Stock returns are generally difficult to explain, as they are comprised of many discrete channels of risk. Empirical asset pricing models (EAPM), such as the Fama-French five-factor model (FF5), have been used to partition these channels across a series of systematic risk factors, such as company size (total market equity), value (book-to-market ratio), investment, and operating profitability. Prior EAPMs only accounted for how such factors contributed to risk at the market-level, ignoring any potential variation across sector. This study developed a sector-heterogenous model (SHM) which directly accounts for this variation by generalizing the Fama-French methodology to sector-subsets of stocks. The results demonstrated that risk is meaningfully heterogenous across sectors for each of the factors in the FF5, with different subgroups of factors being statistically significant within each sector. In a direct comparison of explanatory power, the SHM outperformed the FF5 and improved adjusted R2 by an average of 5% for stocks across all sectors. Several applications of sector-heterogeneity were then demonstrated for stock-picking purposes, including a high-beta portfolio strategy using the SHM-beta which outperformed the S&P 500 in backtesting. This study concludes that meaningful sector-heterogeneity exists in market risk. This information is materially useful to investors.