I’ve been doing news-based trading for a while, and the thing that has always frustrated me most is the same: by the time I finish reading a headline, decide whether it’s good or bad, and figure out which stock it actually affects, the window is already gone.

So I started looking for a tool that could help me make faster decisions, and I eventually found a news API. I’m sharing it because it has saved me a lot of time, and I’m sure there are plenty of people like me who have the same problem. This could solve it for a lot of traders.

Here’s what the API mainly does:

• Pulls in news as soon as it comes out.
• Scores the sentiment for you. Each headline is labeled as positive, negative, or neutral, and it also marks the urgency level. A routine update and a true breaking-news alert are completely different things.
• The part I actually care about most: it tells you which stock the news affects. Not just “market sentiment is tense,” but “this news is clearly bearish for TSLA.” That’s the difference between noise and a tradable signal.

So what you get looks something like: breaking news → bearish → TSLA. Very useful.

I’m honestly not much of a coder, but even I was able to get it running. A normal request can pull the latest news, and if you want updates the moment they happen, you can use the real-time stream. Higher tiers also provide stock-level sentiment, plus semantic search across historical news for backtesting.

I’m not affiliated with them at all. I just found it useful and thought this subreddit might appreciate it. Here’s the API: https://tradingnews.press/

By the way, how do you all optimize your workflow for news-based trading?

Playable Link: aiworldcup.game

Platform: Window, Web, phone

Description: Over the past couple of days, I discovered an AI World Cup game. After playing it, I realized that these AI players, without any prior training, had learned advanced moves on their own, such as passing, pressing, feints, and other complex techniques.

The AIs can even come up with their own tactics, with no need for me to intervene at all. All I have to do is watch them play soccer, which is actually pretty fun.

Free to Play Status:

• Free to play

Involvement: dev

https://preview.redd.it/izcpmpbu7k9h1.jpg?width=928&format=pjpg&auto=webp&s=e8ff4d45ab62307b26f148d89dab8ab3920abb1f

I’ve recently been working on news-driven trading. The goal is simple: the moment a piece of news breaks, my program should receive it immediately — and in a structured format that can be used directly.

Sounds straightforward, right? In practice, I ran into a bunch of pitfalls. So I’m writing this down: the problems I hit, and the solution I eventually settled on.

Don’t Use REST Polling. Use WebSocket.

At first, I used free REST APIs and polled them every few seconds.

The result:

• Slow: your polling interval becomes your minimum latency. By the time your next request returns, the price may have already moved.
• Rate limits: too many API calls can easily get you throttled.
• Messy data: you often get a pile of semi-structured headlines and have to clean HTML, normalize timestamps, and parse everything yourself.

For something event-driven like real-time news, push is the right model.

With a persistent WebSocket connection, the server pushes the news to you the moment it happens. I later switched to TradingNews, and the notes below are based on that experience.

You can think of WebSocket as a phone line that stays open between you and the news source. The moment news breaks, the server speaks directly through that line instead of waiting for you to keep asking, “Anything new yet?”

Latency goes from “tens of seconds” to “almost instant.”

Connecting to that line only takes a few lines of code. The hard part is everything nobody tells you in advance.

Pitfalls I Ran Into

1. The connection will drop — and it won’t come back by itself.

A small network hiccup or a server restart can break the connection.

Your program needs to reconnect automatically. But you also don’t want it to reconnect aggressively in a tight loop, because that can overload both your system and the server.

The right approach is exponential backoff: each retry waits a little longer than the last one.

2. After reconnecting, old news may flood in all at once.

This was the biggest trap.

When the connection comes back, some services will replay all the news you missed while disconnected. If you don’t handle this properly, your program can suddenly get flooded with dozens of stale messages.

Even worse, you might end up trading on old news.

The fix is simple: every news item comes with a publish timestamp. If it’s too old, discard it. Only act on truly fresh events.

3. Don’t grind away building your own sentiment model.

At first, I thought I needed to train my own model to decide whether a headline was bullish or bearish.

Later I realized that a good news stream already gives you this information directly. Each message can include things like urgency and whether the news is bullish or bearish.

That almost saved me from wasting a month.

4. Don’t let one bad message kill the whole stream.

Every now and then, you may receive a malformed message.

If your handler is too fragile, one bad payload can crash the entire program. The better approach is simple: skip the bad message, log it, and keep listening for the next one.

Getting Started Is Actually Pretty Easy

Once you handle the pitfalls above, the whole “receive real-time news” setup is only a few dozen lines of code. You can get it working in an afternoon.

