CryptoPainter
CryptoPainter
An old friend calls me a "painter", technical/data analysis and quantitative trading, providing various tricky angles to see the market, and using time to leverage. The real account is an agent account, a self-evolving strategy system is being tested, please do not copy!
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Spent 2 hours buying a domain and made a Dashboard on the website with all Agent's trading data...
Today is a bit interesting, the strategy positions are all short, let's see if there's hope to dump some altcoins on Friday. Currently, Agent's overall account has already lost 8%, sigh...
If there's anyone to blame, it's me for constantly changing features and fixing bugs every day. Previously, I optimized strategies using backtest data, but this time I want to try pre-testing with live trading data...
The former has perfect backtest data but performs poorly in live trading; the latter performs poorly in live trading but with continuous optimization, the strategy is getting better and better...
I won't disclose the website domain for now, I'm a bit worried about security measures. I'll wait until Claude audits it for me and the strategy starts making profits before saying more...
G... Genetic algorithms really aren't suitable for running locally, the alien laptop broke down...
It was originally used as a development environment for Lobster, didn't expect this...
Luckily, all projects are synced to GitHub, will see how to migrate them to the server to run later...
So exhausting... Now there's really no way to update...
CryptoPainter
Someone asked me why I haven't updated that "genetic algorithm" engine?
I actually want to update it!
After setting up the framework and perfecting the features, the next step is full-scale training. But the problem is, look at the log below: training one tree requires 80 iterations, nearly 1 hour. There are 6 trees in one Forward window, and the entire sample set is divided into 6 windows for Walk Forward...
1h x 6 x 6 = 36h, and this is only the first layer of volume-price data training. After that, it moves on to the macro data layer, and finally the futures, on-chain, and other Alt-Data layers. Running all of this probably takes about 3 days...
And the most, most, most critical issue is that, when luck is bad, the factors randomly injected into the factor library fail to hybridize into excellent expressions, resulting in the current screen full of "Failed" statuses. This means the trained factors perform well in-sample but fail out-of-sample...
These are basically overfitted factors and get directly PASSED...
For a whole week, I've been stuck in this tedious loop, feeling like my alien laptop is going to be wrecked sooner or later...
So, it's really not that I don't want to update, it's just that I honestly have nothing to update...
Someone asked me why I haven't updated that "genetic algorithm" engine?
I actually want to update it!
After setting up the framework and perfecting the features, the next step is full-scale training. But the problem is, look at the log below: training one tree requires 80 iterations, nearly 1 hour. There are 6 trees in one Forward window, and the entire sample set is divided into 6 windows for Walk Forward...
1h x 6 x 6 = 36h, and this is only the first layer of volume-price data training. After that, it moves on to the macro data layer, and finally the futures, on-chain, and other Alt-Data layers. Running all of this probably takes about 3 days...
And the most, most, most critical issue is that, when luck is bad, the factors randomly injected into the factor library fail to hybridize into excellent expressions, resulting in the current screen full of "Failed" statuses. This means the trained factors perform well in-sample but fail out-of-sample...
These are basically overfitted factors and get directly PASSED...
For a whole week, I've been stuck in this tedious loop, feeling like my alien laptop is going to be wrecked sooner or later...
So, it's really not that I don't want to update, it's just that I honestly have nothing to update...
CryptoPainter
While researching new strategies for the Agent and configuring a pure algorithmic state machine, I suddenly realized this mechanism could also be applied to the previous ASR strategy. So I hurriedly started modifying the code, and then I was moved to tears...
An old strategy that hadn’t been successfully optimized forward for a whole year suddenly came back to life!
As for the specific changes, it’s just using the state machine to record market volatility in real time, then fine-tuning the volatility into the original strategy’s parameters. Altogether, it’s less than 20 lines of code, but it made the original ASR channel differ in many subtle details...
The overall return of the 5-year BTC strategy improved by over 75%, while the maximum drawdown decreased by 14%!!!
Previously, when researching pure algorithmic quantification, I looked down on state machines. Only when it truly produced positive optimization effects did I realize how great it is...
I guess an updated version can be released soon!
It’s really been so tough...
While researching new strategies for the Agent and configuring a pure algorithmic state machine, I suddenly realized this mechanism could also be applied to the previous ASR strategy. So I hurriedly started modifying the code, and then I was moved to tears...
An old strategy that hadn’t been successfully optimized forward for a whole year suddenly came back to life!
As for the specific changes, it’s just using the state machine to record market volatility in real time, then fine-tuning the volatility into the original strategy’s parameters. Altogether, it’s less than 20 lines of code, but it made the original ASR channel differ in many subtle details...
The overall return of the 5-year BTC strategy improved by over 75%, while the maximum drawdown decreased by 14%!!!
Previously, when researching pure algorithmic quantification, I looked down on state machines. Only when it truly produced positive optimization effects did I realize how great it is...
I guess an updated version can be released soon!
It’s really been so tough...
Recently, I've noticed that all the major exchanges have launched Pre-IPO markets???
So why was there a bunch of people criticizing @MSX_CN when they first started this Pre-IPO thing???
Now all exchanges, whether it's tokens or contracts, have it and you guys are praising it???
Really strange...
To some extent, it also shows that the market is gradually recognizing:
Participating on-chain in primary/Pre-IPO assets is itself part of the future of financial product innovation...
Many innovations are like this. At the beginning, everyone sees "something unfamiliar"...
Only when more and more people join does the industry start to realize its value...
Now the whole industry is exploring in this direction, which is actually a good thing. At least it shows the market is moving towards a richer, more open asset system.
The staking rewards of $BILL have already reached 12,200 tokens, with an airdrop value of $200,000 and staking rewards worth over 2,000 U. The feeling of on-paper wealth is really good...
Recently, I've seen quite a few people getting restless and wanting to short, so I still plan to watch the show. The situation with @billions_ntwk is very clear right now—if anyone dares to short, they definitely won't get away unscathed...
There are still 6 months until unlocking, and without a 10x margin for hedging, there's simply no such thing as risk-free cashing out...
So, I'll keep watching the show. The best approach is to wait. I had AI model analyze the extreme price prediction based on the unlocking time, and it says $2~3...
The price ceiling depends on when the shorting funds run dry, and the trend reversal depends on when a large amount of retail funds go long. Clearly, this is no longer the project team controlling the market; there are proactive market makers who have figured out this supply-demand model operating behind the scenes...
In other words, you might be anxious holding a bunch of locked tokens, but the project team might be even more anxious...😂
