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Is there an AI board, pls feel free to move.

I'm interested in educating myself more about "fundamental analysis", i.e. analysis of corporate fundamentals. So I engaged in a discussion with ChatGPT about a question that occurred to me.
Spoiler alert: ChatGPT didn't know that a low number in the denominator of a financial ratio can result in a high number for the ratio, but it spouted financial garbage quite confidently despite this fundamental error. Until I called it out, see below.

I had previouly tested ChatGPT a lot on subjects where I am expert in the subject matter. Below confirms my conclusion: ChatGPT is bloody awful, like a bad grad student who does a passable job of talking the talk, until they say something that demonstrates they're clueless.

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USER
Give an example explaining why return on revenue may not be associated with return on equity.

ChatGPT
Return on Revenue (RoR) and Return on Equity (RoE) are both financial metrics used to evaluate a company's performance, but they focus on different aspects of the business. Here's an example to illustrate why RoR may not necessarily be associated with RoE:

Imagine two companies, Company A and Company B, operating in the same industry. Company A has a high RoR, while Company B has a high RoE. Let's break down their financial situations:

Company A (High RoR):

Company A is very efficient at managing its costs and generating profits from its revenue.
It has a low operating cost structure, which results in a high RoR.
However, Company A has a substantial amount of debt on its balance sheet to finance its operations. This high debt load increases financial leverage.
Company B (High RoE):

Company B is not as efficient as Company A in generating profits from its revenue, and it has a lower RoR.
However, Company B has very little debt on its balance sheet, and most of its equity comes from shareholders' investments.
Because of the low debt, the interest expenses are minimal, which results in a high RoE.
Now, let's consider why RoR and RoE may not be associated in these cases:

Different Profitability Models: Company A is highly focused on maximizing short-term profitability by keeping operating costs low. This is reflected in its high RoR. Company B, on the other hand, focuses on long-term growth by relying on equity financing and maintaining a lower debt load. This leads to a high RoE but lower short-term profitability.

Risk and Leverage: The high debt level in Company A's capital structure introduces a significant level of financial risk. If the business faces economic downturns or difficulties in meeting debt obligations, its RoE could be negatively impacted. In contrast, Company B, with low debt, has lower financial risk and is more stable in terms of RoE.

In this example, Company A has a high RoR but a lower RoE due to its focus on short-term profitability and the associated financial leverage. Company B has a high RoE but a lower RoR because it prioritizes long-term growth and has a conservative capital structure. This demonstrates that RoR and RoE are distinct metrics that capture different aspects of a company's financial performance, and they may not necessarily be directly associated.

USER
Is debt usually the difference between ROR and ROE, or are their other factors that might also enter frequently?

ChatGPT
Debt is one of the key factors that can contribute to the difference between Return on Revenue (RoR) and Return on Equity (RoE), but there are other factors as well. The difference between these two metrics can be influenced by various financial and operational factors. Here are some of the common factors that can affect the relationship between RoR and RoE:

Capital Structure: Debt is a significant factor, but the overall capital structure is essential. RoR reflects a company's profitability relative to its total revenue, while RoE considers the profitability in relation to the shareholders' equity. The composition of the capital structure, which includes both debt and equity, can impact these metrics. Companies with more debt may have lower RoE due to interest expenses, while companies relying heavily on equity might have a higher RoE but potentially lower RoR.

Financial Leverage: Financial leverage, which is the use of debt to amplify returns, can magnify the difference between RoR and RoE. When a company has high financial leverage, it can boost RoE if the return on assets (RoA) is higher than the cost of debt. However, it also increases financial risk and interest expenses, which can negatively impact RoE in the long run.

Operating Efficiency: A company's operating efficiency plays a significant role. RoR is influenced by how efficiently a company manages its operating expenses and generates profits from revenue. Improving operational efficiency can lead to a higher RoR. On the other hand, RoE considers the total equity invested, so even if a company is very efficient in generating revenue, if it has a small equity base, RoE might not be as high.

Taxation: The tax environment can affect the relationship between RoR and RoE. Interest expenses on debt are typically tax-deductible, which can reduce the overall tax liability for a company. This can benefit RoE by increasing net income after taxes. However, it doesn't directly impact RoR, which is a pre-tax measure.

Business Strategy: Companies may have different strategies, which can impact both RoR and RoE. For example, a company focusing on rapid expansion and reinvesting profits into the business may have a lower RoE due to retained earnings not contributing to equity, but it can have a higher RoR by capturing more market share and revenue.

In summary, while debt is a significant factor, several other elements can influence the difference between RoR and RoE. These factors can include capital structure, financial leverage, operating efficiency, taxation, and the company's overall business strategy. It's important to consider the specific context and financial situation of a company to understand why RoR and RoE may differ.

USER
The following sentence of your response is wrong, please respond:

"On the other hand, RoE considers the total equity invested, so even if a company is very efficient in generating revenue, if it has a small equity base, RoE might not be as high."

