Hey guys,

As a full-time trader, I’ve spent a lot of time refining my daily routine. I wanted to share especially for the new investors and traders the exact stack of tools I end up keeping open in my browser tabs every single day to do my analysis, tracking, charting, and fundamental sweeps.

1. Charting: Tradingview

You all probably know this one already, but it's honestly just the smoothest web-based charting app out there for technical analysis.

2. Macro & News Flow: Yahoo Finance

Honestly, it’s an absolute must-have just so I don’t get caught off guard by a random economic report or macro news while holding a position.

3. Stock Analysis & Sentiment: Sentimentick

I use this to find new swing opportunities and monitor my existing positions. It really helps filter down the tickers and find healthy candidates for swing trades.

4. Fundamentals & Financials: Koyfin / Finviz

Finviz is great for a quick morning visualization of the heatmaps, while Koyfin lets me dig into the harder financial data and historical ratios.

5. Performance Tracking: TradeZella

Essential for tracking my stats and keeping myself accountable. It automates the journaling process and gives me a deep dive into my execution flaws and win rates.

Hope it helps the new investors and traders out there! Curious to hear what everyone else is using or if I'm missing any hidden gems. Share them below and I'll test them out and share my thoughts!

Hey everyone,

I wanted to share something I noticed after spending a lot of time analyzing how people screen for setups - and a shift that made a huge difference in my own trading.

A lot of people rely almost entirely on standard price/volume scanners. The problem is that by the time a ticker shows up on a top-gainers scan, it’s usually up 12–15% already. The initial entry is long gone, and you’re forced to either chase or sit on your hands.

What made things click for me was overlapping three things before the big candle happens: news catalysts, social buzz, and clean technical levels. Relying on just one or two of these usually leads to bad trades.

1. Clean technical setups without narrative usually sit dead in the water

A textbook flag pattern or key level reclaim looks great on paper. But if there’s no volume, no media coverage, and nobody is talking about the stock, it usually just chops sideways or breaks down. Technicals show you where price might react, but they don't tell you if buyers will actually show up to push it through.

2. Social hype or news alerts in isolation are traps

Buying a stock just because it's trending online or because a headline hit the wire is a quick way to get dumped on. If a major news catalyst drops but the chart is slamming right into heavy daily resistance, you're often buying the exact top of crowd excitement.

How I look for entries now:

The cleanest trades happen when a stock is consolidating tightly near a clear risk level (like a VWAP bounce or EMA reclaim), a real news catalyst drops, and you suddenly see social attention velocity start ticking up while price is still quiet.

Tracking that spike in chatter while price is sitting right at technical support lets you get in before the massive breakout candle alerts the rest of the market.

Curious how you guys structure your daily scanning:

• Do you rely strictly on price action/volume screeners, or do you monitor news and social momentum too?
• What’s been the most reliable "early warning" signal for you before a stock actually moves?

Hey everyone,

I’ve been running an automated momentum strategy in Python for a while, asking for a recommendation on a piece I’m trying to add.

Right now, my execution loop relies on two core building blocks:

• Market Signals & Sentiment (Sentimentick API): This setup has been working really well for me. Instead of running local scrapers for social chatter or news, I hit Sentimentick to pull sentiment scores, attention tiers, and short/medium-term trend bias in one response.
• Execution & Risk Management (IBKR Gateway + ib_async**):** Orders get routed through IB Gateway using ib_async whenever a ticker passes my sentiment and technical filters.

something like:

Python

import asyncio
from ib_async import IB, Stock, LimitOrder
import requests

# Fetch signal from Sentimentick API
def get_signal(symbol):
    url = f"https://www.sentimentick.com/api/ticker/{symbol}"
    headers = {
        "X-API-KEY": "st_your_key_here",
        "Accept": "application/json"
    }
    
    res = requests.get(url, headers=headers).json()
    ticker_data = res["ticker"]
    tech_data = res["technical_analysis"]
    
    # Extract real JSON fields from Sentimentick
    sentiment_score = ticker_data["sentiment_score"]      # 0 - 100
    sentiment_tier = ticker_data["sentiment_tier"]        # e.g., "bullish"
    medium_term_bias = tech_data["medium_term"]["bias"]   # e.g., "bullish", "bearish"
    
    # Return conviction boolean based on sentiment + technical alignment
    return sentiment_score > 60 and sentiment_tier == "bullish" and medium_term_bias != "bearish"

# Execution via IBKR Gateway
async def run_execution():
    ib = IB()
    await ib.connectAsync('127.0.0.1', 4001, clientId=1) # IB Gateway API port
    
    symbol = "NVDA"
    if get_signal(symbol):
        contract = Stock(symbol, 'SMART', 'USD')
        await ib.qualifyContractsAsync(contract)
        
        # Place limit order
        order = LimitOrder('BUY', 10, 120.00)
        trade = ib.placeOrder(contract, order)
        print(f"Placed order for {symbol}: {trade.orderStatus.status}")

asyncio.run(run_execution())

This combo has worked great for filtering out bad trades, but I want to add Form 4 insider buying data (open-market C-suite buys) as an extra signal before routing orders.

