. Trend following is a strategy that aims to capitalise on the directional movements of various asset classes by identifying and riding trends.

Trend following is objective and instead of relying on complex analysis and forecasts, it focuses on the price reality i.e. what is actually happening in the financial markets. In the investment business, every market participant’s equity curve or profit & loss is fuelled by price action and by honing in on the price movement, trend following allows one to stay aligned with the major trends.

The reality is that money in the financial markets is made by following the trends and it is a whole lot easier to swim with the tide. Conversely, fighting the trends does not pay; in fact it is a sure-shot way of burning up a lot of emotional and financial capital.

This article explores the concept of trend following (its underlying principles), long-term performance, key components, benefits, and potential limitations.

Understanding Trend Following

Trend following is a systematic trading strategy that seeks to identify and profit from the momentum or trends in the price movements of financial assets. It operates on the belief that markets tend to exhibit persistent trends over time, and by aligning with these trends, traders can generate profits. Trend followers typically follow a set of rules and use technical analysis tools to identify and confirm trends before entering or exiting positions.

Unlike the “buy & hold” approach, which requires a market participant to remain fully invested at all times (and endure deep and lengthy drawdowns), trend following enables one to sell or hedge one’s portfolio at the start of downtrends. This means that a trend follower does not have to sit through large declines in the financial markets and suffer serious portfolio drawdowns. By either being in cash or hedged during downtrends, a trend follower is able to get out of harm’s way and/or reduce portfolio drawdowns.

As far as the stock market is concerned, “buy & hold” does well over the very long-term. However, the stock market is extremely volatile and the returns tend to be very lumpy. Put simply, the stock market does not go up every year and market participants have to contend with both secular bull-markets as well as secular bear-markets.

If you review the performance of the US stock market over the past 150 years (Figure 1), you will clearly see that the ride has been anything but smooth and there have been rewarding as well as frustrating passages of time. These rewarding long-term passages of time are called secular bull-markets and the frustrating ones are known as secular bear-markets.

Figure 1: The stock market is NOT a smooth ride

A graph showing the price of a stock market

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Source: Kaplan, Goetzmann, Ibbotson, Morningstar Direct, Shiller

Figure 1 shows that since 1870, on an inflation-adjusted basis, the US stock market has undergone four multi-year secular bear-markets (1910-1924, 1929-1954, 1969-1982, 2000-2013). It is worth noting that each secular bear-market not only brought about at least one 50%+ decline at the index-level, every single one lasted for a minimum of 10 years!

Unfortunately, secular bear-markets are not just a US phenomenon and they periodically occur in all the stock markets. Since 1950, there have been 25 secular bear-markets in the major world indices and each of them have lasted for a minimum of 15 years!

What about “buy & hold”?

“Buy & hold” works well over the very long-term at the index-level; however, it does not do so well for the majority of individual stocks. The reason why “buy & hold” with no risk management strategy in place works well over the very long-term at the index-level is because of the fact that stocks have an upward bias and the major stock indices are actively managed i.e. their underlying constituent companies are regularly replaced. Each year, larger and stronger companies are introduced in the major stock indices and the shrinking, weaker companies are replaced. For example, the annual churn rate of the S&P500 Index is around 4.5% and since 2015, ~40% of its constituent companies (~200 out of 500 companies!) have been replaced.

If one invests in individual stocks, then “buy & hold” with no exit strategy is not a good proposition. It is worth noting that the average company lifespan in the S&P500 Index has now shrunk to just 15 years and over the past 90 years, only 20% of the US listed companies both survived and outperformed the S&P500 Index! Furthermore, research reveals that over the past 90 years, only ~50% of US listed companies survived as standalone businesses at the 20-year mark. So, if one owns a portfolio of individual stocks, the odds are that many of the companies will underperform or not survive and this is why a risk management (exit) strategy is essential.

By utilising a trend following strategy, one can participate in the stock market’s uptrends whilst avoiding painful downtrends as well as the wrath of those destructive secular bear-markets. The main benefit of trend following is that it significantly reduces portfolio drawdowns and one ends up with a much smoother equity curve. Research indicates that for the S&P500 Index, trend following rules have reduced volatility by 33-50%, leading to higher Sharpe Ratios.

Figure 2 illustrates how trend following reduces portfolio drawdowns when compared to “buy & hold”. This is a backtest we performed on the S&P500 Index a few years ago and the lookback period was 28 years. This backtest utilised the 150-day moving average with additional rules to minimise whipsaws and as you can see, this strategy not only outperformed “buy & hold”, it also significantly reduced the drawdown to just 21.57% (vs. two 50%+ drawdowns for the S&P500 Index during the lookback period)!

Figure 2: Trend following vs S&P500 “buy & hold”

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Source: Trendspider

For the sake of full transparency, we must point out that trend following strategies underperform “buy & hold” when the S&P500 Index is in a secular bull-market but they really shine and reduce portfolio drawdowns during secular bear-markets.

Finally, trend following can be utilised on all financial markets (bonds, commodities, currencies and stocks).

Key components of Trend Following

A trend following strategy utilises the following key components –

a) Trend identification: Trend followers utilise various technical indicators such as moving averages, momentum channels or volatility bands to identify the direction and strength of a trend. They aim to differentiate between bullish, bearish, or sideways market conditions.

b) Entry and exit signals: Once a trend is identified, trend followers establish specific rules for entering and exiting positions. This may involve using breakouts, moving average crossovers, or other technical signals to initiate trades. Similarly, predetermined exit rules, such as trailing stops or trend reversals, help manage risk and lock in profits.

c) Position sizing and risk management: Proper risk management is crucial in trend following. Traders determine the size of each position based on factors like volatility, account size, and risk tolerance. They often employ techniques like the use of stop-loss orders to limit potential losses and protect capital.

Benefits of Trend Following

Here are some of the benefits of the trend following approach –

a) Diversification: Trend following strategies can provide diversification benefits to an investment portfolio. They have the potential to perform well in various market environments, including bull, bear, or volatile conditions, as they do not rely on predicting market tops or bottoms.

b) Capturing large market moves: Trend following aims to capture substantial market moves by staying in positions for the duration of the trend. By riding these trends, investors and traders can potentially benefit from significant price movements and generate attractive returns.

c) Risk management: Trend following strategies often incorporate risk management techniques that help control downside risk. By setting predefined exit rules and managing position sizes, trend followers aim to limit losses and protect capital during adverse market conditions.

d) Emotional discipline: Trend following strategies are rule-based, which helps eliminate emotional biases and impulsive decision-making. Traders follow their predefined rules and signals, reducing the influence of emotions like fear or greed, which can negatively impact trading outcomes.

Potential limitations

Trend following is not a perfect approach (there is no perfect strategy or system!) and its limitations are set out below –

a) Whipsaw and false signals: Trend following strategies are not foolproof and they are susceptible to false signals, especially during choppy or range-bound markets. Rapid reversals or market noise can result in whipsaw trades, where positions are entered and exited quickly, leading to potential losses.

b) Late entries and exits: Trend following strategies may not capture the entire duration of a trend. One may enter positions after a trend has already been established and exit relatively late, potentially missing some profit potential.

c) Periods of drawdown: Like any trading strategy, trend following can experience periods of drawdown, where consecutive losing trades occur. These drawdowns can test the one’s discipline and patience, requiring a long-term perspective and confidence in the strategy.

d) Underperformance: When a stock index is in a secular bull-market, trend following strategies underperform “buy & hold”.

Summary

Trend following is a popular trading strategy that aims to profit from the directional movements of financial assets. By identifying and riding trends, trend followers seek to generate consistent returns. While there are potential drawbacks and challenges associated with trend following, its benefits, such as diversification, capturing large market moves, and disciplined risk management, make it an attractive approach for many traders and investors. As with any investment strategy, it is essential to thoroughly understand the principles, develop a robust framework, and continuously adapt to changing market dynamics. Trend following can provide a powerful tool for navigating the complexities of financial markets and potentially achieving long-term trading success.

At AlphaTarget, in order to properly time our entries and exits in our preferred growth stocks, we utilise “Stage Analysis” which is a long-term trend following strategy. We initiate new positions during Stage 1 (base building phase) and Stage 2 (rally phase) and book our gains/sell over-extended stocks during Stage 3 (distribution phase).

