AI can help me place trades, but it can’t decide how much I’m willing to lose.
When I talk about AI trading, a few very practical questions come to mind first: How much capital can it use? When should it stop? If a trade loses money, can I find out why?
NeoTrade, part of @NeoSoulAI, builds these questions into its product design.
Users first set their strategy, capital limit, trading scope, and permissions. The Agent then researches information, decides whether to act, carries out authorized actions, and keeps a record of the process and results.
There’s one detail I particularly agree with: waiting and choosing not to act are also decisions an Agent can make. If no opportunity meets the criteria, it should be allowed to do nothing. Trading frequently just to prove it’s working can rack up fees fast.
NeoSoul also has another component, evoevo, which organizes information sources, decisions, results, and review data to support future evaluation and improvement. User data requires explicit authorization.
Why do I think this part is worth paying attention to?
Making money on a trade could mean the judgment was sound—or it could just mean the market happened to move in your favor. It’s hard to tell from a profit screenshot alone. Putting together the reasoning at the time, how the trade was executed, and what happened in the end is what makes it possible to evaluate a strategy.
That also explains why it’s starting with prediction markets: events have settlement rules and final outcomes, making it easier to check past decisions. Of course, a correct prediction doesn’t necessarily mean you’ll make money after trading costs.
Over the next year, I hope NeoSoul makes this process easier to use: ordinary people should be able to turn their trading ideas into strategies, understand the reasons behind each Agent action, and compare performance before and after making changes.
The clearer the records of losses, handling of anomalies, and differences between simulated and live trading, the better.
I’m willing to pay to save time spent watching the markets, researching, and reviewing trades. A trading Agent that follows constraints and keeps complete records gives me more reason to use it long term than a polished profit screenshot does.
#NeoSoul #AI交易
When I talk about AI trading, a few very practical questions come to mind first: How much capital can it use? When should it stop? If a trade loses money, can I find out why?
NeoTrade, part of @NeoSoulAI, builds these questions into its product design.
Users first set their strategy, capital limit, trading scope, and permissions. The Agent then researches information, decides whether to act, carries out authorized actions, and keeps a record of the process and results.
There’s one detail I particularly agree with: waiting and choosing not to act are also decisions an Agent can make. If no opportunity meets the criteria, it should be allowed to do nothing. Trading frequently just to prove it’s working can rack up fees fast.
NeoSoul also has another component, evoevo, which organizes information sources, decisions, results, and review data to support future evaluation and improvement. User data requires explicit authorization.
Why do I think this part is worth paying attention to?
Making money on a trade could mean the judgment was sound—or it could just mean the market happened to move in your favor. It’s hard to tell from a profit screenshot alone. Putting together the reasoning at the time, how the trade was executed, and what happened in the end is what makes it possible to evaluate a strategy.
That also explains why it’s starting with prediction markets: events have settlement rules and final outcomes, making it easier to check past decisions. Of course, a correct prediction doesn’t necessarily mean you’ll make money after trading costs.
Over the next year, I hope NeoSoul makes this process easier to use: ordinary people should be able to turn their trading ideas into strategies, understand the reasons behind each Agent action, and compare performance before and after making changes.
The clearer the records of losses, handling of anomalies, and differences between simulated and live trading, the better.
I’m willing to pay to save time spent watching the markets, researching, and reviewing trades. A trading Agent that follows constraints and keeps complete records gives me more reason to use it long term than a polished profit screenshot does.
#NeoSoul #AI交易
