Artificial Intelligence and Investing

[karlmarx]

I came across this long and interesting read on the potential of learning-capable AI in achieving superior investment returns. What startled me was the performance of the AI, considering it is still in its nascent stage. Should it become more developed in a few years time, will there be more competition for us?


https://www.bloomberg.com/news/features/...ting-on-ai

The Massive Hedge Fun Betting on AI
Initially wary of the technology, Man Group was soon persuaded by the returns from algorithm-centric funds.


...

Over time, Granger built up the firm’s confidence in the technology. By 2015 artificial intelligence was contributing roughly half the profits in one of Man’s biggest funds, the AHL Dimension Programme that now manages $5.1 billion, even though AI had control over only a small proportion of overall assets. Elsewhere in the company—and in the industry as a whole—AI technology is being used to find the speediest way to execute trades, to make bets on market momentum, and to scan press releases and financial reports for keywords that could signal that a stock will rise or fall. Even Man’s very human discretionary division, where business is centered on experienced asset managers, is exploring AI techniques.



Those big clients Ellis was initially worried about clearly like what they’re seeing and have rushed to join Man’s algorithm-centric funds. All told, four Man funds collectively managing $12.3 billion are incorporating AI. Assets under management at Man have surged about 77 percent since the beginning of 2014. AHL Dimension fund assets have more than quintupled since then. 


The firm has gone from viewing AI with skepticism to making it a cornerstone strategy. Among the company’s biggest expenditures now is computer equipment—along with hiring engineers to keep up with the technological change and the ensuing growth. AI is now not only out of the nuclear bunker but on a pedestal. “It went from a total isolation to ‘OK, you are allowed to sit at dinner with the rest of us, but don’t talk’ to the point where it’s become a part of the family,” Ellis says.

...

[weijian]

I came across this long and interesting read on the potential of learning-capable AI in achieving superior investment returns. What startled me was the performance of the AI, considering it is still in its nascent stage. Should it become more developed in a few years time, will there be more competition for us?

Irregardless of whether AI takes off or not, the odds are always against the OPMI and competition is relentless (insiders, PHDs, CFDs, professional full time investors and the list continues...)

This kind of "model-based quant investing" always reminds me of LTCM and its demise. AI supposed to be 1-level up by its ability to "self learn" (in layman data science terms, i guess it is re-fitting the model with newer data?) but it will always be interesting to see whether such talk/performance survives the next bear market.

[brattzz]

no AI for me, unless it's Alien's Intelligence!

[karlmarx]

Indeed, we shall see...Hopefully AI can't learn as well as they claim to do so.

But if one day computers learn how to look for value when investing...

[growthinvestor]

"AI technology is being used to find the speediest way to execute trades, to make bets on market momentum, and to scan press releases and financial reports for keywords that could signal that a stock will rise or fall"

seems being used to trade rather than to invest.

I think AI can be used to do quantitative analysis of companies financials at very fast speed, and immediately recommend which are the quality companies to invest. Perhaps also analyse how the financials correlate with future price performance.

[dreamybear]

For buddies interested in A.I., the course link : https://www.elementsofai.com/

----------------------------------------------------------------------
Finland is making its online AI crash course free to the world
Dec 18, 2019, 8:03am EST

Last year, Finland launched a free online crash course in artificial intelligence with the aim of educating its citizens about the new technology. Now, as a Christmas present to the world, the European nation is making the six week program available for anyone to take.......

https://www.theverge.com/2019/12/18/2102...e-elements

[weijian]

So VB Karlmarx had started a discussion on the hottest topic of the last 1.5years, Artificial Intelligence 7 years ago. Talk about market timing!

My first customer experience with AI was the AirAsia customer chatbot when I was trying to reschedule covid-induced cancelled flights. It was a great experience (definitely infinitely better than waiting for a call operator whom does not share your accent and needs to check with their supervisor every 10s)

So far, it seems like AI is largely providing cost savings that goes straight to the bottomline with improved profits. We could argue better customer satisfaction eventually translates to the topline but the article hasn't clearly pen out any kind of revenue opportunities that can improves profitability exponentially (like the SaaS or platform economics do). But looking at Nvidia and some power generation companies' results, spending on AI is probably exponential (for now).

