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Andro Merćep

Publications and source records attributed to Andro Merćep.

2 recordsLinked to original sources

Robocalls: A Worldwide or US-only Problem? Analyzing Spam and Fraud in International Phone Calls

Unsolicited automated phone calls (robocalls) are a serious threat: in the US alone, these calls resulted in reported losses of 1.1$ billion during 2025. Phishing and spoofing consistently rank among the most reported crimes within the FBI's Internet Crime Complaint Center, with phone call scams having the highest reported median loss. Combating robocalls is difficult due to many legal and practical constraints: robocalls often encompass multiple legal jurisdictions of different countries/states, the large volume of robocalls, their multilingual nature, the lack of publicly available data, privacy concerns with obtaining data, etc. We present a study of international robocalls, aggregating robocall reports from countries across all inhabited continents and contribute by providing new findings on international robocalls from 65 different countries. We also present the first publicly available multimodal and international robocall dataset: 8.7 million call detail records, 839 robocall transcripts from 28 identified robocall campaign clusters, and 677 robocall recordings. We describe our methodology for collecting robocall data over a 9-month period and provide a detailed analysis comparing robocalls in the US with those in other countries. Our analysis covers several aspects, including uncovering calling patterns, identifying co-targeting attacks, discovering common robocall campaigns, extracting callback numbers, analyzing linguistic differences among robocalls in the same language but different regions, and other insights. Our results indicate that although robocalls are an international problem, the severity of the threat is significantly higher in the US than in other countries. We provide steps for future research and suggest remedies to reduce the effectiveness of robocalls based on our analysis.

cs.CR

Statistical arbitrage portfolio construction based on preference relations

Statistical arbitrage methods identify mispricings in securities with the goal of building portfolios which are weakly correlated with the market. In pairs trading, an arbitrage opportunity is identified by observing relative price movements between a pair of two securities. By simultaneously observing multiple pairs, one can exploit different arbitrage opportunities and increase the performance of such methods. However, the use of a large number of pairs is difficult due to the increased probability of contradictory trade signals among different pairs. In this paper, we propose a novel portfolio construction method based on preference relation graphs, which can reconcile contradictory pairs trading signals across multiple security pairs. The proposed approach enables joint exploitation of arbitrage opportunities among a large number of securities. Experimental results using three decades of historical returns of roughly 500 stocks from the S\&P 500 index show that the portfolios based on preference relations exhibit robust returns even with high transaction costs, and that their performance improves with the number of securities considered.

q-fin.PM