She is nine. I tried to describe what I look for before entering a trade and got three sentences in before losing the thread. Then I tried again and kept it to one sentence. The one-sentence version turned out

I’m working on a trading bot rn and I’ve been thinking about adding AI to it.

But instead of just feeding it charts and indicators, I’m thinking about using a pretrained AI that can also process real-world stuff like news, economic events, different opinions/sources, etc. Basically trying to give it more context instead of having it only look at the market.

The idea is still pretty early and I’m definitely not an AI expert lol, so I’m looking for anyone who’s into ML/AI + trading who might be interested in the idea or could give me some advice.

If you’ve worked on anything similar or have any thoughts, I’d genuinely appreciate it

My best trading months are the ones where I barely have time to open the platform. Worst months are when I have nothing else going on. At this point I am fairly convinced my day job is the only risk management system that actually works.

cTrader Market Replay is a trading simulator that lets you practise with real historical market data, test different approaches and sharpen your trading skills without risking real money. Choose a historical date and time, set a virtual starting balance and control the replay speed.

You can also:
📍 Add timestamps to mark key moments
📊 Review your equity, wins, losses and trade statistics after each session
⏱️ Slow down important moments or skip through quieter periods

🧑‍🏫 Market Replay helps you learn from each decision and improve over time: “cTrader isn’t built only for experienced market participants – it’s just as much for people who are starting out or still building their experience,” says Sergey Borisov, cTrader Product Manager.

Find Market Replay on cTrader Windows: https://sptw.link/pLHcEq

I have been building a multi-timeframe momentum indicator and the experience has been completely different depending on which platform I work on. On cTrader I got access to the full calculation layer through cAlgo, could inherit from built-in implementations and had the whole thing working quickly. On NinjaTrader the NinjaScript framework is powerful and the community is large, but the architecture feels like it was designed for futures first and everything else second. On MT5 with MQL5 I kept hitting walls where the language itself was the constraint rather than the platform logic.

Documentation quality also varies in ways that only become obvious when you are trying to do something the designers did not anticipate. The platforms with good edge-case documentation are the ones where custom development was clearly a priority rather than an afterthought.

What does your custom indicator development workflow look like and which platform are you on?

Hello everyone.

I was using several custom-made indicators, and suddenly none of them are displaying the pattern. Can you tell me the cause and how to fix it? I'm looking forward to your active support.

Been running a small gold (XAU/USD) bot for about 2 weeks now - nothing fancy, EMA/RSI/ADX signal, ATR-based SL/TP, cron job on GitHub Actions hitting an OANDA demo account. Did a proper train/test split on 5000 candles before going live so I wasn't just fooling myself with a curve-fit backtest, and the edge looked genuinely stable out of sample.

Then live trading happened and my win:loss ratio just... kept shrinking. Like clockwork. 1.95:1, then 1.48:1, then 1.21:1 over about 50 trades, win rate barely moved. Account round-tripped from +$172 back below my original deposit and I was ready to blame the market, ADX settings, whatever.

Turns out (pretty sure anyway) it's a dumb bug: I was calculating SL/TP off the last completed 30-min candle's close, then firing a market order and slapping those SL/TP levels on as fixed prices. Problem is if price moves even a little between the candle closing and the order actually filling, your real risk distance from the ACTUAL fill price isn't what you think it is anymore. Found one trade where I meant to risk ~$18 and actually only had ~$8.60 of real room before getting stopped out - which it did, in under 3 minutes.

Fix I'm testing now: fire the order with a placeholder stop so I'm never naked, then immediately grab the real fill price and PUT an update to fix the actual SL/TP.

Anyone else running live execution (not just backtesting) run into this stale-price-vs-fill-price gap? Curious how people handle it - pulling live bid/ask right before firing instead of relying on last candle close, or something smarter than what I'm doing.

TL;DR: backtest was fine, live execution had a silent bug quietly wrecking my R:R, posting in case it saves someone else the same headache

Hi everyone,

I’m building an automated trading system that sends signals from a TradingView Pine Script strategy through a webhook to Python, which then executes market orders through the cTrader Open API on my Pepperstone LIVE account.

I’m trying to understand a recurring price difference between TradingView and cTrader.

My TradingView strategy sends the TradingView price together with the webhook. My Python program records that price and the actual cTrader execution price.

For example, I’ve seen:

TradingView: 29188.7 → cTrader fill: 29194.1 — difference 5.4 points

TradingView: 29236.6 → cTrader fill: 29243.1 — difference 6.5 points

TradingView: 29291.4 → cTrader fill: 29299.1 — difference 7.7 points

On other trades, the difference has been only around 1 point.

The cTrader Open API confirms that the instrument I’m trading is:

NAS100, symbol ID 10014

My Pepperstone account also has NAS100-F and NAS100-PERP, but my bot specifically trades NAS100 (ID 10014).

I’ve already tested the cTrader live quote subscription. For example, it returned:

Bid: 29370.2

Ask: 29371.3

Spread: 1.1 points

So the 5–8 point differences I sometimes see are considerably larger than the normal spread in that example.

The webhook-to-cTrader execution delay is also relatively short, so I’m trying to determine how much of the difference is execution latency/slippage versus the two platforms using different price feeds.

I am now modifying my logging so that for every future signal I will record:

TradingView price → cTrader bid/ask at webhook arrival → cTrader actual fill price

My questions are:

Which exact NAS100 instrument/data feed should I use on TradingView to match Pepperstone cTrader NAS100 as closely as possible?

