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Modified Ohlson Model: Firm Valuation with Python

Learn how to use the Modified Ohlson Model and Python to calculate the intrinsic value of firms using accounting data from the ASX.

#ohlson-model#firm-valuation#python-finance#asx#accounting-analysis#intrinsic-value#pandas
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Modified Ohlson Model: Firm Value Analysis with Python

An Accounting-Based Valuation Approach Applied to Australian Listed Firms

10-Minute Presentation | April 2026
Made byBobr AI

Introduction

Why Accounting Beats Stock Prices

Stock prices are driven by sentiment, news cycles, and speculation — not real performance

Accounting figures (profits, book value) reflect true economic activity

The Modified Ohlson Model uses financial statement data to estimate intrinsic firm value

📖
Intrinsic Value — The actual worth of a company based on fundamental financial data, independent of market price fluctuations.
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Project Scope & Accounting Problems

Project Scope

Evaluate true firm worth using accounting metrics

Test if shares are overvalued or undervalued

Focus: Net profit, book value of equity

Test cases: Australian ASX-listed firms

Apply Modified Ohlson Model → compare to market price

Key Accounting Challenges

1

Earnings manipulation distorts book values

2

Different reporting standards create inconsistencies

3

One-time items skew profit figures

4

Intangible assets often excluded from book value

Definition

Book Value of Equity — The net asset value of a company recorded on its balance sheet: Total Assets minus Total Liabilities.

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Data Sources & Strategy

Company Annual Reports

Audited financial data, earnings, equity figures

ASX Filings

Official exchange disclosures, price data, dividend history

Yahoo Finance

Real-time price benchmarks, historical stock data

Key Variables Collected

Variable
Description
Book Value of Equity (BVE)
Recorded net assets per share
Net Profit After Tax (NPAT)
Reported earnings
Dividends Paid
Shareholder payouts
Stock Price
Market benchmark for comparison

Firm Selection Criteria

✔
Financial data consistency over 3+ years
✔
Australian-listed (ASX) companies
✔
Available in public databases
📖

Net Profit After Tax (NPAT)

A company's earnings remaining after all expenses, interest, and taxes have been deducted.

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Data Preparation & Processing Steps

1

Data Collection

Pull from ASX, annual reports, Yahoo Finance

2

Raw Data Ingestion

Load CSV/Excel files into Python

3

Missing Value Treatment

Impute or drop NaN entries

4

Error Detection & Cleaning

Remove outliers, fix format errors

5

Standardisation

Align currencies, date formats, units

6

Load into Pandas

Final clean dataset ready for modelling

data_processing.py
import pandas as pd df = pd.read_csv('asx_firms.csv') df.dropna(inplace=True) df['date'] = pd.to_datetime(df['date'])
📖

Data Cleaning

The process of identifying and correcting errors, inconsistencies, and missing values in raw datasets before analysis.

Methodology Workflow
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The Adjusted Ohlson Framework

V = BVE + ∑ (
Residual Incomet
(1+r)t
)
Where:
•
V = Estimated Firm Value
•
BVE = Book Value of Equity
•
Residual Income = Net Income − (r × BVE)
•
r = Cost of Equity (required rate of return)
•
t = Time period
Firm value = what's on the books + future residual earnings
Residual Income = earnings above what investors expect (cost of equity)
Balance sheet anchors the estimate — speculative guesses excluded
Modified by Wang (2023) to improve
forecast accuracy for contemporary markets
📖
Residual Income — Earnings generated above the minimum required return on equity.
If RI > 0, the firm creates value beyond investor expectations.
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Preliminary Python Implementation

val_model.py
import pandas as pd

# Load cleaned data
df = pd.read_csv('asx_data.csv')

# Cost of equity
r = 0.08

# Calculate Residual Income
df['RI'] = df['net_income'] - (r * df['book_equity'])

# Estimate Firm Value
df['firm_value'] = df['book_equity'] + df['RI'] / r

print(df[['company', 'firm_value']].head())
Pandas
Fast tabular data operations
Residual Income Calc
Automated across all firms
Firm Value Estimate
Derived from equity + RI
Speed & Accuracy
Reduces manual errors
📖
Cost of Equity (r) — The return rate required by investors to compensate for the risk of holding a company's shares, often estimated using CAPM.
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Meeting Project Goals

Target Icon

Accounting-Based Valuation

Apply the Modified Ohlson Model using real financial statement data rather than speculative market prices.

