Combining News Sentiment and Technical Analysis With AI Makler for Smarter Decisions

The best trading decisions consider both what the market is doing (technical analysis) and what's driving it (news and fundamentals). AI Makler accepts both types of data simultaneously, letting it form a complete picture.

This article shows practical patterns for feeding news and technical data into AI Makler, and how the agent combines them for more informed decisions.

Why Combine News + Technicals?

Data Source	What it tells AI Makler
Technical indicators	Price trends, momentum, support/resistance, volatility
News headlines	Market sentiment, catalysts, macro events, sector trends
Both together	"The RSI shows oversold AND there's positive regulatory news → high-confidence buy signal"

Separately, each source gives partial information. Together, they let the agent distinguish between:

• A technical breakdown with no news catalyst → cautious
• A technical breakout confirmed by positive news → confident entry
• Divergence: price says one thing, news says another → market may be wrong

Setting Up the Data Pipeline

[Upstream]                              [AI Makler]
            
RSS News API ──→ news field ────────┐
                                    ├──→ Combined Context
Technical Workers                    │
(Fetch Data + Indicators) ──→ data field ──┘

Feeding Technical Data

Connect any technical analysis workers upstream. AI Makler's data field accepts markdown, so you can pass:

BTCUSD (Bitcoin) — 4h timeframe
────────────────────────────────────
Price: $86,520 | 24h change: +2.3%
RSI(14): 62.4 | MACD: Bullish (20 Jun)
BB Upper: $89,100 | BB Lower: $82,300
Volume: 28.5B (1.2x avg)
Support: $84,000 | Resistance: $89,000
EMA(50): $82,100 | EMA(200): $71,500

Feeding News Data

Connect an RSS Fetch or NewsAPI worker upstream. AI Makler's news field accepts:

1. Federal Reserve holds rates at 5.25-5.50% — neutral for crypto
2. Bitcoin ETF inflows reach $450M — highest in 3 weeks (bullish)
3. Solana network congestion report published — bearish for SOL
4. Ethereum L2 TVL reaches $48B ATH — bullish for ETH ecosystem

Pattern 1: Full Market Scan With News Confirmation

[Schedule: every 4h]
  → [Fetch Price Data: BTC, ETH, SOL (4h timeframe)]
  → [Compute Indicators: RSI, MACD, Bollinger Bands]
  → [Fetch RSS News: Crypto feeds]
  → [AI Makler: decision with data + news]
  → [Condition: ordersCount > 0 AND latestCertainty > 70]
    → [Run Workflow "Execute Trade"]
    → [Telegram Notify: New signal]
  → [Save to Memory + Log to User List]

graph LR
    S[Schedule<br/>Every 4h] --> FD[Fetch Prices<br/>BTC, ETH, SOL]
    FD --> IND[Compute Tech Indicators<br/>RSI, MACD, BB]
    IND --> RSS[Fetch RSS News]
    RSS --> AM[AI Makler<br/>decision mode]
    AM --> C{Condition<br/>orders > 0<br/>AND cert > 70%}
    C -->|Yes| EXEC[Run Workflow<br/>Execute Trade]
    C -->|Yes| TG[Telegram Notify]
    C -->|No| LOG[Log to User List]

What AI Makler Sees

The agent receives BOTH data types in one call:

Market Data:

BTCUSD: RSI 62, MACD bullish, above avg volume, testing resistance at $89K
ETHUSD: RSI 54, neutral, Bollinger Bands narrowing (squeeze forming)
SOLUSD: RSI 45, bearish, declining volume

News:

BTC ETF inflows $450M (bullish)
Fed holds rates steady (neutral/positive)
Solana congestion report (bearish)

Agent's Decision (from our production test):

"Bitcoin showing bullish momentum with 2.3% gain, above-average volume, and bullish MACD crossover. RSI at 62.4 not overbought. Fed holding rates steady is positive for risk assets. Strong ETF inflows ($450M) are a clear bullish catalyst." → BUY BTCUSD @ $86,520 | Target: $89,000 | Stop: $84,000 | Certainty: 75%

Pattern 2: News-Driven Alert + Technical Confirmation

When breaking news hits, use the List Change Trigger or Webhook Trigger to start the workflow, then let AI Makler confirm with technicals.

