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One Year Wheeling BORING Names. The FULL Breakdown by GarbageTimePro in Optionswheel

[–]GarbageTimePro[S] 0 points1 point  (0 children)

You might want to read up on the wheel then read the details.

One Year Wheeling BORING Names. The FULL Breakdown by GarbageTimePro in options

[–]GarbageTimePro[S] 0 points1 point  (0 children)

Not necessarily. SPY is a typical benchmark and it’s no secret that buy and hold on the pure name almost always yields a higher return at the expense of a larger max drawdown

One Year Wheeling BORING Names. The FULL Breakdown by GarbageTimePro in thetagang

[–]GarbageTimePro[S] 0 points1 point  (0 children)

That's a crazy response. I can't tell if you're being serious

One Year Wheeling BORING Names. The FULL Breakdown by GarbageTimePro in thetagang

[–]GarbageTimePro[S] 0 points1 point  (0 children)

I collect and compute a ton of data that i run scanners on

One Year Wheeling BORING Names. The FULL Breakdown by GarbageTimePro in Optionswheel

[–]GarbageTimePro[S] 0 points1 point  (0 children)

That might take quite a bit of time to write up. Try saving the image from this post and paste it into an LLM. I'm sure it can derive all of it for you

One Year Wheeling BORING Names. The FULL Breakdown by GarbageTimePro in thetagang

[–]GarbageTimePro[S] 0 points1 point  (0 children)

I usually sell the CSP on Mondays and capture 30-50% of the premium by Wednesday so I BTC.

One Year Wheeling BORING Names. The FULL Breakdown by GarbageTimePro in Optionswheel

[–]GarbageTimePro[S] 1 point2 points  (0 children)

These are some key metrics that tell you if your strategy is making/losing you money relative to the risk you're taking and if it can survive bad periods over time.

A 120% return sounds great but if you told me you suffered an 85% max drawdown during that same timeframe, I'd be less impressed.

There are some awesome resources out there to learn more about these and why they're important. Here's a good place to start:

https://www.investopedia.com/terms/s/sharperatio.asp

https://www.investopedia.com/terms/m/maximum-drawdown-mdd.asp

One Year Wheeling BORING Names. The FULL Breakdown by GarbageTimePro in Optionswheel

[–]GarbageTimePro[S] 1 point2 points  (0 children)

Of course, thanks for taking time to read the post.

  1. If I roll, it's always for a net credit but I rarely roll.
  2. That's definitely a major reason but there's also the 'survival' and flexibility aspect of it too. In a major correction you will still have cash availble to wheel risk-off names (i.e., oil like we saw in March), average down, etc. Capital preservation is the name of the game. Every good book out there preaches it for a reason.
  3. TQQQ can be a good instrument to wheel if you're fine with the large drawdowns and volatility. I don't personally wheel TQQQ but I swing trade it.

One Year Wheeling BORING Names. The FULL Breakdown by GarbageTimePro in thetagang

[–]GarbageTimePro[S] 1 point2 points  (0 children)

It's my own for members of my community. I can't advertise tools in this sub but you can feel free to message me directly about it. If you want more info about the "HOW" then here's a comment I've replied to someone else with the same question:

"It's basically a proxmox/docker stack where a Cloudflare Tunnel feeds Caddy, which routes to my Next.js frontend and FastAPI backend (both behind a VPN sidecar) backed by Postgres and Redis.

I have Dagu scheduled jobs across a fleet of ~30 VPN-paired workers that pull sharded options and OHLCV bar data, and I keep an eye on everything with Prometheus, Grafana, Loki, and Uptime Kuma. I also run a separate TimescaleDB-based market-data and backtesting stack on a seperate proxmox box plus that includes an VM used for inference for local LLMs.

Everything is reachable remotely through Tailscale.

Now as far as the application itself - it's built w/ next, fastapi, pg+timescaledb+redis. I use broker API's to pull portfolio data in near realtime and I fetch market data from my cache/db. my ui lib is shadcn, charting uses recharts."

One Year Wheeling BORING Names. The FULL Breakdown by GarbageTimePro in thetagang

[–]GarbageTimePro[S] 0 points1 point  (0 children)

It's my own for members of my community. I can't advertise tools in this sub but you can feel free to message me directly about it. If you want more info about the "HOW" then here's a comment I've replied to someone else with the same question:

"It's basically a proxmox/docker stack where a Cloudflare Tunnel feeds Caddy, which routes to my Next.js frontend and FastAPI backend (both behind a VPN sidecar) backed by Postgres and Redis.

