A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
This survey analyzes knowledge discovery in cryptocurrency transactions.
Model shows how price impact and transaction costs affect trading behavior and profits.
Motivated by how transaction amount constrain trading volume and price volatility in stock market, we, in this paper, study the relation between volume and price if amount of transaction is given. We find that accumulative trading volume gradually emerges a kurtosis near the price mean value over a trading price range …
The paper analyzes transaction fees on blockchains using a priority queue model.
A new method detects fraud transactions by analyzing user behavior over time.
Paper uses GANs to simulate consumer transactions with SKU constraints.
This study reveals statistical patterns in ERC20 token transactions on Ethereum blockchain.
We consider fractional Black-Scholes market with proportional transaction costs. When transaction costs are present, one trades periodically i.e. we have the discrete trading with equidistance between trading times. We derive a non trivial hedging error for a class of European options with convex payoff in the…
The paper analyzes strategic behavior in reinsurance transactions leading to Nash equilibria.
We study the arbitrage opportunities in the presence of transaction costs in a sequence of binary markets approximating the fractional Black-Scholes model. This approximating sequence was constructed by Sottinen and named fractional binary markets. Since, in the frictionless case, these markets admit arbitrage, we aim …
Data science detects Ethereum honeypots using transaction behavior.
The paper develops an expansion for optimizing portfolios with small quadratic transaction costs.
Study XRP network, propose Flow Index to analyze transaction frequencies.
UNMIX identifies hidden buyers in darknet markets by clustering anonymized IDs.
Revisits behavioral finance option pricing model to align with rational asset pricing theory.
Model predicts option movements using residual transactions for better market timing.
Research predicts XRP price anomalies using graph topologies.
Investigates portfolio selection with transaction costs and stochastic volatility, using deep learning for computation.
Agent optimizes risky asset trading times based on Prospect Theory.
The paper analyzes portfolio selection with non-concave utility and transaction costs.
Enhances Ponzi scheme detection on Ethereum using time-aware metapaths.
Human stablecoin transactions predict political risk in cryptocurrency markets.
Despite the availability of very detailed data on financial market, agent-based modeling is hindered by the lack of information about real trader behavior. This makes it impossible to validate agent-based models, which are thus reverse-engineering attempts. This work is a contribution to the building of a set of styliz…
We study the tick dynamical behavior of the bond futures in Korean Futures Exchange(KOFEX) market. Since the survival probability in the continuous-time random walk theory is applied to the bond futures transaction, the form of the decay function in our bond futures model is discussed from two kinds of Korean Treasury …
The Bitcoin transaction graph is a public data structure organized as transactions between addresses, each associated with a logical entity. In this work, we introduce a complete probabilistic model of the Bitcoin Blockchain. We first formulate a set of conditional dependencies induced by the Bitcoin protocol at the bl…
Investors in Bitcoin exhibit the disposition effect, selling winners and holding losers.
A new method detects financial fraud using graph transformers.
The cryptocurrency market is a very huge market without effective supervision. It is of great importance for investors and regulators to recognize whether there are market manipulation and its manipulation patterns. This paper proposes an approach to mine the transaction networks of exchanges for answering this questio…
Paper uses Super-App data to improve income estimation models.
The asymmetric price impact between the institutional purchases and sales of 32 liquid stocks in Chinese stock markets in year 2003 is carefully studied. We analyze the price impact in both drawup and drawdown trends with consecutive positive and negative daily price changes, and test the dependence of the price impact…
The common assumption of universal behavior in stock market data can sometimes lead to false conclusions. In statistical physics, the Hurst exponents characterizing long-range correlations are often closely related to universal exponents. We show, that in the case of time series of the traded value, these Hurst exponen…
Bitcoin is a cryptocurrency that features a distributed, decentralized and trustworthy mechanism, which has made Bitcoin a popular global transaction platform. The transaction efficiency among nations and the privacy benefiting from address anonymity of the Bitcoin network have attracted many activities such as payment…
Mining association rules is an important technique for discovering meaningful patterns in transaction databases. Many different measures of interestingness have been proposed for association rules. However, these measures fail to take the probabilistic properties of the mined data into account. In this paper, we start …
We develop a theoretical trading conditioning model subject to price volatility and return information in terms of market psychological behavior, based on analytical transaction volume-price probability wave distributions in which we use transaction volume probability to describe price volatility uncertainty and intens…
The increasing accessibility of data provides substantial opportunities for understanding user behaviors. Unearthing anomalies in user behaviors is of particular importance as it helps signal harmful incidents such as network intrusions, terrorist activities, and financial frauds. Many visual analytics methods have bee…
Different models to study the wealth distribution in an artificial society have considered a transactional dynamics as the driving force. Those models include a risk aversion factor, but also a finite probability of favoring the poorer agent in a transaction. Here we study the case where the partners in the transaction…
Recent research on Bitcoin Transaction Networks reveals a growing, sparse, and core-periphery structure.
We derive behavioral finance option pricing formulas consistent with the rational dynamic asset pricing theory. In the existing behavioral finance option pricing formulas, the price process of the representative agent is not a semimartingale, which leads to arbitrage opportunities for the option seller. In the literatu…
We investigate the correlation properties of transaction data from the New York Stock Exchange. The trading activity f(t) of each stock displays a crossover from weaker to stronger correlations at time scales 60-390 minutes. In both regimes, the Hurst exponent H depends logarithmically on the liquidity of the stock, me…
Paper analyzes liquidity for everlasting options in DeFi, offering strategies to reduce costs.
We study the continuous time random walk theory from financial tick data of the yen-dollar exchange rate transacted at the Japanese financial market. The dynamical behavior of returns and volatilities in this case is particularly treated at the long-time limit. We find that the volatility for prices shows a power-law w…
This paper analyzes tokenized U.S. Treasuries, revealing patterns and roles in blockchain transactions.
Faster Ethereum slots boost CEX-DEX arbitrage by 535% and 203%.
Next basket recommendation, which aims to predict the next a few items that a user most probably purchases given his historical transactions, plays a vital role in market basket analysis. From the viewpoint of item, an item could be purchased by different users together with different items, for different reasons. Ther…
Paper introduces a method to assess liquidity risk in meme tokens using entity-linked address analysis.
Due to the popularity of the Internet and smart mobile devices, more and more financial transactions and activities have been digitalized. Compared to traditional financial fraud detection strategies using credit-related features, customers are generating a large amount of unstructured behavioral data every second. In …
Prediction markets can shape political behavior through persistent signals, not just forecast accuracy.
Paper introduces a specialized text classification system for French Open Banking transactions.