arXiv research

Deep models for financial transactions are vulnerable to adversarial attacks, especially when adding transaction tokens.

This research develops heuristics to detect CoinJoin transactions on Bitcoin blockchain.

Blockchain offers a decentralized, immutable, transparent system of records. It offers a peer-to-peer network of nodes with no centralised governing entity making it unhackable and therefore, more secure than the traditional paper-based or centralised system of records like banks etc. While there are certain advantages…

This survey analyzes knowledge discovery in cryptocurrency transactions.

It is widely believed that fluctuations in transaction volume, as reflected in the number of transactions and to a lesser extent their size, are the main cause of clustered volatility. Under this view bursts of rapid or slow price diffusion reflect bursts of frequent or less frequent trading, which cause both clustered…

BreachRadar detects points-of-compromise in bank transactions to prevent fraud.

Blockchain technology and, in particular, blockchain-based cryptocurrencies offer us information that has never been seen before in the financial world. In contrast to fiat currencies, all transactions of crypto-currencies and crypto-tokens are permanently recorded on distributed ledgers and are publicly available. As …

Study shows priority access in ELA auctions is less valuable due to volatility risks.

Study reveals inefficiencies in EU carbon trading market.

We quantitatively investigate the ideas behind the often-expressed adage `it takes volume to move stock prices', and study the statistical properties of the number of shares traded $Q_{Δt}$ for a given stock in a fixed time interval $Δt$. We analyze transaction data for the largest 1000 stocks for the two-year period 1…

Prices of commodities or assets produce what is called time-series. Different kinds of financial time-series have been recorded and studied for decades. Nowadays, all transactions on a financial market are recorded, leading to a huge amount of data available, either for free in the Internet or commercially. Financial t…

Event ticket price prediction is important to marketing strategy for any sports team or musical ensemble. An accurate prediction model can help the marketing team to make promotion plan more effectively and efficiently. However, given all the historical transaction records, it is challenging to predict the sale price o…

The process of liquidity provision in financial markets can result in prolonged exposure to illiquid instruments for market makers. In this case, where a proprietary position is not desired, pro-actively targeting the right client who is likely to be interested can be an effective means to offset this position, rather …

Paper uses LLMs to detect financial anomalies.

Interaction graphs, such as those recording emails between individuals or transactions between institutions, tend to be sparse yet structured, and often grow in an unbounded manner. Such behavior can be well-captured by structured, nonparametric edge-exchangeable graphs. However, such exchangeable models necessarily ig…

In this paper we consider an information theoretic approach for the accounting classification process. We propose a matrix formalism and an algorithm for calculations of information theoretic measures associated to accounting classification. The formalism may be useful for further generalizations and computer-based imp…

Intensive development of urban systems creates a number of challenges for urban planners and policy makers in order to maintain sustainable growth. Running efficient urban policies requires meaningful urban metrics, which could quantify important urban characteristics including various aspects of an actual human behavi…

Study confirms eurozone interbank market stability but finds higher collateral reuse.

Nowadays, with the availability of massive amount of trade data collected, the dynamics of the financial markets pose both a challenge and an opportunity for high frequency traders. In order to take advantage of the rapid, subtle movement of assets in High Frequency Trading (HFT), an automatic algorithm to analyze and …

Polymarket-v1 Database tracks 1.2B trades across 1.3M markets with 100% ground-truth direction.

FinSurvival provides a large-scale financial survival modeling benchmark.

Real world markets display power-law features in variables such as price fluctuations in stocks. To further understand market behavior, we have conducted a series of market experiments on our web-based prediction market platform which allows us to reconstruct transaction networks among traders. From these networks, we …

TLMG4Eth combines language and graph models for Ethereum fraud detection.

Investment strategy optimized in markets with transaction costs and search delays.

Transaction costs appear in financial markets in more than one form. There are several results in the literature on small proportional transaction cost and not that many on fixed transaction cost. In the present work, we heuristically study the effect of both types of transaction cost by focusing on a portfolio optimiz…

Model shows how price impact and transaction costs affect trading behavior and profits.

The study examines pricing American options with both exogenous and endogenous transaction costs.

Study reveals dynamic causal relationships between Ethereum transaction fees and economic subsystems.

The paper bridges stochastic control and deep hedging for European call options with transaction costs.

New method improves blockchain analysis by handling temporal changes and scalability.

In this short note, we consider mean-variance optimized portfolios with transaction costs. We show that introducing quadratic transaction costs makes the optimization problem more difficult than using linear transaction costs. The reason lies in the specification of the budget constraint, which is no longer linear. We …

PRAGMA models financial event sequences for various banking tasks.

Improved option pricing model with transaction costs.

The paper optimizes portfolios with transaction costs in a large asset universe.

Study how transaction costs impact stock returns and holdings in equilibrium.

The definition of time is still an open question when one deals with high frequency time series. If time is simply the calendar time, prices can be modeled as continuous random processes and values resulting from transactions or given quotes are discrete samples of this underlying dynamics. On the contrary, if one take…

Bank transactions help predict macroeconomic indexes faster and more accurately.

Ethereum block builders can earn up to $14M/month by reordering transactions, harming users.

Generative model predicts NFT collection transactions based on early history.

We examine the relationship between trading volumes, number of transactions, and volatility using daily stock data of the Tokyo Stock Exchange. Following the mixture of distributions hypothesis, we use trading volumes and the number of transactions as proxy for the rate of information arrivals affecting stock volatilit…

Unified asymptotics for investment in markets with transaction costs and search frictions.

Investigates how trading boundaries change with transaction costs in portfolio selection.

The M and A transactions represent a wide range of unique business optimization opportunities in the corporate transformation deals, which are usually characterized by the high level of total risk. The M and A transactions can be successfully implemented by taking to an account the size of investments, purchase price, …

Cohort analysis speeds up Bitcoin blockchain data queries.

Study finds public procurement awards, especially NGEU-funded ones, boost new lending.

We study partial hedging for game options in markets with transaction costs bounded from below. More precisely, we assume that the investor's transaction costs for each trade are the maximum between proportional transaction costs and a fixed transaction costs. We prove that in the continuous time Black--Scholes (BS) mo…

Money flow models are essential tools to understand different economical phenomena, like saving propensities and wealth distributions. In spite of their importance, most of them are based on synthetic transaction networks with simple topologies, e.g. random or scale-free ones, as the characterisation of real networks i…

LineMVGNN improves AML detection by integrating multi-view graph learning.