ATT Stock Forecast - Accumulation Distribution

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T -- USA Stock  


Investors can use this prediction interface to forecast ATT historic stock prices and determine the direction of ATT future trends based on various well-known forecasting models. However looking at historical price movement exclusively is usually misleading. Macroaxis recommends to always use this module together with analysis of ATT historical fundamentals such as revenue growth or operating cash flow patterns. Although naive historical forecasting may sometimes provide an important future outlook for the firm we recommend to always cross-verify it against solid analysis of ATT systematic risks associated with finding meaningful patterns of ATT fundamentals over time. Additionally take a look at Historical Fundamental Analysis of ATT to cross-verify your projections.
On December 23, 2019 ATT had Accumulation Distribution of 275425.863302. The accumulation distribution (A/D) indicator shows the degree to which ATT is accumulated by the market over a given period. It uses the quote sensitivity to the highest or lowest daily price of ATT to determine if accumulation or reduction is taking place in the market. This value is adjusted by ATT trading volume to give more weight to distributions with higher volume over lower volume.
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ATT Trading Date Momentum

On December 24 2019 ATT was traded for  38.96  at the closing time. The highest price during the trading period was 39.12  and the lowest recorded bid was listed for  38.90 . The volume for the day was 8.7 M. This history from December 24, 2019 contributed to the next trading day price decline. The trading price change to the next closing price was 0.28% . The overall trading delta to the current price is 0.51% .
Accumulation distribution indicator can signal that a trend is either nearing completion, at a continuation, or is about to break-outs. The actual value of this indicator is of no significance. What is significant is the change in value of over time. The formula for A/D of a given trading day can be expressed as follow: ((Close - Low) - (High - Close)) / (High - Low) X Volume
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