Search

Search

Papers, wiki, Option Blackboard, encyclopedia, and cards.

Results for “BTC” · papers 16 · wiki 4
Academic Papers · 16arXiv q-fin live 8 · desk corpus 13
arXiv · arXiv q-fin · 2025

Bootstrapping Liquidity in BTC-Denominated Prediction Markets

Prediction markets have gained adoption as on-chain mechanisms for aggregating information, with platforms such as Polymarket demonstrating demand for stablecoin-denominated markets. However, denominating in non-interest-bearing stablecoins introduces inefficiencies: participants face opportunity costs relative to the fiat risk-free rate, and Bitcoin holders in particular lose exposure to BTC appreciation when conver

Fedor Shabashev
arXiv · arXiv · 2025

RL-Exec: Impact-Aware Reinforcement Learning for Opportunistic Optimal Liquidation, Outperforms TWAP and a Book-Liquidity VWAP on BTC-USD Replays

We study opportunistic optimal liquidation over fixed deadlines on BTC-USD limit-order books (LOB). We present RL-Exec, a PPO agent trained on historical replays augmented with endogenous transient impact (resilience), partial fills, maker/taker fees, and latency. The policy observes depth-20 LOB features plus microstructure indicators and acts under a sell-only inventory constraint to reach a residual target. Evalua

Enzo Duflot, Stanislas Robineau
arXiv · arXiv q-fin · 2023

dYdX: Liquidity Providers' Incentive Programme Review

Liquidity providers are currently incentivised to provide liquidity through the LP Incentives Programme on dYdX. Based on the various parameters - makerVolume, depths and spreads, they are rewarded accordingly based on their activities. Given the maturity of the BTC and ETH markets, alongside other altcoins which enjoy a consistent amount of liquidity, this paper aims to update the formula to encourage more active an

Colin Chan
arXiv · arXiv q-fin · 2026

Detecting unusual trading patterns on cryptocurrency exchanges by means of complexity measures

Artificial transaction generation remains an important source of potential market manipulation on cryptocurrency exchanges, as it may distort reported liquidity and reduce market transparency. This study proposes a diagnostic framework for detecting unusual trading patterns based on complexity and statistical-structure measures derived from high-frequency trade-level data. The analysis considers log-returns, trading

Jakub Zwydak, Marcin Wątorek, Jarosław Kwapień, Stanisław Drożdż
arXiv · arXiv q-fin · 2026

OpenMarket: A Synchronized Polymarket-Binance Dataset for High-Frequency Prediction-Market Research

OpenMarket began as an attempt to trade Polymarket's BTC 15-minute binary markets against Binance BTC/USDT order flow. The attempt did not produce a tradable edge: out-of-sample, a walk-forward logistic model over 43 microstructure features does not beat, and slightly underperforms, the probability already implied by Polymarket's own order book, and simulated trading nets -0.116 normalized payoff units per attempted

Gregory Young
arXiv · arXiv q-fin · 2025

Price Discovery in Cryptocurrency Markets

This document analyzes price discovery in cryptocurrency markets by comparing centralized and decentralized exchanges, as well as spot and futures markets. The study focuses first on Ethereum (ETH) and then applies a similar approach to Bitcoin (BTC). Chapter 1 outlines the theoretical framework, emphasizing the structural differences between centralized exchanges and decentralized finance mechanisms, especially Auto

Juan Plazuelo Pascual, Carlos Tardon Rubio, Juan Toro Cebada, Angel Hernando Veciana
arXiv · arXiv q-fin · 2025

Quantifying Crypto Portfolio Risk: A Simulation-Based Framework Integrating Volatility, Hedging, Contagion, and Monte Carlo Modeling

Extreme volatility, nonlinear dependencies, and systemic fragility are characteristics of cryptocurrency markets. The assumptions of normality and centralized control in traditional financial risk models frequently cause them to miss these changes. Four components-volatility stress testing, stablecoin hedging, contagion modeling, and Monte Carlo simulation-are integrated into this paper's modular simulation framework

Kiarash Firouzi
arXiv · arXiv q-fin · 2024

Reinforcement Learning Pair Trading: A Dynamic Scaling approach

Cryptocurrency is a cryptography-based digital asset with extremely volatile prices. Around USD 70 billion worth of cryptocurrency is traded daily on exchanges. Trading cryptocurrency is difficult due to the inherent volatility of the crypto market. This study investigates whether Reinforcement Learning (RL) can enhance decision-making in cryptocurrency algorithmic trading compared to traditional methods. In order to

