Hyster-Yale HY
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Relative Strength Index (RSI)
- The Relative Strength Index (RSI) is a momentum oscillator that measures the speed and change of price movements. It is typically used to identify overbought or oversold conditions in financial markets.
- The RSI is calculated using the following formula:
RSI = 100 - (100 / (1 + RS))
Where RS is the ratio of the average gains to the average losses over a specified period.
- The default time period used is 14 days.
- RSI values range between 0 and 100.
RSI values above 70 are considered overbought (indicating a potentially opportune time to sell)
RSI values below 30 are considered oversold (indicating a potentially opportune time to buy)
RSI is not a perfect indicator and should be used in conjunction with other technical analysis tools, this is for informational purposes only and is not a substitute for professional financial advice.
About
Hyster-Yale (HY) Business Model and Operations Summary
Hyster Yale Inc designs, engineers, manufactures, sells and services a comprehensive line of lift trucks, attachments, aftermarket parts and technology solutions marketed globally under the Hyster and Yale brand names. The Company has five segments, which include three in the lift truck business as discussed below, as well as Bolzoni S.p.A. (Bolzoni) and Nuvera Fuel Cells, LLC (Nuvera). Majority of revenue is from Lift Trucks. geographically operates in America, EMEA, JAPIC, maximum revenue from America.
Key Insights
Hyster-Yale (HY) Core Market Data and Business Metrics
Latest Closing Price
$40.83Market Cap
$723.54 MillionTotal Outstanding Shares
14.26 Million SharesTotal Employees
8,500IPO Date
September 28, 2012SIC Description
Industrial Trucks, Tractors, Trailors & StackersPrimary Exchange
New York Stock ExchangeHeadquarters
5875 Landerbrook Drive, Cleveland, OH, 44124
Earnings Reports
Expected vs. Actual Quarterly Earnings-Per-Share & Revenue
Short Volume
Daily short volume activity identifies short-term trading pressure and potential price volatility
Revenue Breakdown
Distribution of revenue across unique business segments & geographies
Historical Stock Splits
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