W4: Lecture 9 Flashcards
"Rethinking nonfinancial metrics" (13 cards)
What are the different corporate finance models?
- Shareholder Model
*Shareholder value created
*Main stakeholders: shareholders
MAX VALUE= FV - Refined shareholder model
Shareholder value created
Main stakeholders: shareholders
MAX VALUE= FV+bSV+cEV
where: 0>b&c«1 - Stakeholder model
*Stakeholder value created
Main stakeholders: current stakeholders
MAX VALUE= FV+bSV
b=1 - Integrated Model
Integrated value created
Main stakeholders: current & future stakeholders
MAX VALUE= FV+bSV+cEV
where: b&c=1
What is Value Creation?
In financial terms, value creation is defined as an increase in the net present value (NPV) of a company’s projects.
Responsible companies manage for integrated value creation (profit and impact) rather than merely shareholder value (profit).
–>FV is often generated at the expense of SV & EV, since resources are spent and not many are left to invest in these “secondary” values.
Price vs.True Price
Price: The actual market price a consumer pays for a product.
True Price: The market price plus the hidden social and environmental costs (externalities) associated with making the product.
Example of Jeans:
If you count up the price of “dirty jeans” and + hidden social and environmental costs, the cost is higher than a clean alternative.
Why is it in a company’s interest to manage for integrated value?
*Ethical case basis- corporate responsibility (case for SV and EV)
+Also, less likely to lose the license to operate at some stage
*Business case basis- long-term value creation (case for FV)
Companies that also create EV and SV will be more creative and successful in creating better FV.
Relevance of Integrated Value for Companies
▶ Taking investment decisions
▶ Measuring and reporting performance
▶ Conducting risk management
▶ Developing incentives
▶ Taking structural decisions: capital structure, payouts, M&As, etc.
Moritz Wiedemann (RSM) B3T2104
Integration of nonfinancials (S and E) in DCF model
Social (S) and environmental (E) factors can be added to the DCF model by:
1. Expressing S and E issues in their own units Q
2. Determining the respective shadow price SP of each S and E issue
3. Multiplying Q and SP to get the value flows VF
4. Cash flows CF can be seen as value flows VF expressed in cash.
5. Integrated value IV can be determined by discounting the value flows VF using the DCF
model
Challenges for the integration of non-financials in a DCF
- Availability of company information on S&E
*Voluntary and mandatory disclosure
*Digital data- rethinking data
*How do we measure social and environmental value for a company? - Determining the correct shadow price
- Identifying the correct discount rate for environmental and social costs
Expected effect of S and E inclusion in DCF on a value flow
The cost of capital increases with social and environmental externalities (because of a risk premium) and decreases with positive social and environmental impact (because of reduced risk)
–>Carbon premium
Expected effect:
1. Short term
*Value flow: ???
*Cost of capital: lower
=
Value: ???
- Long term
*Value flow: higher
*Cost of capital: lower
=
Value: higher
–>So, companies with a positive impact are likely to produce long-term value.
–>The challenge lies in trade-offs across time and between types of value, which can interact in numerous ways
“Tragedy of Horizon”
Internalisation effect on value flows
Companies that create FV at the expense of SV or EV will be affected by lower FV when internalisation occurs.
–>Internalisation means that the burdens of externalities are increasingly shifted back from society to the companies (in the long term).
Digital data: effect on non-financial performance indicators
Many traditional non-financial performance indicators can be improved with digital data.
*Tracking customers via web:
▶ Customer retention: % of customers that return
▶ Churn rate: % of customers that do not return
▶ Conversion rate: % of prospects that become customers
▶ Customer lifetime value: an estimate of the lifetime revenue generated by a customer
▶ Bounce rate: % of website visitors that leave after viewing one page
*Measuring quality and support:
▶ Employee engagement
▶ Product defect rate
▶ On-time delivery
▶ Customer support tickets
▶ Customer support response time
▶ Contact volume by channel
*Get the feedback via surveys:
▶ Customer satisfaction
▶ Employee satisfaction
▶ Brand awareness/reputation
▶ Net promoter score: classifies customers as promoters, passives, or detractors
*Quantifying fuzzy concepts:
▶ Social media engagement
▶ Return on investment for marketing
▶ Lead generation: number of legitimate prospects created through marketing
Nonfinancial performance indicator: “Satellite images”
Satellite images can track real-world company activity, such as parking lot fill rates at retail stores, factory output, or shipping activity.
These images provide real-time, external, and unbiased data that correlate with operational performance.
For example, higher parking lot occupancy has been shown to predict stronger earnings announcements, making it a useful leading indicator of demand and sales performance.
–>
▶ Effects are almost twice as large for abnormal decreases vs. increases in parking lot fill rates.
▶ Evidence of more informed short selling, with individual investors being net buyers for underperforming retailers.
Nonfinancial performance indicator:
“Wisdom of crowds”
The wisdom of crowds refers to aggregating many individual predictions or opinions, such as customer reviews or investor sentiment on social media, to gain valuable insights.
In class, we discussed how aggregated predictions reduce individual noise and can predict stock returns or earnings surprises, as shown in studies using Amazon reviews or Twitter sentiment.
It reflects market perception, brand reputation, and consumer satisfaction.
–>
▶ Opinions predict both future earnings surprises and announcement returns.
▶ No difference in effect between original and disseminated tweets.
▶If there is a lack of information across individuals, then the more valuable information can be recovered by averaging individual predictions.
Customer reviews:
▶ Abnormal customer ratings are positively associated with future stock returns and earnings
surprises.
▶ Stronger for stocks with more limits to investor attention.
▶ Effect does not reverse in the long run.
Nonfinancial performance indicator:
“Web traffic”
Web traffic data (like Google Trends) measures online interest in a company or its products. It is a proxy for consumer attention and potential demand.
In Lecture 9, we saw that abnormal spikes in search traffic often precede revenue announcements, making it an early indicator of business performance.
High web traffic can also relate to brand visibility, marketing effectiveness, and customer engagement.
–>
▶ Stocks with abnormal search frequency have higher returns over the next two weeks, but completely reverse over the next year.
▶ Google searches for firm products significantly predict revenue announcements, but less so earnings.
▶ Significant cross-sectional variation in predictability.
