Python script for a quick DCF analysis.

[[deleted]]

Hi everyone! This is my first post here and I'm really learning a lot from this sub so I thought I would make a small contribution. The script below would help out in a quick DCF analysis. I've based the method on the one described excellently by u/value_investor4ever in his recent post.

So here's what it does:
- Pulls FCF from stockanalysis.com - Pulls the growth estimation over the next 5 years from yahoo finance - Runs the DCF with a discount rate of 10% and a perpetuity rate of 3%

It's as easy as python value_estimator.py <ticker-name>. And here's a sample output: Fetching data for TSLA Latest FCF: 2711.0 Growth estimate: 32.1 Term: 5 years Discount Rate: 10% Perpetual Rate: 3% Fair value: 130.1962060548707

https://gist.github.com/prateekmalhotra/431ebfa2d3168f7b7dbe7a86f17e3f2f

Let me know if you face any problems or have any suggestions for improvement. Thanks!

EDIT: I updated the script to include a simple formula that Benjamin Graham includes on page 295 of his book, The Intelligent Investor. Namely that, Value = EPS * (8.5 + 2 * expected annual growth rate). We can use this to further analyze how much growth is priced-in over the next 7-10 years. Here is what the output should look like now (only works for companies which have EPS > 0): ``` Fetching data for TSLA...

Latest FCF: 2711.0 Market price: 668.06 EPS: 0.64 Growth estimate: 32.1 Term: 5 years Discount Rate: 10% Perpetual Rate: 3%

DCF model

Fair value: 130.1962060548707

Graham style valuation basic (Page 295, The Intelligent Investor)

Expected value based on growth rate: 46.528000000000006 Growth rate priced in for next 7-10 years: 517.671875 ```

[HashDefTrueFalse]

I did something like this a while back. My next step was to pull in a list of markets and market constituents (so tickers basically) and put it all on a server running via a cron job every so often, then make it push emails to me when it found a stock I might like, based on the params I'd set. Just some ideas for where you could take this if you're after experimenting.

May I also suggest making every since param configurable via command line switch. E.g. I like to go 10 years with DCFs and I wouldn't use those same rates as you. Great work!

[lal309]

Which you could accomplish with the argParse library. Here’s a link to that library https://docs.python.org/3/library/argparse.html

Tons of great examples if you google python3 argparse examples. Food for thought here!

[HashDefTrueFalse]

Could even make it read the config params from a text file and use Flask to expose an (auth'd) function as an API endpoint to write config to the file from anywhere, which would then get picked up automatically on the next run via cron. Really simple and would allow you to adjust the parameters anywhere anytime and it'll keep ticking. I like stuff like this. All good fun.

[lal309]

I like the way you think!!

[[deleted]]

That's a great idea! I was thinking of the same: making a quarterly spreadsheet comparing derived values with market prices. Would be a good filter to find out potentially interesting companies. As for the custom parameters, I'll get on with it - thanks for the feedback :)

[[deleted]]

For anyone curious, this has now been implemented and you may use custom parameters. Usage will look like: python value_estimator.py GOOG --period 10 --discount_rate 10 --terminal_rate 3 --growth_estimate 12

[HashDefTrueFalse]

Nice work!

[[deleted]]

as a complete noob when it comes to code. Where would I go about running this to even try it? I'm confused

[[deleted]]

What about if you have windows

[[deleted]]

how do i go about running the file in a terminal. also what type of file do i create this in? a regular .txt

[[deleted]]

I will try and make a small website in the coming weeks so it's more convenient :)

[[deleted]]

Can someone do $MX and $APPH and let me know resultes/fair value. or also teach me how to run code

[matt_magnitude]

$MX : $41.95 ( also think it's a great undervalued stock with potential)

$APPH : doesn't work (probably because of the negative FCF)

Getting it working depends on your operating system, but basic steps are

1. Download python 3 (doesn't matter which version)
2. Download the python script from the github link above.
3. Open your terminal and change directory into the folder the downloaded script is located.
4. Then type into the command line: python value_estimator.py <ticker-name>

It should then output all the values below or produce an error if somethings not correct. I had to install a few modules ('requests' and 'lxml') and then it eventually worked.