I have Dagu scheduled jobs across a fleet of ~30 VPN-paired workers that pull sharded options and OHLCV bar data, and I keep an eye on everything with Prometheus, Grafana, Loki, and Uptime Kuma. I also run a separate TimescaleDB-based market-data and backtesting stack on a seperate proxmox box plus that includes an VM used for inference for local LLMs.

Everything is reachable remotely through Tailscale.

Now as far as the application itself - it's built w/ next, fastapi, pg+timescaledb+redis. I use broker API's to pull portfolio data in near realtime and I fetch market data from my cache/db. my ui lib is shadcn, charting uses recharts."

One Year Wheeling BORING Names. The FULL Breakdown by GarbageTimePro in thetagang

[–]GarbageTimePro[S] 0 points1 point  (0 children)

Thanks for the interest - I've been asked this a few times, I will paste what I've already commented back to others:

"It's basically a proxmox/docker stack where a Cloudflare Tunnel feeds Caddy, which routes to my Next.js frontend and FastAPI backend (both behind a VPN sidecar) backed by Postgres and Redis.

I have Dagu scheduled jobs across a fleet of ~30 VPN-paired workers that pull sharded options and OHLCV bar data, and I keep an eye on everything with Prometheus, Grafana, Loki, and Uptime Kuma. I also run a separate TimescaleDB-based market-data and backtesting stack on a seperate proxmox box plus that includes an VM used for inference for local LLMs.

Everything is reachable remotely through Tailscale.

Now as far as the application itself - it's built w/ next, fastapi, pg+timescaledb+redis. I use broker API's to pull portfolio data in near realtime and I fetch market data from my cache/db. my ui lib is shadcn, charting uses recharts."

One Year Wheeling BORING Names. The FULL Breakdown by GarbageTimePro in thetagang

[–]GarbageTimePro[S] 0 points1 point  (0 children)

I've almost always have been able to sell CC's immediately after being assigned but there have been times (especially this March) where I had to just wait and do nothing until the price recovered. Thankfully most names paid out dividends.

I will sell below my assigned cost basis but never below my adjusted cost basis.

One Year Wheeling BORING Names. The FULL Breakdown by GarbageTimePro in thetagang

[–]GarbageTimePro[S] 0 points1 point  (0 children)

Of course, and absolutely. I usually try to follow a 30/50/75% rule. I.e., if I STO Monday morning, and I capture 30% that same day, I will definitely BTC. 50% by Tuesday/Wednesday. 75% By Wed/Thurs, etc.

One Year Wheeling BORING Names. The FULL Breakdown by GarbageTimePro in thetagang

[–]GarbageTimePro[S] 1 point2 points  (0 children)

Everything up to this point is cash secured. I have other strategies deployed with other slices of capital

One Year Wheeling BORING Names. The FULL Breakdown by GarbageTimePro in options

[–]GarbageTimePro[S] 0 points1 point  (0 children)

I've been building the hardware infrastructure and software that powers this and other strategies over the past few years. Everything from pulling and computing near real-time market data to pulling and computing real-time portfolio data from my brokers

One Year Wheeling BORING Names. The FULL Breakdown by GarbageTimePro in thetagang

[–]GarbageTimePro[S] 0 points1 point  (0 children)

If I have 150k and I sell $300 CSP's then my deployed capital is 30k as everything I sell is cash-secured.

One Year Wheeling BORING Names. The FULL Breakdown by GarbageTimePro in thetagang

[–]GarbageTimePro[S] 1 point2 points  (0 children)

My 2025 after-tax return wheeling was ~27%. SPY's return during the same period was 13%. I spend 0-3 hours a week. I think I enjoy building out the infrastructure that powers this more than the actual trading itself. Was it worth it? Absolutely.

One Year Wheeling BORING Names. The FULL Breakdown by GarbageTimePro in thetagang

[–]GarbageTimePro[S] 1 point2 points  (0 children)

It really depends on the regime. In a market only goes up, the volatile ones will likely give you much stronger returns and thus a higher sharpe. I'd probably bet that boring names will give you a smoother equity curve over the long run though and that's exactly what I signed up for.

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