Offshore
Video
Moon Dev
I feel soooo bad for those who bough Mac studios to run openclaw https://t.co/ASqsdkRSWc
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I feel soooo bad for those who bough Mac studios to run openclaw https://t.co/ASqsdkRSWc
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Offshore
Video
Moon Dev
amazon is going parabolic because of their anthropic exposure
but i think i found a stock with 10x the anthropic exposure https://t.co/eDOEYb07se
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amazon is going parabolic because of their anthropic exposure
but i think i found a stock with 10x the anthropic exposure https://t.co/eDOEYb07se
tweet
Offshore
Video
Moon Dev
3 Cents to Fail: The New Era of Zero-Risk Algorithmic Iteration
most traders are still fighting for crumbs while trying to outsmart an ocean of algorithms with their eyes closed but i just built a system that essentially sees every possible outcome simultaneously and plays them all at once. the reality of modern markets is that if you are not using code to leverage your time then you are just liquidity for someone who is.
i spent years of my life and hundreds of thousands of dollars on developers because i was convinced i could not learn to code myself but the pain of losing money to liquidations and overtrading finally pushed me over the edge. i realized that code is the great equalizer and once i started building my own bots the entire game changed from gambling to iteration.
you probably think you need a massive team and a wall street budget to run a swarm of ai agents that can research and code their own strategies in real time but the truth is actually much more interesting. i have been running nine different threads in parallel where each one is a distinct brain thinking about how to extract value from the market.
this swarm approach is the secret to moving faster than the rest of the world because while a human is stuck staring at one chart my system is researching a dozen ideas at the same time. it does not just think about the ideas though it actually writes the python code to backtest them and if the code fails it has a built in debugger that goes in and fixes it.
the most frustrating part of manual trading is the time it takes to validate if a strategy even has a chance of working over the long term. my new system runs every single idea against twenty five different data sources to ensure that we are not just looking at a fluke or a lucky streak.
we are looking for the absolute gold standard of metrics like sharpe ratios above four and consistent sortino scores that prove the strategy can handle volatility. the system automatically calculates the expected value and compares the return percentage against a simple buy and hold strategy so we know exactly where the edge is.
there is a ghost in the machine that most people miss which is the fact that these reasoning models have become so fast and inexpensive that the cost of failure is now near zero. in the past a failed dev project would cost me fifty grand and six months of my life but now a failed strategy costs me about three cents in api credits.
because the system is running in multiple threads it can hit my minimum target percentages much faster than any human could ever hope to. i have designed this to run all day and all night so it is constantly iterating and searching for the next breakthrough while i am out living my life.
the loop of research and testing and debugging is now fully automated which means the only thing left for me to do is sort through the winners. i am giving all of this away for free and keeping it open source because i believe that retail traders deserve to have the same weapons as the big institutions.
when you stop trying to be the best trader and start trying to build the best system you realize that the market is just a giant data problem waiting to be solved. i am going to keep pushing these updates and building live because i want to prove that anyone can do this if they are willing to put in the work.
the systems are trading for me now and the days of getting liquidated because of an emotional mistake are long gone. we are entering a new era of trading where the machines do the heavy lifting and the code is the only thing that separates the winners from the losers.
tweet
3 Cents to Fail: The New Era of Zero-Risk Algorithmic Iteration
most traders are still fighting for crumbs while trying to outsmart an ocean of algorithms with their eyes closed but i just built a system that essentially sees every possible outcome simultaneously and plays them all at once. the reality of modern markets is that if you are not using code to leverage your time then you are just liquidity for someone who is.
i spent years of my life and hundreds of thousands of dollars on developers because i was convinced i could not learn to code myself but the pain of losing money to liquidations and overtrading finally pushed me over the edge. i realized that code is the great equalizer and once i started building my own bots the entire game changed from gambling to iteration.
you probably think you need a massive team and a wall street budget to run a swarm of ai agents that can research and code their own strategies in real time but the truth is actually much more interesting. i have been running nine different threads in parallel where each one is a distinct brain thinking about how to extract value from the market.
this swarm approach is the secret to moving faster than the rest of the world because while a human is stuck staring at one chart my system is researching a dozen ideas at the same time. it does not just think about the ideas though it actually writes the python code to backtest them and if the code fails it has a built in debugger that goes in and fixes it.
