Abstract:
Purpose and Rationale: It is known that supply chain disruptions have a
negative stock price effect and that the effect is stronger if these are caused by
catastrophes. However, these effects of hurricane-induced supply chain
disruptions on stock price remain unexplored, even though the annual average
hurricane damage in the US due to hurricanes is $54bn, of which $9bn is to
commercial businesses. This thesis aims to: 1. Explore, classify and connect the
three concepts of natural disasters, supply chain disruption (SCD) and firm
financial performance in one framework. 2. Identify potentially influencing factors
and test if, and in which way, these influence the effect of hurricanes on stock
price. 3. Define a statistical model to evaluate the effect of hurricanes on stock
price. The main focus is on manufacturing firms.
Design/Methodology/Approach: This research is quantitative. The daily closing
value of 625 manufacturing companies that were listed on the NYSE between
2014 and 2018 was analysed. Autoregressive Integrated Moving Average
(ARIMA) was applied in combination with intervention analysis to model the stock
price time series. In total six deduced hypotheses were tested. The statistical
interruptions in stock prices due to hurricane announcements and hurricane
incident announcements were investigated. The method allowed estimation of
the magnitude and temporal patterns of change by applying transfer functions.
Multiple factors that potentially influence the magnitude or pattern of the stock
price reaction were tested, including details of damage.
Findings: Both hurricane incident announcements and hurricane
announcements negatively affect a firm’s stock price, mostly in the form of a
transitory change. Industry moderates the stock price reaction to hurricane
announcements. Minor supply chain disruptions are the only impacts resulting in
a positive reaction. Providing details on actual damage leads to less negative and
mostly positive reactions. Companies providing information on preventive
closures are unlikely to suffer a negative reaction.
Practical Implications: Hurricane risk needs to be actively managed by firms in
all sectors; however, the preparation needs to be sector-specific. Firms should
focus their efforts on managing supply chain disruptions. Additionally, firms need
to communicate in a transparent way to reduce shareholders’ uncertainty and
increase trust, so that the stock prices reactions are less negative.
Originality: This thesis provides a single framework connecting disasters, supply
chain disruptions and firm performance, thereby bridging supply chain
management and financial economics literature. The thesis evaluates the effect
of hurricane-induced supply chain disruptions for the first time. It does not analyse
just the effect of hurricane incident announcements but also hurricane
announcements and compares both. Autoregressive integrated moving average
(ARIMA) in combination with an intervention model was applied as an alternative
to the frequently used event study methodology. This approach is chosen to
evaluate the effect of hurricane announcements and hurricane incident
announcements on the daily stock price time series of the firms in scope. Longer
term effects can be evaluated, and the best fitting transfer functions are
assessed. The model accounts for autocorrelation, trend, seasonality, and drift
patterns. Additionally, the effect of the following potentially influencing factors was
tested as these have only been touched on in the existing literature so far: impact
type, impact extent, detailed damage, and preventive closure.