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.
Silence on suspicious stock market patterns persists despite lack of plausible explanations.
Based on empirical financial time-series, we show that the "silence-breaking" probability follows a super-universal power law: the probability of observing a large movement is inversely proportional to the length of the on-going low-variability period. Such a scaling law has been previously predicted theoretically [R. …
Following the approach of standard filtering theory, we analyse investor-valuation of firms, when these are modelled as geometric-Brownian state processes that are privately and partially observed, at random (Poisson) times, by agents. Tasked with disclosing forecast values, agents are able purposefully to withhold the…
New benchmark uncovers hidden biases in LLMs that refuse to answer certain queries.
AI agents on social networks rarely engage in extended conversations.
Model analyzes how firms balance full disclosure with selective disclosure to maintain a good reputation.
The problem of identifying voice commands has always been a challenge due to the presence of noise and variability in speed, pitch, etc. We will compare the efficacies of several neural network architectures for the speech recognition problem. In particular, we will build a model to determine whether a one second audio…
QSD enhances deep network performance through biologically plausible dropout.
The problem of keyword spotting i.e. identifying keywords in a real-time audio stream is mainly solved by applying a neural network over successive sliding windows. Due to the difficulty of the task, baseline models are usually large, resulting in a high computational cost and energy consumption level. We propose a new…
Sequence discriminative training criteria have long been a standard tool in automatic speech recognition for improving the performance of acoustic models over their maximum likelihood / cross entropy trained counterparts. While previously a lattice approximation of the search space has been necessary to reduce computat…
A new property fixes look-ahead bias in backtesting and trading pipelines.
Study optimizes market making in Chinese stock market with stochastic control and scenario analysis.
Open markets are a subset of equity markets with fixed top stocks, changing over time.
Study applies market microstructure to Cuban informal currency market, finding market makers improve liquidity.
Study finds varying market efficiency in prewar and wartime Japanese stock market.
Study uses Kalman-Filter to assess market efficiency in major stock markets.
Recent innovations in Information and Communication Technologies (ICT) provide new opportunities and challenges for integration of distributed energy resources (DERs) into the energy supply system as active market players. By increasing integration of DERs, novel market platform should be designed for these new market …
We study the effect of globalization on the Korean market, one of the emerging markets. Some characteristics of the Korean market are different from those of the mature market according to the latest market data, and this is due to the influence of foreign markets or investors. We concentrate on the market network stru…
Study shows informed traders harm market makers but price discovery benefits outweigh costs.
We investigate the possibility of statistical evaluation of the market completeness for discrete time stock market models. It is known that the market completeness is not a robust property: small random deviations of the coefficients convert a complete market model into a incomplete one. The paper shows that market inc…
This thesis applies RL to market making in China's commodity market.
Research predicts money market volume based on capital market and bank rates ratio.
The possibility of statistical evaluation of the market completeness and incompleteness is investigated for continuous time diffusion stock market models. It is known that the market completeness is not a robust property: small random deviations of the coefficients convert a complete market model into a incomplete one.…
This study examines how DMMs affect market liquidity and competition.
AI learns market manipulation through simulation, suggesting regulation.
Optimal market making strategy for electronic markets with persistent order flows.
The paper finds that bear markets cause recessions and bull markets cause expansions, with bull markets having a stronger causal effect.
PRIME models cryptocurrency exchange market impact.
Article examines NFT market microstructure and trading risks.
In a stock market, the numeraire portfolio, if it exists, is the portfolio with the highest expected logarithmic growth rate at all times. A numeraire market is a stock market for which the market portfolio is the numeraire portfolio. We study open markets, markets comprising the higher capitalization stocks within a b…
This study evaluates prewar Japanese financial market efficiency using time-varying models.
ABM simulates OTC government bond market dynamics, enhancing liquidity and stability.
This study examines how market makers balance risk and impact in foreign exchange markets.
Study shows how market efficiency changes during the pandemic.
Two markets should be considered isomorphic if they are financially indistinguishable. We define a notion of isomorphism for financial markets in both discrete and continuous time. We then seek to identify the distinct isomorphism classes, that is to classify markets. We classify complete one-period markets. We define …
We investigate the relative market efficiency in financial market data, using the approximate entropy(ApEn) method for a quantification of randomness in time series. We used the global foreign exchange market indices for 17 countries during two periods from 1984 to 1998 and from 1999 to 2004 in order to study the effic…
The structure of return spillovers is examined by constructing Granger causality networks using daily closing prices of 20 developed markets from 2nd January 2006 to 31st December 2013. The data is properly aligned to take into account non-synchronous trading effects. The study of the resulting networks of over 94 sub-…
Market-maker optimizes quotes based on strategic market-takers' behavior.
This paper analyzes microstructure dynamics in coupled markets using CFMMs.
We introduce Hermite fractional financial markets, where market uncertainties are described by multidimensional Hermite motions. Hermite markets include as particular cases financial markets driven by multivariate fractional Brownian motion and multivariate Rosenblatt motion. Conditions for no-arbitrage and market comp…
This study examines whether the efficiency of cryptocurrency markets (Bitcoin and Ethereum) evolve over time based on Lo's (2004) adaptive market hypothesis (AMH). In particular, we measure the degree of market efficiency using a generalized least squares-based time-varying model that does not depend on sample size, un…
Uniswap markets perform well and closely track reference prices.
Study uses RL to simulate realistic market behavior.
Pari-mutuel markets are trading platforms through which the common market maker simultaneously clears multiple contingent claims markets. This market has several distinctive properties that began attracting the attention of the financial industry in the 2000s. For example, the platform aggregates liquidity from the ind…
Competition has been introduced in the electricity markets with the goal of reducing prices and improving efficiency. The basic idea which stays behind this choice is that, in competitive markets, a greater quantity of the good is exchanged at a lower and a lower price, leading to higher market efficiency. Electricity …
Paper uses AI to predict tail risks in US financial markets.
In most OTC markets, a small number of market makers provide liquidity to other market participants. More precisely, for a list of assets, they set prices at which they agree to buy and sell. Market makers face therefore an interesting optimization problem: they need to choose bid and ask prices for making money while …
The paper proposes a new algorithm for dealer markets that incorporates hedging and market impact.