[List Change Trigger: News list updated]
  → [Fetch Latest News Item from List]
  → [Fetch Price Data for relevant symbols]
  → [Compute Technical Indicators]
  → [AI Makler: decision with news + tech data]
  → [Condition: strong signal?]
    → [Send Push Notification]
    → [Log Opportunity for Review]

This pattern is excellent for event-driven trading — news events trigger analysis, but the final decision includes technical confirmation.

Pattern 3: Sector Rotation Analysis

Use AI Makler to compare sectors and recommend rotation.

[Schedule: daily]
  → [Fetch Crypto Sector Data]
    → BTC, ETH (Large Cap)
    → SOL, AVAX (Layer 1)
    → MATIC, ARB (Layer 2)
  → [Fetch Sector News]
    → Regulatory updates
    → Network upgrades
    → Institutional adoption
  → [AI Makler: analysis mode with ALL data]
  → [Condition: recommendation?]
    → [The agent identifies strongest sectors]

The agent's memory helps it track which sectors have been performing over days and weeks.

Pattern 4: Earnings / Economic Calendar + Price Action

Combine the Browse Economic Calendar worker with AI Makler:

[Schedule: every 30min on event days]
  → [Browse Economic Calendar → events for today]
  → [Fetch affected symbols data]
  → [Fetch related news]
  → [AI Makler: decision]
  → [Condition: high impact event approaching?]
    → [Reduce positions / tighten stops]
    → [Monitor for post-event opportunity]

Practical Data Formatting Tips

What AI Makler Does Best With

Good data format (keep it structured):

SYMBOL — TIMEFRAME
────────────────────
Price: $86,520 | Change: +2.3%
RSI(14): 62.4 | MACD: Bullish
Support: $84,000 | Resistance: $89,000

Key news:
- ETF inflows $450M (bullish)
- Fed rates unchanged (neutral)

Poor data format (avoid dumping raw data):

// Don't pass raw OHLC arrays or JSON blobs
[{"o": 84500, "h": 87200, "l": 84300, "c": 86520, "v": 28500000}, ...]

What to Include

Data Type	Best Practice	Example
Price levels	Current price + key S/R	`$86,520
Indicators	Name + value + signal	RSI: 62 (neutral-bullish)
Volume	Current + comparison	28.5B (1.2x average)
News	Source + headline + sentiment	Reuters: ETF inflows $450M (bullish)
Trend	Direction + timeframe	Daily: bullish, 4h: ranging

Memory Improves News-Integrated Decisions Over Time

One of AI Makler's key advantages is that it remembers past news and decisions. On the second run, it sees:

PREVIOUS SESSIONS (most recent first):
  [1] 2026-06-21T08:00 | BTC Bullish, ETF inflows | Order: BUY BTC, cert 75%
  [2] 2026-06-20T20:00 | BTC Ranging, no news | No orders
  [3] 2026-06-20T12:00 | BTC Bearish rejection | No orders

This means it can connect news to outcomes — did the ETF inflow signal lead to a profitable trade? It can reference that experience in future decisions.

Workflow for Maximum Context

For the best results, build a workflow that gives AI Makler maximum context:

[Trigger]
  → [Fetch Data: Multi-timeframe prices (1h, 4h, 1d)]
  → [Fetch Indicators: RSI, MACD, BB, Volume Profile]
  → [Fetch News: RSS + NewsAPI (top 5 stories)]
  → [Fetch Calendar: Today's economic events]
  → [Format Everything into Markdown]
  → [AI Makler: decision]
  → [Process Output]

Each data source adds a dimension to the agent's understanding. The formatting step (using a Python Exec or Set Variables worker) keeps the markdown clean and focused.

Legal Disclaimer

This is not financial advice. Trading involves substantial risk of financial loss. News-sentiment analysis and technical indicators are tools for information — they do not guarantee trading outcomes. Always conduct your own research and risk assessment.