Python Icon

Python-Powered Computation

Use Python (Pandas) to automate calculations, reduce errors, and process multiple firms efficiently.

Chart Icon

Evidence-Based Insights

Compare model-estimated values against real ASX market prices to identify mispricing opportunities.

  • ✅ Accounting focus — ACHIEVED
  • ✅ Python integration — ACHIEVED
  • ✅ Real corporate data — ACHIEVED
  • 🔄 Comparative analysis — IN PROGRESS
📖

Mispricing — When a stock's market price significantly diverges from its intrinsic (fundamental) value, creating potential buy or sell signals for investors.

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Preliminary Findings & Conclusion

Preliminary Findings

📈 Firms with higher residual income → larger estimated firm value
⚖️ Gaps found between modelled values and actual stock prices
🔍 Accounting metrics reveal insights invisible in raw market data
⚠️ Broader datasets and refined formulas needed for stronger conclusions
ASX: CBA
ASX: BHP
ASX: CSL
ASX: WBC
Model Value
Market Price

Conclusion

✅ Python + Modified Ohlson Model = practical valuation toolkit
✅ Financial figures provide solid intrinsic value estimates
✅ Preliminary results show promise
🔜 Next steps: broader data collection, formula refinement, deeper statistical testing
📖 Overvaluation — When a stock's market price exceeds its intrinsic value. Undervaluation — When market price is below intrinsic value. Both revealed through accounting models.
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References & Key Definitions

References

1.

Wang, P. (2023). "A Modified Ohlson (1995) Model and Its Applications." European Accounting Review, 32(3), 663–691.

2.

Buren, B., Batbayar, A., & Lkhagvasuren, K. (2024). "The Determination of the 'Other Information' Variable in the Ohlson 1995 Valuation Model." Journal of Accounting Theory and Practice, 8(1).

3.

Navas-Alcívar, S. et al. (2024). "Econometric Modeling of Intangible Assets Using an Adaptive Ohlson Model." Springer Nature Switzerland.

Key Definitions Recap

📖
Intrinsic Value — True company worth from fundamentals
📖
Book Value of Equity — Net assets on balance sheet
📖
Residual Income — Earnings above required return
📖
NPAT — Net Profit After Tax
📖
Cost of Equity (r) — Investor required rate of return
📖
Mispricing — Gap between market price & intrinsic value
Thank you | Questions Welcome
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Modified Ohlson Model: Firm Valuation with Python

Learn how to use the Modified Ohlson Model and Python to calculate the intrinsic value of firms using accounting data from the ASX.

Modified Ohlson Model: Firm Value Analysis with Python

An Accounting-Based Valuation Approach Applied to Australian Listed Firms

10-Minute Presentation | April 2026

Introduction

Why Accounting Beats Stock Prices

Stock prices are driven by sentiment, news cycles, and speculation — not real performance

Accounting figures (profits, book value) reflect true economic activity

The Modified Ohlson Model uses financial statement data to estimate intrinsic firm value

Intrinsic Value

The actual worth of a company based on fundamental financial data, independent of market price fluctuations.

Project Scope & Accounting Problems

Project Scope

Evaluate true firm worth using accounting metrics

Test if shares are overvalued or undervalued

Focus: Net profit, book value of equity

Test cases: Australian ASX-listed firms

Apply Modified Ohlson Model → compare to market price

Key Accounting Challenges

Earnings manipulation distorts book values

Different reporting standards create inconsistencies

One-time items skew profit figures

Intangible assets often excluded from book value

Book Value of Equity

The net asset value of a company recorded on its balance sheet: Total Assets minus Total Liabilities.