We also utilise a systematic trend following strategy to hedge our growth stock portfolio during stock market downtrends. If you would like to learn more about “Stage Analysis” or portfolio hedging, please read our related articles “Stage Analysis: an overview” and “Hedging: umbrella for a rainy day” on the “Resources” subpage of our website www.alphatarget.com

Portfolio hedging is a risk management strategy employed by investors to protect their investment portfolios from potential adverse market movements. It involves the use of various financial instruments or strategies to offset or mitigate the impact of unfavourable market conditions. The primary objective of portfolio hedging is to reduce the overall risk exposure and minimise potential losses.

The stock market does well over very long-term timeframes (15-20+ years) but it is volatile and secular bear-markets occur which bring about horrendous drawdowns (50%+ at the index level). It is not uncommon for secular bear-markets to last for 10/20/30 years and for the related indices to not make any progress for such extended periods of time! Whilst “buy and hold” works during secular bull-markets, this can be a very challenging and frustrating strategy during secular bear-markets.

Since 1950, there have been over 25 secular bear-markets in stocks in different countries / regions of the world, each lasting for more than 15 years (Figure 1)! It goes without saying, such secular bear-markets test the nerves and patience of even the most enthusiastic investor.

Figure 1: Secular bear-markets are not uncommon

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Source: GFD, Deutsche Bank

One way to avoid getting caught in secular bear-markets is by trend-following and cashing out of stocks at the end of primary uptrends and another way is by hedging one’s investment portfolio to offset some of the drawdowns. For our part, we combine both approaches and until we are fully in cash, use a systematic trend following strategy to hedge our long exposure.

In addition to secular bear-markets, hedging also provides protection to an investor’s portfolio from sudden and large stock market declines caused by exogenous shocks, geo-political conflicts, pandemics and recessions.

Portfolio hedging – common approaches

There are several common approaches to portfolio hedging. One popular method is diversification, where investors allocate their capital across different asset classes, sectors, or geographical regions. By spreading investments across a range of assets, an investor hopes that the impact of a downturn in one area can be offset by positive performance in others. In theory, this helps to reduce the correlation and concentration risk within the portfolio. However, under certain market conditions, major asset-classes become highly correlated, and they all decline in tandem!

Another hedging technique is the use of derivatives, such as options or futures contracts. These financial instruments provide investors with the opportunity to protect their portfolio against adverse price movements. For example, investors can purchase put options to establish a predetermined selling price for an asset, thereby limiting potential losses if the asset’s value declines. Similarly, futures contracts can be used to lock in prices for commodities or currencies to hedge against price volatility.

Finally, one can also hedge his/her investment portfolio by shorting ETFs which are correlated to the long holdings in their investment portfolio.

Overall, portfolio hedging is a proactive risk management strategy that helps investors protect their investments from adverse market conditions. It allows them to minimise potential portfolio drawdowns and maintain a more stable and predictable investment performance (equity curve). However, it’s important to note that portfolio hedging strategies come with their own costs and limitations, so investors should carefully consider their objectives, risk tolerance, and always consult with their registered financial adviser before implementing any hedging strategies.

Shorting index ETFs or stock futures is a common strategy used to hedge long exposure in a stock portfolio. When investors short an index ETF or sell stock futures contracts, they aim to profit from a decline in the value of the underlying index or stock. This allows them to offset potential losses in their long positions and create a more market-neutral portfolio, reducing overall risk.

An investor can hedge any type of investment portfolio, but since we allocate our capital to mid to large cap growing businesses, during stock market downtrends, we hedge our exposure by shorting Russell 2000 Index futures. An investor can achieve the same outcome by shorting the related equity index ETF.

By shorting index ETFs, investors can directly hedge their exposure to a specific market index or sector. For example, if an investor holds a portfolio heavily concentrated in technology stocks and wants to hedge against a potential downturn in the technology sector, they can short a technology-focused index ETF. If the technology sector experiences a decline, the short position in the ETF would generate profits that offset the losses in the long positions.

Alternatively, (like us) investors can utilise stock futures contracts to establish a hedge. By selling stock futures contracts, investors commit to selling a specified number of contracts at a predetermined price in the future. If the stock market declines, the value of the futures contracts decreases, thereby generating profits and offsetting losses in the long portfolio.

When implementing a hedge, investors have the option to hedge on a 1:1 basis, where the value of the hedge matches the value of the long position. This provides a direct offset to the portfolio’s risk. Alternatively, investors can choose to beta-hedge, which involves adjusting the size of the hedge based on the beta or correlation of the portfolio to the market index. This approach aims to provide a more effective hedge by considering the portfolio’s specific volatility characteristics.

During the duration of the hedge, the portfolio becomes less risky and more market neutral. The short positions in the index ETFs or stock futures help to balance out potential losses in the long positions, reducing the portfolio’s overall exposure to market fluctuations.

It’s important to note that while shorting index ETFs or stock futures can be an effective hedging strategy, it also carries risks. Instead of declining, if the stock market rallies, the short positions produce losses, but these are offset by the long positions in an investor’s stock portfolio. Additionally, costs such as borrowing fees or margin requirements should be considered.

Systematic trend following hedging

To short index ETFs or stock futures, like us, investors can employ a systematic trend following strategy to determine when to initiate and remove the hedge. By using this approach, the decision-making process becomes rule-based, relying on objective criteria rather than subjective discretion or emotions.

A systematic trend-following strategy involves analysing market trends and using predefined rules to determine whether to implement or remove a hedge. Typically, momentum and/or volatility indicators are utilised to identify stock market downtrends or uptrends.

When the trend following indicators signal the start of a new downtrend, the investor would initiate the hedge by shorting stock index futures or ETFs. This helps protect the portfolio from potential losses during the downward market move.

Conversely, when the trend following indicators indicate the end of the downtrend and the start of an uptrend, the systematic strategy triggers the removal of the hedge. At this point, the investor would close the short positions in the index futures or ETFs, allowing the portfolio to benefit from the subsequent upside in the market.

The use of a systematic trend following strategy adds an objective and disciplined approach to the hedging process. It removes the element of emotion and subjective judgment from the decision-making, relying solely on predetermined rules and technical indicators to determine when to hedge and when to remove the hedge.

By employing this systematic approach, investors can potentially benefit from market trends while reducing the overall risk and volatility of their portfolio. However, it’s important to note that no strategy is foolproof, and investors should carefully evaluate the effectiveness of trend following indicators and consider potential risks and costs associated with implementing this strategy.

Our extensive back testing has revealed that since the start of the new millennium, our proprietary systematic trend following hedging strategy would have marginally reduced long-term returns but significantly reduced one’s portfolio drawdowns during all severe stock market downtrends.

Figure 2 shows the signals generated by our proprietary systematic trend following hedging strategy during the COVID-crash in early 2020 as well as during the 2022 stock bear-market.

As you can see, our proprietary systematic hedging strategy gave us the signal to hedge our portfolio just before the COVID-crash and it told us to remove the hedge just after the crash. Conversely, no hedging signal was generated during the strong stock market uptrend between spring 2020 and summer 2021. There was one false signal (whipsaw) in autumn 2021 but our hedging system correctly got us hedged in late 2021 and the signal to remove that hedge only came in August 2022.

Figure 2: Our proprietary systematic hedging strategy on display

Source: Trendspider

As you can see from the above, during the recent two bear-markets, our proprietary systematic hedging strategy generated accurate signals to protect our capital and mitigate our portfolio drawdown.

Successful investing often requires a disciplined and systematic approach to analysing financial markets. One such approach that has gained popularity among traders and investors is “Stage Analysis”. Stage analysis was developed by Stan Weinstein, an American stock market technician and trader. In 1988, he introduced this approach in his book titled “Secrets for Profiting in Bull and Bear Markets”. In his book, Stan Weinstein outlined his methodology for identifying the primary trend and offered practical guidance for applying stage analysis in managing stock positions.

Stage analysis is based on trend following and it is a comprehensive framework that seeks to identify and capitalise on different stages of a security’s trend (Figure 1). By applying a primary trend filter (long-term moving average) and understanding the market’s stage, investors can make more informed decisions, reduce their portfolio drawdowns and potentially enhance their investment returns.

