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Results for “gating” · papers 18 · wiki 1
Academic Papers · 18arXiv q-fin live 8 · desk corpus 32
arXiv · arXiv · 2024

Filtered not Mixed: Stochastic Filtering-Based Online Gating for Mixture of Large Language Models

We propose MoE-F - a formalized mechanism for combining $N$ pre-trained Large Language Models (LLMs) for online time-series prediction by adaptively forecasting the best weighting of LLM predictions at every time step. Our mechanism leverages the conditional information in each expert's running performance to forecast the best combination of LLMs for predicting the time series in its next step. Diverging from static

Raeid Saqur, Anastasis Kratsios, Florian Krach, Yannick Limmer, Jacob-Junqi Tian
arXiv · arXiv · 2026

Mitigating Adverse Selection in Concentrated Liquidity AMMs with Dynamic Fees: An Agent-Based Model Approach

Automated Market Makers based on concentrated liquidity, such as Uniswap v3, significantly improve capital efficiency but expose Liquidity Providers (LPs) to adverse selection costs, formalized as Loss-Versus-Rebalancing (LVR). While theoretical literature quantifies these costs, the interplay between realistic blockchain microstructure and endogenous pricing mechanisms remains under-explored. This paper develops a g

Daniele Maria Di Nosse, Fabrizio Lillo
arXiv · arXiv q-fin · 2025

Tokenize Everything, But Can You Sell It? RWA Liquidity Challenges and the Road Ahead

The tokenization of real-world assets (RWAs) promises to transform financial markets by enabling fractional ownership, global accessibility, and programmable settlement of traditionally illiquid assets such as real estate, private credit, and government bonds. While technical progress has been rapid, with over \$25 billion in tokenized RWAs brought on-chain as of 2025, liquidity remains a critical bottleneck. This pa

Rischan Mafrur
arXiv · arXiv · 2017

Navigating dark liquidity (How Fisher catches Poisson in the Dark)

In order to reduce signalling, traders may resort to limiting access to dark venues and imposing limits on minimum fill sizes they are willing to trade. However, doing this also restricts the liquidity available to the trader since an ever increasing quantity of orders are traded by algos in clips. An alternative is to attempt to monitor signalling in real time and dynamically make adjustments to the dark liquidity a

Ilija I. Zovko
arXiv · arXiv · 2025

A Midsummer Meme's Dream: Investigating Market Manipulations in the Meme Coin Ecosystem

From viral jokes to a billion-dollar phenomenon, meme coins have become one of the most popular segments in cryptocurrency markets. Unlike utility-focused crypto assets like Bitcoin, meme coins derive value primarily from community sentiment, making them vulnerable to manipulation. This study presents an unprecedented cross-chain analysis of the meme coin ecosystem, examining 34,988 tokens across Ethereum, BNB Smart

Alberto Maria Mongardini, Alessandro Mei
arXiv · arXiv q-fin · 2026

Volatility Forecasting and Return Prediction under Market Regimes: Evidence from High-Frequency Chinese Equity Data

This study investigates whether regime-dependent volatility forecasting and machine-learning-based return prediction can be jointly integrated to improve both statistical forecasting performance and economic strategy outcomes in equity markets. Using high-frequency CSI 300 Index data from 2005 to 2023, a sequential twostage framework is developed. In the first stage, realized volatility is modeled using regime-augmen

Xinyue Fang, Robert Ślepaczuk
arXiv · arXiv q-fin · 2025

Adaptive Market Intelligence: A Mixture of Experts Framework for Volatility-Sensitive Stock Forecasting

This study develops and empirically validates a Mixture of Experts (MoE) framework for stock price prediction across heterogeneous volatility regimes using real market data. The proposed model combines a Recurrent Neural Network (RNN) optimized for high-volatility stocks with a linear regression model tailored to stable equities. A volatility-aware gating mechanism dynamically weights the contributions of each expert

Diego Vallarino
arXiv · arXiv q-fin · 2020

Portfolio Optimization with 2D Relative-Attentional Gated Transformer

Portfolio optimization is one of the most attentive fields that have been researched with machine learning approaches. Many researchers attempted to solve this problem using deep reinforcement learning due to its efficient inherence that can handle the property of financial markets. However, most of them can hardly be applicable to real-world trading since they ignore or extremely simplify the realistic constraints o

Tae Wan Kim, Matloob Khushi
arXiv · arXiv · 2026

AlgoXpert Alpha Research Framework. A Rigorous IS WFA OOS Protocol for Mitigating Overfitting in Quantitative Strategies

Transitioning a strategy from backtest to live trading is a common failure point for quantitative systems due to parameter overfitting, selection bias, and sensitivity to regime changes. This paper presents the AlgoXpert Alpha Research Framework, a standardized protocol that evaluates strategies across three stages: In Sample (IS), which focuses on stable parameter regions instead of single optima; Walk Forward Analy

