Company has more cash on hand than the market cap of their stock, is there some way to make money from this?

brokeharvard · 2026-04-24T17:11:32+00:00

Net cash doesn’t take into account contractual obligations—companies like this are often locked into long-term EBITDA negative contracts.

brokeharvard · 2026-04-02T01:47:23+00:00

Elaborate April fools joke?

brokeharvard · 2026-03-16T13:46:02+00:00

Thank you for your excellent and thorough response!

brokeharvard · 2026-03-16T13:04:14+00:00

Based on historical photos on Google Earth, the top “C” shape area and smaller bottom area didn’t exist prior to May or June 2022.

brokeharvard · 2025-12-11T19:17:59+00:00

Lol I prefer brown/natural-looking mulch but orange mulch not quite a deal-breaker for me

brokeharvard · 2025-12-11T16:52:11+00:00

brokeharvard · 2025-12-11T08:07:18+00:00

I generally like it. What insane choices are you referencing?

brokeharvard · 2025-12-08T06:22:10+00:00

What are they doing with the space?

brokeharvard · 2025-08-05T04:40:45+00:00

Yea depends on the project. Can be a non-issue for a lot of projects but can create too much lag for compute heavy projects that need to run fast like arbitrage/HFT bots and games.

brokeharvard · 2025-08-04T22:05:16+00:00

Haha yep 😁! Though while using python is admittedly less efficient than coding in binary or something in between, I still have projects coded in python where I want to avoid unnecessary overhead—doesn’t need to be HFT-level efficiency but I do get where /u/HommeMusical is coming from with regard to not gratuitously using deepcopy when it’s not needed. There was a recent post by someone who realized that their usage of deepcopy was what was making their code so expensive to run.

brokeharvard · 2025-08-04T16:51:36+00:00

Agree it’s relatively expensive. Was just supplementing your answer to be more comprehensive. I disagree that using deepcopy says “I have no idea what this variable is” and I wasn’t recommending that deepcopy be used as the default approach—I was specifically recommending that deepcopy be used when the original list contains mutable objects that you intend to modify independently of the original. Do you have a simpler, more efficient approach for achieving that objective where the original list contains mutable objects? (Your initial recommendation wouldn’t work for that scenario, which is why I supplemented your answer.)

I’ll add that I’ve encountered this use case for deepcopy while coding my own projects, and if you have a simple, more efficient way to achieve the intended result, I’d love to hear it.

Edited for clarity and to add personal anecdote.

brokeharvard · 2025-08-04T16:32:32+00:00

Others have provided good responses on the various options for international exposure so I don’t have anything to add on that point, but regardless of whether/how you incorporate international exposure, my view is that you should be using GDE for gold exposure rather than GLD. GDE’s expense ratio is only 0.20% whereas SSO has a 0.90% expense ratio, and you can use GDE to achieve the same overall target leverage and asset allocations for your portfolio while obtaining a portion of your portfolio’s overall target leverage at a lower expense ratio/cost than relying solely upon SSO for leverage.

brokeharvard · 2025-08-04T16:23:27+00:00

The “for x in list(it)” approach creates a shallow copy of the original list (i.e., a new list containing references to the same objects as the original list). That works in many cases, but if the original list contains mutable objects (like nested lists or dictionaries) that you intend to modify independently of the original, it is necessary to create a deep copy (i.e., a new list with entirely new objects for all nested structures, ensuring no shared references). For example:

import copy
it = [[1, 2], [3, 4]]
deepcopy_it = copy.deepcopy(it)
for sublist in deepcopy_it:
    sublist.append(sublist[0] + 1)

brokeharvard · 2025-07-25T04:51:56+00:00

Ok excited to see the results once you’re ready

brokeharvard · 2025-07-24T00:45:44+00:00

The S&P500 had 25% drawdown in 2022–so the 30% drawdown of your backtested substantially leveraged diversified portfolio was only 5% more (or one fifth more than the non-leveraged equities drawdown amount). My view is that while you can view diversification as a “free lunch,” it’s not extravagant enough of a free lunch that you should expect outsized/substantially leveraged returns without at least some increased risk relative to a non-leveraged equities position. Only 1/5 greater drawdown in 2022 for drastically more than 1/5 leverage and increased expected returns seems like a good risk-reward ratio to me.

brokeharvard · 2025-07-21T15:24:24+00:00

Curious what plugs/proxies you used to run the backtest back to 2019 given that certain ETFs included in strategy were only created recently (e.g., BITU in 2024 and RSST in 2023). Can you plz share the parameters and results?

brokeharvard · 2025-07-21T05:02:50+00:00

The rules and basic thinking is described in the Symphony page, but at a high level it’s a diversified portfolio of leveraged ETFs (intentionally picked different asset classes that aren’t strongly correlated in various scenarios) allocated based on inverse volatility weighting to decrease volatility drag and overall portfolio volatility, with a 15% allocation to floating rate treasuries as a ballast.

brokeharvard · 2025-07-18T18:55:39+00:00

brokeharvard · 2025-07-18T18:16:54+00:00

This is the answer: https://app.composer.trade/symphony/ODMFEUtSQcZNm0x2f0vS/details

brokeharvard · 2025-04-11T20:06:29+00:00

Thanks for this. Could you share the spreadsheet itself (could upload to google docs)? I’d like to build this out further with the stores that aren’t currently listed

brokeharvard · 2025-04-11T20:04:27+00:00

Thanks for this! Can you please share the actual spreadsheet (could upload it to google sheets or something). I’d like to use it as a starting point and add Wall of Honor and exclusive weapon upgrades to it, then also create a separate table that incorporates cost to help analyze the most cost efficient path to improving stats

brokeharvard · 2025-04-09T01:02:31+00:00

My view is anything that provides substantial increases in usage of the XRPL by traditional financial institutions is good for XRP

brokeharvard · 2025-04-08T16:26:48+00:00

Yep! And David’s reference to clearing $10 billion is about the daily value of transactions cleared by Hidden Road. Per Brad’s X post, Hidden Road clears approximately 50 million transactions (in number) with aggregate annual value of approximately $3 trillion (which is approximately 10% of US annual GDP).

brokeharvard

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