Originally, Stan Weinstein used the 30-week moving average as his primary trend filter but he has now switched to the 40-week moving average (200-day moving average). At AlphaTarget, we use the 40-week moving average as the primary trend filter for identifying any stock’s or stock market’s major trend.

Figure 1: Visual example of Stage Analysis

Source: Secrets of Profiting in Bull and Bear Markets, Stan Weinstein

In this article, we outline the key principles of stage analysis and how it can be applied in practice to profitably invest and trade in stocks.

Understanding Stage Analysis

Stage analysis is based on the premise that stocks and stock indices go through distinct stages of accumulation (Stage 1), markup (Stage 2), distribution (Stage 3), and markdown (Stage 4). These stages are driven by supply and demand; and more importantly by the actions of institutional investors, who have a significant influence on market trends. By identifying which stage a stock or a stock index is in, investors can align their portfolio holdings with the market and swim with the tide.

The underlying principle of stage analysis (a form of trend following) is that an investor or trader ought to buy stocks during the accumulation stage, hold stocks during the markup stage, sell stocks during the distribution stage and stay out of harm’s way during the markdown stage.

Instead of “buying and holding” stocks for the long-term, riding out the periodic downtrends and enduring large portfolio drawdowns, practitioners of stage analysis sell their holdings during the distribution phase (before the onset of large declines during the markdown stage).

A brief description of each stage is provided below:-

Accumulation Stage: The accumulation stage known as “Stage 1” is when a stock or stock index builds a trading range or “base” and this represents a period when smart money slowly accumulates positions in a security. During this stage, the 40-week moving average is flat, there is no clear trend and prices tend to be range-bound, as institutional investors quietly build their positions. Volume is usually low during this stage, and the stock or stock index exhibits a lack of clear direction. The accumulation stage can last for several weeks or even months. At AlphaTarget, we usually build positions in stocks during this stage.

Markup Stage: The markup stage known as “Stage 2” is characterised by a sustained uptrend or markup in prices. During this stage, the 40-week moving average turns up (starts sloping upwards), institutional investors actively buy the security, driving prices higher. Volume typically expands during this stage as more market participants join the trend and the price of the security tends to stay above the 40-week moving average. Breakouts from consolidation patterns and strong upward momentum are common features of the markup stage. This is the stage when the big money is made. During this stage, when the prices of securities run up too far away from their rising 40-week moving average, partial profits are booked and when prices pull back towards the 40-week moving average, cash is re-deployed.

Distribution Stage: The distribution stage known as “Stage 3” occurs when institutional investors start selling their positions. After a steady rise during the markup stage “Stage 2”, prices stop rising and they enter a consolidation phase. Volatility picks up during this stage and every rally attempt is met with renewed selling and this “tug of war” between buyers and sellers causes prices to zig and zag. Volume often remains high as institutions distribute their holdings to retail investors. During this stage, the 40-week moving average stops rising and eventually rolls over. Distribution can last for a considerable period, and it can sometimes be challenging to identify the end of this stage.

Markdown Stage: The markdown stage known as “Stage 4” represents a prolonged decline in prices; therefore, big losses build up during this stage. In this stage, institutional investors have largely exited their positions, and supply overwhelms demand. Prices exhibit a downtrend, characterized by lower lows and lower highs. Volume may initially decline during this stage, and selling pressure dominates the market sentiment. During the markdown stage, the 40-week moving average is declining (sloping downwards) and prices tend to stay below this key technical level. Towards the end of Stage 4, volume often picks up during a selling climax when novice investors throw in the towel and institutions start snapping up bargains. Practitioners of stage analysis, do not hold falling securities during this stage and they stay out of harm’s way.

Applying Stage Analysis in Practice

Stage analysis can be applied to various financial markets, including stocks, commodities, and cryptocurrencies. Here are some key steps to keep in mind when utilising stage analysis:-

Chart Analysis: Start by analysing price charts of the asset you are interested in. Look for evidence of accumulation, markup, distribution, or markdown stages. Identify key support and resistance levels, and chart patterns to assist in determining the market stage.

Volume Analysis: Examine volume patterns during different stages. Volume can provide insights into institutional activity and the strength of market trends. Higher volume during markup stages and lower volume during distribution and markdown stages can be indicative of market behaviour.

Relative strength: When applying stage analysis on stocks, gauge a security’s relative strength versus the S&P500 Index to determine if it is stronger or weaker than the broad market. Focus on securities which are showing relative strength.

Risk Management: Implement proper risk management strategies to protect capital. Set stop-loss orders and define risk-reward ratios based on the identified stage. Adjust position sizes and trailing stops as the market progresses through different stages. Never own a security during the markdown stage (Stage 4) when prices are trending lower beneath the declining long-term moving average.

Real-world example

Financial markets are driven by human emotion and when investors are optimistic and confident about the future prospects, they engage in buying activity, driving prices higher and creating an upward trend. This positive sentiment can become contagious, attracting even more buyers and further fuelling the trend.

Conversely, when fear or pessimism dominates the market sentiment, investors engage in selling activity, causing prices to decline and creating a downward trend. Negative news, economic uncertainty, or geopolitical tensions can trigger such emotions and lead to a cascade of selling pressure.

As long as emotional human beings are involved in the financial markets, assets and securities will continue to trend in both directions and this will allow trend followers and practitioners of stage analysis to exploit these exaggerated price swings.

In order to show that stage analysis still works in the real-world, we want you to review the boom and bust phenomenon of ARK Innovation ETF (Figure 2). Admittedly, this is an extreme example of a severe boom and bust cycle caused by the Federal Reserve’s extreme policies. Nonetheless, this chart beautifully demonstrates how utilisation of stage analysis would have enabled an investor or trader to capture gains and leave the party before everything turned into pumpkin and mice.

During 2020, in response to the unprecedented monetary easing by the Federal Reserve, the ARK Innovation ETF (ARKK) broke out into its markup stage (Stage 2) and its price increased by ~400% within a year! Thereafter, when inflation rose and the Federal Reserve pursued tight monetary policies, ARKK peaked in a classic distribution stage (Stage 3) and eventually, it gave back all of its prior gains during its markdown stage (Stage 4)! Note how the 40-week moving average (red shaded area on the chart) remained flat during Stage 1, rose during Stage 2, peaked/rolled over during Stage 3 and sloped downwards during Stage 4.

The black line in the bottom panel shows how ARKK exhibited relative strength versus the S&P500 Index during Stage 2 and relative weakness during Stage 3 and 4.

Figure 2: Real-world example of stage analysis

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Source: Stockcharts

Whereas “buy and hold” investors just sat through the entire boom and bust and now have nothing to show for their exciting adventure; by utilising stage analysis, an investor or trader would have been able to sell this ETF during Stage 3 and capture the gains.

In case you are wondering, we have not cherry picked this particular ETF to drive home the point that stage analysis works. If you review the weekly charts of numerous stocks (Amazon, Google, Meta, Microsoft, PayPal, Shopify, Square etc) or even the broad stock indices themselves (NASDAQ or S&P500 Index), you will observe that all of them went through the same four stages i.e. accumulation, markup, distribution and markdown.

Some limitations

In the financial markets, no approach is perfect and every system has its limitations. In order to provide you with a balanced view, we have set out the limitations of stage analysis below:-

Whipsaws: Stage analysis is based on trend following, therefore it is susceptible to false price signals which are known as whipsaws. False price signals can lead to incorrect trading decisions and realised financial losses.

Lack of trend: There may be periods when the prices of securities are range-bound i.e. they chop around without a definitive trend and during such periods, stage analysis can produce false breakouts and breakdowns, which result in small realised losses.

Lagging indicator: Stage analysis is based on historical price data and tends to be a lagging indicator. It relies on past price movements to identify trends, which may not always accurately predict future price movements.

Conclusion

Stage analysis offers a systematic approach to market analysis, allowing investors to identify and capitalize on the different stages of a security’s trend. By understanding whether an asset is in an accumulation, markup, distribution, or markdown stage, investors can align their portfolio holdings with the prevalent trend.

It is important to combine stage analysis with fundamental and other technical tools to make well-informed investment decisions. Remember that no approach can guarantee success in the financial markets, but stage analysis provides a valuable framework for market participants to enhance their decision-making processes.

