arXiv · arXiv q-fin · 2026
We develop and counterfactually evaluate a resolution-aware risk-design framework (PIRAP) for perpetual futures whose underlying tracks a single binary prediction-market probability through resolution. The framework specifies six components: an index estimator combining mid-price, depth-weighted mid, and time-decayed VWAP; jump-aware tiered margin sized against bounded-event terminal-collapse magnitude; leverage comp…
Maksym Nechepurenko
arXiv · arXiv q-fin · 2023
Financial data is generally time series in essence and thus suffers from three fundamental issues: the mismatch in time resolution, the time-varying property of the distribution - nonstationarity, and causal factors that are important but unknown/unobserved. In this paper, we follow a causal perspective to systematically look into these three demons in finance. Specifically, we reexamine these issues in the context o…
Xinshuai Dong, Haoyue Dai, Yewen Fan, Songyao Jin, Sathyamoorthy Rajendran
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 · 2025
Decentralized prediction markets (DePMs) allow open participation in event-based wagering without fully relying on centralized intermediaries. We review the history of DePMs which date back to 2011 and includes hundreds of proposals. Perhaps surprising, modern DePMs like Polymarket deviate materially from earlier designs like Truthcoin and Augur v1. We use our review to present a modular workflow comprising eight sta…
Nahid Rahman, Joseph Al-Chami, Jeremy Clark
arXiv · arXiv q-fin · 2026
Prediction markets are attracting growing attention as trading volumes rise and their practical relevance increases. To ensure efficient price discovery, liquidity provision becomes ever more important. Due to the binary settlement structure in prediction markets, optimal market making leads to an optimization problem that is fundamentally different from the ones studied in classical settings. In this paper, we devel…
Dominik Feil, Max Nendel
arXiv · arXiv q-fin · 2026
Automated market makers (AMMs) for prediction markets descend from market scoring rules, where a mechanism operator subsidizes a market to aggregate beliefs about uncertain events. The existing literature has focused on bounding the total worst-case loss to the subsidizer, but has not addressed how that loss is distributed across price states or over time. We use the framework of loss-versus-rebalancing (LVR) to stud…
Ciamac C. Moallemi, Dan Robinson, Brian Zhu
arXiv · arXiv q-fin · 2025
Financial markets exhibit an apparent paradox: while directional price movements remain largely unpredictable--consistent with weak-form efficiency--the magnitude of price changes displays systematic structure. Here we demonstrate that real-time order-flow entropy, computed from a 15-state Markov transition matrix at second resolution, predicts the magnitude of intraday returns without providing directional informati…
Mainak Singha
arXiv · arXiv q-fin · 2026
Forward-looking volatility forecasts are central inputs to derivatives pricing, market making, risk management, and volatility-linked trading strategies, with ARCH and GARCH models serving as the canonical workhorses. Such models are natural in standard asset markets, where prices are positive-valued stochastic processes and volatility is typically inferred from return dynamics. Prediction markets have a different st…
Weiye Xi, Ciamac C. Moallemi, Mallesh Pai, Shouqiao Wang
arXiv · arXiv q-fin · 2026
ForesightFlow is an Information Leakage Score (ILS) framework for detecting informed trading on decentralized prediction markets. For an event-resolved binary market, the score quantifies the fraction of the terminal information move priced in before the public news event. Three operational scope conditions (edge effect, non-trivial total move, anchor sensitivity) are stated as preconditions for interpretation. The s…
Maksym Nechepurenko
arXiv · arXiv q-fin · 2020
Proponents of behavioral finance have identified several "puzzles" in the market that are inconsistent with rational finance theory. One such puzzle is the "excess volatility puzzle". Changes in equity prices are too large given changes in the fundamentals that are expected to change equity prices. In this paper, we offer a resolution to the excess volatility puzzle within the context of rational finance. We empirica…
Abootaleb Shirvani, Frank J. Fabozzi
arXiv · arXiv q-fin · 2018
Online financial markets can be represented as complex systems where trading dynamics can be captured and characterized at different resolutions and time scales. In this work, we develop a methodology based on non-negative tensor factorization (NTF) aimed at extracting and revealing the multi-timescale trading dynamics governing online financial systems. We demonstrate the advantage of our strategy first using synthe…
Teruyoshi Kobayashi, Anna Sapienza, Emilio Ferrara
arXiv · arXiv q-fin · 2017
In this paper we address three main objections of behavioral finance to the theory of rational finance, considered as anomalies the theory of rational finance cannot explain: Predictability of asset returns, The Equity Premium, (The Volatility Puzzle. We offer resolutions of those objections within the rational finance. We do not claim that those are the only possible explanations of the anomalies, but offer statisti…
Svetlozar Rachev, Stoyan Stoyanov, Stefan Mittnik, Frank J. Fabozzi, Abootaleb Shirvani
arXiv · arXiv q-fin · 2017
Black-Scholes (BS) is the standard mathematical model for option pricing in financial markets. Option prices are calculated using an analytical formula whose main inputs are strike (at which price to exercise) and volatility. The BS framework assumes that volatility remains constant across all strikes, however, in practice it varies. How do traders come to learn these parameters? We introduce natural models of learni…
Tushar Vaidya, Carlos Murguia, Georgios Piliouras
arXiv · arXiv q-fin · 2012
We propose a framework to study optimal trading policies in a one-tick pro-rata limit order book, as typically arises in short-term interest rate futures contracts. The high-frequency trader has the choice to trade via market orders or limit orders, which are represented respectively by impulse controls and regular controls. We model and discuss the consequences of the two main features of this particular microstruct…
Fabien Guilbaud, Huyên Pham
arXiv · arXiv q-fin · 2010
We study the cascading dynamics immediately before and immediately after 219 market shocks. We define the time of a market shock T_{c} to be the time for which the market volatility V(T_{c}) has a peak that exceeds a predetermined threshold. The cascade of high volatility "aftershocks" triggered by the "main shock" is quantitatively similar to earthquakes and solar flares, which have been described by three empirical…
Alexander M. Petersen, Fengzhong Wang, Shlomo Havlin, H. Eugene Stanley
arXiv · arXiv · 2026
Magnetohydrodynamic (MHD) phenomena play a pivotal role in the design and operation of nuclear fusion systems, where electrically conducting fluids (such as liquid metals or molten salts employed in reactor blankets) interact with magnetic fields of varying intensity and orientation, influencing the resulting flow dynamics. The numerical solution of MHD models entails the resolution of highly nonlinear, multiphysics …
M. Lo Verso, C. Introini, E. Cervi, L. Savoldi, J. N. Kutz