January 4, 2024 alon@alphaoverbeta.net

Magnificent Seven vs The Market Performance

Magnificent seven performance

The current bull market of the S&P 500 is being driven by subdued inflation figures in the U.S. and Europe, coupled with the widespread anticipation of upcoming declines in interest rates. However, the stock market’s dynamics have become increasingly top-heavy, making the term “bull market” less significant than in the past.
The influence of the so-called “Magnificent Seven” – Apple, Microsoft, Alphabet, Amazon.com, Nvidia, Tesla, and Meta Platforms – has become so pronounced that without their contributions, the S&P 500 would have only seen an 8% increase this year, as opposed to the actual 25%. Notably, these high-growth, technology-related companies, described by analysts as the “Magnificent Seven”, demonstrated resilience by registering slight gains, even as the broader equity market faced challenges.

The case for portfolio concentration.

Certain financial advisors promote diversified portfolios spread on the whole asset spectrum as the most reliable route to market outperformance.
The argument suggests that by diversifying a manager’s top-tier ideas, the portfolio’s returns are not diminished by suboptimal choices. However, the actual outcomes differ significantly.
The evidence indicates that escalating concentration in investments doesn’t enhance the likelihood of outperformance but diminishes it. Less diversified portfolios are less likely to include the fraction of stocks responsible for most of the market’s enduring returns. It’s often underestimated how a small percentage of standout performers disproportionately influences the overall market return. A study by J.P. Morgan Asset Management examining the Russell 3000 from 1980 to 2014 revealed that a mere 7% of components accounted for essentially all of the index’s overall returns, while 40% suffered substantial losses without recovery. The challenge of consistently identifying stocks with above-average returns is underscored by S&P Dow Jones Indices data, indicating that only 22% of S&P 500 stocks outperformed the index from 2000 to 2020.
Although concentration may increase the chances of achieving substantial outperformance, the risk of falling short of the target return escalates more rapidly than the probability of attaining it. For active managers to contribute value through economic predictions, their excess returns must surpass the benchmark, even after factoring in higher management fees. Research indicates that as the number of holdings increases, excess investment returns decrease, challenging the narrative of a “best ideas” portfolio favoring more concentrated stock picks.

So, let’s examine the performance of the “Magnificent Seven” stocks over the last 5 years period as a concentrated portfolio, we may backtest the performance using AlphaOverBeta’s API service to do this with minimal effort, in under 10 lines of code we may use the API to check this portfolio’s performance and compare to the market to see if it outperformed.

Here is the code:

# create the portfolio manager to manage the portfolio we backtest
m_7_portfolio = PortfolioManager(key='DEMO', secret='DEMO')

# create a portfolio and connect to it

# add symbols to the portfolio
m_7_portfolio.add_cost(symbol='AAPL', cost=10000)
m_7_portfolio.add_cost(symbol='MSFT', cost=10000)
m_7_portfolio.add_cost(symbol='GOOG', cost=10000)
m_7_portfolio.add_cost(symbol='AMZN', cost=10000)
m_7_portfolio.add_cost(symbol='NVDA', cost=10000)
m_7_portfolio.add_cost(symbol='META', cost=10000)
m_7_portfolio.add_cost(symbol='TSLA', cost=10000)

# run a backtest on the symbols added before with the requested period and the requested time interval
m7_df, status_code = m_7_portfolio.backtest(period='5y', interval='1d')

The first lines create the portfolio manager object connecting to the API service, then the “Magnificent seven” are added to the portfolio (equal share) and a backtest has been running for the past 5 years, that’s it!

The entire code for accessing the API and examples are here

The performance of the portfolio is :
Total Return – 263.52%
Sharpe – 0.98
CAGR – 29.47%
Max Drawdown – 51.30%

“Magnificent Seven” Performance

The incredible performance of this concentrated portfolio is achieved by investing in the 7 big stocks and letting it run for 5 years untouched, the volatility in such a portfolio is very high and so are the drawdowns which may be as high as 70% ! a number of events through the lifetime of this portfolio

For comparison, here is the market performance during the same time window investing ALL of the portfolio in the S&P500 using the SPY ETF.

S&P500 performance, past 5 years

Covid made a significant dent in performance losing the entire gains achieved a year before, theoretically kicking the investor out of the market for good (by the way, look at the M7 portfolio during that period, it was down but did not terminate the entire portfolio as the S&P did, food for thought…)

Here is the consolidated picture of both portfolio performances:

S&P500 vs M7 portfolio performance


Advocates for concentrated asset portfolios argue that they offer the potential for significant outperformance. By focusing on a select few “best ideas,” returns remain undiluted by weaker choices, potentially leading to higher margins of success. Proponents contend that empirical evidence demonstrates the efficacy of concentration, emphasizing the impact of a small percentage of standout performers on overall market returns. They posit that diversification may dilute exposure to these high-performing assets. Additionally, concentrated portfolios could enable active managers to make more accurate economic predictions, adding substantial value even after factoring in higher management fees.

When it comes to the M7 portfolio vs the entire S&P500, we could see that by leveraging the API we provide, it was not a complicated issue anymore to see the advantages and disadvantages of each thesis, AlphaOverBeta API service aims to reduce financial service complexity, which it does.

Trade Smart,