Can anyone recommend a good, low-latency API or library for real-time SEC Form 4 data? What are you guys using in your pipelines?

Thanks!

Hey everyone,

I’ve been running an automated momentum strategy in Python for a while, asking for a recommendation on a piece I’m trying to add.

Right now, my execution loop relies on two core building blocks:

• Market Signals & Sentiment (Sentimentick API): This setup has been working really well for me. Instead of running local scrapers for social chatter or news, I hit Sentimentick to pull sentiment scores, attention tiers, and short/medium-term trend bias in one response.
• Execution & Risk Management (IBKR Gateway + ib_async**):** Orders get routed through IB Gateway using ib_async whenever a ticker passes my sentiment and technical filters.

something like:

Python

import asyncio
from ib_async import IB, Stock, LimitOrder
import requests

# Fetch signal from Sentimentick API
def get_signal(symbol):
    url = f"https://www.sentimentick.com/api/ticker/{symbol}"
    headers = {
        "X-API-KEY": "st_your_key_here",
        "Accept": "application/json"
    }
    
    res = requests.get(url, headers=headers).json()
    ticker_data = res["ticker"]
    tech_data = res["technical_analysis"]
    
    # Extract real JSON fields from Sentimentick
    sentiment_score = ticker_data["sentiment_score"]      # 0 - 100
    sentiment_tier = ticker_data["sentiment_tier"]        # e.g., "bullish"
    medium_term_bias = tech_data["medium_term"]["bias"]   # e.g., "bullish", "bearish"
    
    # Return conviction boolean based on sentiment + technical alignment
    return sentiment_score > 60 and sentiment_tier == "bullish" and medium_term_bias != "bearish"

# Execution via IBKR Gateway
async def run_execution():
    ib = IB()
    await ib.connectAsync('127.0.0.1', 4001, clientId=1) # IB Gateway API port
    
    symbol = "NVDA"
    if get_signal(symbol):
        contract = Stock(symbol, 'SMART', 'USD')
        await ib.qualifyContractsAsync(contract)
        
        # Place limit order
        order = LimitOrder('BUY', 10, 120.00)
        trade = ib.placeOrder(contract, order)
        print(f"Placed order for {symbol}: {trade.orderStatus.status}")

asyncio.run(run_execution())

This combo has worked great for filtering out bad trades, but I want to add Form 4 insider buying data (open-market C-suite buys) as an extra signal before routing orders.

Can anyone recommend a good, low-latency API or library for real-time SEC Form 4 data? What are you guys using in your pipelines?

Thanks!

Hey everyone,

I’ve been running an automated momentum strategy in Python for a while, asking for a recommendation on a piece I’m trying to add.

Right now, my execution loop relies on two core building blocks:

• Market Signals & Sentiment (Sentimentick API): This setup has been working really well for me. Instead of running local scrapers for social chatter or news, I hit Sentimentick to pull sentiment scores, attention tiers, and short/medium-term trend bias in one response.
• Execution & Risk Management (IBKR Gateway + ib_async**):** Orders get routed through IB Gateway using ib_async whenever a ticker passes my sentiment and technical filters.

something like:

Python

import asyncio
from ib_async import IB, Stock, LimitOrder
import requests

# Fetch signal from Sentimentick API
def get_signal(symbol):
    url = f"https://www.sentimentick.com/api/ticker/{symbol}"
    headers = {
        "X-API-KEY": "st_your_key_here",
        "Accept": "application/json"
    }
    
    res = requests.get(url, headers=headers).json()
    ticker_data = res["ticker"]
    tech_data = res["technical_analysis"]
    
    # Extract real JSON fields from Sentimentick
    sentiment_score = ticker_data["sentiment_score"]      # 0 - 100
    sentiment_tier = ticker_data["sentiment_tier"]        # e.g., "bullish"
    medium_term_bias = tech_data["medium_term"]["bias"]   # e.g., "bullish", "bearish"
    
    # Return conviction boolean based on sentiment + technical alignment
    return sentiment_score > 60 and sentiment_tier == "bullish" and medium_term_bias != "bearish"

# Execution via IBKR Gateway
async def run_execution():
    ib = IB()
    await ib.connectAsync('127.0.0.1', 4001, clientId=1) # IB Gateway API port
    
    symbol = "NVDA"
    if get_signal(symbol):
        contract = Stock(symbol, 'SMART', 'USD')
        await ib.qualifyContractsAsync(contract)
        
        # Place limit order
        order = LimitOrder('BUY', 10, 120.00)
        trade = ib.placeOrder(contract, order)
        print(f"Placed order for {symbol}: {trade.orderStatus.status}")

asyncio.run(run_execution())

This combo has worked great for filtering out bad trades, but I want to add Form 4 insider buying data (open-market C-suite buys) as an extra signal before routing orders.

Can anyone recommend a good, low-latency API or library for real-time SEC Form 4 data? What are you guys using in your pipelines?

Thanks!