Great thought. You've hit the classic Munger philosophy - think about what would cause failure and then do the exact opposite. In his words: "It is remarkable how much long-term advantage people like us have gotten by trying to be consistently not stupid, instead of trying to be very intelligent"
12
u/DaveFoSrs
Don't invest in a business you don't understand. Don't "figure out" what a company does from its shills on WSB and Stocktwits--they have a vested interest in duping people.
Avoid small cap stocks, especially if the above it true.
Don't invest pre-revenue or pre-cash flow positive
Source: I was a moron in my 20s
9
u/mrmrmrj
Minimize losses. Sell losers quickly. You can always buy them back.
There seems to be a psychological resistance to selling a stock after owning it for only a month or two if it is down. I don't get this.
4
u/Q16Q
Great to see someone think about fundamentals. You have a better chance of succeding.
2
u/Few-Perspective4430
Good point. In investing, sometimes the biggest wins come from simply avoiding bad decisions.
Many people chase hype without understanding the business or checking the fundamentals. Sticking to what you understand and avoiding obvious red flags can save a lot of money in the long run.
2
u/Hamzehaq7
totally get what you're saying. it's wild how many people jump into stuff without really digging into the basics. like, sure, AI is hot, but if you're looking at companies like Oracle with that kind of debt, maybe take a step back? lol. sometimes it feels like folks want the thrill of investing without the actual work. it's all about balancing enthusiasm with common sense, imo. avoiding those super obvious red flags can save you a lot of pain later. what’s your take on the whole AI hype right now? seems like everyone's trying to chase that next big thing.
2
u/CherryRoutine9397
Avoiding dumb mistakes honestly does more for your money than trying to find the perfect strategy. Most people lose because they chase hype stocks, overtrade, or copy random portfolios they saw online. Keeping things simple and actually understanding what you own already puts you ahead of most investors. I write about stuff like this sometimes, link is on my profile if anyone’s curious.
2
u/Dependent-Panic-9457
I agree with the point about debt. I am nonetheless up to my neck in Jadestone Energy. Actually: above my neck.
1
u/BCECVE
give us more. thx
1
u/CalendarNo6655
I actually genuinely enjoy reading and learning about these companies. I think big pharma, nvidia, or biotech is really interesting though investment wise they are not ideal. I think there are some 10/10 companies but they rarely go on sale. Unfortunately the market prices them too well
1
u/jay_0804
Avoid obvious mistakes first. Examples: Snapchat never profitable, Tesla P/E 363, Oracle high debt.
My rules: long profitability, decent ROIC, understand what you own, low debt, real moat. Avoid dumb errors before chasing perfect setups.
1
u/One-Event6199
Someone on this subreddit who actually has useful thoughts/insights. This is so spot on. This is Buffett/Munger/Lynch in a nutshell.
1
u/Lost_Percentage_5663
Most ppl are IQ100. But they think they are IQ110. All tragedies happen with it.
1
u/AInotG
Lesson: If it is being discussed publicly, probably it is already overpriced
Thanks for this. I’ve previously read both parts of your analysis and tried to stress test it myself. Not having biostatistics expertise this has been hard to do.
I began to think about other ways to prove the trial is working through looking at other evidence (investigator testimonials, clinical supply and logistics, etc). Did not find anything to contradict your conclusion
Have you looked at any of these avenues? Any new thoughts or evidence since you did your analysis a while back?
7
u/Remarkable-Big-9849
Hello,
We discussed things a few days ago on one of these threads and I've spent the last week doing even more testing and wanted to update you since a few things you said inspired me a bit.
First you mentioned I was using an agnostic 50% prior and that a literature-informed prior would be closer to70% with a pessimistic prior at 20%. While I agree that if we take overall oncology phase-3 trial success rates and the biological mechanistic plausibility, it would imply around 70% as a reasonable prior but vaccines and immunotherapies like this especially in diseases like AML have had much lower success rates so I actually think a 20-40% prior is more supported with the 40% being driven by the phase-2 evidence and biological plausibility.
Second, you mentioned that you looked at what the failures actually looked like and that inspired me to look into the failures myself and other trial data where the trial was a statistical miss but the biological signal was strong enough that another trial happened. Using those conditions, I was able to separate out failures where the drug works but failed due to statistical power and another trial happens.
Combining that with the prior range I mentioned earlier, I got the following scenario probabilities:
Final derived scenario probabilities
Scenario Probability
Strong success (cure tail) 70-85%
Moderate success 8–15%
Statistical miss but signal 3–6%
No effect 1–2%
which actually brings me a bit in more line with your reproduction of my methodology where you got 98-99% chance the drug works. I do think we should treat the statistical miss scenario as a 50% value haircut due to extending the timeline out a few years and increasing early costs (which may or may not increase dilution, as they do have a lot of cash)
I also wanted to share a histogram I produced in my initial testing for the probabilistic feasible region for cure fraction but reddit doesn't let me post images in a comment it seems. So here is some of the data:
Number of feasible draws: 50000
Mean implied cure fraction: 0.578
Median implied cure fraction: 0.590
Probability cure fraction >= 0.20: 1.000
5th, 10th, 25th Percentiles: [0.39379246 0.43575868 0.51072057]
Probability of Cure Fraction above 35%: 0.9784
Talking about the economics a bit:
Revenue=N*Penetration*Price*Duration
and we know that a cure fraction is going to increase both Duration and effective N over time as patients stay alive longer so if the average treatment duration without cure is represented by D and cured patients that stay treated by kD, we have:
Duration=(1−p)D+p(kD) =D[1+p(k−1)]= D[1 + p(k-1)]=D[1+p(k−1)]=1+p(k−1)
where k represents how much longer the patients stay treated and p is the cure fraction. If the baseline therapy duration is ~12 months and durable responders last 3-5 years on the treatment, we would have a revenue model of 1 +2p to 1 +4p and if an acceptable cost per quality life-year gained is ~$100-150k in the USA then we could have a 2-3.5x revenue effect over baseline (current population) based on my histogram data. If the drug is extremely effective and adds 10-20 life years then the total price might be limited due to payer pressure so I didn't want to model that out.
5
u/Limp_Leg3323
Really appreciate the insights you shared here! Stress testing can feel like trying to solve a Rubik’s cube blindfolded, right? I’d love to hear if you’ve unearthed any fresh evidence or thoughts since your analysis!
5
u/Adeus_Atticus
I’ve already thanked you for this but will do so again! Do you see the basement value rising the longer REGAL goes on?
3
u/hariharsharma
Just curious on 2 things:
I don't see any disclaimer on this post, is it sponsored? don't get offended please. Just curious.
how far the stock will go if the result is positive as the model/analysis indicates
most important, how likely SLS will release more stocks during up coming meeting in 2 weeks, like they did in early January 2026 taking benefit of higher market price.
Thanks for reading and responding my comment.
u/Ok_Choice_3228
I evwn got bored of scrolling. I can't imagine anyone has a whole free day to read all of this...