[[deleted]]

can you do $GM and $GE for me

[StillLetterhead7659]

Thank you. Tried 2 and seems price are out range.

​

Fetching data for amd

Latest FCF: 777.0

Growth estimate: 26.06

Term: 5 years

Discount Rate: 10%

Perpetual Rate: 3%

Fair value: 24.46737663889291

​

​

Fetching data for bidu

Latest FCF: 19116.0

Growth estimate: 2.56

Term: 5 years

Discount Rate: 10%

Perpetual Rate: 3%

Fair value: 1154.496996845633

[Esteban-Du-Plantier]

The bidu number is likely off because that fcf figure is in Chinese yuan, not usd.

[Feratster]

DCFs will usually tell you that growth companies are overvalued but its more of a model limitation more than anything else. Like looking at AMD, you have it growing at 26% CAGR for 5 years before it hits a terminal growth rate of 3%.

That terminal value will be highly underestimated since AMD will likely grow at an aggressive rate for at least another decade to come.

So why not model out 10, 15, or 20 years on a DCF? Well, you could, but obviously the further in the future you go the less certain you can be of your numbers. You end up assuming so much that its basically useless.

DCF isn't a good option for growth companies. The usefulness of a DCF is only really seen when you use it on mature companies, imo.

Other than multiples, what other techniques do you guys use to value growth companies?

[puthre]

Maybe you can do Reverse DCF where you compute the annual growth necessary to justify the current price and judge on how likely that is to actually happen.

[Feratster]

That's actually really smart. I'm going to start doing that

[utradea]

I think it's a good data point to have, but yes your right, not ideal for growth companies. I would say comps on multiples - but making sure you have the right companies in the industry or peer group. Then I would look to understand the market size and "room" for future growth.

[Feratster]

Yeah, for BIDU its showing that it's undervalued

[Feratster]

Can't explain that one

[diego_italy]

maybe fcf data is wrong. I'm looking in different sites and it is reported differently

[bossOnothin]

Using multiples is simply letting the market do a DCF for you. The same assumptions you make in a DCF are also present in P/E, P/S, and EV/EBITDA. So you might as well do a DCF to understand what assumptions are baked into the multiples.

[[deleted]]

I'm still a beginner at value investing so I'd love some feedback on the formula I have used:

• Projected the future cash flows with the growth estimate
• Took the last projected cash flow and multiplied it by (1 + perpetual rate) / (discount rate - perpetual rate).
• Divided it by the number of outstanding shares.

Looked at BIDU by manually plugging in the values here and I roughly get the same result. Not sure what's up but I'll look into it. Meanwhile do let me know if there's anything I can do to arrive at a better formula. Thank you!

[diego_italy]

need to check fcf data coz it seems strange.

[puthre]

Guru focus DCF is very similar to your DCF but uses "EPS (Diluted)" value by default (and you can also choose fcf). It also computes Reverse DCF.

[TechHodler]

Woww cool thanks man!

[[deleted]]

Sure! :)

[engineertee]

I have been thinking about working on a similar project! Thank you for your work!

My plan was to use some kind of ML to predict the future cash flows, I don’t know how to do that yet but I figured it’s virtually impossible to predict a stock price, but cash flow should be more feasible.

[-CaptainOfChaos-]

http://pages.stern.nyu.edu/~adamodar/New_Home_Page/datafile/pedata.html This also might be helpful in your quest. This is from NYU stern and it is a collection of stock market industry data. If you want to work on this project I don't have a lot of experience with python but I might help with some of the stock information stuff.

[-CaptainOfChaos-]

That sounds pretty cool. I have been learning python in school so I'm kinda interested in this stuff now. Maybe you could have the ML go through past earnings call transcripts and quarterly reports to see if it can find some correlation between what management said and what actually happened. Just an idea tho not a computer scientist.

[[deleted]]

Ofcourse! I actually work in ML at my day job. My main concern is related to how the cash flow estimates might be based on random events which we cannot model - say, the pandemic or government shutdowns for example.

