Kuldeep Singh Rathore | AI Trading Automation

🚀 The ULTIMATE Algorithmic Trading Course is HERE! 🚀
💡 23+ Hours of PURE Value | Complete Beginner to Advanced

🔥 This is not just a course…
It’s THE MOST COMPREHENSIVE guide on Algorithmic Trading with Python you’ll ever find on the internet!

✅ What you’ll get:
✔ Full 23+ Hours Video Course
✔ Highly Researched MCQs to test your knowledge
✔ 50 Real-World Mini Projects (Beginner → Advanced)
✔ Access to Our Exclusive Algo Trading Community – Weekly Live Sessions & Discussions
✔ Downloadable Resources & Book – Practical Python for Algorithmic Trading (compiled from 9+ years of experience!)

https://youtu.be/b9EXshJM94g

#algotrading #algorithmictrading #quanttrading #hedgefund #hft

4 months ago (edited) | [YT] | 29

Kuldeep Singh Rathore | AI Trading Automation

50. What is a "breakout" trading strategy?

a) Taking positions when the price moves beyond a defined support or resistance level
b) Trading only during market crashes
c) Identifying when an algorithm stops working
d) Finding when a company is about to go bankrupt

Join Elite Quant Community for more: - rb.gy/zsffyv



#algotrading #quanttrading #trading #btc #forex #bitcoin #freqtrade #algorithmictrading #quantitativetrading

6 months ago | [YT] | 2

Kuldeep Singh Rathore | AI Trading Automation

49. What would this code do with a DataFrame of stock data?

```python
df_daily = df.resample('D').last()

```

a) Samples random days from the data
b) Resamples the data to get one entry per day
c) Deletes all but the last day's data
d) Creates a new sample of the original data

Join Elite Quant Community for more: - rb.gy/zsffyv



#pythontrading #quanttrading #trading #btc #forex #bitcoin #freqtrade #algorithmictrading #quantitativetrading

6 months ago | [YT] | 5

Kuldeep Singh Rathore | AI Trading Automation

🚀 Day 8 of our 100 Days of Python Algo Trading Challenge


Ready to take your coding to the next level?
In this episode, we unlock powerful function concepts that every quant and data-driven trader must know.

🔥 What you’ll learn today:
✅ Nested Functions – Write cleaner and more modular logic
✅ First-Class Functions – Treat functions as objects
✅ Lambda Functions – One-liners that power your code
✅ map(), filter(), reduce() – Transform data efficiently
✅ Normal vs Lambda Functions – When & how to use them

📈 These tools are essential for creating flexible, reusable, and high-performance trading strategies.

🎥 Watch now:
👉 https://www.youtube.com/watch?v=yogx-...

💬 Comment "🔥Functions Mastered!" if you're keeping up with the series!

#PythonFunctions #AlgoTrading #QuantTrading #PythonForFinance #100DaysOfCode #FunctionalProgramming #LambdaFunctions #MapFilterReduce #TradingAlgorithms #QuantDev #PythonAlgoTrading #LearnToCode

6 months ago | [YT] | 4

Kuldeep Singh Rathore | AI Trading Automation

48. What is "mean reversion" based on?

a) The idea that asset prices will always return to their starting price
b) The theory that prices tend to move toward the average price over time
c) The concept that all markets eventually decline
d) The principle that trading volume reverts to the mean

Join Elite Quant Community for more: - rb.gy/zsffyv



#algotrading #quanttrading #trading #btc #forex #bitcoin #freqtrade #algorithmictrading #quantitativetrading

6 months ago | [YT] | 1

Kuldeep Singh Rathore | AI Trading Automation

🚀 Day 7 of 100 Days of Python Algo Trading is here!
📌 Topic: Python Functions - Part 1

Want to write cleaner, smarter, and modular code for your trading algorithms?
This video teaches you everything about functions — the backbone of structured programming in Python!

💡 Here's what you'll master:
✅ How to define and call functions
✅ Understanding *args and **kwargs
✅ Different types of arguments
✅ Return values, scope, and call stacks
✅ Best practices for writing reusable code
✅ Real-world use in trading strategies

🎯 Whether you're building a backtest engine, signal generator, or execution script – functions are your best friend!

🎥 Watch now:
👉 https://www.youtube.com/watch?v=QlOjD...

💬 Drop a comment if you’re loving the challenge so far or want more advanced examples in Part 2!

#PythonFunctions #AlgoTrading #QuantTrading #PythonForFinance #100DaysOfCode #TradingAlgorithms #ModularProgramming #LearnPython #FunctionScope #argsAndkwargs #QuantDev #PythonAlgoTrading

6 months ago | [YT] | 3

Kuldeep Singh Rathore | AI Trading Automation

47. What's the purpose of this code in a trading context?

```python
df['MA20'] = df['Close'].rolling(window=20).mean()

```

a) To calculate the average of all stock prices
b) To calculate a 20-day moving average of closing prices
c) To find the 20 highest closing prices
d) To smooth out the graphical display

Join Elite Quant Community for more: - rb.gy/zsffyv



#pythontrading #quanttrading #trading #btc #forex #bitcoin #freqtrade #algorithmictrading #quantitativetrading

6 months ago | [YT] | 2

Kuldeep Singh Rathore | AI Trading Automation

🚀 Day 6 of 100 Days of Python Algo Trading is live!

🔍 Today’s focus: Python Sets & Dictionaries – the powerhouse data structures every aspiring quant should master!

📈 Whether you're analyzing market symbols, managing trade logic, or storing financial indicators, sets and dictionaries offer:
✅ Lightning-fast lookups
✅ Clean data storage
✅ Efficient key-value mapping
✅ Easy set operations like union & intersection
✅ Advanced tools like frozensets & comprehension tricks

🧠 Learn how to:
🔹 Organize & track unique symbols
🔹 Perform data mapping in trading systems
🔹 Use set/dict operations to simplify strategy logic
🔹 Speed up your code for real-time decision making

🎥 Watch now: [Python Sets & Dictionaries – Day 6 of 100 Days Challenge]
🔗 https://www.youtube.com/watch?v=Lh-HP...

👨‍💻 Whether you're a trader, coder, or learner – don't miss this one!

#PythonAlgoTrading #QuantTrading #PythonSets #PythonDictionaries #100DaysOfCode #PythonForFinance #TradingAlgorithms #FinancialDataScience #AlgoTradingChallenge #DataStructures #QuantDevTools

6 months ago | [YT] | 3

Kuldeep Singh Rathore | AI Trading Automation

46. What is a market-neutral strategy?

a) A strategy that always produces neutral returns
b) A strategy that works equally well in all market conditions
c) A strategy designed to minimize exposure to market-wide movements
d) A strategy that only trades neutral-rated stocks

Join Elite Quant Community for more: - rb.gy/zsffyv



#algotrading #quanttrading #trading #btc #forex #bitcoin #freqtrade #algorithmictrading #quantitativetrading

6 months ago | [YT] | 0

Kuldeep Singh Rathore | AI Trading Automation

45. If 'df' is a DataFrame of stock data, what does this return? `df.describe()`

a) A text description of what the data represents
b) Statistical summary of the numerical columns (count, mean, std, min, max, etc.)
c) The data types of each column
d) A description of the stock's business model

Join Elite Quant Community for more: - rb.gy/zsffyv



#pythontrading #quanttrading #trading #btc #forex #bitcoin #freqtrade #algorithmictrading #quantitativetrading

6 months ago | [YT] | 0