Category Archives: Management Science

Using hypothesis testing in important marketing and e-commerce decisions

This time, the focus is on e-commerce and digital marketing.

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Hypothesis testing is underutilized in many sectors although it is cheap, effective, and quick.

From manufacturing and medicine to marketing and e-commerce, its applications are abundant.

Quick experiment follows ⬇️

You are contemplating adding a new feature to your e-commerce website.

You are wondering whether this new feature will lift your sales.

You can randomly channel your customers to both sites, i.e. one without the feature and the other with the feature.

You will launch the new feature provided that you are 95% confident that website with the feature will yield more sales than that without the feature.

How would you design this experiment so that you can make a decision based on it?

What do you need to measure? Which metrics?

In this article, I show how you design this experiment and solve this problem cost- and time-efficiently.

Solution to Management Science Series #177: How to estimate beta in mergers and acquisitions: Real-world example 🧮 Nvidia and Texas Instruments

How to estimate beta in mergers and acquisitions: Real-world example 🧮

NVIDIA’s top executives are looking for potential targets that could provide economies of scale and scope.

They consider Texas Instruments a top candidate.

Estimate the post-merger beta of NVIDIA for the following two scenarios!

Scenario A: Assume that NVIDIA will pay in equity for this acquisition. Assume that the acquisition will take place on the 31st of December, 2023.

Scenario B: Assume that NVIDIA will issue bonds worth $12B and fund the rest with equity. Assume that the acquisition will take place on the 31st of December, 2023.

Note: Solution of this question, as well as those of all the questions asked so far, is shared on my website.

Solution to Management Science Series #176: Estimating the optimal WACC 🧮

You have calculated the unlevered beta of Adobe as 0.79. Adobe’s cost of debt is estimated to be 3% as of August 2024.

For the risk-free rate, use the current yield on 10-year US Treasuries (20th of August, 2024). Equity risk premium will be 6.5%.

Corporate tax rate for Adobe is 21%. You want to investigate how the WACC of Adobe will change in changing capital structures.

Assume that the cost of debt for Adobe increases with the amount of debt in the capital structure, by 2.75% at each 15% incremental increase in the debt-to-asset ratio.

Investigate how the cost of equity and WACC will change with changing debt-to-assets ratios, i.e. start from 0% and incrementally increase it by 15% and stop when the ratio hits 90%.

Plot the cost of equity, cost of debt, and WACC at changing debt to asset ratios!

Calculate the optimal value of WACC!

Associating Traffic (and all other similar metrics) with Monetization

Many people mistake traffic, you can also add likes and followers in the same basket, as monetization.

For a pure-play e-commerce company, more traffic may not mean more revenues as the conversion rate for a pure-player is at low single digits; however, a decreasing one will almost always result in decreasing revenues.
For omni-channel operations, the relationship is more convoluted.

Solution to Management Science Series #175: Accounting for PP&E: Investigating Apple 🧮

1.    What was the original cost of Property Plant and Equipment disposed of in 2020? Assume that all purchases in 2020 were made in cash (neither equity nor debt financing). Assess the feasibility of this assumption.

2.    What was the Accumulated Depreciation on the Property Plant and Equipment sold in 2020?

3.    Are Apple’s Property, Plant, and Equipment more or less than half way through their useful lives on average? How did you know? Assume there is no salvage value on PP&E Apple currently holds.

Note: Solution of this question (and those of all the questions asked so far) is shared on my website.

If only you had known these before investing in a tech venture (or any private company): Some well-known secrets ;) Part 1 of many

If only you had known these before investing in a tech venture (or any private company)
Some well-known secrets 😉
#1
Tendency to stay private as long as possible not necessarily results from the motivation of glossing over “subpar execution” and “problems concerning financial viability of founders’ business model” although there are many cases in which these have been the real motivations of staying private. It has been driven mainly by excessive private capital, albeit currently drying up, incentivized by supplying easy, i.e. not smart, liquidity so that valuations shoot up before IPOs, which have become just down rounds recently.
So, now you know why many ventures are waiting for a decade or more on average before going public.

Solution to Management Science Series #174: Capital Structure and WACC🧮

You have calculated the unlevered beta of Adobe as 0.79 (actually, this is the answer of the question posted on the 4th of January, 2025. If your estimate were different from that value in higher orders of magnitude, you should check your model and assumptions).

Adobe’s cost of debt is estimated to be 3% as of August 2024.

For the risk-free rate, use the current yield on 10-year US Treasuries (9th of August, 2024).

Equity risk premium will be 6.5%. Corporate tax rate for Adobe is 21%.

You want to investigate how the WACC of Adobe will change in changing capital structures.

Assume that the cost of debt for Adobe does not increase with the amount of debt in the capital structure (seemingly not realistic but there are such cases; do you know why?).

Investigate how the cost of equity and WACC will change with changing debt-to-assets ratios, i.e. start from 0% and incrementally increase it by 15% and stop when the ratio hits 90%.

Plot the cost of equity, cost of debt, and WACC at changing debt to asset ratios!

Solution to Management Science Series #173: How to estimate project betas 🧮Adobe Example

How to estimate project betas 🧮

Adobe plans to invest in a project, risk of which is similar to company’s own risk.

Nonetheless, Adobe plans to finance this project with only equity (100% equity-financed).

Estimate the beta of this project!

On Capital Asset Pricing Model (CAPM) and its real-world validity: Investigating Amazon stock

Does CAPM really do its job of simplifying the calculation of cost of equity and returns on individual stocks? How is its predictive power in estimating stock returns? Can it cause the returns on very disparate stocks to converge? What can one do to assess the risk of and returns on stocks better?
In this article, I investigate Amazon stock and compare the expected returns on Amazon stock calculated through the use of different approaches while also discussing the perils of CAPM.

Solution to Management Science Series #172: Real world example: Cost of Equity of Netflix 🧠

Calculate the cost of equity for Netflix.

Calculate two betas; one for the last 10 years and the other for the last 5 years.

Use the equity risk premium you calculated in the previous post through the historical approach.