the most frustrating part of manual trading is the time it takes to validate if a strategy even has a chance of working over the long term. my new system runs every single idea against twenty five different data sources to ensure that we are not just looking at a fluke or a lucky streak.
we are looking for the absolute gold standard of metrics like sharpe ratios above four and consistent sortino scores that prove the strategy can handle volatility. the system automatically calculates the expected value and compares the return percentage against a simple buy and hold strategy so we know exactly where the edge is.
there is a ghost in the machine that most people miss which is the fact that these reasoning models have become so fast and inexpensive that the cost of failure is now near zero. in the past a failed dev project would cost me fifty grand and six months of my life but now a failed strategy costs me about three cents in api credits.
because the system is running in multiple threads it can hit my minimum target percentages much faster than any human could ever hope to. i have designed this to run all day and all night so it is constantly iterating and searching for the next breakthrough while i am out living my life.
the loop of research and testing and debugging is now fully automated which means the only thing left for me to do is sort through the winners. i am giving all of this away for free and keeping it open source because i believe that retail traders deserve to have the same weapons as the big institutions.
when you stop trying to be the best trader and start trying to build the best system you realize that the market is just a giant data problem waiting to be solved. i am going to keep pushing these updates and building live because i want to prove that anyone can do this if they are willing to put in the work.
the systems are trading for me now and the days of getting liquidated because of an emotional mistake are long gone. we are entering a new era of trading where the machines do the heavy lifting and the code is the only thing that separates the winners from the losers.
tweet
Offshore
Photo
Moon Dev
my ai agents just secured 2 new homes (2 mac neos)
i will be running kimi 2.5 locally 24/7/365
you literally can't compete
i would have bought more but apples maxes you out at 2 https://t.co/7VgggL0Nvh
tweet
my ai agents just secured 2 new homes (2 mac neos)
i will be running kimi 2.5 locally 24/7/365
you literally can't compete
i would have bought more but apples maxes you out at 2 https://t.co/7VgggL0Nvh
tweet
Offshore
Video
Moon Dev
I’ll be the one to say it
If you bought a Mac Studio for openclaw
You are cooked https://t.co/hzq1N0yatm
tweet
I’ll be the one to say it
If you bought a Mac Studio for openclaw
You are cooked https://t.co/hzq1N0yatm
tweet
Moon Dev
Claude Chrome Built My WW3 Trading Bot
While everyone is debating on openclaw this and that
me and claude are trading ww3 https://t.co/FPn5kZSBBY
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Claude Chrome Built My WW3 Trading Bot
While everyone is debating on openclaw this and that
me and claude are trading ww3 https://t.co/FPn5kZSBBY
tweet
Moon Dev
The AI Alpha Machine: Using Claude Code to Turn 10 Years of Data Into Winning Strategies
if you are still staring at charts and wondering where the next move is going you are essentially bringing a knife to a gunfight in a world where ai just turned the holy grail into a copy paste operation. most traders think they are one indicator away from wealth but they are actually just one workflow away from sanity. i spent years losing money to liquidations and overtrading before i realized that the only way out was to automate everything through code
the title of this story is not some clickbait promise because finding winning strategies finally became easy once i stopped trying to be right and started trying to be fast. i used to spend hundreds of thousands on developers for apps because i thought i would never be able to code myself. now i believe code is the great equalizer because it allows a single person to iterate to success without getting liquidated by emotions
most people spend weeks coding a single bot only to realize it fails on every timeframe except the one they cherry picked for their test. i decided to open a loop and figure out if an ai could build a universal runner that tests every strategy on every dataset i own at once. this is the secret to finding strategies that actually have an edge instead of just finding random noise in the market
the process of automating your trading always starts with my rbi system which stands for research backtest and implement. you have to research the strategies in books or through alpha generation techniques before you even touch a line of code. if you just sit there and guess you will eventually get caught up by the market and lose everything you have worked for
on a recent saturday morning i sat down with claude code to build something that i think is the most revolutionary thing i have ever created. i needed a way to test a single idea across thirty different markets and timeframes in less than four seconds. up until this point i was manually swapping out data files which was a massive waste of energy and time
we created a comprehensive multi data backtest template system that can test any strategy on ten plus data sources automatically. currently it is configured with twenty eight different datasets including bitcoin ethereum solana and traditional stocks like nvidia. this allows me to see the truth of a strategy across one minute five minute and daily timeframes all in one go
