index.qmd

---
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pagetitle: "Tidy Finance"
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description: |
  An opinionated approach on empirical research in financial economics.
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metadata:
  pagetitle: Welcome to Tidy Finance
  description-meta: An opinionated approach on empirical research in financial economics using the programming languages R and Python.
---

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[★ Open-source · R & Python · Reproducible]{.tf-badge}

# Empirical finance, [reproducible]{.tf-grad} in R and Python

[Tidy Finance takes an opinionated, fully transparent approach to empirical research in financial economics. One open-source code base now covers R and Python, side by side in every chapter.]{.tf-lead}

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[Start here](chapters/working-with-stock-returns.html){.tf-btn .tf-btn--primary}
<!-- [Factor Library](https://factors.tidy-finance.org){.tf-btn .tf-btn--ghost} -->
[Python Library](https://python.tidy-finance.org){.tf-btn .tf-btn--ghost}
[R Package](https://r.tidy-finance.org){.tf-btn .tf-btn--ghost}
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```{=html}
<span class="tf-dot tf-dot--r"></span><span class="tf-dot tf-dot--y"></span><span class="tf-dot tf-dot--g"></span><span class="tf-window__file">download &amp; plot prices</span>
```
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::: {.panel-tabset .tf-no-margin-tabs group="language"}

### R

```r
library(tidyfinance)
library(ggplot2)

prices <- download_data(
  domain = "Stock Prices",
  symbols = "AAPL",
  start_date = "2000-01-01",
  end_date = "2024-12-31"
)

prices |>
  ggplot(aes(date, adjusted_close)) +
  geom_line()
```

### Python

```python
import tidyfinance as tf
from plotnine import ggplot, aes, geom_line

prices = tf.download_data(
  domain="Stock Prices",
  symbols="AAPL",
  start_date="2000-01-01",
  end_date="2024-12-31"
)

(ggplot(prices, aes("date", "adjusted_close"))
  + geom_line())
```

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[20+]{.tf-stat__num}
[Hands-on chapters]{.tf-stat__label}
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[2]{.tf-stat__num}
[Languages, one code base]{.tf-stat__label}
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[100%]{.tf-stat__num}
[Open source & reproducible]{.tf-stat__label}
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<!-- ============================ FEATURES ============================ -->
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## Everything you need for reproducible research in finance

A single, transparent code base takes you from raw data to publication-quality results, in R and Python.
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```{=html}
<div class="tf-feature__icon"><svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"><polyline points="16 18 22 12 16 6"/><polyline points="8 6 2 12 8 18"/></svg></div>
```
### One code base, two languages

Every chapter ships R and Python side by side from a single source. Switch with a tab. Your choice follows you through the book.
:::

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```{=html}
<div class="tf-feature__icon"><svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"><polyline points="23 4 23 10 17 10"/><polyline points="1 20 1 14 7 14"/><path d="M3.51 9a9 9 0 0 1 14.85-3.36L23 10M1 14l4.64 4.36A9 9 0 0 0 20.49 15"/></svg></div>
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### Fully transparent & reproducible

Open code you can run end to end, from raw data to every figure and table, with no black boxes.
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```{=html}
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```
### Powered by `tidyfinance`

A companion package for R and Python that wraps data downloads and the routines we use throughout the book.
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```{=html}
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### Real financial data

Work with the data professionals use, like CRSP, Compustat, and TRACE, through clean, documented access patterns.
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```{=html}
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### From sorts to machine learning

Portfolio sorts, factor models, fixed effects, causal inference, and modern ML give you the full empirical toolkit.
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### A free, open book

Read the whole book online for free or dive into the blog all in the open.
:::

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<!-- ============================ CURRICULUM ============================ -->
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## Browse the book by topic

Five parts take you from your first stock return to constrained portfolio backtests.
:::

```{=html}
<div class="tf-tracks">
  <a class="tf-track" href="chapters/working-with-stock-returns.html">
    <div class="tf-track__no">PART 01</div>
    <h3>Getting Started</h3>
    <p>Stock returns, modern portfolio theory, the CAPM, and financial statement analysis.</p>
    <div class="tf-track__cta">Start here →</div>
  </a>
  <a class="tf-track" href="chapters/accessing-and-managing-financial-data.html">
    <div class="tf-track__no">PART 02</div>
    <h3>Financial Data</h3>
    <p>Access and manage WRDS, CRSP, Compustat, TRACE, and FISD with documented workflows.</p>
    <div class="tf-track__cta">Explore data →</div>
  </a>
  <a class="tf-track" href="chapters/beta-estimation.html">
    <div class="tf-track__no">PART 03</div>
    <h3>Asset Pricing</h3>
    <p>Beta estimation, univariate and bivariate sorts, Fama-French factors, and Fama-MacBeth.</p>
    <div class="tf-track__cta">Price assets →</div>
  </a>
  <a class="tf-track" href="chapters/fixed-effects-and-clustered-standard-errors.html">
    <div class="tf-track__no">PART 04</div>
    <h3>Modeling &amp; Machine Learning</h3>
    <p>Fixed effects, difference-in-differences, factor selection, and option pricing via ML.</p>
    <div class="tf-track__cta">Model it →</div>
  </a>
  <a class="tf-track" href="chapters/parametric-portfolio-policies.html">
    <div class="tf-track__no">PART 05</div>
    <h3>Portfolio Optimization</h3>
    <p>Parametric portfolio policies and constrained optimization with realistic backtesting.</p>
    <div class="tf-track__cta">Optimize →</div>
  </a>
</div>
```

