Compare Price to Sales Ratio Across Equities

You can use any or all of fundamental ratio historical patterns as a complementary method for asset selection as well as a tool for deciding entry and exit points. Many technical investors use fundamentals to limit their universe of possible positions. Check out your portfolio center.
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Cross Equities Price to Sales Ratio Analysis

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2010201120122013201420152016201720182019202020212022
JPM1.3341.3341.7262.2722.4762.6413.2693.7713.0483.8813.2653.9333.7332
CAT0.9720.9720.8881.0531.0240.8591.4062.0511.3731.5422.3722.2061.9874
CVX0.8350.8350.8751.051.01.2231.9411.6781.251.5551.6651.3921.4905
MSFT3.4843.4843.7163.9853.8584.4495.5296.888.16810.82912.1639.718.9421
AA0.5510.5510.5510.5510.5510.5510.5510.8550.370.3830.4620.9170.8247
DD0.5510.5510.6660.9230.9181.1931.3179.645.4463.1043.6482.6332.9647
WMT1.3010.4750.5040.5130.5650.4410.4410.4410.4410.4410.4410.510.6368
T2.8681.4141.5031.4391.3151.4421.5951.5951.5951.5951.5951.831.9842
KO3.4343.4343.43.9094.0274.2214.2755.4135.8796.3517.1346.616.3579

JP Morgan Chase, Caterpillar, Chevron Corp, Microsoft Corp, Alcoa Corp, Dupont Denemours, Walmart, ATT Inc, and Coca-Cola Price to Sales Ratio description

Price to Sales Ratio is figured by comparing entities stock price to its revenues. An advantage to using Price to Sales ratio is that it is based on companies sales, a figure that is much harder to manipulate than other organizations multiples. Because sales tend to be more stable P/S ratio can be a good tool for screening cyclical companies fluctuating earnings patterns. An alternative calculation method to [PS]; that measures the ratio between a company's [Price] and it's [SPS].

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Check out your portfolio center. Note that this page's information should be used as a complementary analysis to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try Watchlist Optimization module to optimize watchlists to build efficient portfolio or rebalance existing positions based on mean-variance optimization algorithm.

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