Dicker Data (Australia) Price Pattern Analysis
| DDR Stock | 9.31 0.10 1.09% |
Momentum
OversoldOverbought
54 · Impartial
Quarterly Earnings Growth 6.7% | EPS Estimate Current Year 0.54 | EPS Estimate Next Year 0.58 | Wall Street Target Price 11.14 | Quarterly Revenue Growth 10.9% |
How headlines align with Dicker Data's price movement reveals the strength of sentiment-driven trading. Relationships between news activity and market behavior are quantified.
Dicker Data Current Signal Summary
Dicker Data's momentum reading (RSI at 54) sits in neutral territory, while the expected daily return of -0.04% is slightly negative and hype elasticity is slightly positive. Daily volatility at 2.38% is moderate, suggesting a standard range of near-term outcomes. Low headline density (4 events/month) suggests limited media attention. Overall, signals for Dicker Data are mixed — momentum is positive but expected returns are negative, suggesting potential divergence.
Attention patterns around Dicker Data reveal how closely headline activity correlates with price direction. Volatility framing alongside headline metrics helps separate signal from noise.
Dicker Data Post-Event Predicted Price | A$ 9.33 |
Hype analysis sits alongside price forecasting, technical analysis, and analyst consensus for a fuller picture. Earnings data and momentum signals add quantitative depth to the sentiment picture.
Statistical evidence for mean reversion in Dicker Data's appears through its tendency to revert after extreme valuations. Under mean reversion theory, Dicker Data's price extremes are viewed as temporary dislocations that may self-correct.
Post-Sentiment Price Density Analysis
The probability distribution for Dicker Data's predicted price encodes the full spectrum of outcomes by estimated likelihood. Confidence intervals from Dicker Data's distribution widen as the forecast horizon extends, reflecting compounding uncertainty.
Next price density |
| Expected price to next headline |
Estimated Post-Sentiment Price Volatility
After analyzing Dicker Data's historical price reactions to major news, we derive upside and downside boundaries for Dicker Data. Dicker Data's post-sentiment downside and upside margins for the prediction period are 6.95 and 11.71, respectively. This analysis complements technical and fundamental research by adding a news dimension to Dicker Data's forecasting.
Current Value
Macroaxis estimates the after-hype price of Dicker Data across a 3 months horizon to evaluate where the instrument could settle once headline distortion subsides. The practical value is that it frames how far price could retrace or stabilize once the headline cycle loses intensity.
Price Outlook Analysis
Sudden rallies in Dicker Data without backing data often point to speculative buying or fund shifts. Sentiment often acts as momentum, and if good press slows, the Stock price loses steam. Telling apart data-backed price moves from momentum runs is vital for managing risk in Dicker Data. The interplay between sentiment-driven and data-driven forces in Dicker Data creates a complex risk environment.
| Expected Return | Period Volatility | Sentiment Sensitivity | Peer Sensitivity | News Density | Peer Density | Next Expected Sentiment |
0.04 | 2.38 | 0.02 | 0.50 | 4 Events | 1 Events | In 4 days |
| Latest Traded Price | Expected Post-Event Price | Potential Return on Next Event | Post-Sentiment Volatility | |
9.31 | 9.33 | 0.21 |
|
Market Sentiment Timeline
Dicker Data is currently traded for 9.31on Australian Securities Exchange of Australia. Dicker Data has a historical sentiment sensitivity of 0.02. Peers average a sentiment sensitivity of -0.5. is anticipated to increase in value after the next headline, with the post-event price near 9.33 or above. The average volatility of media hype impact on DDR the price is over 100%. The price appreciation on the next news is anticipated to be 0.21%, whereas the daily expected return is currently at -0.04%. The volatility of peer sentiment impact on Dicker Data is about 19.07%, with the expected peer-implied price after the next announcement near 8.81. DDR reported revenue of A$ 2.56 billion. Net Income was A$ 85.59 million with profit before overhead, payroll, taxes, and interest of A$ 354.25 million. Over the selected 90-day horizon, the next anticipated press release will be in 4 days. Dicker Data Basic Forecasting Models provides a cross-check on projections for Dicker Data.Related Market Sentiment Analysis
The comparative sentiment analysis table for Dicker Data provides risk metrics for Dicker Data's direct competitors. Value-at-risk and maximum drawdown for Dicker Data's competitors provide context for assessing Dicker Data's relative risk.
| SentimentElasticity | NewsDensity | SemiDeviation | InformationRatio | PotentialUpside | ValueAt Risk | MaximumDrawdown | |||
| ATM | Aneka Tambang TBK | 0.00 | 0 per month | 0.00 | -0.18 | 0.00 | -1.00 | 4.06 | |
| RIO | RIO Tinto | 0.01 | 6 per month | 1.88 | 0.1 | 3.51 | -3.27 | 8.20 | |
| ANZ | ANZ Group Holdings | 0.08 | 5 per month | 0.00 | -0.04 | 1.91 | -2.53 | 12.17 | |
| AN3PJ | Australia and New | 0.00 | 0 per month | 0.00 | -0.19 | 0.32 | -0.65 | 1.35 | |
| AN3PI | Australia and New | -99.90 | 8 per month | 0.00 | -0.13 | 0.39 | -0.45 | 1.39 | |
| CBAPM | Commonwealth Bank of | 0.00 | 0 per month | 0.19 | 0.04 | 0.53 | -0.70 | 1.92 | |
| CBA | Commonwealth Bank of | 0.00 | 0 per month | 1.05 | 0.12 | 2.50 | -1.80 | 9.65 | |
| BHP | BHP Group | -0.02 | 7 per month | 1.83 | 0.10 | 3.30 | -3.47 | 9.85 |
Dicker Data Additional Predictive Modules
Price prediction tools for Dicker Data synthesize indicator signals with time-series patterns to model directional expectations. Time-series models tend to perform better when fed clean, stationary data with consistent periodicity.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Sentiment Indicators & Methodology
Sentiment analysis for Dicker Data evaluates news tone, positioning, and narrative momentum. Information shocks can change volatility expectations abruptly. Dicker Data has a market cap of 1.66 billion, ROE of 33.78%.
Dicker Data inputs come from periodic company reporting and market reference feeds and are mapped into a consistent reporting framework.
Editorial review and methodology oversight provided by: Raphi Shpitalnik, Junior Member of Macroaxis Editorial Board
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