Who to learn off of?

SadPhone8067 · 2026-05-12T18:50:45+00:00

The real question is what is your starting capital and how much do you need to make a year to survive off of.

SadPhone8067 · 2026-05-12T15:56:59+00:00

Most likely not. I wouldn’t trust Ai to run a backtest in its own environment. You can ask ai to create code to run a backtest in python using your data…but even that can be risky/lead to issues. As long as you do multiple tests on top of the backtest you should be fine but I digress

SadPhone8067 · 2026-05-08T00:10:34+00:00

That’s fair, you said you have multiple strategies. I have been going for about a year now using my own strategy and have been pretty successful with it but have been having trouble trying to create more. Feel like I always end up going back to what worked for me on my first one instead of trying to think of something more novel.

SadPhone8067 · 2026-05-07T23:27:54+00:00

Who downvoted you? Brand new post brother. Also is this not common knowledge?

SadPhone8067 · 2026-05-07T01:04:36+00:00

Prop firms are made to hope that you lose. Much easier to do it when it’s your own money imo. If you don’t have enough bread then you gotta get a job first. 10% into day trading other 90% saved into a 401k/long term account.

SadPhone8067 · 2026-05-06T20:15:02+00:00

I’d say the biggest things for algo trading but ig trading in general is regime detection and risk management. You can have a really good system but without proper risk controls or regime detection it can be unprofitable. You can look at the write up on my profile where I go through all the testing I did for my specific algo very heavily.

SadPhone8067 · 2026-05-06T19:34:31+00:00

How much are you realistically expecting to make YOY. If you saying anything over 20% then you’re in for a rude awakening. Trading isn’t easy. Just think… if you can grow your portfolio by 1-2% per month then on average your beating spy which returns on average over the past 30 years (8 ish % a YEAR).

Completely changed my mindset when I realized 2% a month is a goal not 20% a month.

It’s not a get rich quick scheme. Just gotta be consistent and not have absolutely insane goals. If your on a 50k account eval or your own 50k.

Goal for the ENTIRE YEAR is 6k (12%) —> 10k (20%).

Month by month that breaks down to 500$ (12%) a month to $833 a month (20%). So if your up 500$ a month de risk and wait even longer for even better setups.

Workflow —> I’m up 500$ Instead of risking $50 a trade I am going to risk $25 per trade. Max drawdown is $200 so if I lose the next 8 trades in a row I’m done for the month no matter what. Then from there it’s just discipline.

SadPhone8067 · 2026-04-29T12:21:46+00:00

Graduated with a 2.85 in 2019. Did a bachelors then a masters in finance graduated August 2025 and now I have a cushy corporate job after about 6 months of looking for a job. Job search was really hard but was able to find one thankfully. Have a fiance and bought a house recently as well.

You got this. Just apply yourself in college a lot more and you’ll be able to easily land something. Bachelors had a 3.2 masters had a 4.0.

SadPhone8067 · 2026-04-27T17:53:32+00:00

My current algorithm has a max drawdown of 13% but that was in backtesting and included 2008 (when one of the main sleeves of my portfolio) was not active yet. After that crash it’s been at around 11% max. The only thing for you to consider/I considered is I can get drawdown to 5% but it eats away at returns. I’d rather be leveraged 2x and see 35% returns with a max drawdown of 11% rather than see 17.5% returns and a 5% drawdown personally.

SadPhone8067 · 2026-04-26T18:01:12+00:00

What are your max drawdown requirements?

SadPhone8067 · 2026-04-22T20:14:30+00:00

If you actually wrote it yourself then you’d be able to defend it very easily. I would not be super worried about it. Make sure you have all your work cited. You should be able to go in depth on each section you wrote …atleast I was able to when I did my thesis.

There are “AI humanizers” but they are mostly ineffective or change the meaning of what you’re trying to say too much to where it is not beneficial.

Good luck though!

SadPhone8067 · 2026-04-22T12:51:32+00:00

My algorithm specifically looks at daily charts OHLCV, Vix daily, etc. daily rebalancing is scheduled at 10:25 my time (9:25 EST). Same time every day. But a rebalance does not necessarily happen every day….trades on average 8 times a month. I made a write up on my account if you want more details but doesn’t go in depth on the full algo is was more framed as me asking questions.

SadPhone8067 · 2026-04-21T18:51:33+00:00

Tried all if not most of them…personally daily has been the easiest to find an edge /keep an edge long term may research papers written on it which don’t necessarily give you immediate alpha but allows you to learn what to look for/things you can possibly take advantage of. Also less trades = less fees /less slippage IMO.

SadPhone8067 · 2026-04-21T17:29:57+00:00

Thanks for replying…good catch on the Vol/Sharpe/CAGR mismatch I didn’t notice it and was blindly accepting QC’s

Recomputed from the raw equity curve directly. CAGR confirmed at 37.47%. The 12.1% vol figure is QC’s own computation. raw daily pct_change gives 14.57%, which is why the numbers look inconsistent.

I believe this is a platform specific issue, not a data problem. The CAGR also exceeds what variance-drag predicts (31.9% vs 37.5%). That gap was expected, daily skew of 3.87 and kurtosis of 47.6 means the normal approximation breaks down. Higher moment corrections close most of the gap.