Artificial Intelligence (AI) has undeniably become all the rage in recent times and it has captivated the attention and imagination of individuals across various domains.

This research piece aims to explore the fascinating world of AI, shedding light on its true nature, its origins, societal impact and the potential for investors to capitalise on this transformative wave.

At a fundamental level, AI refers to the simulation of human intelligence in machines that are programmed to learn, reason and perform tasks with minimal human intervention. It encompasses a broad range of techniques, including machine + deep learning, natural language processing and computer vision. Thus far, AI has demonstrated remarkable capabilities in diverse industries such as finance, healthcare and transportation; and it is rapidly transforming how humans live, work and play. However, it is worth noting that as of now, AI is not a magical entity with human-like consciousness or emotions. AI is ultimately a tool developed by humans, which relies on algorithms and data to make predictions and decisions. So, let us embark on a journey to uncover the remarkable possibilities offered by AI and explore its impact on our lives.

AI – a cluster of related technologies

It is important to understand that “AI” is not any one standalone technology, but rather a group of related technologies.

The term AI is used as a catch-all for software that possesses and seeks to replicate characteristics of human intelligence. Although this might seem like a magic black box, AI systems are essentially just looking for patterns in data and drawing conclusions from them.

To better grasp AI and its investment implications, it will be helpful to first understand how the following key technologies have made AI possible and led to many of the recent breakthroughs in the field.

Machine Learning and Neural Networks

Machine learning algorithms ingest data, learn from it, and then form conclusions informed by that data. Neural networks are a type of machine learning algorithm inspired by the structure and function of neural networks in the human brain. Neural networks are capable of learning from previous experiences and examples, and can adapt their internal parameters to improve performance on specific tasks.

The key to understanding machine learning is that it allows software systems to learn and improve from data, without being explicitly programmed for every possible scenario. Instead of manually coding all the logic, developers provide machine learning algorithms with large amounts of data and let them iteratively optimise their internal models until they achieve satisfactory results on the task at hand. This enables machine learning to solve complex problems that would be extremely difficult or impossible to manually program using traditional software approaches.

For example, when social media platforms X or Facebook determine what should appear in your “feed” or timelines, they are using machine learning to make predictions about the content and posts that will be most relevant to you. Advertisers already use machine learning to optimise the bidding on millions of ad placements every second. It’s used elsewhere in tasks like monitoring customer-service calls, underwriting loans and insurance, detecting fraud, and a bevy of other applications across every industry today.

Deep Learning

Deep learning is a powerful form of neural networks. It involves training artificial neural networks with multiple layers (hence “deep”) to learn from large amounts of data and perform specific tasks, such as image recognition, natural language processing, or decision-making.

While deep learning has been studied in academic circles for decades, it gained broader attention and adoption in industry after researchers at companies like Google demonstrated its effectiveness in solving complex problems, particularly in the field of artificial intelligence.

Today, deep learning is widely used by various companies and organisations for a range of applications. For example, Google utilises deep learning in its search algorithms, language translation services, and computer vision systems. Salesforce employs deep learning in its CRM platform to analyse customer data and provide insights. IBM’s Watson system, which uses deep learning, is deployed in healthcare and retail settings for tasks like diagnosis and customer service. CrowdStrike leverages deep learning in its Falcon platform for advanced cybersecurity threat detection. Finally, companies like Tesla and Waymo heavily lean on deep learning for their self-driving vehicle technologies, enabling tasks such as object detection, path planning, and decision-making.

Natural Language Processing

Natural Language Processing (NLP) is an area of artificial intelligence that focuses on understanding, processing, and generating human language. It encompasses a wide range of algorithms and techniques designed to analyse and extract meaning from textual data, such as articles, books, social media posts, and spoken language.

Thanks to the availability of large datasets, powerful computing resources and deep learning models, NLP has made significant advancements in recent years. These advancements have enabled the creation of more accurate and robust language processing systems, leading to improved performance in applications such as chatbots, virtual assistants, language translation services, and sentiment analysis on social media.

Large Language Models (LLMs)

Large Language Models (LLMs) are powerful deep learning models trained on massive amounts of text data, enabling them to understand and generate human-like language with remarkable coherence.

LLMs such as GPT (Generative Pre-trained Transformer), PaLM, and LaMDA, are autoregressive models that generate text in a sequential manner, predicting each subsequent token based on the previously generated context. This autoregressive property allows LLMs to produce coherent and contextually appropriate language.

LLMs are capable of performing a wide range of language tasks, including text generation, question answering, summarisation, and translation. These models can be adapted to different contexts and domains via a process called “fine-tuning”, which makes these models ever so versatile for various NLP applications.

While LLMs have demonstrated impressive capabilities, there are some well-known limitations. These models can generate biased or misleading outputs (referred to as “hallucinations”), and their lack of true understanding or reasoning abilities means they should be used judiciously and with appropriate oversight.

Nonetheless, LLMs represent a significant milestone in AI research and application, given the success of tools such as OpenAI’s ChatGPT, Google’s Gemini, and X’s Grok. This is a young research area with ongoing investments in research and development, and LLMs can be expected to play an increasingly important role in various industries and applications that rely on natural language processing.

Computer Vision

Computer vision enables machines to perceive and understand visual information from images and videos. It involves techniques such as image recognition, object detection and image segmentation. Computer vision has found applications in various fields including autonomous vehicles, surveillance systems, facial recognition and augmented reality.

The above technologies have collectively played a significant role in advancing AI and enabling the development of intelligent systems that can perceive, understand, reason and interact with the world around them.

AI’s impact on society

AI’s transformative power manifests through its wide array of practical use cases across various industries.

In education, AI is revolutionising personalised learning and adaptive education systems. Nowadays, intelligent tutoring systems leverage AI algorithms to provide individualised instruction and feedback, catering to the unique learning needs of students. AI-powered content recommendation systems suggest relevant learning materials, resources, and courses, enhancing the educational experience and facilitating lifelong learning.

In the field of mobility and transportation, AI is making significant strides. Self-driving cars powered by AI algorithms are being developed and tested, promising safer and more efficient transportation systems. AI-based traffic management systems are optimising traffic flow, reducing congestion and improving overall transportation infrastructure. Furthermore, ride-hailing and ride-sharing platforms are incorporating AI algorithms to optimise driver routing and matching, thereby maximising efficiency and reducing travel times.

AI is also playing a crucial role in addressing environmental challenges. The technology is being used in climate modelling to analyse vast amounts of data and predict climate patterns, aiding in the development of effective mitigation and adaptation strategies. AI-powered energy management systems are optimising energy consumption and reducing waste in buildings, leading to increased energy efficiency and sustainability.

Moreover, AI has found applications in the creative industry, enabling new forms of artistic expression. AI algorithms can now generate music, art, and literature, blurring the boundaries between human creativity and machine-generated content. This opens up exciting possibilities for collaboration between artists and AI systems, pushing the boundaries of imagination and innovation.

AI is also positively impacting other industries. For instance, in healthcare, AI is now assisting in diagnosing diseases, drug development, analysing medical images and developing personalised treatment plans. In finance, AI is automating risk management, fraud detection and trading activities. AI-powered chatbots and virtual assistants are now enhancing customer service by providing instant support and personalised services. Industries like manufacturing are benefiting from AI-driven automation, optimisation of production processes and predictive maintenance. AI is also enhancing cybersecurity by detecting anomalies and preventing cyberattacks. In the entertainment industry, AI now fuels recommendation systems, content creation and virtual reality experiences.

As AI continues to evolve and advance, its impacts are expected to be even more profound. From personalized medicine and smart cities to cybersecurity and space exploration, the potential of AI is vast and ever-expanding.

The challenges and risks

While AI’s potential is vast, this technology is not without challenges and risks that require careful consideration.

The rapid advancement of AI is now raising concerns about the ethical implications and responsible use of this technology. There are ongoing discussions around issues such as bias in AI algorithms, privacy concerns, and the potential for AI to be used maliciously. Additionally, some deeply knowledgeable experts in this field are cautioning that AI poses an existential threat to humanity, highlighting the need for robust safeguards and responsible development to ensure the technology remains beneficial to humanity.

Another concern revolves around the potential displacement of human labour as AI technologies automate tasks previously performed by humans. While this can lead to increased efficiency and productivity, it may also result in job losses and require the workforce to adapt to new roles.