And the two hardest questions — “Is this urgent?” and “Is this bullish or bearish?” — can already be included in the data, which saves a lot of work.

The real challenge is not getting the news into your system.
The real challenge is what you do after you receive it.

Summary

The hard part of real-time financial news is not access. It’s reconnection, filtering stale messages, and making sure old news doesn’t overwhelm your system.

I’ve personally run into most of the pitfalls above.

Curious to hear from others: what issues have you run into when building real-time news or event streams? What sources are you using?

TradingNews: https://tradingnews.press/

https://preview.redd.it/u3y2zxamzd9h1.jpg?width=2742&format=pjpg&auto=webp&s=535ca04ee8b522ca2ee7a08132ec15bc03b4f42b

I’ve recently been working on news-driven trading. The goal is simple: the moment a piece of news breaks, my program should receive it immediately — and in a structured format that can be used directly.

Sounds straightforward, right? In practice, I ran into a bunch of pitfalls. So I’m writing this down: the problems I hit, and the solution I eventually settled on.

Don’t Use REST Polling. Use WebSocket.

At first, I used free REST APIs and polled them every few seconds.

The result:

• Slow: your polling interval becomes your minimum latency. By the time your next request returns, the price may have already moved.
• Rate limits: too many API calls can easily get you throttled.
• Messy data: you often get a pile of semi-structured headlines and have to clean HTML, normalize timestamps, and parse everything yourself.

For something event-driven like real-time news, push is the right model.

With a persistent WebSocket connection, the server pushes the news to you the moment it happens. I later switched to TradingNews, and the notes below are based on that experience.

You can think of WebSocket as a phone line that stays open between you and the news source. The moment news breaks, the server speaks directly through that line instead of waiting for you to keep asking, “Anything new yet?”

Latency goes from “tens of seconds” to “almost instant.”

Connecting to that line only takes a few lines of code. The hard part is everything nobody tells you in advance.

Pitfalls I Ran Into

1. The connection will drop — and it won’t come back by itself.

A small network hiccup or a server restart can break the connection.

Your program needs to reconnect automatically. But you also don’t want it to reconnect aggressively in a tight loop, because that can overload both your system and the server.

The right approach is exponential backoff: each retry waits a little longer than the last one.

2. After reconnecting, old news may flood in all at once.

This was the biggest trap.

When the connection comes back, some services will replay all the news you missed while disconnected. If you don’t handle this properly, your program can suddenly get flooded with dozens of stale messages.

Even worse, you might end up trading on old news.

The fix is simple: every news item comes with a publish timestamp. If it’s too old, discard it. Only act on truly fresh events.

3. Don’t grind away building your own sentiment model.

At first, I thought I needed to train my own model to decide whether a headline was bullish or bearish.

Later I realized that a good news stream already gives you this information directly. Each message can include things like urgency and whether the news is bullish or bearish.

That almost saved me from wasting a month.

4. Don’t let one bad message kill the whole stream.

Every now and then, you may receive a malformed message.

If your handler is too fragile, one bad payload can crash the entire program. The better approach is simple: skip the bad message, log it, and keep listening for the next one.

Getting Started Is Actually Pretty Easy

Once you handle the pitfalls above, the whole “receive real-time news” setup is only a few dozen lines of code. You can get it working in an afternoon.

And the two hardest questions — “Is this urgent?” and “Is this bullish or bearish?” — can already be included in the data, which saves a lot of work.

The real challenge is not getting the news into your system.
The real challenge is what you do after you receive it.

Summary

The hard part of real-time financial news is not access. It’s reconnection, filtering stale messages, and making sure old news doesn’t overwhelm your system.

I’ve personally run into most of the pitfalls above.

Curious to hear from others: what issues have you run into when building real-time news or event streams? What sources are you using?

TradingNews: https://tradingnews.press/

https://preview.redd.it/xgch0bfizd9h1.jpg?width=2742&format=pjpg&auto=webp&s=a2dd68862115e9b6f82378b238fceda75197387d

I’ve recently been working on news-driven trading. The goal is simple: the moment a piece of news breaks, my program should receive it immediately — and in a structured format that can be used directly.

Sounds straightforward, right? In practice, I ran into a bunch of pitfalls. So I’m writing this down: the problems I hit, and the solution I eventually settled on.

Don’t Use REST Polling. Use WebSocket.

At first, I used free REST APIs and polled them every few seconds.