Data Sources & Strategy

Company Annual Reports

Audited financial data, earnings, equity figures

ASX Filings

Official exchange disclosures, price data, dividend history

Yahoo Finance

Real-time price benchmarks, historical stock data

Data Preparation & Processing Steps

Data Collection

Pull from ASX, annual reports, Yahoo Finance

Raw Data Ingestion

Load CSV/Excel files into Python

Missing Value Treatment

Impute or drop NaN entries

Error Detection & Cleaning

Remove outliers, fix format errors

Standardisation

Align currencies, date formats, units

Load into Pandas

Final clean dataset ready for modelling

Data Cleaning

The process of identifying and correcting errors, inconsistencies, and missing values in raw datasets before analysis.

Methodology Workflow

Preliminary Python Implementation

Pandas

Fast tabular data operations

Residual Income Calc

Automated across all firms

Firm Value Estimate

Derived from equity + RI

Speed & Accuracy

Reduces manual errors

Meeting Project Goals

Accounting-Based Valuation

Apply the Modified Ohlson Model using real financial statement data rather than speculative market prices.

Python-Powered Computation

Use Python (Pandas) to automate calculations, reduce errors, and process multiple firms efficiently.

Evidence-Based Insights

Compare model-estimated values against real ASX market prices to identify mispricing opportunities.

<strong style="color: #FFFFFF;">Accounting focus</strong> — ACHIEVED

<strong style="color: #FFFFFF;">Python integration</strong> — ACHIEVED

<strong style="color: #FFFFFF;">Real corporate data</strong> — ACHIEVED

<strong style="color: #A0ABC0;">Comparative analysis</strong> — IN PROGRESS

<strong style="color: #FFFFFF; font-style: normal;">Mispricing</strong> — When a stock's market price significantly diverges from its intrinsic (fundamental) value, creating potential buy or sell signals for investors.

Preliminary Findings & Conclusion

Preliminary Findings

Conclusion

📈 Firms with higher residual income → larger estimated firm value

⚖️ Gaps found between modelled values and actual stock prices

🔍 Accounting metrics reveal insights invisible in raw market data

⚠️ Broader datasets and refined formulas needed for stronger conclusions

✅ Python + Modified Ohlson Model = practical valuation toolkit

✅ Financial figures provide solid intrinsic value estimates

✅ Preliminary results show promise

🔜 Next steps: broader data collection, formula refinement, deeper statistical testing

📖 <strong style="color: #FFFFFF; font-weight: 600;">Overvaluation</strong> — When a stock's market price exceeds its intrinsic value. <strong style="color: #FFFFFF; font-weight: 600;">Undervaluation</strong> — When market price is below intrinsic value. Both revealed through accounting models.

References & Key Definitions

References

Wang, P. (2023). "A Modified Ohlson (1995) Model and Its Applications." European Accounting Review, 32(3), 663–691.

Buren, B., Batbayar, A., & Lkhagvasuren, K. (2024). "The Determination of the 'Other Information' Variable in the Ohlson 1995 Valuation Model." Journal of Accounting Theory and Practice, 8(1).

Navas-Alcívar, S. et al. (2024). "Econometric Modeling of Intangible Assets Using an Adaptive Ohlson Model." Springer Nature Switzerland.

Key Definitions Recap

Intrinsic Value

True company worth from fundamentals

Book Value of Equity

Net assets on balance sheet

Residual Income

Earnings above required return

NPAT

Net Profit After Tax

Cost of Equity (r)

Investor required rate of return

Mispricing

Gap between market price & intrinsic value

Thank you | Questions Welcome

  • ohlson-model
  • firm-valuation
  • python-finance
  • asx
  • accounting-analysis
  • intrinsic-value
  • pandas