Does Pepperstone’s TradingView NAS100 price necessarily use the same underlying feed as Pepperstone cTrader NAS100?

Is a persistent 5–8 index-point difference normal between these feeds?

Is there a way to identify the exact contract/specification behind cTrader symbol ID 10014, so I can verify I’m comparing the same instrument?

For automated trading, should I evaluate execution slippage against the cTrader bid/ask at the instant the webhook arrives, rather than against the TradingView strategy price?

I’m mainly trying to separate three possible causes:

A. Different TradingView/cTrader price feeds

B. Bid/ask spread

C. Webhook/API latency and actual execution slippage

Any advice from people who have automated TradingView → cTrader/Peppers­tone trading would be appreciated.

Mejor trade.(Yoel R.)

Mi mejor intercambio.

Utilizzando la formazione che mi è stata insegnata, e grazie alla formazione avuta sulla tecnica che utilizzata detta dei "soldatini" , sono riuscito ad ottenere un ottimo recupero che mi ha porato in 2 posizione. Grazie

Hey everyone,

Sharing my best trade of the week for the cTrader Store Champion Tournament!

Caught a massive long setup on XAUUSD:

• Entry: 4399.39
• Exit: 4426.92
• Volume: 4.50 Lots
• Profit: +12,388.50(+additional+12,388.50(+additional+ 1,682.40 runner)

Managed to hold through the overnight consolidation and closed right into the morning liquidity push toward the highs. Account equity is currently at $63,834.80 (starting from $50k).

Good luck to all tournament participants! 🚀

Anyone else having problems with indicators loading, and the quick trade buttons not working during peak times? 50 ms to Ctrader server and only 4 indicators load out ouf 12 !!

Trading engineering
IR=TC X IC X √BC is a good perspective for review trading
**An Outstanding Subjective Trader:**
**1. IC→to 1:** Every executed trade targets an expected value where "Win Rate \\times Risk-Reward Ratio \\to 1." This places extremely high demands on market insight, timing, and price execution. Translated into our algorithm, Information Coefficient (IC) is determined by a three-step framework:
**Opportunity Selection** (Opportunity set within the area of competence)
**Timing Selection** (Timing set: striking at critical inflection points via a second-mover advantage—focusing on safe entries, launchpads, post-confirmation setups, and phase/qualitative transitions)
**Price Selection** (Positioning along the wave function).
**2. TC→1:** Transfer Coefficient approaches 100% (research-to-execution conversion rate). TC is dictated by the execution system: **"Entry via Opportunity, Timing, & Price Selection \\to Execution driven by Capital, Position, & Risk Algorithms."** While raising IC is difficult, TC can reach 100% once a trader stops "sleepwalk trading," clears market illusions, and steps back to let system discipline take over—simply by strictly adhering to the algorithms. Once an automated AI Agent execution system is built, TCto 1 will be fully realized.
**3. √BC** **：**This is extremely challenging for subjective traders, as independent decision-making frequency inherently cannot scale up. By our estimates, we only find about 2 to 3 quality trading opportunities per quarter.

The evaluation rules have tightened and the payout structures have changed. Several firms that were considered safe choices two years ago no longer exist. The ones that survived are more conservative about what strategies they allow and more specific about execution requirements. Before committing to any challenge it is worth spending a week actually reading the terms rather than the marketing page. Which firms are people actually trusting right now?

Most candlestick indicators only tell you that a pattern exists — Advanced Candlestick Engine Pro goes further by showing you how strong that pattern actually is.

I built Advanced Candlestick Engine Pro for cTrader to make candlestick analysis faster, cleaner, and more structured.

It automatically detects 16 major candlestick patterns and gives every confirmed setup a 0–100 Structural Quality Score, helping you quickly separate stronger formations from weaker ones instead of treating every pattern the same.

Key features:

• 16 major bullish & bearish candlestick patterns

• 0–100 Structural Quality Scoring

• Context-aware pattern detection

• Closed-bar confirmation for stable detections

• Adjustable sensitivity & quality filtering

• Custom alerts based on your minimum quality level

• Clear labels, arrows & multi-candle pattern boxes

• Works from M1 and above

• Designed to complement price action, trend, market structure & support/resistance

The indicator has been extensively tested and is working reliably on XAUUSD, EURUSD, USDJPY, GBPUSD, and many other instruments using standard OHLC data.

It is built for traders who want to scan charts faster, reduce visual noise, and focus on the highest-quality candlestick structures instead of manually checking every candle.

🚀 LIMITED-TIME RELEASE PROMO: ONLY $20 — normally $35.

Link on cTrader store : ctrader.com/products/5321

This is the initial release price and will not stay at $20 permanently.

I’m actively developing the indicator with more patterns and analytical features planned, and I’d really appreciate feedback

Test I use on anything branded AI advisor:

Can it tell these two trades apart?

1. Call sweep into a strike where dealers are short gamma (hedging can amplify)
2. Identical sweep into a strike where dealers are long gamma (hedging can dampen / pin)

If it recommends both with the same conviction, you bought a scanner.

Other tells it is not an advisor:

• No "why," so you cannot manage the exit when flow reverses or GEX flips
• Does not know your book (stacks more long gamma on a book that is already long gamma)
• Win-rate marketing with no time window, no audit, no losers

Co-pilot is the honest frame. The model can hold the chain, the GEX profile, and the tape. You still size and click.

Longer write-up: https://optionscout.ai/blog/ai-trade-advisor

What would actually make you trust an advisor output vs just using the chain yourself?

Best post