Project 2: Financial Data Visualizer

Build a dashboard that plots price, volume, and returns.

Project Overview

Attribute Value
Difficulty Level 1: Beginner
Time Estimate Weekend
Main Language Python
Alternative Languages JavaScript, R
Knowledge Area Time series visualization
Tools Plotting library
Main Book “Python for Data Analysis” by Wes McKinney

What you’ll build: A script or notebook that visualizes OHLCV data, returns, and moving averages.

Why it teaches quant: Visualization exposes trends, volatility, and anomalies quickly.

Core challenges you’ll face:

  • Choosing time scales and axes
  • Plotting multiple series together
  • Highlighting significant changes

Real World Outcome

You will generate a multi-panel chart showing price, volume, and returns.

Example Output:

$ python visualize.py --symbol AAPL
Saved charts to charts/AAPL_overview.png

Verification steps:

  • Confirm alignment of time axes
  • Check that returns match price differences

The Core Question You’re Answering

“How can I quickly see behavior, volatility, and anomalies in market data?”

Visualization is the fastest sanity check.

Concepts You Must Understand First

Stop and research these before coding:

  1. Log returns
    • Why do quants use log returns instead of simple returns?
    • Book Reference: “Quantitative Trading” by Ernest Chan, Ch. 2
  2. Moving averages
    • How do moving averages smooth data?
    • Book Reference: “Trading and Exchanges” by Larry Harris, Ch. 12
  3. Volatility
    • How is volatility measured from returns?
    • Book Reference: “Options, Futures, and Other Derivatives” by John Hull, Ch. 13

Questions to Guide Your Design

  1. Chart structure
    • Will you use candlesticks or line charts?
    • How will you plot volume without clutter?
  2. Metrics
    • Which indicators (SMA, EMA, RSI) will you include?
    • How will you handle multiple scales?

Thinking Exercise

Return Calculation

Given prices 100, 102, 101, compute simple and log returns.

Questions while working:

  • Why are log returns additive?
  • Which is easier to model statistically?

The Interview Questions They’ll Ask

Prepare to answer these:

  1. “Why use log returns?”
  2. “What does volatility represent?”
  3. “How do moving averages help analysis?”
  4. “What is the difference between candlestick and line charts?”
  5. “How do you visualize drawdowns?”

Hints in Layers

Hint 1: Starting Point Plot closing price first.

Hint 2: Next Level Add volume and returns panels.

Hint 3: Technical Details Use consistent date alignment across plots.

Hint 4: Tools/Debugging Check return calculations against known examples.

Books That Will Help

Topic Book Chapter
Log returns “Quantitative Trading” by Ernest Chan Ch. 2
Moving averages “Trading and Exchanges” by Larry Harris Ch. 12
Volatility “Options, Futures, and Other Derivatives” by John Hull Ch. 13

Implementation Hints

  • Normalize time axes across all charts.
  • Use subplots to avoid clutter.
  • Save charts in a consistent naming scheme.

Learning Milestones

  1. First milestone: You can plot price and volume together.
  2. Second milestone: You can compute and plot returns.
  3. Final milestone: You can explain volatility from visual charts.