Paper
Official diplomatic text series
Diplomatic Sentiment Observatory
Daily country-level indices derived from official foreign-ministry publications. Three parallel series measure war-related, economic, and other diplomatic sentiment on a common -3 to 3 scale.
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Citation
Please cite the paper when using this dataset
APA Style
Yang, C., Zhang, S., Kyriakou, I., & Papapostolou, N. C. (2026). When words move money: Diplomatic sentiment and international capital flows. SSRN. https://ssrn.com/abstract=6437669
Chicago Style
Yang, Cunyi, Shuchi Zhang, Ioannis Kyriakou, and Nikos C. Papapostolou. 2026. "When Words Move Money: Diplomatic Sentiment and International Capital Flows." SSRN. https://ssrn.com/abstract=6437669
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Selected branch - 30-day change
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Compared with the 30-day smoothed value 30 days earlier
Latest publication
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Earliest observation
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Latest observation
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Overview
Cross-Country DSI Signal Board
Latest seven-day readings for the fifteen-country panel. Each series uses the same construction rules and common score range.
Explorer
Index Explorer
Country-level publication-day scores with seven-day and thirty-day smoothed series for each DSI branch.
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Method
How Diplomatic Text Becomes DSI
DSI is neither keyword counting nor one-shot sentiment scoring. It comes from cleaning official diplomatic texts, scoring them across three diplomatic dimensions, validating the results through consensus checks, and aggregating them into daily high-frequency indices.
Collect and clean official texts
The paper starts from official releases by multiple foreign ministries, including press-conference transcripts, statements, briefings, and written responses. These texts are segmented, stripped of greetings and procedural language, and reorganized into comparable daily series.
Identify sentiment in three stages
The paper scores official texts across three diplomatic dimensions: war-related, economic, and other diplomatic sentiment. Each dimension is converted into a discrete score from -3 to 3 before daily aggregation.
Run consensus checks and manual audits
To reduce misclassification, the paper repeats each judgement multiple times. Only matching results pass directly; disagreements are reviewed before moving on. The pipeline is also audited against manually labelled samples to keep the classifications close to researcher judgement.
Construct the daily index series
The paper first forms a raw score on each publication day for each DSI branch. When multiple texts appear on the same day, the raw daily value takes the lowest score observed that day rather than an average. Missing days are then forward-filled, and the 3-day, 7-day, and 30-day series are computed as rolling means on that filled daily path.
Why It Matters
What We Have Already Found in the DSI Data
Our current paper evidence is strongest on the war-related branch, but the broader DSI family is designed to support parallel work on geopolitical expectations, cross-border capital flows, market responses, and future branch-specific extensions.
It moves before conventional risk measures
Our paper finds that war-related diplomatic wording often shifts before standard geopolitical risk indicators do, making it useful for detecting changes in market expectations around escalation or de-escalation earlier.
It changes the direction of cross-border flows
In the China sample, more negative war-related diplomatic sentiment is associated with stronger capital outflow pressure. Our estimates show that a one-unit decline in China's war-related DSI corresponds to roughly a 35.6 million USD shift in daily net flows toward outflows.
It carries both safe-haven and spillover effects
Our paper also finds that more negative U.S. diplomatic sentiment is associated with stronger safe-haven demand for U.S. equities. Negative sentiment from the United Kingdom, Japan, and South Korea also spills over into the Chinese market, with clearer effects on returns and trading activity.
Research extensions
The raw, 7-day, and 30-day series support event studies, cross-country comparisons, asset-pricing applications, and capital-flow analysis.
Download
Data Downloads
This section provides a combined DSI workbook, branch-specific cross-country panels, and country-level workbooks that include all three DSI branches together with raw publication-day values and 3-day, 7-day, and 30-day smoothed series.
Supplement
Trump Indices Supplement
This bottom panel adds an actor-level signal alongside the ministry-based DSI family. It tracks Donald Trump's own cross-platform posting tone, geopolitical stance, and shock intensity across Twitter and Truth Social, and should be read as a complement to the broader DSI site rather than as a substitute for any single ministry-based DSI branch.
Coverage
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Latest date
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Scored posts
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Platforms
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Trump Tone Index
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Trump Geopolitical Index
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Trump Shock Index
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Directed Signals
Trump Directed Sentiment by Country
This extension isolates Trump's country-targeted rhetoric across the same fourteen-country universe used elsewhere on the site. Country-directed tone and geopolitical stance are only defined on dates with a material mention of that country, while attention tracks how intensely the country is being referenced.
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Countries
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Candidate texts
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Directed Tone
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