The ROI on Generative AI

The poster child for this has been Klarna which leveraged AI to elevate their customer support. Their AI assistant has taken over the work of 700 employees, reducing resolution times from 11 minutes to just 2 minutes while maintaining high customer satisfaction levels.

Salesforce’s Agentforce platform, which helps resolve tickets is another one that is showing real ROI for early customers.

Microsoft casually dropped that they too are expecting to save hundreds of millions of dollars a year on call centers after adopting Generative AI.

https://www.tanayj.com/p/the-roi-on-generative-ai

[weijian]

As usual, Howard Marks gives a piece that is the "middle path" （中庸之道）. In his words, there is "exuberance" but it is hard to say that it is "irrational". The market has many participants and every participant has different motivations and/or play different games. Therefore what is rational to one participant may sound absurd to another.

From behavorial economics, we know that hindsight is 20/20 and sometimes rationality may only be fully appreciated on hindsight.

Is It a Bubble?

Here’s my actual bottom line:

There’s a consistent history of transformational technologies generating excessive enthusiasm and investment, resulting in more infrastructure than is needed and asset prices that prove to have been too high. The excesses accelerate the adoption of the technology in a way that wouldn’t occur in their absence. The common word for these excesses is “bubbles.”

AI has the potential to be one of the greatest transformational technologies of all time.

As I wrote just above, AI is currently the subject of great enthusiasm. If that enthusiasm doesn’t produce a bubble conforming to the historical pattern, that will be a first.

Bubbles created in this process usually end in losses for those who fuel them.

The losses stem largely from the fact that the technology’s newness renders the extent and timing of its impact unpredictable. This in turn makes it easy to judge companies too positively amid all the enthusiasm and difficult to know which will emerge as winners when the dust settles.

There can be no way to participate fully in the potential benefits from the new technology without being exposed to the losses that will arise if the enthusiasm and thus investors’ behavior prove to have been excessive.

The use of debt in this process – which the high level of uncertainty usually precluded in past technological revolutions – has the potential to magnify all of the above this time.

Since no one can say definitively whether this is a bubble, I’d advise that no one should go all-in without acknowledging that they face the risk of ruin if things go badly. But by the same token, no one should stay all-out and risk missing out on one of the great technological steps forward. A moderate position, applied with selectivity and prudence, seems like the best approach.

https://www.oaktreecapital.com/insights/...t-a-bubble

[swakoo]

The Radio Corporation of America (RCA) in the 1920s and early 1930s was a dominant "poster child" stock of a transformative new technology (radio and TV). That was symptomatic of a huge bubble leading to the Great Depression of the early 1930s.

Let's use AI to compare "poster child" RCA of the 1920s/30s to the "poster child" AI stock of today, Nvidia. From Gemini AI:

The comparison between the Radio Corporation of America (RCA) in the 1920s and early 1930s and Nvidia Corp. today reveals some striking parallels, primarily around their roles as the dominant "poster child" stocks of a transformative new technology, their incredible stock appreciation, and questions of market control. However, there are also fundamental differences in their business models and the broader economic environments that make the comparison complex.

Striking Parallels: The "It" Stocks of Transformative Tech

Both companies served as the primary, most visible proxies for a revolutionary new technology that promised to change the world.

Synonymous with an Emerging Industry: In the 1920s, commercial radio was a novel, world-changing medium, bringing mass communication and entertainment directly into people's homes for the first time. RCA was the stock for anyone wanting to invest in this future. Similarly, Artificial Intelligence (AI) is seen as the next great technological frontier, promising immense productivity gains across every sector, and Nvidia's GPUs are the foundational "picks and shovels" powering this revolution.

Phenomenal Stock Growth and Investor Mania: Both stocks experienced a seemingly unbridled, "meteoric" rise fueled by intense investor speculation and "new era" optimism. RCA's stock soared from $1.50 a share in 1921 to a peak of $114.75 in September 1929, an astronomical increase that made it the "it" stock of its era (but plummeted to a devastating low of about $2.625 by May 1932—a nearly 98% decline in value). Nvidia has achieved a similarly breathtaking trajectory in recent years, becoming one of the world's most valuable companies on the back of the AI boom.

