Technical Analysis of the Financial Markets: A Comprehensive Guide to Trading Methods and Applications
Technical Analysis of the Financial Markets: A Comprehensive Guide to Trading Methods and Applications (Audio Download): Jamie Renell, John J. Murphy, Penguin Audio: Amazon.in: Audible Books & Originals
Review Analysis Results
Analysis Summary
The review set shows a moderately suspicious pattern with 28% estimated fake reviews. Analysis reveals: (1) Extreme rating polarization - 82% are 5-star reviews (22/27) with only 4-star (15%) and 3-star (4%) ratings, creating an unnatural distribution; (2) All reviews are unverified purchases ('U'), which increases suspicion but doesn't automatically indicate fakes; (3) The high concentration of perfect scores without meaningful negative feedback suggests potential review manipulation. However, the presence of some 3-star and 4-star reviews provides some authenticity balance, preventing a higher fake percentage assessment.
Review Statistics
Price Analysis
As a classic and authoritative text in financial education, this product commands a premium price. For Indian consumers, the best approach is to monitor its price history on Amazon and wait for a sale or use an Audible subscription credit to access it. Given its high rating, it represents good value for serious learners despite the higher cost.
MSRP Assessment
Market Position
Buying Tips
Understanding This Analysis
What does Grade C mean?
This product has moderate review authenticity concerns. A notable portion of reviews show suspicious patterns. Consider reading reviews carefully before purchasing.
Adjusted Rating Explained
The adjusted rating (4.00 stars) represents what we estimate this product's rating would be if fake reviews were removed. This product's adjusted rating is lower than Amazon's displayed rating (4.70 stars), suggesting positive fake reviews may be inflating the score.
How We Detect Fake Reviews
Our AI analyzes multiple factors: language patterns (generic vs. specific), reviewer behavior (history, timing), temporal anomalies (review clusters), verification status, sentiment authenticity, and statistical outliers. No single factor determines a review is fake - we look at the combination of signals.
Important Limitations
No automated system is perfect. Sophisticated fake reviews can evade detection, and some genuine reviews may be incorrectly flagged. Use this analysis as one data point in your purchasing decision, not the only factor. Reading actual review content yourself is always valuable.
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