Episode 1-11: How to Start in Quant Trading (Even If You Don’t Know Math or Code)

Introduction

Quantitative trading (quant trading) often seems like an exclusive domain for hedge funds, PhDs, and software engineers. Many retail traders hesitate to explore quant strategies because they assume deep knowledge of mathematics and programming is required.

The reality? You don’t need to be a math or coding expert to get started.

With the rise of user-friendly platforms, no-code tools, and structured learning resources, anyone can begin exploring systematic, data-driven trading.

In this guide, you’ll learn:

• What quant trading is and why it matters
• The essential steps to start without coding or advanced math
• The best tools, platforms, and resources for beginners

If you’ve ever been curious about automated, rules-based trading, this guide will help you take the first steps—without getting overwhelmed.

1. What is Quant Trading and Why Should You Care?

Quantitative trading is systematic trading that relies on rules, data, and algorithms instead of emotions and gut feelings.

Why Does Quant Trading Matter?

• Removes emotions – All trades are based on pre-defined logic, reducing psychological mistakes.
• Backtesting possible – You can test strategies on historical data before risking real money.
• Scalable – Strategies can be applied to multiple assets, timeframes, or markets simultaneously.
• Automation potential – Many quant strategies can be executed without manual intervention.

If you’ve ever struggled with emotional decision-making, inconsistent trading performance, or subjective bias, quant trading can help bring structure and repeatability to your process.

2. Getting Started Without Math or Coding

The biggest myth about quant trading is that you need a math or programming background to get started. While these skills help, they are not essential for beginners.

How to Start Without Coding or Math:

1. Use No-Code and Low-Code Trading Platforms

   • AlgoBlocks, Streak.Tech, TrendSpider, TradingView Pine Script (Visual strategy builders)
   • Interactive Brokers API with third-party integrations (Plug-and-play automation)

2. Learn Quant Concepts Through Visual Tools

   • QuantConnect and Quantopian (now part of Robinhood) have simple drag-and-drop tools
   • Python for Finance courses on Udemy (Beginner-friendly with minimal coding)

3. Study Simple Rule-Based Strategies

   • Moving Average Crossovers (trend-following)
   • RSI Overbought/Oversold (mean reversion)
   • Breakout Trading (momentum-based)

4. Use Backtesting Software That Requires No Programming

   • TradingView Strategy Tester (Basic strategy backtesting)
   • MetaTrader 4/5 Strategy Tester (For Forex and CFD trading)
   • QuantConnect’s No-Code Strategy Builder

5. Leverage Pre-Built Models and Signals

   • Many platforms offer ready-to-use strategies that you can modify and test.
   • Use copy trading services that allow you to replicate systematic strategies.

Starting with these approaches lets you understand the core principles of quant trading before diving into programming or complex data science.

3. Understanding Data-Driven Trading (Without the Math Jargon)

One of the key differences between discretionary trading and quant trading is that quant traders rely on data and statistical analysis instead of intuition.

But this doesn’t mean you need to do advanced math. Instead, focus on:

• Historical Price Data – Looking at past performance of stocks, forex, or crypto assets.
• Technical Indicators – Using moving averages, RSI, Bollinger Bands, and other tools to spot patterns.
• Backtesting and Forward Testing – Checking how a strategy would have performed in the past and testing it in real time.

Many quant traders rely on simple concepts like probabilities, risk-reward ratios, and position sizing rather than complex formulas.

How to Learn Data-Driven Trading Without Math Expertise

• Use TradingView to analyze price trends visually.
• Follow step-by-step strategy tutorials on YouTube or Coursera.
• Read books like Quantitative Trading by Ernest Chan (simple language, no deep math required).

4. Tools & Platforms for No-Code Quant Trading

Here are some beginner-friendly quant trading tools that require little to no programming:

These tools allow you to experiment, test, and refine trading strategies without writing a single line of code.

5. Developing Your First Simple Quant Strategy

You don’t need complex models to start quant trading. Here’s a step-by-step guide to developing a simple rule-based strategy:

Step 1: Choose a Market & Timeframe

• Stocks, forex, crypto, futures?
• Day trading or swing trading?

Step 2: Define Entry & Exit Rules

Example: Moving Average Crossover Strategy

• Buy when the 50-day moving average crosses above the 200-day moving average (Golden Cross).
• Sell when the 50-day moving average crosses below the 200-day moving average (Death Cross).

Step 3: Backtest Your Strategy

• Use TradingView Strategy Tester to see past performance.
• Adjust parameters based on market conditions.

Step 4: Optimize for Risk Management

• Use a stop loss (e.g., 2% below entry price).
• Set a profit target (e.g., 5% gain before exiting).

Step 5: Forward Test and Execute

• Test in a demo account before going live.
• Track performance and refine as needed.

Following this simple framework, you can develop a working quant strategy without coding or math-heavy calculations.

Conclusion: You Can Start Quant Trading Today

You don’t need a PhD or years of programming experience to become a quant trader. By using visual tools, no-code platforms, and simple rule-based strategies, you can:

• Remove emotions from trading decisions.
• Backtest ideas before risking real money.
• Scale and automate your strategies over time.

The key is starting small, experimenting, and refining your approach. Quant trading is no longer just for Wall Street—it’s now accessible to anyone willing to learn.

Ready to get started? Subscribe to The Independent Quant Podcast and explore TheIndependentQuant.com for more beginner-friendly resources.