Shares of Amazon (NasdaqGS: AMZN) are up 25.5% this year. Apple (NasdaqGS: AAPL), the world’s largest company by market value, is higher by 15.6%.

This tidbits should bold well for traditional Nasdaq exchange traded funds, such as the PowerShares QQQ (NasdaqGM: QQQ), the Nasdaq-100 tracking ETF. Conversely, knowing that Apple and Amazon have been surging this year, it would be reasonable to expect that QQQ’s equal-weight counterparts are lagging the cap-weighted fund.

That is not the case as the Direxion NASDAQ-100 Equal Weighted Index Shares (NYSEArca: QQQE) has performed mostly in line with QQQ this year as both funds have posted gains of roughly 4.2%. As its name suggests, QQQE’s underlying holdings make up more or less 1% of the overall portfolio. [A Preference for Nasdaq ETFs]

As a result of the equal-weight methodology, QQQE is significantly less dependent on large- and mega-caps like Apple, Amazon and Microsoft (NasdaqGS: MSFT) as a driver of its returns. Those stocks combine for about 3% of QQQE’s weight, but combine for nearly a quarter of QQQ’s weight. Due to the equally weighted methodology, QQQE , with a greater focus on smaller and more nimble companies, could outperform mega-cap stocks during bull markets. [Equal-Weight Works for Nasdaq ETFs]

Additionally, the equal-weight indexing method helps emphasis more undervalued stocks, since market-cap-weighted methodologies typically overweight larger components that have been outperforming. In contrast, the equal-weighting methodology would rebalance on a regular basis, selling recent winners and buying recent losers to maintain its equal tilt.

The equal-weight methodology also means significant differences at the sector level. At the end of the first quarter, the Nasdaq-100 allocated 56.15% of its weight to tech stocks compared to 40.6% for the equivalent equal-weight index. Although it is lighter on discretionary behemoth Amazon than QQQ, QQQE’s consumer discretionary weight was more than 800 basis points larger than QQQ’s at the end of March, according to Direxion data.