Quantitative model predicts Sri Lankan stock market using NLP, clustering, and time-series forecasting.
problem Predicting economic regimes and market signals in Sri Lankan stock indices.
method Integrates NLP, clustering, and time-series forecasting; uses FinBERT for sentiment analysis, UMAP/HDBSCAN for clustering, and GRU/LSTM for forecasting.
result GRU model achieves 80.1% R-squared for daily closing price forecasts.
New systemic risk indicator measures stock market reactions globally.
problem Analyzing systemic risk in diverse financial markets.
method Implied and realized volatility approach, focusing on historical and long-term volatility.
result IVRVSRI shows varying stock market reactions and shock persistence across locations.
Study examines USD exchange rate dynamics using Kramers-Moyal expansion.
problem Understanding and predicting exchange rate instability.
method Kramers-Moyal expansion and Fokker-Planck formalism applied to log-return data.
result Identifies a stabilizing linear drift and nonlinear diffusion term in exchange rate fluctuations.
Paper tackles ESG rating disagreement in sustainable investing portfolios.
problem Lack of alignment between ESG ratings from different agencies affects investment decisions.
method Proposes a nonlinear optimization model reformulated as a convex quadratic program to address ESG rating disagreement.
result The proposed model can effectively manage ESG rating disagreement and improve investment decisions.
New method certifies images against transformations like rotations and translations.
problem Certifying robustness of images against transformations like rotations and translations.
method Randomized smoothing with three different kinds of defenses.
result Individual certificates can be obtained via statistical error bounds or efficient online inverse computation.
Paper introduces FoMoH for optimization without backpropagation.
problem Optimizing machine learning models without backpropagation.
method Second-order hyperplane search, forward-mode stochastic gradient method, hyper-dual numbers, FoMoH.
result Developed a novel optimization algorithm that avoids backpropagation.
Direct neural ratio estimator for likelihood-free inference.
problem Efficient likelihood estimation for complex models.
method Amortized likelihood ratio estimation using neural networks.
result DNRE often outperforms previous ratio estimators.
A new model selects low-carbon mutual funds considering ESG criteria, risk, and investor preferences.
problem Aligning financial investments with a low-carbon economy.
method Tri-criterion portfolio selection model using a preference-based multi-objective genetic algorithm (ev-MOGA).
result The model successfully incorporates carbon risk exposure and loss-adverse attitudes into portfolio construction.
Study optimizes market making in Chinese stock market with stochastic control and scenario analysis.
problem Limited research on market making in Chinese stock market.
method Optimal market making framework with exponential CARA utility function, accounting for market conditions and risks.
result Impact of volatility and stamp duty on market maker's profit and liquidity.
Open markets are a subset of equity markets with fixed top stocks, changing over time.
problem Understanding the dynamics and characteristics of open markets.
method Analyzing the similarities and differences between open markets and closed equity markets, and exploring specific topics like CAPM and portfolio construction.
result The equivalence of market viability and the existence of a numeraire portfolio holds in open markets, similar to closed markets.
Study applies market microstructure to Cuban informal currency market, finding market makers improve liquidity.
problem Understanding dynamics of informal currency markets.
method Modeling bid/ask intentions using Limit Order Book, applying Avellaneda-Stoikov model with Market Maker.
result Market Maker improves market quality and bid/ask dynamics.
Study finds varying market efficiency in prewar and wartime Japanese stock market.
problem Measuring market efficiency in prewar and wartime Japanese stock market.
method Using a new market capitalization-weighted stock price index, the study examines market efficiency over time and historical events.
result The adaptive market hypothesis is supported in the prewar and wartime Japanese stock market, with efficiency varying over time and with historical events.
Study uses Kalman-Filter to assess market efficiency in major stock markets.
problem Assessing market efficiency in major stock markets.
method Utilizes Kalman-Filter in two stages, assuming a trendline representing true market value.
result Significant portfolio returns in emerging and developed 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.
problem Informed traders' impact on market makers' profitability.
method Agent-based model with heterogeneous learning agents, multi-agent reinforcement learning.
result Informed market order flow is harmful when aggregate informedness is low but beneficial as it increases.
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.
problem Leverage RL for market making in China's commodity market.
method Developed an automatic trading system using RL.
result RL is feasible for market making in China's commodity market.
Research predicts money market volume based on capital market and bank rates ratio.
problem Understanding the influence of capital market and bank rates on money market instruments.
method Correlation matrix and time series model to predict money market volume.
result Predictive model for money market instrument volume based on historical data.
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.
problem The impact of DMMs on market liquidity and competition.
method Agent-based simulations to explore the effects of varying competition levels and incentive structures among DMMs.
result Optimal competition among DMMs maximizes liquidity benefits without negatively impacting price discovery.
