AlphaAutomated

"Algorithmic trader sharing the playbook. AI automation | Backtesting | Live results. Free resources for retail traders. Let's build. 🚀"

[AlphaAutomated @AlphaAutomated]

After years of manual trading, I'm going full algo.

Why?
• I'm tired of emotional decisions
• I want systems that trade while I sleep
• I believe retail traders deserve institutional-grade tools

Starting today, I'm documenting the entire journey:

✅ Every strategy I develop
✅ Every backtest (wins AND losses)
✅ Every tool I build
✅ Every lesson I learn

My background:
📊 Data analyst (markets, futures, crypto)
💻 Python for analysis + automation
📈 Trading futures (ES, NQ) + crypto since 2020

My goal:
Build a profitable algo trading system from scratch. Share the playbook for free.

Why share everything?
Because I wish someone had done this for me when I started.

Follow if you want:
• Real trading strategies (not theory)
• Python code (not pseudocode)
• Honest results (not fake screenshots)
• Free tools (not $2K courses)

First post: Tomorrow.
First strategy: Mean reversion on ES futures.
First lesson: Already learned that "easy backtests" are a myth.

Let's build. 🚀

[Derivatives Monkey 衍生品猴子 (billionaire arc) @derivativemonky]

been working on something dope for quite some time & I'm excited announce the launch of our crypto options analytics platform :

https://t.co/u0lmtU5fUu

No Login or Payment Required. It's completely free to use!

will explain in tweets below what it does below & how it works👇

[AlphaAutomated @AlphaAutomated]

@Tradesyncer @FundedNext Done

[Tradesyncer @Tradesyncer]

🚀 $2,500,000 GIVEAWAY 🚀

We teamed up with @FundedNext to celebrate their new FLEX Challenge 🤝

Win 1 of 25x $100K FLEX accounts!!

To enter:

• Follow @Tradesyncer & @FundedNext
• Like & repost
• Comment “DONE”

⏳ Winners announced Friday.

[Mom @mom_agency_]

Claude's first day at Dunder Mifflin

[AlphaAutomated @AlphaAutomated]

@tradeifycrypto 37

[AlphaAutomated @AlphaAutomated]

@Tradesyncer @Tradeify done

[Tradesyncer @Tradesyncer]

$1,250,000 TRADEIFY EVALUATION GIVEAWAY 🎉

It's time. @Tradesyncer x @Tradeify

We're giving away 25x $50K Select Plan evaluation accounts. Here's all you gotta do:

✅ Follow @Tradesyncer & @Tradeify
✅ Like, Repost & Comment "DONE"

P.S. Tag someone for an extra entry.

Good luck! 💙

[AlphaAutomated @AlphaAutomated]

Unpopular opinion:

Most "profitable" algo strategies shared online are:

1. Curve-fitted to historical data
2. Cherry-picked best results
3. Ignoring transaction costs
4. Tested on clean data (not real market conditions)

Always verify. Always question. Always test yourself.

#AlgoTrading #TradingReality

[AlphaAutomated @AlphaAutomated]

Best free resources to learn algorithmic trading:

📚 Books:
• "Algorithmic Trading" - Ernest Chan
• "Quantitative Trading" - Ernest Chan

🎥 YouTube:
• QuantPy
• Part Time Larry
• Coding Jesus

💻 Platforms:
• QuantConnect (free tier)
• Backtrader (open source)

No paid courses needed to start.

#AlgoTrading #FreeResources

[AlphaAutomated @AlphaAutomated]

Position sizing formula I use:

Position Size = (Account Risk % × Account Size) / (Entry Price - Stop Loss)

Example:
• Account: $10,000
• Risk: 1% ($100)
• Entry: $50
• Stop: $48
• Risk per share: $2

Position Size = $100 / $2 = 50 shares

Never guess. Always calculate.

#RiskManagement #AlgoTrading

[AlphaAutomated @AlphaAutomated]

The difference between backtesting and forward testing:

BACKTEST:
• Test strategy on historical data
• Shows what WOULD have happened
• Fast, cheap, easy
• Risk: Overfitting

FORWARD TEST:
• Test strategy on NEW data (or live)
• Shows what ACTUALLY happens
• Slow, real-money risk
• Proof: It works now

You need BOTH.

#Backtesting #AlgoTrading

[AlphaAutomated @AlphaAutomated]

Free tools every algo trader should know:

📊 TradingView (charting + backtesting)
🐍 Python + pandas (data analysis)
📈 QuantConnect (cloud backtesting platform)
💾 Yahoo Finance API (free historical data)
📉 Backtrader (Python backtesting library)

All FREE. No excuses.

What am I missing? 👇

#AlgoTrading #FreeResources

[AlphaAutomated @AlphaAutomated]

Common backtesting mistakes that inflate results:

1. Look-ahead bias (using future data)
2. Ignoring slippage/commissions
3. Overfitting to historical data
4. Survivorship bias (only testing "winners")
5. Not testing on out-of-sample data

Which one have you fallen for?

#Backtesting #AlgoTrading

[AlphaAutomated @AlphaAutomated]

4/ The lesson:

Lower risk per trade = longer survival = more opportunities to be right.

High risk per trade = one bad streak and you're done.

Protect your capital first. Profits second.

[AlphaAutomated @AlphaAutomated]

Risk management rule I wish I learned earlier:

Never risk more than 1-2% of your account on a single trade.

Why?

Because even a 50% win rate strategy can blow up your account if you risk 10% per trade.

Math breakdown 👇

#RiskManagement #AlgoTrading

[AlphaAutomated @AlphaAutomated]

3/ The Kelly Criterion formula:

f = (bp - q) / b

Where:
• f = fraction of capital to risk
• b = win/loss ratio
• p = win probability
• q = loss probability (1 - p)

For most strategies, Kelly suggests 0.5-2% per trade MAX.

[AlphaAutomated @AlphaAutomated]

The 5 levels of trading automation:

Level 1: Manual execution (you click buy/sell)
Level 2: Alert-based (system alerts, you execute)
Level 3: Semi-auto (system executes, you approve)
Level 4: Fully automated (system trades, you monitor)
Level 5: Autonomous (system trades AND manages risk)

Where are you? 👇

#AlgoTrading #TradingAutomation

[AlphaAutomated @AlphaAutomated]

import pandas as pd

# 1-minute OHLC data
df_1min = https://t.co/6m4Nil6rab_csv('price_data.csv', index_col='timestamp', parse_dates=True)

# Convert to 5-minute bars
df_5min = df_1min.resample('5min').agg({
'open': 'first',
'high': 'max',
'low': 'min',
'close': 'last',
'volume': 'sum'
})

# Or convert to 1-hour bars
df_1hour = df_1min.resample('1H').agg({
'open': 'first',
'high': 'max',
'low': 'min',
'close': 'last',
'volume': 'sum'
})

Game changer for multi-timeframe analysis.

No need to download separate datasets—just resample.

[AlphaAutomated @AlphaAutomated]

Python tip for algo traders:

Use pandas `.resample()` to convert timeframes instantly.

1-min data → 5-min bars
5-min data → 1-hour bars
Daily data → weekly/monthly

One line of code.

Example 👇

#Python #AlgoTrading