algotrading

Yesterday I shared my first results.
Today — things got real 👇
📊 What changed:
❌ Before:
• 0 trades
• Wide spreads → no execution
• Bot looked “smart”… but did nothing
✅ Now:
• 20+ trades in session
• Balanced BUY/SELL cycles
• Real market interaction
But here’s the twist…
💰 PnL Result:
• Trade PnL: positive
• Total PnL: slightly negative
🤔 Why?
Because of one brutal truth:
⚠️ Fees > Edge
Even with perfect execution, small spreads (0.1–0.2%) get eaten by fees.

🔥 Biggest realizations so far:
1️⃣ A bot that doesn’t trade = useless
2️⃣ A bot that trades too cheap = also useless
3️⃣ Execution is step 1… but EDGE is step 2

📉 Market context:
• SOL moving in tight range (~82–84)
• Low volatility → harder to capture profit
• High competition → spreads must be precise

🧠 What I changed:
✔ Removed artificial spread distortion
✔ Fixed inventory skew behavior
✔ Increased effective spread (0.25%+)
✔ Focused on PnL per TIME, not per trade

📊 Current goal:
👉 Fewer trades
👉 Higher profit per cycle
👉 Positive net PnL after fees

💡 My current hypothesis:
“More fills ≠ more profit
Better edge + controlled fills = profit”

🤔 Question for traders & bot runners:
What matters more for you?
1️⃣ High frequency (many trades, small edge)
2️⃣ Lower frequency (fewer trades, higher edge)

📌 Next step:
Testing dynamic spreads based on volatility (ATR-based)
Will update results soon 👇
#Hummingbot #MarketMaking #SOL #CryptoTrading #AlgoTrading

Most beginners look at technical indicators like magic lines on a chart. They wait for a line to cross another line and click "Buy." But if you don't understand the why behind the formula, you are just gambling.
Today, we are combining pure logic with Python. We are going to build a script that calculates the RSI (Relative Strength Index) for $BTC or $ETH , but first, let's understand what we are actually coding.
Step 1: The Conceptual Math of RSI
RSI is a momentum oscillator that measures the speed and change of price movements. It oscillates between 0 and 100.
Traditionally:
• Over 70: The asset is considered "Overbought" (due for a pullback).
• Under 30: The asset is considered "Oversold" (due for a bounce).
But why? The math behind RSI simply compares the magnitude of recent gains to recent losses over a specified time period (usually 14 periods).
If the average of your recent up-closes is much higher than the average of your down-closes, the RSI goes up. It's a mathematical representation of buyer vs. seller exhaustion. We aren't predicting the future; we are calculating the current mathematical probability of a trend reversal.
Step 2: The Python Code
To calculate this automatically, we will use our trusty ccxt library to get the data, and pandas_ta (a technical analysis library) to do the heavy math.
Install the required libraries first: pip install ccxt pandas pandas_ta
Here is a clean, conceptual script to get the current RSI of $BTC :

import ccxt
import pandas as pd
import pandas_ta as ta
import time
# Settings
SYMBOL = 'BTC/USDT'
TIMEFRAME = '15m' # 15-minute candles
LIMIT = 100 # We need enough candles to calculate the 14-period average
# Initialize exchange
exchange = ccxt.binance()
def get_rsi(symbol, timeframe, limit):
try:
# 1. Fetch OHLCV data (Open, High, Low, Close, Volume)
bars = exchange.fetch_ohlcv(symbol, timeframe, limit=limit)

# 2. Convert to a Pandas DataFrame
df = pd.DataFrame(bars, columns=['timestamp', 'open', 'high', 'low', 'close', 'volume'])

# 3. Calculate RSI using the close price (default length is 14)
df.ta.rsi(close='close', length=14, append=True)

# 4. Get the last (current) RSI value
current_rsi = df['RSI_14'].iloc[-1]
current_price = df['close'].iloc[-1]

return current_price, current_rsi

except Exception as e:
print(f"Error fetching data: {e}")
return None, None
# Run the check
price, rsi = get_rsi(SYMBOL, TIMEFRAME, LIMIT)
if rsi:
print(f"Current {SYMBOL} Price: ${price}")
print(f"Current RSI (14): {rsi:.2f}")

if rsi < 30:
print("🚨 MATHEMATHICAL SIGNAL: RSI is Oversold (<30). Potential buying opportunity.")
elif rsi > 70:
print("🚨 MATHEMATHICAL SIGNAL: RSI is Overbought (>70). Potential selling opportunity.")
else:
print("Neutral zone. Let the code wait.")