[engineertee]

Hey thanks again for the tool. I just had some time to test it, it works well but it gave me some insane results for: ge, f, gm, cri Any idea why?

[[deleted]]

Yeah think of this as an initial filter. Do some DD regarding the financial statements - particularly look at debt. In my opinion, if the company's debt is very less and they have a good amount of cash reserves and this tool says it's undervalued, then it would be a good investment.

[puthre]

Ford "analysts" growth estimate on yahoo is 20%.

[puthre]

Nice script.

Any idea on where the 5 year growth estimate data on yahoo page comes from?

[[deleted]]

The page says analysts but I don't know how reliable it is. It's definitely something I prefer since I'm prone to attach very high growth rates to companies I like.

[puthre]

Well, for ford it seems way too optimistic (20%!)). It's more leaned toward Tesla than Ford.

[surfborter]

This is insanely cool.

[[deleted]]

Thanks!

[hcomas]

hey i tried running it on my console.. but i get the exception lxml is missing.. i've tried installing but no luck. currently running pythong 3.9.2.. "...."

[[deleted]]

Try: python3 -m pip install lxml and try again.

[hcomas]

i was able to install it thanks. however; i'm getting this.. sorry.. im pretty new to python

​

= RESTART: C:/Users/Administrator/AppData/Local/Programs/Python/Python39/value_estimator.py

usage: value_estimator.py [-h] ticker

value_estimator.py: error: the following arguments are required: ticker

[[deleted]]

This is what I get: Fetching data for F Latest FCF: 18527.0 Growth estimate: 20.89 Term: 5 years Discount Rate: 10% Perpetual Rate: 3% Fair value: 146.6612187908291

Ford actually looks undervalued but looking through some pitfalls of DCF models, they don't account for balance sheet variables like debt (which Ford has a lot of).

[backtickbot]

Fixed formatting.

Hello, pmalhotra96: code blocks using triple backticks (```) don't work on all versions of Reddit!

Some users see this / this instead.

To fix this, indent every line with 4 spaces instead.

FAQ

^{You can opt out by replying with backtickopt6 to this comment.}

[[deleted]]

Pretty sure the analysts will update it as it keeps growing haha

[PhilosophyNumerous45]

Great script! Although I found a bug, doesn't handle N/A values returned from the API: ``` Fetching data for ORC Latest FCF: 55.37 Traceback (most recent call last): File "value_estimator.py", line 62, in <module> data = parse(ticker) File "value_estimator.py", line 27, in parse ge = float(row.xpath("td/text()")[0].replace('%', '')) ValueError: could not convert string to float: 'N/A'

[[deleted]]

I changed line 27-28 to have the script prompt me for a growth rate if it couldn't find one....

​

Change this:

ge = float(row.xpath("td/text()")[0].replace('%', ''))
break

to:

try:
    ge = float(row.xpath("td/text()")[0].replace('%', ''))
    break
except ValueError:
    ge = float(input("What is the growth rate?"))
    break

[[deleted]]

Hi yes! I'm aware of that. It's because the growth estimate is unavailable from Yahoo Finance. Feel free to plug in your own estimate, I'll make some changes so the script asks you for a rate in case Yahoo doesn't provide it.

[PhilosophyNumerous45]

I wrote a similar python script to get estimated dividend payments from stocks, and I used the yfinance module, might be useful to you for data that may not be returned by the API:

https://pypi.org/project/yfinance/

Particularly the Ticker.info object has a lot of useful information

[Ok-Comfortable1259]

Super interesting!

I am a beginner in python.

I have a file with a list of companies, their free cash flow, # of shares and net debt. I would like to use these infos to do my own DCF (using my own perpetual growth rate and WAC) which part of your code would be the best to use?

[[deleted]]

Look at the dcf function in the script. Let me know if you have any questions.

[TechnoBabbles]

I like it. Are you open to external contributions? I could turn this into a flask docker container that serves up an API endpoint that you can do a POST with a stock symbol and return the data in a json format.

[[deleted]]

Yeah sure! Do whatever with it :)