Factor Report

Data as of market close on 8/5/2022.

Validea's factor report analyzes any stock using the major investing factors, including value, quality, momentum, and low volatility.
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KIMBELL ROYALTY PARTNERS LP (KRP)

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Latest Close: $17.54 Market Cap ($ mil): $1,150 Sector: Energy Industry: Oil & Gas - Integrated 52 Week High: $20.08 52 Week Low: $10.00 Relative Strength: 96 Twelve Minus One Return: 40.9% Standard Deviation: 59.0%
PE Ratio: 43.3 Price/Sales: 7.8 Price/Book: 2.5 Price/Cash Flow: 14.3 EV/EBITDA: 14.40 Yield: 10.03% Shareholder Yield: -19.97% F Score: 5 G Score: 4
Return on Equity: 8.6% Return on Assets: 7.2% Return on Tangible Capital: 7.0% Return on Invested Capital: 8.5% WACC: 8.9% Debt/Equity: 0.49 LT EPS Growth: N/A LT Sales Growth: 58.6% Beta: 1.57
Kimbell Royalty Partners, LP owns and acquires mineral and royalty interests in oil and natural gas properties throughout the United States. The Company owned mineral and royalty interests in approximately 11.4 million gross acres and overriding royalty interests in approximately 4.7 million gross acres. The mineral and royalty interests in over 16 million gross acres are located in 28 states in every onshore basin across the continental United States and include ownership of approximately 122,000 gross wells, including over 46,000 wells in the Permian Basin. The Company's properties include the Permian Basin, Mid-Continent, Terryville/Cotton Valley/Haynesville, Appalachian Basin, Eagle Ford, Bakken/Williston Basin, and DJ Basin/Rockies/Niobrara.

Factor Profile

KRP's exposure to the major factors (100 is highest).

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Optimal portfolios presented on Validea.com represent the rebalancing period that has led to the best historical performance for each of our equity models. Each optimal portfolio was determined after the fact with performance information that was not available at portfolio inception. As a result, an investor could not have invested in the optimal portfolio since its inception. Optimal portfolios are presented to allow investors to quickly determine the portfolio size and rebalancing period that has performed best for each of our models in our historical testing.

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