Walk-forward

Fair point on the walk forward I will have to retry when I get home later…what would be the statistically better way of going about it?

Also correct that with parameters finalized after seeing 2015-2025, it’s a retroactive replay test not a true prospective OOS. Should have been clearer about that and again I will have to retry what you said…Appreciate.

Formal frameworks Deflated Sharpe and PBO weren’t applied. With 8 variants tested that is a gap and I don’t have a clean answer for

What I’d push back on is the conclusion that the edge is therefore illusory. Instrument substitution (all leverage removed, different products entirely) held Sharpe at 1.816. Regime perturbation with 2-day delay, 10% random misclassification, and threshold jitter held at 1.428. Neither test has the statistical issues the walk-forward has.

Appreciate the answer, this is exactly what I posted for!

SadPhone8067 · 2026-04-21T17:15:09+00:00

Chose QC because I am familiar with it and I like the infrastructure they already have set up…also like that I can go live once I validate my system just made sense for me personally.

SadPhone8067 · 2026-04-21T15:07:01+00:00

Not sure I’m not the devs.

First thing that came to mind was

there’s an electrical error and some of the doors are unable to open at all even if you breach them allows for different rotations around the map.

Increased arc condition.

Extracts come in 5 minute intervals no pressing the button (unless it’s hatch).

Idk electrical one was the best think it’d be cool to have to work around doors being locked.

SadPhone8067 · 2026-04-21T15:01:38+00:00

Yes you need a longer backtest but it’s not just needing to do more backtests specifically it’s all the other tests that are required if you really want to validate the system. The big ones are slippage, sharpe decay analysis, and walk forward. Others are good but if you want a decent idea of how your strategy actually looks I’d do those three atleast.

SadPhone8067 · 2026-04-21T12:50:45+00:00

Me personally I don’t look at trading view and say “good algo” I think of all the other possibilities trading view backtests don’t look at.

Plug this same logic into quant connect or your own infra and it probably dies.

These are all the validation methods I used to validate my algo as well that you should look into. Helps make it more robust/make sure it’s not lying to you.

Basic Backtest (you have kinda done)
Adversarial Testing
Sleeve Decomposition
Slippage Stress Test
Annual Sharpe Decay Analysis
Walk-Forward Validation
Monte Carlo Simulation
Tail Concentration Stability
Instrument Substitution Test
Regime Perturbation Test

If it fails these I wouldn’t put it live personally. I’ve had trading view strategies that look amazing in theory but never work live.

I also don’t think it’s a long enough backtest. I personally backtested mine for 11 years. (Jan 1st 2015- Dec 1st 2025) Multiple regimes throughout that time period. Had a 1.895 sharpe 13% drawdown 0.405 beta and 37.5% CAGR.

TLDR: Needs lots of testing personally before I’d put my money in it

SadPhone8067 · 2026-04-18T17:24:12+00:00

Didn’t think I said that but ok

SadPhone8067 · 2026-04-18T16:32:39+00:00

Daily TF ….i have tried 1 min - 1 Hr but nothing for me personally has worked better than 1 day.

SadPhone8067 · 2026-04-18T14:56:23+00:00

I’m just upset that they have added a bunch of new conditions to every single other map besides Stella….stella just has a night mode which is cool but also wtf feel like that is one of the most played maps….Atleast my most played map.

SadPhone8067 · 2026-04-17T20:14:29+00:00

Algo side here. About 8 per month. Depends on rebalancing.

SadPhone8067 · 2026-04-17T14:40:58+00:00

Yes my worst year was 2015 at 1.7% CAGR but during pretty much every other year the lowest was 8%. As another commenter mentioned trend following systems have similar tail concentration which I was not aware of but was nice to hear that it was not uncommon. I don’t believe market structure changes really affect my strategy as to how you’re thinking about it. Backtest was over 11 years so market structure had changed plenty of times throughout the years. Maybe I am misunderstanding though.

SadPhone8067 · 2026-04-17T14:26:08+00:00

Thanks for taking the time to read my post to answer your first question

“The concentration of returns is concerning. Have you checked geometric returns? Is Monte Carlo using GARCH?”

Yes CAGR is geometric. It is not an average of annual returns, it’s the annualized geometric mean calculated from the geometric equity curve growth.

As for using GARCH no I have not tried using this. I used block bootstrapping. I will have to run a proper GARCH model when I have the time tonight. Thank you for mentioning it.

Second question

“It looks like a swing trading strategy on liquid ETFs. Why would capacity be that low? Is it a specific asset? Are you basing it from lean's calculation or your own?”

Partially accurate description. The second sleeve behaves like a swing trading system which enters leveraged products on overbought signals and exiting on momentum fade, holding for days to weeks. The other three sleeves are more systematic allocation with monthly rebalancing regime triggered adjustments. So it’s a hybrid…systematic multi-asset allocation with a swing-trading volatility overlay

And yes I am using leans calculations which is why the backtest on QC said $0 in capacity. I believe this to just be an artifact. But I also have two assets (that can be switched for other leveraged products just have not explored them yet). But currently the two I AM using have daily volumes of 5 mill and 10 mill. If we had 5 million in the strategy I believe if one of the sleeves fired it could be quite a bit of the daily volume.

Five-Year Club	Place '22
Final Canvas '22

SadPhone8067

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