#Nvidia $NVDA, #Microsoft $MSFT, #Alphabet $GOOGL, #Amazon $AMZN, and #MetaPlatforms $META collectively represent a substantial 25% of the S&P 500's market capitalization. This significant concentration within the index exemplifies how its inherent composition increasingly skews its representation of the broader market. This phenomenon, though not unprecedented, necessitates prudent evaluation, while avoiding speculative conclusions.
Particularly noteworthy is the concentrated nature of Information Economies. Unlike the diversified Manufacturing Economies of yesteryears, which engaged a wider swath of the population, Information Economies exhibit a narrower participation rate despite lower barriers to entry.
In these Information Economies, content is king. The ongoing consolidation of economic power within a select few corporations, as evidenced by the aforementioned concentration, is no longer the growth engine it once was during the 1980-2010 period of burgeoning network infrastructure development.
It is my firm belief that numerous investment committees are cognizant of the inherent risk this concentration poses to their portfolios. The imperative to maintain parity with benchmark indexes compels them to concentrate their holdings, consequently impacting risk-adjusted returns and eroding established principles of return dispersion.
This is precisely why prudent portfolio managers, have historically diversified returns across a multitude of positions, rather than concentrating them in a handful of companies. Institutional investors have traditionally prioritized such diversification, seeking to avoid "stock jockeys" whose performance is contingent upon a limited number of stocks. Instead, they favored a distribution of returns across the entire portfolio, as it served as a reliable indicator of the manager's skill and investment strategies. Some institutions even declined investment opportunities due to returns perceived as "excessive."
High returns are intrinsically unsustainable; moderate returns are not. The compounding effect of moderate returns over time consistently outperforms sporadic instances of high returns. This is the rationale behind our reliance on proprietary algorithms to guide our trading decisions. Ascertaining the precise timing of market corrections is impossible, hence our utilization of algorithms.
For our Swing Trading we have maintained long positions since May 6, 2024, and prior to that, we initiated long positions on November 3, 2023. For our long-term investment strategies, our proprietary weekly chart analysis identifies optimal entry points for accumulating long positions in stocks. Our strategy eschews shorting the S&P 500, instead opting to await our algorithm's buy alerts to initiate long positions.
Source: Goldman Sachs
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