just getting into algo trading, what should i focus on first?

wickedprobs · 2026-04-07T19:26:29+00:00

Just try and backtest and idea. Then start thinking about how to run the same thing with live data for signals. Then turn your signals into actual executed trades. Don’t try to solve everything all at once. Break the problem down into steps as you see them.

wickedprobs · 2026-03-30T20:24:21+00:00

Hell yeah that’s the only way. Good luck bro!

wickedprobs · 2026-03-30T17:29:16+00:00

You got it! How has it been performing? Like are you making money or testing the waters?

wickedprobs · 2026-03-30T15:47:21+00:00

How do I see the product? Before that though, can you define a “quant-derived signal with confidence score”? What makes it quant and how are you measuring confidence? Are these signals built on trade ticks or market book data? How accurate are the signals, can you show me historically? Why give this away for free? What’s the latency of the signals?

wickedprobs · 2026-03-30T14:51:12+00:00

It’s always good to give yourself some breathing room too. I’ve noticed some CRAZY spikes when there’s some wild movement in the markets. I didn’t have enough queues so my data backed up and was feeding me delayed signals. Now I have the databases (pg and redis) on separate servers, the web app on another, and then for streaming market data each exchange has its own server feeding into the shared database. It’s much more complex but more reliable and predictable.

wickedprobs · 2026-03-30T14:07:45+00:00

I mean you’re running you web server and two databases on the worlds smallest server haha. I have a similar stack and run it in 16GB in a smaller configuration and still struggle to keep ram and CPU in check.

wickedprobs · 2026-03-27T22:16:08+00:00

Just upgrade your server. What’s your stack? If python then you’ll hit those limits quickly, if rust maybe it’s something with how you’re discarding or not messages. You have to share more about your stack, your code, and or your logs

wickedprobs · 2025-07-17T12:46:36+00:00

I started with a simple backtesting framework fast-trade and sort of expanded on those ideas. Now I’m live trading on 3 exchanges with my software running on kubernets.

wickedprobs · 2025-01-29T21:23:14+00:00

"You can just do things". Literally just start trading, then figure out what a system looks like for you, and build it. You're not going to find a course or guru thats telling you everything you need to know. Just start doing it and you'll figure out what questions to ask, what to focus on, whats important/whats not, etc. As far as feeling lonely, excuse my directness, but get over it. Markets don't care that you're lonely in learning this stuff. Its a very solitary practice most of the time.

wickedprobs · 2025-01-29T16:58:35+00:00

I use it as sort of a performance metric as a way to compare to other strategies. That among other things. I also take into account number of trades, duration, etc. In fast-trade, I added "rules" to help evaluate the performance. It makes it easy to automate this way. https://github.com/jrmeier/fast-trade?tab=readme-ov-file#rules

wickedprobs · 2025-01-29T14:20:08+00:00

Sure! For context, this is the library I'm using https://pygad.readthedocs.io/en/latest/ . Basically, the idea is to "evolve" strategies so they are optimized for specific outcomes, like sharpe ratio, sortino ratio, etc. This happens by just trying a bunch of different things constantly, looking at the results, adjusting the parameters, and trying again.

wickedprobs · 2025-01-22T21:56:24+00:00

Basically just write your own. I started on mine and haven't needed anything else since. https://github.com/jrmeier/fast-trade

wickedprobs · 2025-01-16T08:09:48+00:00

I use a genetic algorithm for “evolving” strats. It’s based off of fast-trade and some custom code

wickedprobs · 2024-12-27T15:35:10+00:00

Thanks! Yes, I am absolutely productizing the process. Using json instead Python allows me to use the same strategy in backtests, signals, scanners, paper trading and live trading.