While the probability of such risks materialising is uncertain, it is crucial to address them proactively and establish frameworks that promote transparency, fairness, and the ethical use of AI.

AI – sizing the opportunity

Now that you are familiar with the key AI technologies, in order to conceptualise and frame the AI investment opportunity, it is worth revisiting the previous major technology platform shifts i.e. the adoption of the internet, the advent of the mobile era and cloud computing.

So, without further ado, let us take a trip down memory lane…

You may recall that the internet only became popular in the late 1990s/early 2000s and it enabled global connectivity, facilitated the sharing of data and knowledge, and opened up new avenues for commerce, education, and entertainment.

Only a few years later, in early 2007, former Apple CEO – Steve Jobs stepped onto a stage and unveiled the iPhone. The smartphone took the world by storm, the status quo got disrupted and the era of mobile computing was unleashed. Mobile devices enabled people to access the internet, communicate, and perform various tasks on the go, leading to significant changes in how humans interact, work, and consume information.

In the late 2000s, the cloud revolution (the widespread adoption of cloud computing) began to gain prominence and continues to evolve today. Cloud computing involves the delivery of computing services, such as storage, processing power, and software applications, over the internet. It allows organisations and individuals to access and utilise powerful computing resources without the need for extensive on-premises infrastructure.

The internet, mobile and cloud revolutions not only fostered one of the fastest technological shifts in history; they unleashed the largest wealth-building opportunity in human history! These technologies gave rise to exceptionally successful companies, which created tens of trillions of dollars in shareholder value. Firms like Amazon, Apple, Google, and Microsoft capitalised on these technologies to revolutionise industries, disrupt traditional business models, and create immense wealth for their shareholders. Numerous other companies in ecommerce, online payments, enterprise software also capitalised on these technologies and they collectively created trillions of dollars in shareholder value.

Before the internet and mobile computing, for almost a century, the list of the world’s most valuable companies was perennially dominated by businesses in banking, consumer goods, oil, and industrial conglomerates. Today, less than 25 years after the widespread adoption of the internet, mobile and cloud technologies, seven of the world’s Top 10 largest businesses (as measured by market capitalisation) are technology companies and apart from Taiwan Semiconductor Manufacturing which is currently valued around US$620 billion, the market capitalisation of each of these technology businesses in this list exceeds US$1 trillion!

If our assessment is correct, after the internet, mobile and cloud computing, AI is the next major platform shift in technology and it has the potential to impact every industry.

AI is still in its early days, but if the viral adoption of generative AI-powered large language models (LLMs) is any indication, this technological revolution has a very long growth runway.

Figure 1 shows OpenAI’s ChatGPT exceeded 100 million monthly active users within its first two months post-launch – the fastest pace of adoption of any application the world has seen to date!

Figure 1: ChatGPT’s meteoric rise!

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Source: ARK Invest

So far, due to the build out of data centres, the AI megatrend has primarily benefited businesses at the infrastructure layer. The biggest beneficiary has been NVIDIA which currently has more than a 95% market share of specialist AI chips. However, over the past 18 months, investors have also bid up the stocks of the mega-cap technology companies such as Alphabet, Amazon, Meta and Microsoft (which owns a sizeable stake in Open AI).

In these early years of truly useful AI, we believe the key competitive edge for companies will come from accumulating data and having the infrastructure to use AI in their own business (and even provide it to other companies). In AI, data accumulation is crucial because large datasets fuel the accuracy and performance of the AI models. The more diverse and extensive the dataset, the better equipped AI models are to understand nuanced patterns and make accurate predictions. Large datasets enable AI systems to capture a wide range of scenarios, variations and edge cases, allowing them to generalise well and handle real-world complexities. Furthermore, data accumulation facilitates the training and fine-tuning of AI models, enabling continuous improvement and adaptation to changing conditions. In essence, data accumulation is the foundation on which AI algorithms build their understanding of the world, enabling them to deliver meaningful insights, drive innovation, and unlock the full potential of AI across various industries.

Looking to the future, the next steps for AI will be transforming entire industries that have often had limited association with cutting-edge technology. As we noted earlier, self-driving cars are today’s most obvious example of how AI could transform the transportation industry, but this is just a preview of what is to come. It is highly probable that AI will soon be leveraged by nascent industries such as robotics, finance, genomics, the space economy and more.

According to a new report by Bloomberg Intelligence, the generative-AI market is poised to grow revenue by 40% CAGR to approximately US$1.3 trillion by 2032 (Figure 2)!

Figure 2: Generative AI revenue (40% CAGR until 2032)

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Source: Bloomberg Intelligence

Up until now, the stocks of the “picks and shovels” plays and the mega-cap technology companies have benefited from the AI boom. However, going forwards, we expect companies at the application layer as well as innovative enterprise software companies to deliver outsized gains to investors.

Recently, NVIDIA’s CEO – Jensen Huang summed it up best when he stated that “enterprise software companies are sitting on goldmines and in the future, these AI factories will have their AI agents sitting on top of their software”!

There can be no doubt that some businesses will prosper from the AI revolution but the key for investors will be to separate those businesses that are merely capitalising on hype from those that are building truly useful, scalable, investable AI applications and platforms.

The robotics industry encompasses the design, development, production, and application of robots across various sectors, with applications ranging from manufacturing and healthcare to entertainment and exploration. Robots are programmable machines capable of carrying out tasks autonomously or semi-autonomously, typically with precision and efficiency that extends beyond human capabilities.

This research piece aims to explore the current state, trends, and future potential growth of the robotics market so investors can better understand this nascent, long-term opportunity.

Though the world generally thinks of robots as primarily hardware, robotics does not necessarily require a hardware component; software robots have become more commonplace in recent years – most prominently including solutions such as automated chatbots and robotic process automation (RPA) platforms – enabled by recent rapid advancements in computing power and artificial intelligence.

The robotics industry is rapidly evolving with major technological advancements, including developments in artificial intelligence, machine learning, sensors, actuators, and materials science. These innovations are driving the creation of more intelligent, agile, and versatile robots capable of adapting to more dynamic environments and performing increasingly complex tasks both in the digital and physical worlds. As the capabilities of robots continue to evolve, their applications across industries should only expand, ushering in new opportunities and challenges for businesses, workers, investors, and society as a whole.

Current state of the industry

In manufacturing, industrial robots from companies such as Japan-based Fanuc and Sweden’s ABB already play crucial roles in automating repetitive tasks such as assembly, welding, painting, and material handling. These robots increase productivity, improve product quality, and enhance workplace safety by taking on hazardous or physically demanding tasks.

Collaborative robots, or cobots, are a newer development in the industry, designed to work alongside humans in shared workspaces, offering flexibility and adaptability in production lines.

One key example of cobots are warehouse robots in the logistics space, which have played a key part in bolstering productivity and streamlining inventory management, order fulfilment, and automated delivery in the e-commerce industry. Amazon.com was an early leader in this space, acquiring warehouse automation specialist Kiva Systems for US$775 million in 2012 and subsequently rolling out its warehouse-navigating bots across its vast network of fulfilment centres.

In healthcare, robots are revolutionising patient care and medical procedures. Surgical robots developed by Intuitive Surgical, Medtronic and Stryker have assisted surgeons in performing millions of minimally invasive surgeries with greater precision and control, leading to reduced patient trauma, faster recovery times, and improved surgical outcomes. Robots also aid in tasks such as medication dispensing, patient monitoring, and rehabilitation therapy, helping healthcare professionals deliver more efficient and personalised care.

Beyond manufacturing, healthcare, and logistics, robots are improving sectors such as agriculture, retail, and defence. In agriculture, autonomous drones and robotic harvesters are transforming crop management and harvesting processes, increasing efficiency and yields. In defence, robots from companies including Lockheed Martin, AeroVironment, Textron, and RTX are deployed for surveillance, reconnaissance, bomb disposal, and other hazardous missions, keeping human personnel out of harm’s way.

Market size, revenue share, and recent growth rates

The global robotics industry will generate revenue of more than US$40 billion in 2024, according to Statista, with the vast majority still concentrated in medical and industrial applications. The industry overall served a total addressable market (TAM) worth more than US$80 billion in 2023, having grown at a more than 10% annual clip for the past several years.