The result:

• Slow: your polling interval becomes your minimum latency. By the time your next request returns, the price may have already moved.
• Rate limits: too many API calls can easily get you throttled.
• Messy data: you often get a pile of semi-structured headlines and have to clean HTML, normalize timestamps, and parse everything yourself.

For something event-driven like real-time news, push is the right model.

With a persistent WebSocket connection, the server pushes the news to you the moment it happens. I later switched to TradingNews, and the notes below are based on that experience.

You can think of WebSocket as a phone line that stays open between you and the news source. The moment news breaks, the server speaks directly through that line instead of waiting for you to keep asking, “Anything new yet?”

Latency goes from “tens of seconds” to “almost instant.”

Connecting to that line only takes a few lines of code. The hard part is everything nobody tells you in advance.

Pitfalls I Ran Into

1. The connection will drop — and it won’t come back by itself.

A small network hiccup or a server restart can break the connection.

Your program needs to reconnect automatically. But you also don’t want it to reconnect aggressively in a tight loop, because that can overload both your system and the server.

The right approach is exponential backoff: each retry waits a little longer than the last one.

2. After reconnecting, old news may flood in all at once.

This was the biggest trap.

When the connection comes back, some services will replay all the news you missed while disconnected. If you don’t handle this properly, your program can suddenly get flooded with dozens of stale messages.

Even worse, you might end up trading on old news.

The fix is simple: every news item comes with a publish timestamp. If it’s too old, discard it. Only act on truly fresh events.

3. Don’t grind away building your own sentiment model.

At first, I thought I needed to train my own model to decide whether a headline was bullish or bearish.

Later I realized that a good news stream already gives you this information directly. Each message can include things like urgency and whether the news is bullish or bearish.

That almost saved me from wasting a month.

4. Don’t let one bad message kill the whole stream.

Every now and then, you may receive a malformed message.

If your handler is too fragile, one bad payload can crash the entire program. The better approach is simple: skip the bad message, log it, and keep listening for the next one.

Getting Started Is Actually Pretty Easy

Once you handle the pitfalls above, the whole “receive real-time news” setup is only a few dozen lines of code. You can get it working in an afternoon.

And the two hardest questions — “Is this urgent?” and “Is this bullish or bearish?” — can already be included in the data, which saves a lot of work.

The real challenge is not getting the news into your system.
The real challenge is what you do after you receive it.

Summary

The hard part of real-time financial news is not access. It’s reconnection, filtering stale messages, and making sure old news doesn’t overwhelm your system.

I’ve personally run into most of the pitfalls above.

Curious to hear from others: what issues have you run into when building real-time news or event streams? What sources are you using?

TradingNews: https://tradingnews.press/

First, the conclusion: news can affect prices. The real question is: can you make money from news? And whether you can or not comes down to three things.

1. Timeliness

The market does not price in news instantly. There is a window between "the news happens" and "the price has fully moved" — and that window is your opportunity.

If your news feed relies on minute-level polling, forwarded push alerts, or watching an app, then you're not really trading the news. You're trading the result.

Compressing latency from tens of seconds down to milliseconds — WebSocket real-time push vs REST polling — is what actually puts you inside that window.

2. Accuracy: Dirty Data = False Signals

Fast but messy is useless.

Semi-structured headlines, missing timestamps, and vague sentiment only make your strategy fire randomly into noise.

Usable data needs to be structured, calibrated, and precisely timestamped: urgency, sentiment, and published_at precise enough to measure how much faster you are than the market.

What you need is clean input, not "parse it yourself and good luck."

3. Filtering and Judgment: Most News Is Noise

99% of all news has nothing to do with your current trade.

The hard part is not "getting all the news." The hard part is knowing which few items actually matter right now.

Urgency classification, deduplication, and relevance filtering are what turn news into a signal.

News data can indeed create an edge, but only if it is fast enough, clean enough, and properly filtered.

At its core, you need real-time WebSocket delivery for timeliness, structured fields for accuracy, and urgency/deduplication for filtering — so you can focus your attention on judgment and risk control.

So far, I’ve only found one API that meets all three requirements. 

First, the conclusion: news can affect prices. The real question is: can you make money from news? And whether you can or not comes down to three things.

1. Timeliness

The market does not price in news instantly. There is a window between "the news happens" and "the price has fully moved" — and that window is your opportunity.

If your news feed relies on minute-level polling, forwarded push alerts, or watching an app, then you're not really trading the news. You're trading the result.