Market Dominance and Regulatory Scrutiny: Both companies established near-monopolies early in their respective technological cycles. RCA achieved its dominance through a government-sanctioned patent pool that effectively required competitors to license its technology. This led to a significant antitrust suit by the U.S. government that eventually forced its independence. Nvidia currently commands an estimated 92% market share in the critical data center GPU market, an astonishing level of control that has led to recent antitrust investigations and scrutiny from regulators in various countries, including China.

Key Differences: The Business and Economic Context

Despite the compelling similarities, there are critical distinctions that challenge a one-to-one comparison.

Profitability and Fundamentals: This is a crucial difference. RCA in the 1920s was largely a speculative investment that paid no dividends, its price driven purely by growth expectations. Nvidia, by contrast, is a highly profitable company with massive actual revenues and earnings that are currently growing faster than almost any other company in history. The AI boom is generating tangible, immense profits for Nvidia today, whereas RCA's profits in the 1920s were relatively modest compared to its market capitalization.

Business Model: RCA was a sprawling conglomerate involved in everything from manufacturing radios and records to broadcasting (NBC) and government contracts. Nvidia is a focused semiconductor designer (fabless model) that built a full software ecosystem (CUDA) around its hardware, which is a major reason for its current moat and customer lock-in.

Monetary and Regulatory Environment: The 1920s featured lax financial regulations, massive use of margin debt (leveraged stock purchases) by retail investors, and a Federal Reserve that did not act as a lender of last resort when the crash hit. The current market has more investor protections (like FDIC insurance) and modern central banks are more equipped to intervene to prevent a total systemic collapse like the Great Depression.

In summary, while the psychological parallels of investor mania and technological awe are undeniably similar, Nvidia's current market position is built on a foundation of immense, real-world profits and a deep technological moat that RCA, in its early days, could not match. The fundamental difference between a speculative bubble stock and a highly profitable market leader is a point of vigorous debate among today's financial minds.

[weijian]

There is an old joke (or fact) on bubbles that goes like this: What is worse than been trapped in a bubble after it bursts? Been outside of it before it bursts.

The PwC survey on AI implementation is an interesting one: ~33% had net tangible benefits, slightly over half saw net zero benefits and the remainder saw net negative effects. Isn't it similar to the "bell curve distribution" that we generally observe for most events. But while inputs are "bell curve", outputs will probably resemble the "power curve" where cumulative benefits accrue to those at the top.

If everyone benefits (eg. cost savings), then no one eventually captures the accrued value. I always like to go back to Buffet's simple example if everyone stands up in the stadium for a good view of Shakira, no one will have a good view of Shakira. This is especially true if everyone is proficient and forward looking with growth mindset. However, the real business world still has a lot inefficient people and industries. Especially so for those old foggy industries, and if we do see competent Mgt managing businesses in some of these industries where your peers are not as flexible,  I suppose the opportunity is tremendous if we can find folks quietly tiptoeing to have a better view of Shakira while everyone else around them haven't notice!

Thoughts on Market Valuations, AI, Productivity and Shortages

Two years ago, I wrote a post about the rising capital intensity of big tech and the depreciation charges that would soon flow through income statements. This continues to be my valuation concern, as free cash flow lags net income significantly. Big tech stocks might look reasonably valued on a P/E basis but they are quite expensive on a P/FCF basis

That said, the big tech companies have incredible core businesses and I believe that if the returns come in lower than expected, eventually they will cut back on spending. This will lead to a digestion period that will feel like a mere stomach ache for the big tech stocks but could resemble a more serious bout of food poisoning for some of the AI infrastructure companies that are currently thriving on all of this spending (datacenters, chips, memory, hardware, and other service companies helping fuel this boom).

The other side of the productivity coin is efficiency, and I completely believe that efficiency gains will happen, but reducing expenses only goes so far and is somewhat of a one-time event. To justify the hundreds of billions of capex, I think there likely has to be major growth in sales volumes as well.

A recent PwC survey of over 4,000 CEOs suggests the majority of companies spending on AI have not seen any benefits yet. However, it very well might be too early to tell… but something to watch.

https://basehitinvesting.substack.com/p/...uations-ai