Figure 1: Robotics industry revenue share by industry

Source: Statista

Much of the industry’s recent growth, however – as well as most of its projected future growth (more on that below) – has come from professional services robots.

It was hardly surprising to that end, then, when Amazon attempted to acquire home robotics company iRobot in 2022 – a move that would have bolstered its robotics repertoire in the smart home and services segments – before the deal was ultimately scuttled by antitrust regulators in early 2024.

The case for robotics

Investing in robotics offers numerous advantages, from boosting efficiency to fostering innovation, which makes it a critical focus for future-oriented businesses and industries. Here are some of the key tailwinds that make investing in robotics a compelling option:

1. Increased productivity and efficiency: Robotics technology significantly enhances productivity in manufacturing and service sectors by performing tasks faster and with greater precision than human workers. Robots can operate continuously without breaks, which maximises output and efficiency and they do not become ill or require annual leave.
2. Cost reduction: Over time, the use of robotics can lead to substantial cost savings. Robots reduce labour costs, minimise errors, and decrease waste. Additionally, predictive maintenance capabilities of modern robots can prevent costly downtime for a wide variety of both robotic and non-robotic platforms alike, anticipating and addressing potential mechanical issues before they become problematic.
3. Safety and ergonomics: Robotics can tackle dangerous or hazardous tasks that pose undue risks to human workers. This not only reduces the likelihood of workplace injuries but also improves the overall working conditions.
4. Innovation and competitive advantages: The deployment of robotics technology drives innovation by introducing new capabilities and enabling businesses to explore new product lines and markets. Companies that adopt robotics can gain a significant competitive edge, as they are often seen as leaders in technological adoption.
5. Addressing labour shortages: In many industries, there is a growing gap between the availability of skilled labour and the requirements of modern production processes. Robots can fill this gap, especially in regions or sectors experiencing labour shortages, ensuring that production levels and growth targets are met.

Investing in robotics is not just about automating tasks; it’s about transforming business operations to be more efficient, safe, and innovative. This transformation is crucial as industries evolve and the global market becomes more competitive. By embracing robotics, companies can better position themselves for future growth and success. And investors can benefit from this success by putting their capital to work accordingly.

Key developments and trends

At present, the industrial sector is primarily using robots in manufacturing to enhance productivity and efficiency. The integration of incrementally advanced AI in recent years has allowed these robots to perform increasingly complex tasks such as predictive maintenance and quality control, further driving their adoption. The professional services sector, which includes logistics, healthcare, and hospitality, is also seeing increased utilisation of robots for tasks like transportation, cleaning, and personal assistance.

The robotics industry is experiencing dynamic growth and accelerating innovation, driven by advancements in artificial intelligence (AI), collaborative robots (cobots), and service robotics.

At the time of writing (May 2024), the key trends shaping the robotics sector include:

1. Artificial intelligence integration: AI continues to be a major driver in the robotics industry, enhancing robot capabilities in autonomy, predictive maintenance, and interaction. AI enables robots to handle complex tasks and environments by improving their decision-making and efficiency
2. Growth of collaborative robots (Cobots): Cobots are designed to work alongside humans in a shared workspace, enhancing safety and efficiency. They are increasingly being used across various industries, including automotive and electronics, due to their adaptability and ease of integration.
3. Expansion of service robotics: Service robots are being deployed across a wide range of non-industrial sectors such as healthcare, logistics, and hospitality. These robots perform tasks ranging from transportation and logistics support to personal assistance and healthcare services, reflecting a growing diversification in robot applications.
4. Improving dexterity and digital twins: Innovations like mobile manipulators combine mobility with manipulative abilities, enabling robots to perform material handling and maintenance tasks more efficiently. Additionally, digital twin technology is being used to optimise robot operations through virtual simulations, which predict performance outcomes and maintenance needs. Autonomous vehicle designers are actively using digital twin technology, for instance, to explore new designs and sensor combinations as well as improving reaction times.
5. Humanoid robots and Robot-as-a-Service (RaaS): Humanoid robots are being developed to operate in environments designed for humans, performing a range of tasks from warehouse operations to customer service. Meanwhile, RaaS models are also gaining traction, allowing companies the ability to deploy robotics without massive upfront investments in R&D and hardware, further lowering the barrier to automation adoption.

Sizing the opportunity

The robotics market is expected to grow rapidly over the next several years (Figure 2). According to research firm Boston Consulting Group, the market for robotics is expected to grow from approximately US$40 billion in 2024 to US$160-$260 billion by 2030. This represents an annual compounded growth rate of 26-37% over the next 6 years!

Figure 2: The robots are coming

Source: Boston Consulting Group

A substantial portion of this growth is likely to come from professional services robots, which could generate twice as much revenue as conventional and logistics robots.

The collaborative robots (cobots) segment alone is projected to grow at a compound annual growth rate (CAGR) of 30.7% from 2022 to 2030 – to just under US$8 billion – indicating strong demand for robots that can safely complement the work of human partners.

Given that the total addressable market (TAM) for the robotics industry is expected to grow exponentially, it is worth considering which specific sub-sectors might represent the most promising investment opportunities.

Our research suggests that humanoid robots are arguably the most exciting growth opportunity for their combination of high-tech novelty and immense potential growth. According to research from Goldman Sachs, the global humanoid TAM could reach an estimated US$38 billion by 2035 and this projection assumes that 1.4 million units are being sold annually a decade from today. Initial humanoid robot applications will likely focus on industrial and manufacturing operations, before gradually transitioning to other industries including hospitality and personal care.

We expect Tesla and Hyundai Motor subsidiary Boston Dynamics to stand tall as leaders in humanoid robotics development in the coming years.

Various “Robots as a Service” (RAAS) offerings should also enjoy outsized growth, recurring revenues and high margins. Symbotic is one notable leader to that end, having recently teamed up with SoftBank to offer a compelling AI-based warehouse-as-a-service platform in the logistics space.

Tesla also has the potential to benefit greatly on the RAAS front through its planned robotaxi ride hailing service as well as its Optimus humanoid robot. The electric vehicle leader only recently offered consumers the first glimpse of its robotaxi app in April 2024 and Elon Musk is of the view that ultimately, Tesla’s Optimus business will become the company’s biggest business division.

Apart from Tesla and Boston Dynamics, a number of start-ups in the private markets in China, Europe and the US have also developed humanoid robots and given the size of the industry, some of these companies are likely to reward their shareholders.

The financial technology (fintech) and digital payments industries encompass a broad range of financial services that leverage technology to enhance or automate financial processes and services.

Fintech refers specifically to the integration of technology into offerings by financial services companies to improve their use and delivery to customers. Early stage fintech companies are typically founded with the intent of disrupting incumbent financial institutions and corporations that rely less on software and technology as cornerstones of their respective businesses.

Some of the primary products and services offered by fintech businesses include:

Digital payment solutions: Facilitating the exchange of money between parties through various digital methods, rather than cash or cheques.
Personal finance and wealth management: Providing digital banking solutions, financial management and financial planning services directly to consumers.
Lending services: Including peer-to-peer or marketplace lending platforms, which connect borrowers directly to lenders through digital platforms.
Insurance technology (Insurtech) platforms: Using technology to simplify and streamline the insurance industry, handling everything from underwriting to claims processing and fraud detection.
Cryptocurrencies and Blockchain products: Implementing new financial technologies for creating, managing, and transacting cryptocurrencies, and using blockchain technology for secure transactions and record-keeping.

The fintech and digital payments industries are crucial in our modern digital economy, driving innovation in financial transactions and offering consumers and businesses more flexible, efficient, and secure options for managing their financial operations. These industries are nascent and continually evolving, propelled by technological advancements and growing digital connectivity.

Current state of the industry

The fintech industry has continued to experience remarkable growth and transformation in recent years, solidifying its position as a crucial player in the global financial landscape. As of now, the industry is thriving, driven by a combination of technological advancements, evolving consumer preferences, and regulatory changes.

Fintech companies are revolutionising traditional financial services by leveraging artificial intelligence, machine learning, blockchain, and cloud computing to deliver innovative and user-friendly solutions. The adoption of mobile banking, digital payments, and online lending has accelerated, with consumers embracing the convenience, speed, and accessibility offered by these digital platforms. Moreover, fintech has extended its reach beyond retail banking, and expanded into areas such as insurance, wealth management, and capital markets.