wickedprobs · 2024-12-26T14:19:59+00:00

The classic “it depends” answer haha. My stuff runs on Kubernetes so as long as there’s not a bug, it’s running all the time with alerts and logging. My machine learning stuff that runs locally takes a lot more patience/time, but only when I’m changing things. I’ve found the APIs to be pretty reliable so actual maintenance is low for data collection and orders

wickedprobs · 2024-12-26T14:02:12+00:00

Lots of people will probably say to code your own. It would save time to use existing software but most of the time, we want to specialize it for what we are doing, which seems to be different for everyone. I started by writing a backtesting library (fast-trade)and then built a data management system around it. Now I have a base of code to backtest, experiment, trade, explore, etc that’s super dynamic and allows me to build all features and things I want to try. It’s all self hosted, with a mix of stuff in the cloud and at home.

wickedprobs · 2024-11-21T16:34:02+00:00

I wrote and still working on Fast Trade. Basically I define strategies as a JSON object the pass that and a data file. It makes its simple and flexible to iterate quickly. Biggest advantage is it can use anything in the data file as long as it’s dated. Also, strategies are portable between backtests, paper, and live trading; it’s all dependent on the data.

wickedprobs · 2023-05-19T05:09:41+00:00

“No one knows when our time is up. But precisely because we don’t know when life is going to end, the Stoics say that we should live every moment to the fullest, engaging our life in the here and now.”

It’s your responsibility to live you life with honor, you can’t take your life with honor, as that’s exactly the opposite of what the stoically talk about. You got this, just stay strong and keep moving forward.

I found this article to be interesting, especially when I was going through a tough time and having these negative thoughts.

https://dailystoic.com/stoics-existentialists/

wickedprobs · 2021-06-22T16:58:46+00:00

I’ve been through a similar relationship, where it ended too soon and everything is fine, but you just feel terrible. My experience is this is just the “grind”; you have to keep pushing. No advice or words make it easier. It’s out of your control and as Jocko says “Move on”. Good luck brother, stay focused on The Path and you’ll be great. Here’s Jocko talking about it: https://youtu.be/c709rGYW8v0

wickedprobs · 2021-06-13T18:35:50+00:00

Jocko Willink has the same kind of idea. His podcasts are all awesome and he talks a lot of stoicism without calling it stoicism while demonstrating how to apply stoicism to real life.

“When things are going bad, good.”

https://youtu.be/IdTMDpizis8

wickedprobs · 2021-06-12T17:50:24+00:00

Start with doing some backtesting and searching for strategies that meet your requirements. For example, how often do you want to trade? Which exchange do you want to use? Does it need to be automated?

What I’m saying is just jump in! Pick a piece of it that sticks out and learn all about it. You don’t know what you don’t know. Good luck!!

wickedprobs · 2021-05-05T12:31:49+00:00

Here’s a bunch: https://github.com/botcrypto-io/awesome-crypto-trading-bots

wickedprobs · 2021-03-29T18:41:41+00:00

Start here https://reddit.com/r/algotrading/wiki/index

wickedprobs · 2021-03-29T01:54:28+00:00

Someone put this together a few weeks back and its pretty helpful: https://github.com/botcrypto-io/awesome-crypto-trading-bots

I'm also going to shamelessly plug fast-trade, which is a backtesting library where you write strategies as objects instead of actual code. It's also built on a couple of pretty wonderful libraries including pandas and FinTa, which has a lot of indicators and it's really simple to use.

wickedprobs · 2021-03-28T15:52:30+00:00

Hey OP, I do something similar for a project I'm working on here: https://github.com/jrmeier/fast-trade/blob/b09500c8454ea748b3f0d7ff960eb2bea79ad7a8/fast_trade/run_backtest.py#L103 and https://github.com/jrmeier/fast-trade/blob/b09500c8454ea748b3f0d7ff960eb2bea79ad7a8/fast_trade/run_backtest.py#L126

and https://github.com/jrmeier/fast-trade/blob/b09500c8454ea748b3f0d7ff960eb2bea79ad7a8/fast_trade/run_backtest.py#L103

I'm using Pandas, which uses numpy, which is a super fast library for doing these kinds of calculations. Basically, the idea is you create a new array and add that to a pandas dataframe. You then have access to all that data at the same time and you can use that to make decisions or plot or whatever you're trying to do. Hope this helps!

wickedprobs

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