Portfolio

To ensure maximum transparency, we monitor the performance of the companies analyzed in the Stock Opinion section through a simulated portfolio on a professional trading platform.

Our methodology follows strict rules:

  • Equal Weight: Each stock is initially assigned the same dollar weight.
  • Rebalancing: The portfolio is updated with each new publication to promptly reflect our analyses.
  • Risk Management: We have set a maximum allocation cap of 20% per individual stock. In the initial phase or during periods of limited selection (fewer than five stocks), excess liquidity is invested in the S&P500.

This approach explains why, during the launch phase, the portfolio’s performance was closely correlated with the benchmark index; as additional analyses were progressively incorporated, the strategy began to demonstrate its distinctive value relative to the broader market.

Below is the chart showing the performance of our portfolio compared with the S&P 500 index.

2026-02-28T12:53:23.714089 image/svg+xml Matplotlib v3.10.3, https://matplotlib.org/

To provide an even clearer and more transparent picture of our investment performance, we present below the Portfolio Spread, i.e., the excess return generated by our portfolio relative to the S&P 500 benchmark. It visually represents the added value produced by our analyses over time.

2026-02-28T12:53:25.177071 image/svg+xml Matplotlib v3.10.3, https://matplotlib.org/

To prove true Alpha generation, we adjust the cumulative returns of our benchmark to match our portfolio’s Beta

2026-02-28T12:53:26.599556 image/svg+xml Matplotlib v3.10.3, https://matplotlib.org/

We then take the spread between our portfolio’s cumulative returns and the beta-adjusted benchmark, simulating a market neutral, beta 0 portfolio

2026-02-28T12:53:28.007371 image/svg+xml Matplotlib v3.10.3, https://matplotlib.org/

Lastly, we plot our daily beta-adjusted spread, showing the distribution of our daily spread compared to our beta-adjusted benchmark’s daily return

2026-02-28T12:53:29.532901 image/svg+xml Matplotlib v3.10.3, https://matplotlib.org/

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