The Anh Pham, Bao Chan Nguyen, Nguyet Nguyen Thi
arXiv · arXiv · 2025

Investigating Conditional Restricted Boltzmann Machines in Regime Detection

This study investigates the efficacy of Conditional Restricted Boltzmann Machines (CRBMs) for modeling high-dimensional financial time series and detecting systemic risk regimes. We extend the classical application of static Restricted Boltzmann Machines (RBMs) by incorporating autoregressive conditioning and utilizing Persistent Contrastive Divergence (PCD) to incorporate complex temporal dependency structures. Comp

Siddhartha Srinivas Rentala
arXiv · arXiv · 2025

Mitigating Financial Risk from Climate-Induced Agricultural Price Volatility

Agricultural price volatility, driven by market dynamics and meteorological factors such as temperature and precipitation, poses challenges for sustainable finance, planning, and policy. This study analyzes the impact of climate on crop price volatility for soybean in Madhya Pradesh (India) and Illinois (US), rice in Assam (India), wheat in North Dakota (US), cotton in Gujarat (India), and corn in Iowa (US). Using CM

Sourish Das, Sudeep Shukla, Abbinav Sankar Kailasam, Anish Rai, Sejal Garg
arXiv · arXiv · 2025

The Market Maker's Dilemma: Navigating the Fill Probability vs. Post-Fill Returns Trade-Off

Using data from a live trading experiment on the Binance Bitcoin perpetual, we examine the effects of (i) basic order book mechanics and (ii) the persistence of price changes from immediate to short timescales, revealing the interplay between returns, queue sizes, and orders' queue positions. We document a fundamental trade-off: a negative correlation between maker fill likelihood and post-fill returns. This dictates

Jakob Albers, Mihai Cucuringu, Sam Howison, Alexander Y. Shestopaloff
arXiv · arXiv · 2024

Investigating the Impact of Sovereign Credit Rating Downgrade on the US Equity Market

The primary objective of this study was to examine the impact of the US sovereign credit rating downgrade on its equity market. Utilizing the event study methodology, a sample of three most capitalized listed companies -- Microsoft, Apple, and Amazon -- and the equity market index -- S&P500 -- were used as the proxy for the overall equity market. Three market models were constructed within the estimation window to de

Japheth Torsar Jev
arXiv · arXiv · 2024

Mitigating Extremal Risks: A Network-Based Portfolio Strategy

In financial markets marked by inherent volatility, extreme events can result in substantial investor losses. This paper proposes a portfolio strategy designed to mitigate extremal risks. By applying extreme value theory, we evaluate the extremal dependence between stocks and develop a network model reflecting these dependencies. We use a threshold-based approach to construct this complex network and analyze its stru

Qian Hui, Tiandong Wang
arXiv · arXiv · 2024

Investigating the price determinants of the European Emission Trading System: a non-parametric approach

The European carbon market plays a pivotal role in the European Union's ambitious target of achieving carbon neutrality by 2050. Understanding the intricacies of factors influencing European Union Emission Trading System (EU ETS) market prices is paramount for effective policy making and strategy implementation. We propose the use of the Information Imbalance, a recently introduced non-parametric measure quantifying

Cristiano Salvagnin, Aldo Glielmo, Maria Elena De Giuli, Antonietta Mira
arXiv · arXiv · 2023

Exploiting Unfair Advantages: Investigating Opportunistic Trading in the NFT Market

As cryptocurrency evolved, new financial instruments, such as lending and borrowing protocols, currency exchanges, fungible and non-fungible tokens (NFT), staking and mining protocols have emerged. A financial ecosystem built on top of a blockchain is supposed to be fair and transparent for each participating actor. Yet, there are sophisticated actors who turn their domain knowledge and market inefficiencies to their

Priyanka Bose, Dipanjan Das, Fabio Gritti, Nicola Ruaro, Christopher Kruegel
arXiv · arXiv · 2023

Mitigating Decentralized Finance Liquidations with Reversible Call Options

Liquidations in Decentralized Finance (DeFi) are both a blessing and a curse -- whereas liquidations prevent lenders from capital loss, they simultaneously lead to liquidation spirals and system-wide failures. Since most lending and borrowing protocols assume liquidations are indispensable, there is an increased interest in alternative constructions that prevent immediate systemic-failure under uncertain circumstance

Kaihua Qin, Jens Ernstberger, Liyi Zhou, Philipp Jovanovic, Arthur Gervais
arXiv · arXiv · 2022

Investigating the concentration of High Yield Investment Programs in the United Kingdom

Ponzi schemes that offer absurdly high rates of return by relying on more and more people paying into the scheme have been documented since at least the mid-1800s. Ponzi schemes have shifted online in the Internet age, and some are re-branded as HYIPs or High Yield Investment Programs. This paper focuses on understanding HYIPs' continuous presence and presents various possible reasons behind their existence in today'

Sharad Agarwal, Marie Vasek
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