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[Praise]{.tf-eyebrow}

## What experts say about Tidy Finance
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        <img src="assets/img/quotes/harald_lohre.jpg" alt="A portrait of Harald Lohre">
      </div>
      <p><i>A clean coding environment is a prerequisite for building a relevant investment platform and conducting meaningful factor research. Tidy Finance is the name of the game, giving aspiring academics and finance practitioners just what they need to perform clean and reproducible  research. Highly recommended.</i></p>
      <div class="quote-author">
          <p><strong>Harald Lohre</strong></p>
          <p>Executive Director at Robeco</p>
          <p>Honorary Researcher at Lancaster University Management School</p>
      </div>
    </div>

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      <div class="quote-image">
        <img src="assets/img/quotes/albert_j_menkveld.jpeg" alt="A portrait of Albert J. Menkveld">
      </div>
      <p><i>From our crowd-sourced paper on non-standard errors, I learned how important clean coding is. Tidy Finance is a rich resource for empirical finance researchers, offering clean coding techniques that benefit both beginners and experts.</i></p>
      <div class="quote-author">
          <p><strong>Albert J. Menkveld</strong></p>
          <p>Professor of Finance at Vrije Universiteit Amsterdam</p>
          <p>Fellow at Tinbergen Institute</p>
      </div>
    </div>

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      <div class="quote-image">
        <img src="assets/img/quotes/nikolaus_hautsch.jpeg" alt="A portrait of Nikolaus Hautsch">
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      <p><i>A fantastic book bringing together financial theory, sound econometrics, thorough data processing and powerful programming techniques. An absolute must for every student and scholar in empirical finance.</i></p>
      <div class="quote-author">
          <p><strong>Nikolaus Hautsch</strong></p>
          <p>Professor of Finance & Statistics at University of Vienna</p>
      </div>
    </div>

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      <div class="quote-image">
        <img src="assets/img/quotes/bjoern_hagstroemer.jpeg" alt="A portrait of Björn Hagströmer">
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      <p><i>Tidy Finance is a fantastic resource that lowers the threshold for entry into empirical finance, all in the spirit of open and reproducible science.</i></p>
      <div class="quote-author">
          <p><strong>Björn Hagströmer</strong></p>
          <p>Professor of Finance at Stockholm Business School</p>
      </div>
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      <div class="quote-image">
        <img src="assets/img/quotes/raman_uppal.jpeg" alt="A portrait of Raman Uppal">
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      <p><i>To have a deep understanding of empirical asset pricing, one needs to write code using actual data. To learn how to do this, there is no better starting point than Tidy Finance. [...] I strongly recommend Tidy Finance to both beginners and experts.</i></p>
      <div class="quote-author">
          <p><strong>Raman Uppal</strong></p>
          <p>Professor of Finance at EDHEC Business School</p>
      </div>
    </div>

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      <div class="quote-image">
        <img src="assets/img/quotes/mark_salmon.jpeg" alt="A portrait of Mark Salmon">
      </div>
      <p><i>Students and professionals alike are led step by step until they suddenly find themselves coding on their own. A brilliant and required resource!</i></p>
      <div class="quote-author">
          <p><strong>Mark Salmon</strong></p>
          <p>Professor of Economics at University of Cambridge</p>
      </div>
    </div>

  </div>

  <!-- Pagination buttons -->
  <div class="swiper-button-prev"></div>
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</div>
```
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<!-- ============================ TEAM ============================ -->
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[The team]{.tf-eyebrow}

## Who maintains Tidy Finance
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```{=html}
<div class="team-grid">
  <div class="team-member" onclick="openInNewTab('https://www.linkedin.com/in/christophscheuch/');">
    <img src="assets/img/christoph_scheuch.jpeg" alt="A portrait of Christoph Scheuch">
    <h3>Christoph Scheuch</h3>
    <p>Associate Researcher at HU Berlin</p>
    <span class="team-member-cta">LinkedIn &#x2192;</span>
  </div>
  <div class="team-member" onclick="openInNewTab('https://www.voigtstefan.me/');">
    <img src="assets/img/stefan_voigt.jpeg" alt="A portrait of Stefan Voigt">
    <h3>Stefan Voigt</h3>
    <p>Assistant Professor of Finance at University of Copenhagen</p>
    <span class="team-member-cta">Website &#x2192;</span>
  </div>
  <div class="team-member"  onclick="openInNewTab('https://sites.google.com/view/patrick-weiss');">
    <img src="assets/img/patrick_weiss.jpeg" alt="A portrait of Patrick Weiss">
    <h3>Patrick Weiss</h3>
    <p>Assistant Professor of Finance at Reykjavik University </p>
    <span class="team-member-cta">Website &#x2192;</span>
  </div>
  <div class="team-member" onclick="openInNewTab('https://sites.google.com/site/christophfrey/');">
    <img src="assets/img/christoph_frey.jpeg" alt="A portrait of Christoph Frey">
    <h3>Christoph Frey</h3>
    <p>Quantitative Researcher</p>
    <span class="team-member-cta">Website &#x2192;</span>
  </div>
</div>

<script>
function openInNewTab(url) {
  window.open(url, '_blank').focus();
}
</script>
```
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