Compressing latency from tens of seconds down to milliseconds — WebSocket real-time push vs REST polling — is what actually puts you inside that window.

2. Accuracy: Dirty Data = False Signals

Fast but messy is useless.

Semi-structured headlines, missing timestamps, and vague sentiment only make your strategy fire randomly into noise.

Usable data needs to be structured, calibrated, and precisely timestamped: urgency, sentiment, and published_at precise enough to measure how much faster you are than the market.

What you need is clean input, not "parse it yourself and good luck."

3. Filtering and Judgment: Most News Is Noise

99% of all news has nothing to do with your current trade.

The hard part is not "getting all the news." The hard part is knowing which few items actually matter right now.

Urgency classification, deduplication, and relevance filtering are what turn news into a signal.

News data can indeed create an edge, but only if it is fast enough, clean enough, and properly filtered.

At its core, you need real-time WebSocket delivery for timeliness, structured fields for accuracy, and urgency/deduplication for filtering — so you can focus your attention on judgment and risk control.

So far, I’ve only found one API that meets all three requirements.

https://preview.redd.it/g2b2o5aqm59h1.jpg?width=2856&format=pjpg&auto=webp&s=9398337ed9fcbb728df31b6b7a4193a43a70c46f

https://preview.redd.it/51fcy0ge419h1.jpg?width=2856&format=pjpg&auto=webp&s=ac3615d0374238cc9687769d05addb8173005107

First, the conclusion: news can affect prices. The real question is: can you make money from news? And whether you can or not comes down to three things.

1. Timeliness

The market does not price in news instantly. There is a window between "the news happens" and "the price has fully moved" — and that window is your opportunity.

If your news feed relies on minute-level polling, forwarded push alerts, or watching an app, then you're not really trading the news. You're trading the result.

Compressing latency from tens of seconds down to milliseconds — WebSocket real-time push vs REST polling — is what actually puts you inside that window.

2. Accuracy: Dirty Data = False Signals

Fast but messy is useless.

Semi-structured headlines, missing timestamps, and vague sentiment only make your strategy fire randomly into noise.

Usable data needs to be structured, calibrated, and precisely timestamped: urgency, sentiment, and published_at precise enough to measure how much faster you are than the market.

What you need is clean input, not "parse it yourself and good luck."

3. Filtering and Judgment: Most News Is Noise

99% of all news has nothing to do with your current trade.

The hard part is not "getting all the news." The hard part is knowing which few items actually matter right now.

Urgency classification, deduplication, and relevance filtering are what turn news into a signal.

News data can indeed create an edge, but only if it is fast enough, clean enough, and properly filtered.

At its core, you need real-time WebSocket delivery for timeliness, structured fields for accuracy, and urgency/deduplication for filtering — so you can focus your attention on judgment and risk control.

So far, I’ve only found one API that meets all three requirements. Sharing it here for free: https://tradingnews.press/

I've gone through the phase most traders go through: too many indicators, too many data sources, too many inputs pulling me in different directions during market hours. At some point, I realized I was spending more time managing information than managing my actual positions.

So I cut everything back and simplified.

Now, the only external input I keep for handling news intraday is TradingNews. The rule is simple: if a breaking tag hits on something I'm holding, and the per-ticker sentiment for that position turns negative, I close.

That's it.

Does that mean I always make the right call? No. Plenty of times, I've closed a position and nothing happened. Holding would have been fine. Someone with better intuition or more experience might have held and made money. I'm not saying this is the optimal strategy for maximizing returns.

What I'm really saying is this: it helps me remove a specific kind of bad decision-making that used to cost me.

The problem it solves isn't "how do I make more money?" It's "how do I avoid making subjective decisions about an open position when I'm already naturally biased toward holding it?" Those are two completely different problems.

When a geopolitical headline suddenly drops and you're already in a trade, you're not objective. Your instinct is to look for reasons to stay in. A pre-committed rule takes away that entire space for hesitation and self-persuasion.

What makes this approach actually usable is per-ticker sentiment, not just article-level sentiment. A headline about Eastern Europe might be noise for most of my positions, but genuinely relevant to one specific ticker. Article-level sentiment doesn't give you that level of granularity.

I had this happen last week: I was holding a position when a breaking story about the Eastern Europe situation came out intraday. My ticker sentiment turned negative. I closed immediately. That ticker kept dropping through the day before eventually recovering.

Maybe I missed some profit by not re-entering. But I wasn't sitting there underwater for hours, constantly second-guessing myself. And that mental clarity affected the rest of my trading day.

