I'm building a crypto trading bot that you can follow live on Telegram

Hacker News

Hi HN! For the last few weeks I've been building an algotrading bot based on the Supertrend indicator. It's a trend-following bot that uses the Supertrend lines as support/resistances to enter long/short trades and it's currently running in simulated mode (not real money) on all Binance futures pairs. I've written a somewhat detailed write-up about the strategy here: https://ailef.tech/2021/05/20/im-building-a-cryptocurrency-trading-bot-that-you-can-follow-live-on-telegram/ The cool thing about the bot is that he reports everything on his Telegram channel: https://t.me/traderino He periodically reports his current open positions, closed positions recap and PNL plots so I can monitor what he's doing all the time. The channel is public as well, so if somebody is interested you can just join! Even though it's trading with fake money I think it's really cool to observe its behaviour and it was a fun project to build (still working on it, nowhere near finished), so I thought I would share. Happy to hear any question or feedback!

Visit product View on Hacker NewsMay 20, 2021

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

57%57% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

46%46% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: trading · Missing: mobile apps, ios, personal

41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

27%27% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: open · Missing: mac, agents, macos

11%11% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: crypto, cryptocurrency · Missing: web3, chat, make money

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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