one of the strategies we put through this machine is called consecutive down which is a long only model based on mean reversion. the logic is simple because it looks for four consecutive bars moving downward and then enters a trade to catch the bounce. i wanted to see if adding indicators like adx or the kaufman filter would actually help the performance
we built five different versions of this strategy including ones that use mfi and vwap to see which one holds up across the board. it is one thing to see a strategy work on a one hour chart but it is another thing to see it perform across ten years of daily data. by the end of this session we closed the loop on the universal runner and created a system that outputs eighteen different metrics per dataset
if you want to be a data dog you have to realize that most traders are just gamblers wearing a suit. a real data dog does not care about being right about the next move because they only care about the expectancy of their system. we are looking for an expectancy of over zero point nine two and sharp ratios that indicate we are not taking insane risks
the multi data tester is slick because it handles all the different headers from coinbase and yahoo finance automatically. i used to struggle with formatting data for hours but now the ai just builds a universal loader that cleans everything up. this means i can focus on the actual logic of the strategy instead of fighting with csv files all day long
i am going to open another loop here and talk about why most [...]
The AI Alpha Machine: Using Claude Code to Turn 10 Years of Data Into Winning Strategies
if you are still staring at charts and wondering where the next move is going you are essentially bringing a knife to a gunfight in a world where ai just turned the holy grail into a copy paste operation. most traders think they are one indicator away from wealth but they are actually just one workflow away from sanity. i spent years losing money to liquidations and overtrading before i realized that the only way out was to automate everything through code
the title of this story is not some clickbait promise because finding winning strategies finally became easy once i stopped trying to be right and started trying to be fast. i used to spend hundreds of thousands on developers for apps because i thought i would never be able to code myself. now i believe code is the great equalizer because it allows a single person to iterate to success without getting liquidated by emotions
most people spend weeks coding a single bot only to realize it fails on every timeframe except the one they cherry picked for their test. i decided to open a loop and figure out if an ai could build a universal runner that tests every strategy on every dataset i own at once. this is the secret to finding strategies that actually have an edge instead of just finding random noise in the market
the process of automating your trading always starts with my rbi system which stands for research backtest and implement. you have to research the strategies in books or through alpha generation techniques before you even touch a line of code. if you just sit there and guess you will eventually get caught up by the market and lose everything you have worked for
on a recent saturday morning i sat down with claude code to build something that i think is the most revolutionary thing i have ever created. i needed a way to test a single idea across thirty different markets and timeframes in less than four seconds. up until this point i was manually swapping out data files which was a massive waste of energy and time
we created a comprehensive multi data backtest template system that can test any strategy on ten plus data sources automatically. currently it is configured with twenty eight different datasets including bitcoin ethereum solana and traditional stocks like nvidia. this allows me to see the truth of a strategy across one minute five minute and daily timeframes all in one go
one of the strategies we put through this machine is called consecutive down which is a long only model based on mean reversion. the logic is simple because it looks for four consecutive bars moving downward and then enters a trade to catch the bounce. i wanted to see if adding indicators like adx or the kaufman filter would actually help the performance
we built five different versions of this strategy including ones that use mfi and vwap to see which one holds up across the board. it is one thing to see a strategy work on a one hour chart but it is another thing to see it perform across ten years of daily data. by the end of this session we closed the loop on the universal runner and created a system that outputs eighteen different metrics per dataset
if you want to be a data dog you have to realize that most traders are just gamblers wearing a suit. a real data dog does not care about being right about the next move because they only care about the expectancy of their system. we are looking for an expectancy of over zero point nine two and sharp ratios that indicate we are not taking insane risks
the multi data tester is slick because it handles all the different headers from coinbase and yahoo finance automatically. i used to struggle with formatting data for hours but now the ai just builds a universal loader that cleans everything up. this means i can focus on the actual logic of the strategy instead of fighting with csv files all day long
i am going to open another loop here and talk about why most [...]