AI learns market manipulation through simulation, suggesting regulation.
problem Regulating AI to prevent market manipulation.
method Used a genetic algorithm in an artificial market simulation.
result AI discovered market manipulation as an optimal strategy.
Optimal market making strategy for electronic markets with persistent order flows.
problem Market making on electronic markets with persistent order flows.
method Formulated as a stochastic control problem, characterized by viscosity solutions, and implemented numerically.
result Characterization of an optimal market making strategy.
The paper finds that bear markets cause recessions and bull markets cause expansions, with bull markets having a stronger causal effect.
problem Understanding the asymmetric causal relationships between market conditions and economic cycles.
method Asymmetric causality tests using partial sums of positive and negative market components, with bootstrap simulations and leverage adjustments.
result Bear markets cause recessions and bull markets cause expansions, with bull markets having a stronger causal effect.
PRIME models cryptocurrency exchange market impact.
problem Understanding and predicting market impact in cryptocurrency exchanges.
method Developed a multi-agent simulation to model market impact.
result Allows better estimation of market slippage and knock-on consequences.
Article examines NFT market microstructure and trading risks.
problem Difficulty in distinguishing genuine NFTs from fads and scams.
method Analyzes price formation, market structure, and transparency.
result Provides due-diligence pointers to mitigate NFT trading risk.
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.
problem Determining when prewar Japanese financial market lost its price formation function.
method Time-varying parameter model, generalized least squares-based time-varying vector autoregressive model.
result The prewar Japanese financial market lost its price formation function in 1932.
ABM simulates OTC government bond market dynamics, enhancing liquidity and stability.
problem Understanding and ensuring market stability and liquidity in OTC government bond markets.
method Developed a bespoke ABM to simulate market-maker interactions and test hypotheses.
result Greater agent diversity enhances market liquidity and reducing market-making costs improves stability.
This study examines how market makers balance risk and impact in foreign exchange markets.
problem Balancing risk management with market impact in foreign exchange markets.
method An intermediate scenario approach considering both instantaneous and permanent market impact components.
result Transient market impact is more prevalent than previously thought, challenging traditional market impact models.
Study shows how market efficiency changes during the pandemic.
problem Understanding market efficiency during the pandemic.
method Applied time-varying vector autoregression model.
result Market efficiency changes over time and can be improved by enhanced linkages.
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.
problem Optimizing market-making strategies in a strategic trading environment.
method Mean-field game approach to model strategic market-takers and derive optimal controls.
result Derivation of optimal controls for market-maker and market-taker.
This paper analyzes microstructure dynamics in coupled markets using CFMMs.
problem Quantifying contributions of CFMMs to market dynamics in coupled markets.
method Examined constant function market makers (CFMMs) in coupled markets, focusing on basket inflation/deflation.
result CFMMs contribute significantly to basket inflation/deflation in coupled markets.
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.
problem Understanding and validating the performance of Uniswap markets.
method Formal analysis and numerical simulation of constant product markets.
result Uniswap markets closely track reference prices under common conditions.
Study uses RL to simulate realistic market behavior.
problem Traditional market simulators lack realistic dynamic behavior.
method Agent-based simulation with reinforcement learning agents.
result RL agents simulate realistic stylized facts and 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.
problem Predicting extreme risks in US financial markets.
method Multivariate multilevel CAViaR model optimized by gradient descent and genetic algorithm.
result Credit market's spillover effect on stock market is greater and longer-lasting.
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.
problem How to manage risk and quote prices in dealer markets with limited internalization.
method Develops a mathematical model that allows dealers to hedge part of their inventory and adjust quotes based on inventory size.
result Dealers can internalize risk within a certain inventory range and externalize it outside of that range, optimizing their quoting strategy.
Optimizes profit in targeted marketing across multiple markets with varying marketing expenditures.
problem Maximizing profit in a sequential marketing strategy with multiple markets and varying marketing costs.
method Near-optimal algorithms in an adversarial bandit setting, proving regret bounds for different demand curve types.
result Proved near-optimal regret bounds for the profit-maximization problem in targeted marketing.
Decentralized prediction markets use AMMs to pool and withdraw liquidity, improving financial properties.
problem Creating a fair and efficient decentralized prediction market.
method Developed a liquidity-based AMM structure for prediction markets, studied liquidity management, and proposed trading fees.
result The decentralized AMM structure satisfies financial properties and can be managed with liquidity withdrawal.
In the age of globalization, it is natural that the stock market of each country is not independent form the other markets. In this case, collective behavior could be emerged form their dependency together. This article studies the collective behavior of a set of forty influential markets in the world economy with the …