arXiv · arXiv q-fin · 2023
We investigate the information content of 3PROTV, a south Korean financial youtube channel. In our sample we found evidence for the hypothesis that the channel have information content on stock selection, but only on negative sentiment. Positively mentioned stock had pre-announcement spike followed by steep fall in stock price around announcement period. Negatively mentioned stock started underperforming around the a…
HyeonJun Kim
arXiv · arXiv · 2013
In agreement with the recent research findings in the econophysics, we propose that the nonlinear dynamic chaos can be generated by the turbulent capital flows in both the quantitative easing transmission channels and the transaction networks channels, when there are the laminar turbulent capital flows transitions in the financial system. We demonstrate that the capital flows in both the quantitative easing transmiss…
Dimitri O. Ledenyov, Viktor O. Ledenyov
arXiv · arXiv · 2008
We study the cluster dynamics of multichannel (multivariate) time series by representing their correlations as time-dependent networks and investigating the evolution of network communities. We employ a node-centric approach that allows us to track the effects of the community evolution on the functional roles of individual nodes without having to track entire communities. As an example, we consider a foreign exchang…
Daniel J. Fenn, Mason A. Porter, Mark McDonald, Stacy Williams, Neil F. Johnson
OpenAlex · The Journal of Economic Perspectives · 1995 · cites 4183
The ‘credit channel’ theory of monetary policy transmission holds that informational frictions in credit markets worsen during tight-money periods. The resulting increase in the external finance premium--the difference in cost between internal and external funds--enhances the effects of monetary policy on the real economy. The authors document the responses of GDP and its components to monetary policy shocks and desc…
Ben Bernanke, Mark Gertler
arXiv · arXiv · 2026
Hybrid Deep Learning for equity index forecasting is limited by three problems: propagation of OHLCV noise into derived technical indicators (TIs), channel-indiscriminate multi-scale decomposition that conflates heterogeneous frequency signatures, and static multi-branch fusion that cannot adapt to market regime shifts. WaVeFuse addresses these limitations through a unified dual-branch architecture. Symlet-4 wavelet …
Aashish Bohra, Vivek Vijay
arXiv · arXiv · 2026
Investors interpret social disclosures from a risk perspective, yet relevant information can reach them through channels that differ sharply in regulatory enforcement and materiality: SEC filings, sustainability reports, or financial reports. We analyse how social disclosure via each channel relates to idiosyncratic risk. Studying S&P 1,500 constituents, we distinguish between initiated and continued disclosure along…
Andreas G. F. Hoepner, Blerita Korca, Frank Schiemann, Fabiola I. Schneider
arXiv · arXiv · 2020
After a market downturn, especially in an uncertain economic environment such as the current state, there can be a relatively long period with a sideways market, where indexes, stocks, etc., move in channels with support and resistance levels. We discuss option pricing in such scenarios, in both cases of unattainable as well as attainable boundaries, and obtain closed-form option pricing formulas. Our results also ap…
Zura Kakushadze
arXiv · arXiv q-fin · 2026
Prediction markets are starting to look less like crowd polls and more like electronic markets. The central question is therefore no longer only whether these markets forecast well, but what happens when institutional liquidity enters: do spreads tighten, does price discovery improve, and do those gains actually reach the traders who are slowest to react when information arrives? This paper offers a research design f…
Shaw Dalen
arXiv · arXiv q-fin · 2026
An order-book market whose liquidity provision is anchored to a fundamental value carries a restoring force: the price mean-reverts to value and the book refills after a shock. We show this restoring force is a robust intrinsic stabiliser and identify it causally-dialling the anchor down removes the mean-reversion, and a leverage-driven fire-sale then self-sustains. Separately, we ask whether a stressed market transm…
Jan Novotny
arXiv · arXiv q-fin · 2026
Automated market maker (AMM) fee rules are often evaluated by liquidity-provider (LP) welfare, but that objective mixes fee revenue, adverse-selection loss (loss-versus-rebalancing, LVR), routing response, and liquidity supply. Fixed-fee Uniswap v3 history cannot separate these channels or identify counterfactual trader-facing dynamic-fee rules. Real fee-related variation nonetheless exists: the Uniswap protocol-fee …
Wen-Ting Wang
arXiv · arXiv q-fin · 2024
We study liquidity on decentralized exchanges (DEXs), identifying factors at the platform, blockchain, token pair, and liquidity pool levels with predictive power for market depth metrics. We introduce the v2 counterfactual spread metric, a novel criterion which assesses the degree of liquidity concentration in pools using the ``concentrated liquidity'' mechanism, allowing us to decompose the effect of a factor on ma…
Brian Z. Zhu, Dingyue Liu, Xin Wan, Gordon Liao, Ciamac C. Moallemi
arXiv · arXiv q-fin · 2019
In order to scale transaction rates for deployment across the global web, many cryptocurrencies have deployed so-called "Layer-2" networks of private payment channels. An idealized payment network behaves like a Credit Network, a model for transactions across a network of bilateral trust relationships. Credit Networks capture many aspects of traditional currencies as well as new virtual currencies and payment mechani…
Geoffrey Ramseyer, Ashish Goel, David Mazieres
arXiv · arXiv q-fin · 2016
Credit and liquidity risks represent main channels of financial contagion for interbank lending markets. On one hand, banks face potential losses whenever their counterparties are under distress and thus unable to fulfill their obligations. On the other hand, solvency constraints may force banks to recover lost fundings by selling their illiquid assets, resulting in effective losses in the presence of fire sales - th…
Giulio Cimini, Matteo Serri
arXiv · arXiv q-fin · 2026
Leverage does not create manipulation or informed trading in event markets, but it changes their economics. We separate four conduct channels: market-price manipulation, real-world outcome manipulation, resolution-process manipulation, and informed trading that exploits non-public information without changing the event or resolution rule. A capital-constrained amplification model shows that gross directional gains sc…
Maksym Nechepurenko
arXiv · arXiv · 2026
Loss-versus-Rebalancing (LVR) is the dominant adverse-selection cost borne by liquidity providers on automated market makers. Under geometric Brownian motion, arbitrage profit scales with the probability of a profitable block, which vanishes as the block time $Δt \to 0$; this is the standing argument for ever-shorter blocks. Modeling the reference price instead as a jump-diffusion, I show that the constant-product LV…
Nils Bundi
arXiv · arXiv · 2021
This article is part of a comprehensive research project on liquidity risk in asset management, which can be divided into three dimensions. The first dimension covers the modeling of the liability liquidity risk (or funding liquidity), the second dimension is dedicated to the modeling of the asset liquidity risk (or market liquidity), whereas the third dimension considers the management of the asset-liability liquidi…
Thierry Roncalli
arXiv · arXiv · 2026
Privacy-preserving exchange designs price on a coarsened view of order flow. We show that a market maker committed to informationally efficient (posterior-mean) pricing on a signal strictly coarser than the flow it settles necessarily cedes a closed-form welfare transfer to traders -- the privacy subsidy -- and that no rule restricted to the coarse signal is simultaneously efficient and zero-profit against the settle…
Yuki Nakamura
arXiv · arXiv · 2023
Introduction: The paper addresses the challenging problem of predicting the short-term realized volatility of the Bitcoin price using order flow information. The inherent stochastic nature and anti-persistence of price pose difficulties in accurate prediction. Methods: To address this, we propose a method that transforms order flow data over a fixed time interval (snapshots) into images. The order flow includes trade…
Artem Lensky, Mingyu Hao