ChatGPT
I apologize for the confusion. The sentence you mentioned is not accurate. RoE, or Return on Equity, is a measure of a company's profitability in relation to its equity base. Therefore, if a company is efficient in generating revenue, it can lead to a higher RoE, especially when compared to its equity base. In fact, a small equity base with efficient revenue generation can result in a higher RoE.

Here's a corrected explanation:

"On the other hand, RoE considers the total equity invested, so if a company is very efficient in generating revenue, especially when compared to its equity base, it can lead to a higher RoE. A smaller equity base with efficient revenue generation can result in a higher RoE."

Thank you for pointing out the error, and I appreciate your understanding.
Is this conversation helpful so far?

USER
No.

ChatGPT can replace a manager, not a professional 😀

So far.

There are other examples of AI that do do a better job than the professional, for example, in x-ray analysis, versus a radiologist. I expect chatGPT to get better over time so it can be as good as a finance professional, or a software engineer. My friend, who owns his own company successfully employed chatGPT to write some low level embedded software after guiding it through questions and answers. He said it was far cheaper (free except for his time) than hiring an embedded software engineer. Therein lies the nub.

ChatGPT does not have to be perfect, just better than the best human, which it will be soon.

...embedded software...
ChatGPT does not have to be perfect, just better than the best human, which it will be soon.

Hmm, there's a big difference between a great programmer and a typical programmer.
I can't think of many human skills with such a wide distribution of skill. Maybe singing?

But of course in terms of churn in the job market, it doesn't have to knock out the best.

So, I'd rephrase:
ChatGPT does not have to be perfect, just better than an average human in that profession, which it will be soon.

Jim

programmer.... I can't think of many human skills with such a wide distribution of skill.

Painting? Writing? Photography? Dancing? Driving? Thinking? ..........

In my experience, the code that ChatGPT produces now is often bad code, on two very different levels:

Level 1: obviously buggy as hell, of course doesn't execute
Level 2: actually pretty good, but with one or three subtle logical errors (not programming error)

As coding LLMs improve and are widely adopted, Level 2 errors will proliferate. That said, I use ChatGPT for coding assistance now, e.g. it was easier to correct its errors in code for scraping data from macrotrends.net, see above thread, then to start from scratch. As mentioned, AIs equal or exceed humans in other limited domain areas (radiology etc).

My concern is that we're at a point in AI where, to make an analogy, we're going from the Wright brothers at Kitty Hawk, to having airports all over the world with high tech jets ferrying humans everywhere -- but with no equivalent of an FAA or an NSTB (U.S. regulatory and investigative agencies). Commercial jet aircrafts are also marvels of technology that have transformed the world, but they've been strictly regulated and consequently air travel is extremely safe. I think we're going to have lots of spectacular crashes with AI.

That said, the mad scientist in me is dying to have LLM's learn to rewrite their own code (best done in equivalent of BSL-4 facilities).

I'd agree with Jim with regards to programming talent. I've done various programming work (usually low level stuff) for close to 40 years and you get a few exceptional programmers with a lot of marginal ones and more than a few mostly incompetent ones. Sadly there are a lot of people who somehow managed to get a CS or other tech degree and can't program or do engineering work efficiently or even correctly.

I'd agree with Jim with regards to programming talent. I've done various programming work (usually low level stuff) for close to 40 years and you get a few exceptional programmers with a lot of marginal ones and more than a few mostly incompetent ones. Sadly there are a lot of people who somehow managed to get a CS or other tech degree and can't program or do engineering work efficiently or even correctly.

I've found the main "fat tail" is at the high end.
The best programmers are sometimes measurably 1000 times better than the median ones.
Admittedly an aid like ChatGPT can presumably help the median folks be more productive, moving the whole curve. But perhaps not more insightful.

Jim

Hmm, there's a big difference between a great programmer and a typical programmer.
I can't think of many human skills with such a wide distribution of skill. Maybe singing?

But of course in terms of churn in the job market, it doesn't have to knock out the best.

So, I'd rephrase:
ChatGPT does not have to be perfect, just better than an average human in that profession, which it will be soon.

This is very very true. Few white collar professions other than programming have such a wide distribution of productivity. (Non white collar like athletics are more common.)
That's why AI is such a threat to humans' jobs. From "better than average" to "better than the best", while orders of magnitude more, is achievable in far less time for AI than to a human.
Eg I have heard that in programming, exceptional to average productivity ratio in 1:100. Almost insurmountable for even smart humans. But it's just 100x more computing power for an AI.
AI beat Go champion. Programming too is a game assuming perfect or even "good" input requirements. And far more structured than a blue collar pursuit like welding or basketball.

Few white collar professions other than programming have such a wide distribution of productivity ..... I have heard that in programming, exceptional to average productivity ratio in 1:100

Lawyer: White collar profession, right? What's that ratio for the productivity of a shitty lawyer because of whom you lost a trial versus a good one who would have won it?

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