This kind of strategy isn't for everyone, but it works for me.

The news source I use: https://tradingnews.press/

I've gone through the phase most traders go through: too many indicators, too many data sources, too many inputs pulling me in different directions during market hours. At some point, I realized I was spending more time managing information than managing my actual positions.

So I cut everything back and simplified.

Now, the only external input I keep for handling news intraday is TradingNews. The rule is simple: if a breaking tag hits on something I'm holding, and the per-ticker sentiment for that position turns negative, I close.

That's it.

Does that mean I always make the right call? No. Plenty of times, I've closed a position and nothing happened. Holding would have been fine. Someone with better intuition or more experience might have held and made money. I'm not saying this is the optimal strategy for maximizing returns.

What I'm really saying is this: it helps me remove a specific kind of bad decision-making that used to cost me.

The problem it solves isn't "how do I make more money?" It's "how do I avoid making subjective decisions about an open position when I'm already naturally biased toward holding it?" Those are two completely different problems.

When a geopolitical headline suddenly drops and you're already in a trade, you're not objective. Your instinct is to look for reasons to stay in. A pre-committed rule takes away that entire space for hesitation and self-persuasion.

What makes this approach actually usable is per-ticker sentiment, not just article-level sentiment. A headline about Eastern Europe might be noise for most of my positions, but genuinely relevant to one specific ticker. Article-level sentiment doesn't give you that level of granularity.

I had this happen last week: I was holding a position when a breaking story about the Eastern Europe situation came out intraday. My ticker sentiment turned negative. I closed immediately. That ticker kept dropping through the day before eventually recovering.

Maybe I missed some profit by not re-entering. But I wasn't sitting there underwater for hours, constantly second-guessing myself. And that mental clarity affected the rest of my trading day.

This kind of strategy isn't for everyone, but it works for me.

The news source I use: https://tradingnews.press/

https://preview.redd.it/snts01hgsy7h1.jpg?width=2874&format=pjpg&auto=webp&s=f19ddc338ed5156b01721eb5138774fed0afd750

I’ve recently been building a news-driven trading bot, and I was convinced that its core had to be sentiment judgment: is this news bullish or bearish, and how strong is the signal?

So I built my own sentiment classifier. I automatically collected news, manually labeled a few hundred items, fine-tuned a model, fought with tokenization, adjusted thresholds, handled negation cases like “the Fed will not cut rates”... I spent a solid month on it. On a good day, it was barely usable.

Then I finally went back and actually read through the documentation for the news API I was already using — TradingNews. Every message payload already came with a sentiment score. From -1 to 1. It had been there the whole time. The thing I had spent a month grinding on was just a field I had casually thrown away during JSON.parse.

{
  "content": "...",
  "urgency": "high",
  "sentiment": -0.6,
  "published_at": "..."
}

So I deleted my own classifier.

Using that sentiment field isn’t perfect, but it’s calibrated, stable, arrives in real time with the news, and costs zero extra compute. After deleting a month’s worth of my own code, the bot actually became simpler and faster.

I really wish there were an API that could meet everyone’s needs, but the API I’m currently using is already one of the better ones I’ve found — and even then, it still can’t satisfy every use case. Maybe that’s the whole point of vibe coding?

I’m looking for a better news + trading integration API besides the TradingNews API. If you know of a better one, or have a better manual approach for building this yourself, I’d love to hear about it.

If you want to try the API I’m using, it’s here: https://tradingnews.press/

https://preview.redd.it/akq28s6fnr7h1.jpg?width=2862&format=pjpg&auto=webp&s=d3b9df77f0d9441915b39a66a864c222e2cf5c60

I recently built an event-driven trading bot, and I found that most free real-time news sources are basically useless for actual trading.

For example, delayed polling of REST endpoints, no structured data, no urgency labels, and headlines only showing up after the move has already happened. By the time you parse the content, the edge is already gone.

What I actually wanted was very simple: a real-time push stream where the content is already structured, so I can act immediately when news breaks. I looked at related APIs for a while, and the one that finally met my needs was the TradingNews API. A few things that made it useful for me:

• It is a WebSocket stream, not polling. News enters your code as soon as it is published — no need to run a REST loop every 30 seconds.
• Every message is already structured. The two hardest parts — “Is this news urgent?” and “Is this good news or bad news?” — are already handled for you.

