$130.190
-3.059 (-2.35%)At close
Price Predictions
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JXN Prediction & Forecast by Similar Chart Analysis
Alphio's JXN stock price prediction model matches the current Jackson Financial Inc tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $130.03 (-0.12%). The 1-week path is $127.96 (-1.71%). Longer windows use the same pattern set plus seasonality; the 1-month and multi-year forecasts sit behind unlock because they include precise min / avg / max bands.
Should I Buy Jackson Financial Inc Stock?
Jackson Financial Inc is currently a hold. The stock is priced at $130.19, which is below the average analyst price target of $143.67 (average of $151 and $136). However, the RSI is at 46.262, indicating it is nearing oversold territory, but not yet a strong buy signal. The company has shown a year-to-date change of +21.15% and a one-year change of +30.37%, indicating strong long-term performance. The main risk is the high P/E ratio of 62.27, suggesting potential overvaluation compared to industry peers, which could lead to price corrections if earnings do not meet expectations.
JXN stock price ended at $130.19 on Friday, after losing -2.35%
Jackson Financial Inc (JXN) last closed at $130.19, losing -2.35%. These facts feed the 1-day and 1-week JXN price prediction above.
Forecast Drivers
Jackson Financial Inc (JXN) forecast drivers combine similar chart patterns, seasonality, and moving averages.
Similar patterns
Bullish
Seasonality
Bullish
SMA 20
Bearish
SMA 200
Bullish
Similar Chart Patterns
Stocks whose recent price path most closely matches JXN, ranked by similarity.
Seasonality analysis for JXN
Historically the probability of a positive October return for JXN is 100.00%. September offers the highest probability of a positive month at 100.00%, while March is the weakest seasonal window. Alphio blends this calendar with technical signals and similar chart pattern matching before it writes the forecast.
This page is for research only and is not investment advice. Models can be wrong. Past performance does not guarantee future results.