Hongshen Yang, Avinash Malik
arXiv · arXiv q-fin · 2024

FinBERT-BiLSTM: A Deep Learning Model for Predicting Volatile Cryptocurrency Market Prices Using Market Sentiment Dynamics

Time series forecasting is a key tool in financial markets, helping to predict asset prices and guide investment decisions. In highly volatile markets, such as cryptocurrencies like Bitcoin (BTC) and Ethereum (ETH), forecasting becomes more difficult due to extreme price fluctuations driven by market sentiment, technological changes, and regulatory shifts. Traditionally, forecasting relied on statistical methods, but

Mabsur Fatin Bin Hossain, Lubna Zahan Lamia, Md Mahmudur Rahman, Md Mosaddek Khan
arXiv · arXiv · 2026

When Does Order Flow Matter? State-Dependent L2 Liquidity-State Transitions in Crypto Futures

Building event-conditioned market models requires separating macro-event labels from persistent microstructure state. We study this distinction in Binance BTCUSDT and ETHUSDT futures from 2023-2026, combining top-20 L2 order book data, trade-flow records, and macro-event windows. We define a supervised discrete L2 liquidity-state transition task, distinct from latent-regime detection and price-direction prediction, a

Joohyoung Jeon
arXiv · arXiv · 2025

A Deterministic Limit Order Book Simulator with Hawkes-Driven Order Flow

We present a reproducible research framework for market microstructure combining a deterministic C++ limit order book (LOB) simulator with stochastic order flow generated by multivariate marked Hawkes processes. The paper derives full stability and ergodicity proofs for both linear and nonlinear Hawkes models, implements time-rescaling and goodness-of-fit diagnostics, and calibrates exponential and power-law kernels

Sohaib El Karmi
arXiv · arXiv · 2026

Dynamic Collateral Control for Permissionless Spot Perpetual Basis Trading

We study permissionless spot--perpetual basis trading in decentralized finance as a collateral control problem. The strategy holds spot inventory, hedges directional exposure with a short perpetual, and allocates capital between spot inventory and derivative margin under on-chain liquidity and execution frictions. The paper delivers three results. First, it solves a static control problem for the collateral share and

Anatoly Krestenko, Mikhail Butov, Rostislav Berezovskiy, Danila Bolotin
arXiv · arXiv · 2025

How Digital Asset Treasury Companies Can Survive Bear Markets: The Case of the Strategy and Bitcoin

Digital Asset Treasury (DAT) companies, public firms that hold large crypto reserves as a core strategy, deliver levered exposure to digital assets but face acute downside risk when equity premia over net asset value multiples (mNAV) compress in bear markets. This paper develops a survival framework that couples conservative treasury policy with an operating line that monetizes holdings independent of mark-to-market

Hongzhe Wen
arXiv · arXiv · 2025

Multifractality and its sources in the digital currency market

Multifractality in time series analysis characterizes the presence of multiple scaling exponents, indicating heterogeneous temporal structures and complex dynamical behaviors beyond simple monofractal models. In the context of digital currency markets, multifractal properties arise due to the interplay of long-range temporal correlations and heavy-tailed distributions of returns, reflecting intricate market microstru

Stanisław Drożdż, Robert Kluszczyński, Jarosław Kwapień, Marcin Wątorek
arXiv · arXiv · 2025

Cryptocurrencies in the Balance Sheet: Insights from (Micro)Strategy -- Bitcoin Interactions

This paper investigates the evolving link between cryptocurrency and equity markets in the context of the recent wave of corporate Bitcoin (BTC) treasury strategies. We assemble a dataset of 39 publicly listed firms holding BTC, from their first acquisition through April 2025. Using daily logarithmic returns, we first document significant positive co-movements via Pearson correlations and single factor model regressi

Sabrina Aufiero, Antonio Briola, Tesfaye Salarin, Fabio Caccioli, Silvia Bartolucci
arXiv · arXiv · 2023

PRIME: A Price-Reverting Impact Model of a cryptocurrency Exchange

In a financial exchange, market impact is a measure of the price change of an asset following a transaction. This is an important element of market microstructure, which determines the behaviour of the market following a trade. In this paper, we first provide a discussion on the market impact observed in the BTC/USD Futures market, then we present a novel multi-agent market simulation that can follow an underlying pr

Christopher J. Cho, Timothy J. Norman, Manuel Nunes
Wiki Entities · 4
Option Blackboard · 0
No Option Blackboard entries matched.
Encyclopedia · 2
Cards · 0
No cards matched.
← Back to Codex