In 2023, the banking industry generated more than US$7 trillion in revenues with year-over-year growth in volume and revenue margins. Fintech accounted for just 5 percent of the global banking sector’s net revenue! This shows that the penetration rate is still very low and the industry should continue to grow for several years. McKinsey & Company estimates that the fintech industry’s revenue is likely to double to more than $400 billion by 2028, representing a 15 percent compound annual growth rate vs. the overall banking industry’s compound growth rate of roughly 6 percent.

The digital payments market has also experienced significant growth and transformation over the past 20-plus years, led by a combination of technological innovation, increasing global digitalisation and changing consumer preferences.

According to Statista (Figure 1), the transaction value of digital payments completed annually has more than tripled since 2017 and it is expected to reach US$11.53 trillion in 2024.

Figure 1: Steady growth in digital payments

Source: Statista

E-commerce transactions have historically represented an outsized share of the world’s total digital transaction value, and will likely continue to do so for the foreseeable future. As we noted in our recent e-commerce industry report, e-commerce currently accounts for a surprisingly low 20% of total retail sales worldwide and this figure is expected to expand to 23% of total retail sales by 2027.

The penetration rates are even lower in most of the developing nations where e-commerce represents just 7-9% of total retail sales. In our view, this is a major growth opportunity and the increasing adoption of e-commerce should serve as a meaningful tailwind for digital payments.

Fintech is a good industry

Fintech and online payments have some attractive business characteristics which is why we have invested a portion of our capital in a few promising companies in this industry. Here are some of the favourable attributes of fintech businesses –

High growth potential: The fintech and payments industry is characterised by rapid growth, driven by the increasing adoption of digital solutions across banking, investments, and everyday transactions. As more consumers and businesses embrace digital and mobile payment solutions, companies operating in this space continue to expand their market reach and service offerings, offering significant growth opportunities for investors.

Low cost structures: Digital companies’ overheads tend to be far lower than traditional banks. For example, fintech players do not need to invest in extensive networks of physical branches so they do not have to employ as many employees as the legacy financial institutions. This significantly reduces their operating expenses and capital requirements; and improves margins. Moreover, fintech businesses lean more on cutting-edge technology/software solutions to handle almost every aspect of their businesses, and this further enhances their offerings whilst cutting down on their human resources costs.

Passing on cost savings: Often, fintech companies pass along the resulting cost savings of their digital foundations to their customers and this enables them to grab market share. For instance, digital banks and online lenders typically offer more favourable interest rates on savings or loans; meanwhile “Insurtech” companies are able to underwrite policies with lower premiums and superior combined ratios. Since fintech companies have lower cost structures, they are able to invest more in technology which results in customer benefits such as top-notch fraud detection, faster claims processing and quicker loan approvals. These enhanced services attract more customers and enable these businesses to grow.

Frequent, repeat purchases: Fintech is known for its stickiness as customers stay loyal and engage in frequent repeat transactions. Payments and banking are inherently sticky industries i.e. once customers sign up, unless they are very disappointed, they tend to stay. This can be attributed to the innovative and diverse solutions offered by fintech companies, which address specific pain points in the financial industry. The comprehensive service offerings provided by fintech companies enhance customer satisfaction and encourage consolidation of financial activities. Frequent, repeat transactions reduce cyclicality and generate more stable cash flows for these businesses.

Rapid diversification of services: Fintech companies disrupt traditional financial sectors including banking, insurance, and asset management by continuously introducing new products and services. This diversification not only attracts a broader range of consumers and makes the company’s offerings more “sticky”, this spreading of revenue streams across different financial services also mitigates business risk.

Financial inclusion: Fintech companies often provide financial services to underserved or unbanked populations, particularly in emerging economies. For instance, over the past decade, mobile payment systems have enabled transactions and financial management in much of the developing world without the need for traditional bank accounts, thereby opening up the financial system to a larger subset of the population. Globally, 76% of adults have a bank account today, up from 51% a decade ago! This is not only good for society, it is also a solid opportunity, as it allows fintech businesses to tap into previously unreachable customers who are often disenfranchised with their countries’ long-established financial institutions.

As financial technology continues to evolve, the industry’s significance is expected to increase further. It is notable that key fintech players such as PayPal, Ant Group, Stripe and Square parent Block have already achieved impressive scale given their early industry leadership. Meanwhile, startups such as digital banking leader SoFi Technologies, Brazilian fintech StoneCo, and U.S.-based insurance company Lemonade have also stormed onto the scene in recent years, bringing innovative solutions to the market, which is good for consumers.

Sizing the opportunity

The fintech industry is still fairly young and it is likely to continue its steady growth over the next decade. It is interesting to note that Mordor Intelligence expects the global fintech market to nearly double in value to $608 billion over the next five years (Figure 2), representing a compound annual growth rate of over 14% between now and 2029.

Figure 2: Fintech market size to double in 5 years

Source: Mordor Intelligence

If recent industry trends are any guide, much of the industry growth in the future will be fuelled by the developing economies. In 2023, fintech revenues in Africa, Asia–Pacific (excluding China), Latin America, and the Middle East represented 15 percent of fintech’s global revenues. It is estimated that this number will rise to 29 percent in aggregate by 2028! Conversely, last year North America accounted for 48 percent of worldwide fintech revenues and this number is expected to decrease to 41 percent by 2028.

Today, fintech penetration in the developing world is the highest in the world. This is not surprising given that up until recently, many of these nations lacked access to basic banking services which gave fintech companies the opportunity to serve unmet needs.

Due to the explosive adoption of smartphones over the past 15 years, fintech services have proliferated in the developed world. Despite this progress, the World Bank recently estimated that there are still 1.4 billion unbanked adults worldwide and most of them are in the developing world. According to the World Bank’s Global Findex report, approximately 29% of adults in the developing world still do not have a bank account and this is a major business opportunity for fintech companies in Africa, Asia and South America.

The fintech industry’s explosive growth over the past 5 years has created significant wealth for investors. According to McKinsey & Company, as of July 2023, publicly traded fintech companies represented a market capitalisation of US$550 billion, a two-times increase versus 2019. In addition, as of the same period, there were more than 272 fintech unicorns, with a combined valuation of US$936 billion, a sevenfold increase from 39 firms valued in excess of US$1 billion just 5 years ago!

In our view, the high quality, dominant fintech businesses with good unit economics will continue to prosper over the following years and that will be rewarding for their shareholders.

Just like any industry though, not all businesses are created equal and there will be winners and losers. Therefore, investors will have to carefully evaluate potential businesses before committing their capital.

In the age of digital transformation, the influence of software is pervasive and undeniable. As technology continues to advance at an unprecedented pace, software is revolutionising traditional business models and redefining customer experiences. From e-commerce to finance, manufacturing to transportation, industries across the board are being reshaped by the transformative power of software.

The appetite for software is insatiable and enterprise software, cloud software, and Software-as-a-Service (SaaS) markets are each playing their part in the digitalisation of businesses. Together, they represent critical pieces in companies’ efforts to efficiently manage virtually every aspect of their businesses and often provide mission critical functions.

Before we delve deeper into how we think about those opportunities – and for perspective on how they fit together – here is a quick breakdown of each market:

Enterprise Software

Enterprise software is designed to meet the needs of organisations rather than individual users. These applications are complex and scalable, and integrate with other software and network configurations on a large scale. They serve a variety of business functions such as enterprise resource planning (ERP), customer relationship management (CRM), supply chain management (SCM), cybersecurity, observability, and data warehousing. Companies use enterprise software to manage vast amounts of data, streamline their operations, support decision-making and enhance productivity across multiple departments.

Cloud Software

Cloud software refers to applications that are hosted on remote servers and accessed over the internet, which are maintained by external vendors rather than the users themselves. In contrast to old on-premises models, cloud software allows for flexibility, scalability, and cost efficiency as it eliminates the need for organisations to purchase, run, and maintain physical servers and other on-premises infrastructure. Cloud software can be delivered through several models including Infrastructure-as-a-Service (IaaS), which provides virtualised computing resources like servers, storage, and networking; Platform-as-a-Service (PaaS), which offers a complete platform for developing, testing, and deploying applications; and Software-as-a-Service (SaaS).

