How do Firms Hedge in Financial Distress?

SND-ID: 2022-47

Creator/Principal investigator(s)

Niclas Andrén - Lund University, Department of Business Administration orcid

Håkan Jankensgård - Lund University, Department of Business Administration

Evan Dudley - Queen's university, Goodes Hall, Smith School of Business

Description

We examine how firms hedge in financial distress. Using hand-collected data from oil and gas producers, we find that derivative portfolios in these firms are characterized by short put options. These positions are part of a composite three-way collar strategy that combines buying put options and selling put and call options with differing strike prices. We show that because liquidity demand varies with the degree of financial distress, the three-way collar strategy is the optimal risk management strategy that preserves incentives for future growth.

The sample consists of publicly traded oil and gas producers in the US (SIC code 1311) between Q1:2013 and Q4:2015. Hedging strategies are hand-coded based on quarterly reports (10Q/10-Q reports). We sum each firm's outstanding derivatives positions regardless of maturity for each quarter and create a variable per hedging strategy that takes the value 1 if the sum is positive, zero otherwise. We classify individual firms’ hedge portfolios into five distinct hedging strategies based on the character of the provided protection and the cash flow impac

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Language

English

Research principal, contributors, and funding

Research principal

Lund University

Responsible department/unit

Department of Business Administration

Funding 1

  • Funding agency: Knut Wicksell Financial Centre for Financial Studies

Funding 2

  • Funding agency: Jan Wallander and Tom Hedelius Foundation rorId
Protection and ethical review

Data contains personal data

No

Method and time period

Population

The population consists of publicly traded oil and gas producers in the US (SIC code 1311)

Sampling procedure

Total universe/Complete enumeration
The sample consists of publicly traded oil and gas producers in the US (SIC code 1311) between Q1:2013 and Q4:2015.

The sample period is Q1:2013 to Q4:2015. Firms are eligible for inclusion in the sample if their headquarters are in the US, they are publicly listed, and they have at least $1mn in total assets in all quarters. We furthermore require that 10-Qs (quarterly reports) be available from the online EDGAR database, and that firms report their derivative positions in sufficient detail to quantify different hedging strategies. The latter criterion essentially means that firms must report their hedging position in tabular form. Finally, a firm is eligible if it uses derivatives in at least one quarter of the sample period.

Time period(s) investigated

2012-12-31 – 2015-12-31

Geographic coverage

Geographic spread

Geographic location: United States

Publications

Dudley, E, Andrén, N, Jankensgård, H 2022. How do Firms Hedge in Financial Distress?, working paper.
DOI: https://doi.org/10.1002/fut.22336

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Dataset
Classification of hedging strategies in the US oil industry 2013-2015

Description

The dataset contains quarterly classification of US oil companies' hedging strategies over the period 2013-2015. The strategies are classified based on reporting in each company's quarterly report. Five strategies are identified (described in the data file). Companies are identified by Global Company Key. The Global Company Key or GVKEY is a unique six-digit number key assigned to each company in the Capital IQ Compustat database

Version 1

Citation

Niclas Andrén, Evan Dudley, Håkan Jankensgård. Lund University (2022). Classification of hedging strategies in the US oil industry 2013-2015 . Swedish National Data Service. Version 1. https://doi.org/10.5878/rmrg-9341

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Data format / data structure

Numeric

Creator/Principal investigator(s)

Niclas Andrén - Lund University, Department of Business Administration orcid

Evan Dudley - Queen's university, Goodes Hall, Smith School of Business

Håkan Jankensgård - Lund University, Department of Business Administration

Time period(s) investigated

2013 – 2015

Data collection

  • Mode of collection: Content coding
  • Description of the mode of collection: Coding of derivatives positions in quarterly reports
  • Time period(s) for data collection: 2012-12-31–2015-12-31
  • Instrument:
  • Sample size: 1116
  • Number of responses: 96
  • Non response size: 1037
  • Cause of non response - Respondent unable to participate: 1037
  • Source of the data: Registers/Records/Accounts: Economic/Financial

Variables

7

Number of individuals/objects

96

Response rate/participation rate

The sample consists of publicly traded oil and gas producers in the United States (SIC code 1311) between Q1:2013 and Q4:2015. Firms are eligible for inclusion in the sample if their headquarters are in the United States, they are publicly listed, and they have at least $1mn in total assets in all quarters. This yields 2153 firm‐quarters, corresponding to 220 unique firms. We furthermore require that 10‐Qs (quarterly reports) be available from the online SEC EDGAR database, and that firms report their derivative positions in sufficient detail to quantify different hedging strategies. Since our object of study is hedging‐instrument choice, we are ultimately constrained to those firms that are derivative users. We use keyword search to identify sample firms that use derivatives. A firm is eligible if it uses derivatives in at least one quarter of the sample period, thereby allowing firms to begin or stop using derivatives. This leaves us with 1320 derivative firm‐quarters. The firm must also report production figures to allow us to calculate hedge ratios, further reducing the sample to 1215 firm‐quarters. To fully explore the impact of distress on hedging portfolios we balance the sample by requiring firms to have at least three quarters of data before (Q1:2013–Q3:2014) and after the oil price collapse in the autumn of 2014 (Q4:2014–Q4:2015). This leaves 1116 firm‐quarters, corresponding to 96 unique firms.

License

Creative Commons  Attribution 4.0 International (CC BY 4.0)
Published: 2022-04-07
Last updated: 2022-05-05