I built a small open-source demo where you can see it working in real time: the news stream enters the system and is turned into an automated trading strategy in real time: https://github.com/KoNananachan/OpenPoly

I’m not saying it’s some kind of magic tool. Fast news is an edge, not free money, and you still need to correctly judge what the news means and manage risk properly (test with paper trading first). But for the problem of “getting structured, market-moving news into my code right now,” it’s the first thing that didn’t make me want to smash my laptop.

TradingNews: https://tradingnews.press/

https://preview.redd.it/obmi2vewmr7h1.jpg?width=2862&format=pjpg&auto=webp&s=eded10d9e05dd8219d2f0f43c9504692c5d4d8d4

When it comes to news-driven trading, the part that usually gets people stuck isn’t the strategy itself — it’s how to get news fast and cleanly.

At first, I was foolishly polling free APIs. The delay was often tens of seconds, and I still had to clean up a bunch of messy data myself. By the time I finished parsing everything, the entry price I wanted had already moved, making it basically impossible to trade properly.

Later, I realized it didn’t have to be that complicated. For trading with a news feed, what you really need is just a real-time push stream of already-structured news.

My requirements were probably a bit demanding: I wanted the feed to show things like urgency, sentiment, publish time, and other useful fields. Honestly, I spent weeks looking for a usable and reasonably priced tool 😂. So far, the only API I’ve found that fits my needs is https://tradingnews.press/. All you need to do is sign up, get an api_key, connect to its real-time stream with a WebSocket, and you can start receiving news in real time and making decisions from it.

One thing to keep in mind: you still need your own decision-making logic. No matter how fast the news is, it’s only a tool. I’d suggest validating your logic in a paper trading environment first, and only using real money once it’s running reliably.

I also put together an open-source demo that turns real-time news pushes into long/short signals with very low latency: https://github.com/KoNananachan/OpenPoly

https://preview.redd.it/d65e4002lr7h1.jpg?width=2862&format=pjpg&auto=webp&s=916b4fc5bfff9015c1951e20d6554ad97660fea8

When it comes to news-driven trading, the part that usually gets people stuck isn’t the strategy itself — it’s how to get news fast and cleanly.

At first, I was foolishly polling free APIs. The delay was often tens of seconds, and I still had to clean up a bunch of messy data myself. By the time I finished parsing everything, the entry price I wanted had already moved, making it basically impossible to trade properly.

Later, I realized it didn’t have to be that complicated. For trading with a news feed, what you really need is just a real-time push stream of already-structured news.

My requirements were probably a bit demanding: I wanted the feed to show things like urgency, sentiment, publish time, and other useful fields. Honestly, I spent weeks looking for a usable and reasonably priced tool 😂. So far, the only API I’ve found that fits my needs is https://tradingnews.press/. All you need to do is sign up, get an api_key, connect to its real-time stream with a WebSocket, and you can start receiving news in real time and making decisions from it.

One thing to keep in mind: you still need your own decision-making logic. No matter how fast the news is, it’s only a tool. I’d suggest validating your logic in a paper trading environment first, and only using real money once it’s running reliably.

I also put together an open-source demo that turns real-time news pushes into long/short signals with very low latency: https://github.com/KoNananachan/OpenPoly

https://preview.redd.it/borgfjsvkr7h1.jpg?width=2862&format=pjpg&auto=webp&s=b4ed6f81e5964a2038522fec73f4d20747f4d273

When it comes to news-driven trading, the part that usually gets people stuck isn’t the strategy itself — it’s how to get news fast and cleanly.

At first, I was foolishly polling free APIs. The delay was often tens of seconds, and I still had to clean up a bunch of messy data myself. By the time I finished parsing everything, the entry price I wanted had already moved, making it basically impossible to trade properly.

Later, I realized it didn’t have to be that complicated. For trading with a news feed, what you really need is just a real-time push stream of already-structured news.

My requirements were probably a bit demanding: I wanted the feed to show things like urgency, sentiment, publish time, and other useful fields. Honestly, I spent weeks looking for a usable and reasonably priced tool 😂. So far, the only API I’ve found that fits my needs is https://tradingnews.press/. All you need to do is sign up, get an api_key, connect to its real-time stream with a WebSocket, and you can start receiving news in real time and making decisions from it.

One thing to keep in mind: you still need your own decision-making logic. No matter how fast the news is, it’s only a tool. I’d suggest validating your logic in a paper trading environment first, and only using real money once it’s running reliably.

I also put together an open-source demo that turns real-time news pushes into long/short signals with very low latency: https://github.com/KoNananachan/OpenPoly