Software-as-a-Service (SaaS)

SaaS is one of the most significant subsets of the cloud computing market. It is a software distribution model in which applications are hosted by third-party providers and made available to customers over the internet. Unlike traditional software that requires a license purchase and installation on individual machines, SaaS products are typically subscription or usage based and centrally hosted. This means users can access software and its functions remotely from any device with internet connectivity. SaaS offers numerous advantages, including lower upfront costs, reduced time to benefit, high scalability, and automatic updates.

Many enterprise software providers have already transitioned part or all of their offerings to the cloud, capitalising on the cloud’s scalability and operational efficiency to better serve large organisations. Similarly, the rise of SaaS over the past two decades has reshaped how businesses think about software expenditure and management, shifting from capital-intensive software ownership to more operational expense models with ongoing subscriptions.

These markets continue to grow as businesses increasingly rely on digital solutions to manage their operations, interact with customers, and compete in today’s global economy. The push toward digital transformation, accelerated by factors like remote work trends and the global scaling of businesses, further drives the demand for sophisticated enterprise software solutions, robust cloud service platforms, and accessible SaaS applications.

Cloud-based software-as-a-service models are not just good for enterprise end users; they have also ushered in an era of superior software businesses characterised by higher recurring revenues, sticky business models, stable cash flows, and lower cyclicality.

Current state of the industry

The software industry is currently experiencing a period of rapid growth and transformation. With the increasing reliance on digital technologies across various sectors, software has become a critical component of modern businesses and everyday life. The industry is driving innovation in areas such as artificial intelligence, cloud computing, blockchain, and cybersecurity.

Open-source software is thriving, fostering collaboration and community-driven development.

The industry is facing challenges such as cybersecurity threats, privacy concerns, and the need to address ethical considerations in emerging technologies. Overall, the dynamic software industry is evolving, shaping the way humans live, work, and play.

Over the past decade, the enterprise software industry has experienced rapid growth driven by increasing demand for integrated solutions across every aspect of a business’ operations.

Gartner research indicates that over the past several years, the global enterprise software market has enjoyed solid mid-double-digit percent growth (ranging between 11% and 16%), buoyed in part by initiatives to increase productivity during the COVID-19 pandemic.

According to Precedence Research, the worldwide software market grew to US$659 billion in 2023 with North America responsible for 44% of the total spend, followed by Europe (27%) and Asia Pacific (24%). It is interesting to note that the software market is expected to continue growing to US$1.789 trillion by 2032, representing a CAGR of 11.74% (Figure 1).

Figure 1: Evolution of the worldwide software market

A graph of a software market

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Source: Precedence Research

In 2022, on-premises software deployments still represented more than half of global enterprise software spending, highlighting the significant opportunity remaining for software companies to capitalise on the industry’s ongoing transition away from on-premises solutions and toward cloud-based offerings.

With more than half the world’s enterprise workloads still on-premises, the SaaS industry is expected to grow at a rapid clip as enterprises continue to migrate to the cloud. Today, the enterprise software and cloud/SaaS markets are dominated by several key players that have played pivotal roles in shaping its direction and technological advancements.

In 2022, the top five vendors — Microsoft, Oracle, Amazon, Salesforce and SAP — captured 34% market share, whereas the next five vendors — IBM, Adobe, Google, VMware and Cisco — held 11% market share.

In the Infrastructure-as-a-Service (IaaS) space, Amazon Web Services, Microsoft Azure, and Google Cloud dominate the industry and command decisive leadership positions (Figure 2).

Figure 2: Leaders in Infrastructure-as-a-Service

A graph of a cloud company

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Source: Statista

Amazon Web Services (AWS) has been the clear dominant player in the IaaS industry thanks to its leadership and first-mover advantage. However, Microsoft Azure and Google Cloud are rapidly closing the gap, leveraging their existing enterprise customer relationships and integrating their cloud offerings with popular productivity and collaboration tools. The big three hyperscalers are growing quickly at scale, with AWS growing sales at high teens, with Azure and Google Cloud growing at close to 30% annually. The enormous size of the world’s cloud computing market is intensifying competition with players such as Oracle and IBM now jostling to become key players in the IaaS/PaaS market. This ongoing battle for market share could lead to more competitive pricing, better service levels, and faster innovation, ultimately benefiting customers.

Software is a good industry

The dominant businesses in enterprise software, cloud software, and Software-as-a-Service (SaaS) have business characteristics which make them attractive investments. Some of these attributes are set out below:

High growth potential: The software industry has demonstrated strong growth and the market is enormous! The SaaS market, in particular, is expanding rapidly, with projections indicating significant increases in market size over the coming years due to the shift toward cloud-based solutions and digital-transformation initiatives. Accelerated by the COVID-19 pandemic, this growth is being driven by the increased need for scalable software solutions that can adapt to changing business environments.

Recurring revenue model: SaaS and cloud services typically operate on a subscription-based model, offering predictable and recurring revenue streams and consequently, more stable cash flows and less-cyclical businesses. Unlike the traditional licence-based software business, this new model is attractive to investors because these recurring revenues provide more visibility into future earnings.

Scalability: Cloud and SaaS businesses are highly scalable as they can easily accommodate growing customer demands without the need for significant capital investments. Unlike old economy businesses which usually require significant sums of capital to grow, the marginal cost of distribution for these businesses is minimal or zero. Moreover, the subscription-based model allows for flexible pricing tiers and the ability to add or remove users seamlessly, allowing these businesses to better align their resources with customer needs.

Stickiness (high switching costs): Software businesses often exhibit stickiness due to high switching costs associated with their products or services. Once customers integrate a particular software solution into their workflows, it becomes challenging and costly to switch to an alternative. The switching costs may arise from data migration, retraining employees, or the need to rebuild processes around a new software system. This stickiness creates a competitive advantage as it fosters customer loyalty and reduces the likelihood of churn. The software vendors typically expand their offerings and upsell to their existing customers which results in high net retention rates (i.e., existing customers spending more each year). These high retention rates, combined with the recurring revenue model, lead to attractive customer lifetime values (LTV) and when combined with lower customer acquisition costs (CAC), lead to improving profitability and cash flow visibility.

Network effects: Software businesses can benefit from network effects, whereby the value of their product or service increases as more users or customers join the network. As the network expands, it creates a positive feedback loop, attracting more users and generating additional value. The larger the user base, the more valuable the software becomes, creating a barrier for potential competitors and enhancing the market position of the business.

High margins: Software businesses often enjoy high margins due to the relatively low marginal costs associated with producing and distributing software. Once the initial development costs are covered, the incremental cost of serving additional customers or delivering software updates is typically minimal or zero. This characteristic allows software companies to achieve significant economies of scale, resulting in healthy profit margins.

Innovation and Integration: Software businesses at the forefront of technological innovation, especially when it comes to integrating cutting-edge technologies like artificial intelligence (AI), machine learning (ML), and advanced business analytics. These advancements enhance the functionality and competitiveness of cloud and SaaS offerings, making them more attractive to end users. Software vendors today are sitting on rhetorical gold mines and they are increasingly building value by deploying their own AI agents on top of their respective leading software platforms.

Our team at AlphaTarget has been studying and investing in the software industry for almost two decades. At present, a significant portion of our investment portfolio is allocated to high quality, rapidly growing software businesses.

Sizing the opportunity

Though the enterprise software, cloud computing, and SaaS markets can each be quantified individually, these three closely intertwined markets collectively present an immense opportunity for vendors to drive outsized top-line growth with attractive unit economics.

According to Precedence Research, the SaaS market is likely to nearly triple from US$358 billion in 2024 to US$1.016 trillion by 2032 (Figure 3). Whilst this market-wide growth forecast is impressive, it is notable that some mission-critical software vendors are growing their revenues and free cash flows at an even faster clip.

Figure 3: SaaS market size expected to triple by 2032

A graph of software as a service market size

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Source: Precedence Research

While the aforementioned leaders in the IaaS space are undoubtedly dominant businesses, our in-depth research at AlphaTarget has led us to invest our capital in the most promising, rapidly growing enterprise software and cloud-computing businesses with long growth runways. Our preferred businesses are run by strong management teams and we expect them to keep performing well over the foreseeable future.