Looking at the macro market picture, Panayotis “Takis” Sparaggis, chief investment officer for the multi-billion dollar New York based hedge fund, Alkeon Capital Management, sees that “major segments of the market are significantly overvalued.” But within this general high valuation, there are idiosyncratic points of strong valuation, the fund manager wrote to investors in a 31 page third-quarter letter to investors reviewed by ValueWalk.
Alkeon Capital Management: "One of the best stock-picking environments since the 2000 technology bubble"
It might be difficult to peg the headline coming out of Alkeon. Is it the raw performance numbers, with the Long / Short hedge fund up 26.23% year to date? Or is it the fact that Sparaggis thinks that value can be found in what is generally considered a highly overvalued market?
“We believe this is shaping to become one of the best stock-picking environments since the 2000 technology bubble,” Sparaggis opined in the Alkeon Growth Partners letter to investors, with the returns to prove up. Up 7.64% in the third quarter alone, the sectors in which he currently sees value have already enjoyed strong performance.
Alkeon Capital Management likes high-quality growth sectors and in particular, sees technology and healthcare “to be undervalued and attractive relative to the market.” The Technology Select Sector SPDR ETF, for instance, is up 32.36% year to date while the Vanguard Health Care ETF is up 21.52%.
Alkeon Capital Management considers it “quite remarkable” that these already highly valued sectors have so much more value left in them, but that’s the case. “Even more astounding when one considers the strong secular growth outlook for the technology sector, which is dramatically improving in our view and is reflective of the potential for a largescale, broadly impactful wave of technological innovation, similar to the internet wave of the 1990s,” he writes, sounding a familiar cord among tech investors.
Alkeon Capital Management - Technology trends are just beginning to play themselves out, he says
At a macro level, the US labor force is shrinking and technology spending is spiking. Both trends are likely to find continuation patterns.
With tech spending currently clocking in near 3.5% of GDP, that number is set to increase by near 64% to grow to 5.5%, creating a long-term uptrend of value.
“Remarkably, technology is trading at a discount to the market at a time when the long-term secular growth outlook for the sector is dramatically improving,” he wrote, pointing to a compelling risk/reward opportunity ahead similar to the internet wave of the 1990s. “But unlike this last innovation wave, technology stocks now are highly profitable and among the cheapest in the S&P 500 Index.”
Among the developments Alkeon Capital Management is watching are high data usage applications growing exponentially, specifically with the connected automobile, which gobbles up nearly 25 gigabytes per hour.
But it is not just processing power that benefits stocks such as Nvidia that get Alkeon Capital Management excited. The interconnected nature of the future will bring about the fourth wave of development for society.
“This confluence of expanded connectivity, the IoT and advances in AI presents a future where robots, drones, cellphones, cars and millions of devices are all connected – a potentially massive opportunity for the technology sector,” he wrote.
In certain sectors, while stunning progress has already been made, there is more work to be done:
To contemplate how early we find ourselves in this wave of technological innovation, it is instructive to review the recent progress that has been made in AI. For example, only in the last two years did machines begin to recognize images and words better than people. Yet, the theory behind parallel processing and computation, which is the foundation of machine learning, had been fully developed and taught in graduate schools for decades. During that time it was well-known that there is little algorithmic differentiation in AI, i.e., the value in AI is not in the algorithm. Instead, and what had been the hurdle for AI until recently, was the inability to cost-effectively deploy the tremendous amounts of processing power necessary to solve complex problems using relatively simple algorithms. In other words, AI needed a tremendous amount of silicon optimized for machine learning. Enter the era of massive parallel processing Graphic Processing Units (GPUs), which have now emerged as the dominant computing platform for AI and machine learning. As AI applications demanded massive amount of computational power, high-performance GPUs emerged as the de-facto tool to meet such demand and solve major AI problems.
And this extends to more than just cars, drones and robots. The ability of a computer to see and process images is, likewise, changing society and providing a plateau from which investment opportunity will not fall down, but grow more.