Detecting Illegal Arms Trade

Abstract

Illegal arms are responsible for thousands of deaths in civil wars every year. Yet, their trade is very hard to detect. We propose a method to statistically detect illegal arms trade based on the investor knowledge embedded in financial markets. We focus on eight countries under UN arms embargo in the period 1990-2005, and analyze eighteen events during the embargo that suddenly increase or decrease conflict intensity. If the weapon-making companies are not trading or are trading legally, an event worsening the hostilities should not affect their stock prices or affect them adversely, since it delays the removal of the embargo. Conversely, if the companies are trading illegally, the event may increase stock prices, since it increases the demand for illegal weapons. We detect no significant effect overall. However, we find a large and significant positive reaction for companies head-quartered in countries where the legal and reputation costs of illegal trades are likely to be lower. We identify such countries using measures of corruption and transparency in arms trade. We also suggest a method to detect potential embargo violations based on stock reactions by individual companies, including chains of reactions. The presumed violations are higher for conflicts with more UN investigations and for companies with more Internet stories regarding embargo.