---
title: "Level 1: financial data, markets and analysis"
description: "Level 1 of the Python Trading Course: how markets work, asset classes, data sources, financial data engineering and analysis."
url: "https://pythonparatrading.com/en/python-trading-course/level-1/"
lang: "en"
image: "https://pythonparatrading.com/og/en/python-trading-course/level-1.png"
---

# Level 1: Financial data, markets and analysis

> How the market works on the inside and how its data is obtained, cleaned and stored without bias: from orders and costs to a personal data lake.

- Hours: 90–100
- Prerequisite: Basic Python, high-school statistics
- Profile: Programmer without finance, or trader with some Python
- Course: [Python Trading Course](https://pythonparatrading.com/en/python-trading-course/)

## How markets work

- `1.1.1` Participants: retail, institutional, market makers, HFT, brokers, clearing houses; exchanges, MTFs, dark pools, OTC.
- `1.1.2` Sessions, auctions, holidays and calendars (exchange_calendars, pandas_market_calendars).
- `1.1.3` Order book: bid/ask, spread, depth, L1, L2 and L3 levels.
- `1.1.4` Order types: market, limit, stop, stop-limit, trailing, MOC/LOC, IOC/FOK, iceberg, bracket/OCO.
- `1.1.5` Costs (commissions, spread, impact, slippage, financing); settlement (T+1 in the US, T+2 in Europe), leverage and margin.

## Asset classes

- `1.2.1` Equities: capital increases, splits, dividends, corporate actions, indices.
- `1.2.2` ETFs: physical or synthetic replication, creation and redemption, tracking error, leveraged and inverse, UCITS versus US (PRIIPs/KID).
- `1.2.3` Futures: specifications (multiplier, tick, expiries), margin, mark-to-market, roll, contango and backwardation.
- `1.2.4` Forex: pairs, pips, lots, spot versus forwards and FX futures, swaps and rollover, CFDs and ESMA limits.
- `1.2.5` Options: calls and puts, premium, intrinsic and extrinsic value, American and European, chains.
- `1.2.6` Crypto: spot, perpetuals, dated futures, funding rate, stablecoins, DEX and CEX, custody.
- `1.2.7` Fixed income and rates (macro context and interest rate futures); CFDs and leveraged retail products in the EU.

## Market data sources

- `1.3.1` Types: EOD, intraday (bars), tick, quotes, L2/L3 book, reference data.
- `1.3.2` Free or educational: yfinance (unofficial; rate limits), Stooq, FRED (macro), SEC EDGAR, Banco de España and ECB, CNMV.
- `1.3.3` Retail and prosumer APIs: Massive (formerly Polygon.io; equities plans at $0, $29, $79 and $199 a month, with real time only on Advanced), Alpaca Data, Tiingo, EODHD, Alpha Vantage, Twelve Data, Financial Modeling Prep.
- `1.3.4` Professional: Databento (CME since 2010, all US exchanges, OPRA; historical pay-per-use and real time by plan), Nasdaq Data Link, LSEG/Refinitiv, Bloomberg (background), ICE.
- `1.3.5` Crypto: exchange APIs via ccxt, Kaiko, CoinGecko and CoinMarketCap, Glassnode and on-chain data.
- `1.3.6` Brokers as a source: IBKR (ib_async), MetaTrader 5, OANDA.
- `1.3.7` Licences, terms of use, redistribution, “professional” versus “non-professional” data.
- `1.3.8` How to choose a provider: coverage, historical depth, survivorship-bias-free universes, corporate action adjustments, cost.

## Financial data engineering

- `1.4.1` Downloading via REST and websockets; pagination, rate limits, retries with backoff.
- `1.4.2` Cleaning: missing values, outliers, bad ticks, duplicates, gaps; time zone alignment.
- `1.4.3` Split and dividend adjustments; adjusted versus unadjusted prices.
- `1.4.4` Survivorship-bias-free universes; delisted tickers; symbol changes (point-in-time).
- `1.4.5` Bar construction: time, tick, volume, dollar, imbalance bars.
- `1.4.6` Continuous futures series: back-adjusted, ratio-adjusted, by volume or open interest.
- `1.4.7` Storage: CSV versus Parquet; partitioning; DuckDB; PostgreSQL and TimescaleDB; ArcticDB.
- `1.4.8` A reproducible pipeline for download, validation and incremental update, with data quality tests.

## Fundamental and macro data

- `1.5.1` Financial statements, ratios, XBRL and SEC EDGAR; publication date versus period date, to avoid look-ahead.
- `1.5.2` Macro data (FRED, ECB, INE), economic calendars, analyst estimates and transcripts (a bridge to NLP).

## Financial exploratory analysis

- `1.6.1` Returns, volatility (historical, EWMA), rolling correlations, drawdown and time under water.
- `1.6.2` Stylised facts: fat tails, volatility clustering, weak autocorrelation, leverage effect.
- `1.6.3` Seasonality: day of the week, month, turn of the month, intraday sessions.

## Programmed technical analysis

- `1.7.1` Moving averages (SMA, EMA, KAMA), MACD, RSI, stochastic, Bollinger, ATR, ADX, Donchian, Keltner; OBV, VWAP, volume profile.
- `1.7.2` Own implementation versus TA-Lib or pandas-ta; validating results.
- `1.7.3` Candlestick patterns and support and resistance: how to code them and why many are not robust.
- `1.7.4` Multi-timeframe without look-ahead.

## Level project

A personal data lake in Parquet and DuckDB with equities, ETFs, a continuous futures series, a currency pair and a crypto perpetual. Updatable, with data quality checks and an exploratory Streamlit dashboard.

## Practice

Research on this site to practise this level

1. [Python for Trading Course - Part 1: Market Data with OpenBB](https://pythonparatrading.com/en/openbb-free-market-data/)
2. [Limit Order Book - Aggregated Market Liquidity](https://pythonparatrading.com/en/limit-order-book-and-market-liquidity/)
3. [Big Data Management. 1 - Introduction to Big Data for Trading with ArcticDB](https://pythonparatrading.com/en/big-data-for-trading/)
4. [Big Data Management 3 - Building a Datalake on the Nasdaq with ArcticDB.](https://pythonparatrading.com/en/big-data-with-arcticdb/)
5. [Seasonality in Python. Searching for Intraday Patterns](https://pythonparatrading.com/en/seasonality-intraday-preprocessing/)

Previous level: [Level 0: Python from scratch and a data mindset](https://pythonparatrading.com/en/python-trading-course/level-0/)

Next level: [Level 2: Systematic strategies and rigorous backtesting](https://pythonparatrading.com/en/python-trading-course/level-2/)