Why This Beats Manual Trading
By running this script (or combining it with the Telegram bot from our previous article), you remove emotion entirely. You act strictly on mathematical data. No FOMO, no panic.
Challenge for you: Can you modify this code to check $ETH and $SOL at the same time? Let me know in the comments if you want the multi-coin version tomorrow! 👇
Disclaimer: This is for educational purposes. RSI is a probability tool, not a guarantee. Always manage your risk.

#PythonTrading #CryptoMath #RSITrading #BinanceAPI #AlgoTrading #BTC #ETH

Still staring at the screen all day, waiting for that perfect entry point? 📉 Stop it. Welcome to the other side: The world where code works and traders relax (mostly).
Using the Binance API (Application Programming Interface) is like giving your strategy a direct, high-speed connection to the exchange. It’s not just for advanced quant traders; it’s for anyone tired of manually refreshing charts.
In this first article, let’s make it real. Here’s a basic, step-by-step guide to getting your first taste of crypto automation. No fluff.
Step 1: Why Bother with API? (The "Secret Sauce")
You might be thinking, "I can just place orders on the app." Why the API?
1. Speed: Code is faster than your thumb. Much faster.
2. No Emotion: A script doesn't panic-sell when it sees a red candle. It follows instructions.
3. Scale: A human can only monitor 2-3 charts at once. A script can check hundreds of pairs in milliseconds.
4. 24/7: Your script doesn’t sleep, eat, or have social life.
Step 2: The Security Baseline (READ THIS!)
The biggest mistake beginners make is security. When you generate an API key on Binance:
• NEVER share your API Secret. Treat it like your private seed phrase. If anyone gets it, they can access your account.
• Restrict IP Access: In the Binance API settings, only allow access from your specific IP address. This is a game-changer.
• Disable Withdrawals: Unless absolutely necessary for a specific reason, keep withdrawal permissions for the API disabled. A typical trading script only needs "Enable Reading" and "Enable Spot & Margin Trading".
Step 3: Getting Your Keys on Binance
Let's get the keys to the castle.
1. Log into your Binance account on the web
2. Click on your profile icon and select API Management.
3. Click Create API Key. Give it a label (e.g., "Automation Start").
4. You’ll get an API Key and an API Secret. Copy them immediately and store them securely. Once you close this window, the secret will be masked.
5. Click Edit Restrictions and set up the permissions (as mentioned in Step 2). Add your IP restriction.
Step 4: Your First Request (Python Example)
To keep it simple, we'll use Python and the powerful ccxt library, which standardizes crypto API calls. Install it: pip install ccxt
Here’s the absolute minimum to fetch your BTC balance without manual trading.
import ccxt
# 1. Initialize the exchange (Replace with YOUR keys)
# Note: In a real bot, use environment variables to hide keys!
binance = ccxt.binance({
'apiKey': 'YOUR_ACTUAL_API_KEY_HERE',
'secret': 'YOUR_ACTUAL_API_SECRET_HERE',
'enableRateLimit': True,
})
# 2. Make the API call to get account info
try:
balance = binance.fetch_balance()
# 3. Print only the BTC portion for clarity
btc_balance = balance['total'].get('BTC', 0)
print(f"Your BTC balance is: {btc_balance}")
except Exception as e:
print(f"An error occurred: {e}")

Congratulations! You’ve just communicated directly with the exchange using code. This is the moment your trading changes.
What's Next?
This was just to open your balance. What should we build next?
• A basic alert system for sharp price moves?
• An automated dollar-cost averaging (DCA) bot?
• A "panic sell" button that triggers in code?
Let me know in the comments. This is only the beginning.
Disclaimer: Not financial advice. The CCXT library is a third-party tool; use at your own risk. Automating trading involves risk, including the loss of capital. Always backtest and test on testnets.
#BinanceAPI #AlgoTrading #PythonTrading #cryptobot
#CryptoEducation #tradingtips #TechInCrypto #LearnAndEarn #CryptoStrategy