How do Firms Hedge in Financial Distress? - Classification of hedging strategies in the US oil industry 2013-2015
SND-ID: 2022-47-1. Version: 1. DOI: https://doi.org/10.5878/rmrg-9341
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Creator/Principal investigator(s)
Niclas Andrén
- Lund University, Department of Business Administration
Evan Dudley - Queen's university, Goodes Hall, Smith School of Business
Håkan Jankensgård - Lund University, Department of Business Administration
Research principal
Lund University
- Department of Business Administration
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
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 impact. The dataset contains the classifiers for these five hedging strategies and is identified by quarter and global company key (GVKEY).
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 Show less..
Data contains personal data
No
Language
Unit of analysis
Population
The population consists of publicly traded oil and gas producers in the US (SIC code 1311)
Time Method
Sampling procedure
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
2013 – 2015
Variables
7
Number of individuals/objects
96
Response rate/participation rate
Data format / data structure
Geographic spread
Geographic location: United States
Responsible department/unit
Department of Business Administration
Research area
Economics (Standard för svensk indelning av forskningsämnen 2011)
Business administration (Standard för svensk indelning av forskningsämnen 2011)
Keywords
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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