> For the complete documentation index, see [llms.txt](https://docs.fiinpro.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.fiinpro.com/english/bonds/bond-list/case-study.md).

# Case Study

<h3 align="center"><strong>Case Study 1: What are the bond repayment cash flows in the last two months of 2023, and how do they reflect issuers’ repayment pressure?</strong></h3>

<h3 align="center"><strong>Steps 1</strong></h3>

<figure><img src="https://706516220-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2Fn9brzGqnNDoN4CEHksRO%2Fuploads%2FxammJVRCNodJN1EXv1R2%2Fimage.png?alt=media&amp;token=e88d93d3-5da8-4e88-847d-55ba23f70f8c" alt=""><figcaption></figcaption></figure>

<figure><img src="https://706516220-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2Fn9brzGqnNDoN4CEHksRO%2Fuploads%2FZ3jFVzMAZhKRTmxcPMwa%2Fimage.png?alt=media&amp;token=cf5ed216-cded-4230-8637-f1b2b9d81a26" alt=""><figcaption></figcaption></figure>

**1.** To drill down into individual bonds, go to the **Bond List** tab.\
*Note: This module allows users to create multiple custom filters, which can be saved as templates for future use.*

**2.** To assess repayment pressure in the last two months of 2023, apply the following filters:

* **Maturity Date:** from **06/10/2023 to 31/12/2023**
* **Bond Status:** *Normal* (i.e., not yet matured and not bought back by the issuer)

This filter returns **121 results**, representing bonds that will mature before year-end 2023 and thus contribute to short-term repayment pressure.

<h3 align="center">Steps 3</h3>

<figure><img src="https://706516220-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2Fn9brzGqnNDoN4CEHksRO%2Fuploads%2FHrFAeemqJsywmfk0b2vE%2Fimage.png?alt=media&amp;token=39ec9c26-d882-4c81-8488-53c98192b6dc" alt=""><figcaption></figcaption></figure>

<h3 align="center">Steps 4</h3>

<figure><img src="https://706516220-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2Fn9brzGqnNDoN4CEHksRO%2Fuploads%2Frp1BQ2UhJsHQSzYxCMrn%2Fimage.png?alt=media&amp;token=4f4c8b82-f9a7-4d87-b836-900235565f3f" alt=""><figcaption></figcaption></figure>

**3.** From the filtered results, select **Column Customization**.

**4.** Add columns such as **Outstanding Value** and **Credit Events**, while removing unnecessary fields for a cleaner view.

<h3 align="center">Steps 5</h3>

<figure><img src="https://706516220-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2Fn9brzGqnNDoN4CEHksRO%2Fuploads%2F5JJqhAGoZ3LHmW5FgnCp%2Fimage.png?alt=media&amp;token=8ad57e48-d746-4d6c-a1fa-ba6e6c7b3809" alt=""><figcaption></figcaption></figure>

**5.** Sort the results by **Issue Value** to identify which bonds have the largest issuance amounts.

<h3 align="center">Steps 6</h3>

<figure><img src="https://706516220-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2Fn9brzGqnNDoN4CEHksRO%2Fuploads%2FqwDFezGnu6tmMJHavMmb%2Fimage.png?alt=media&amp;token=df7b13a4-b6bf-4083-8ee5-30a1d0de0223" alt=""><figcaption></figcaption></figure>

**6.** Next, refine the results by excluding certain sectors to avoid noise. For example, the **Banking** sector can be filtered out, as it is generally considered lower risk and enjoys stronger credit quality.

<h3 align="center">Steps 7</h3>

<figure><img src="https://706516220-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2Fn9brzGqnNDoN4CEHksRO%2Fuploads%2FgAmvxd4MrqyzUrY5m6dt%2Fimage.png?alt=media&amp;token=e11735c7-3d01-4d9e-b371-699df225a899" alt=""><figcaption></figcaption></figure>

**7.** In the **Credit Events** column, users may see notes such as *“Debt restructuring”* or *“Executive risk event.”* These indicate that the issuer has previously faced credit-related issues. For issuers with such events in their history, users should conduct deeper analysis to evaluate the likelihood of future repayment risks.
