BIOX vs IPI

Bioceres Crop Solutions Corp. vs Intrepid Potash, Inc — Valuation Comparison 2026

BIOX

Agricultural Inputs
Bioceres Crop Solutions Corp.
Quality
6.2
out of 10
Value Trap
33
LOW
Price
$0.42
Last close
Models
5/13
Active
VS

IPI

Agricultural Inputs
Intrepid Potash, Inc
Quality
7.1
out of 10
Value Trap
6
SAFE
Price
$39.43
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType BIOX Fair ValueBIOX Upside IPI Fair ValueIPI Upside
Bayesian DCF Intrinsic $2.40 +464.2% $34.34 -12.9%
Earnings Power Value Intrinsic $10.40 -73.6%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $0.01 -97.7%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $•••.•• ••.•% $•••.•• ••.•%
PWERM Option-Based $•••.•• ••.•% $•••.•• ••.•%
Regime Cross-Sectional Relative $•••.•• ••.•% $•••.•• ••.•%
Sentiment SOTP Hybrid $•••.•• ••.•% $•••.•• ••.•%
CUCE Ensemble Ensemble $•••.•• ••.•% $•••.•• ••.•%
FTNN Topology Relative $•••.•• ••.•% $•••.•• ••.•%
RCMH-DCF Intrinsic $•••.•• ••.•% $•••.•• ••.•%
🔒

Unlock Full 13-Model Comparison

Access all valuation models for BIOX vs IPI — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

BIOX vs IPI — Which Stock Is More Undervalued?

IPI scores higher with a 7.1/10 quality rating vs BIOX's 6.2/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Bioceres Crop Solutions Corp. (BIOX) and Intrepid Potash, Inc (IPI) across 13 institutional-grade valuation models reveals how each company's intrinsic value stacks up against its market price. CirclFi's engine processes SEC EDGAR 10-K and 10-Q filings, FRED macroeconomic data, and GDELT news sentiment to generate independent fair value estimates daily.

BIOX currently trades at $0.42 with a QOC of 6.2/10, while IPI trades at $39.43 with a QOC of 7.1/10.

Both companies are analyzed with models spanning intrinsic (Bayesian DCF, EPV), scenario-based (First Chicago), regime-switching (Markov DDM, RCMH-DCF), machine learning (ML-RIV, FTNN Topology), and ensemble methods (CUCE).