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Cryptocurrency portfolio management requires the fusion of heterogeneous multi-modal signals, including structured price and on-chain time series, unstructured news text, and technical indicators, under high-volatility and real-time constraints. While deep learning approaches show predictive capability, their opacity limits practical adoption, and single large language model (LLM) agents struggle to process the bread…
We develop a new framework to detect wash trading in crypto assets through real-time liquidity fluctuation. We propose that short-term price jumps in crypto assets results from wash trading-induced liquidity fluctuation, and construct two complementary liquidity measures, liquidity jump (size of fluctuation) and liquidity diffusion (volatility of fluctuation), to capture the behavioral signature of wash trading. Usin…
We propose that the liquidity of an asset includes two components: liquidity jump and liquidity diffusion. We show that liquidity diffusion has a higher correlation with crypto wash trading than liquidity jump and demonstrate that treatment on wash trading significantly reduces the level of liquidity diffusion, but only marginally reduces that of liquidity jump. We confirm that the autoregressive models are highly ef…
Uniswap is a Constant Product Market Maker built around liquidity pools, where pairs of tokens are exchanged subject to a fee that is proportional to the size of transactions. At the time of writing, there exist more than 6,000 pools associated with Uniswap v3, implying that empirical investigations on the full ecosystem can easily become computationally expensive. Thus, we propose a systematic workflow to extract an…
The rapid growth of crypto markets has opened new opportunities for investors, but at the same time exposed them to high volatility. To address the challenge of managing dynamic portfolios in such an environment, this paper presents a practical application of a multi-agent system designed to autonomously construct and evaluate crypto-asset allocations. Using data on daily frequencies of the ten most capitalized crypt…
This paper analyzes the intersection of presidential authority and cryptocurrency markets during Donald J. Trump's second term (2025-2029). We examine developments from 2024 through October 2025, focusing on how executive influence, family business ventures, and digital assets became intertwined in ways that blurred boundaries between public office and private profit. Using a mixed-methods approach that combines quan…
We have designed an innovative portfolio rebalancing mechanism termed the Cascading Waterfall Round Robin Mechanism. This algorithmic approach recommends an ideal size and number of trades for each asset during the periodic rebalancing process, factoring in the gas fee and slippage. The essence of the model we have created gives indications regarding whether trades should be made on individual assets depending on the…
This study employs an event study methodology to investigate the market impact of the U.S. Securities and Exchange Commission's (SEC) classification of crypto assets as securities. It explores how SEC interventions influence asset returns and trading volumes, focusing on explicitly named crypto assets. The empirical analysis highlights significant adverse market reactions, notably returns plummeting 12% over one week…
The study proposes a quote-driven predictive automated market maker (AMM) platform with on-chain custody and settlement functions, alongside off-chain predictive reinforcement learning capabilities to improve liquidity provision of real-world AMMs. The proposed AMM architecture is an augmentation to the Uniswap V3, a cryptocurrency AMM protocol, by utilizing a novel market equilibrium pricing for reduced divergence a…
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…
Despite being described as a medium of exchange, cryptocurrencies do not have the typical attributes of a medium of exchange. Consequently, cryptocurrencies are more appropriately described as crypto assets. A common investment attribute shared by the more than 2,500 crypto assets is that they are highly volatile. An investor interested in reducing price volatility of a portfolio of crypto assets can do so by constru…
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 …
This study aims to determine whether the application of Deep Reinforcement Learning (DRL) as a specialized execution overlay can enhance pair trading in highly volatile cryptocurrency markets. Although classical implementations of the strategy have proven successful in traditional equities, they frequently exhibit rigidity and suffer from severe divergence risks when applied to high-variance environments. To address …
This paper develops a robust mathematical framework for Constant Function Market Makers (CFMMs) by transitioning from traditional token reserve analyses to a coordinate system defined by price and intrinsic liquidity. We establish a canonical parametrization of the bonding curve that ensures dimensional consistency across diverse trading functions, such as those employed by Uniswap and Balancer, and demonstrate that …
We establish innovative liquidity premium measures, and construct liquidity-adjusted return and volatility to model assets with extreme liquidity, represented by a portfolio of selected crypto assets, and upon which we develop a set of liquidity-adjusted ARMA-GARCH/EGARCH models. We demonstrate that these models produce superior predictability at extreme liquidity to their traditional counterparts. We provide empiric…
Automated market makers (AMMs) are a new type of trading venues which are revolutionising the way market participants interact. At present, the majority of AMMs are constant function market makers (CFMMs) where a deterministic trading function determines how markets are cleared. Within CFMMs, we focus on constant product market makers (CPMMs) which implements the concentrated liquidity (CL) feature. In this thesis we…
We test various volatility models using the Bitcoin spot price series. Our models include HIST, EMA ARCH, GARCH, and EGARCH, models. Both of our in-sample-fit and out-of-sample-forecast results suggest that GARCH and EGARCH models perform much better than other models. Moreover, the EGARCH model's asymmetric term is positive and insignificant, which suggests that Bitcoin prices lack the asymmetric volatility response…
We audit whether candle-based machine-learning models can turn predictions of cryptocurrency extrema or short-horizon outcomes into positive Binance Spot paper policies after assumed costs. Numerical results come from scripted fixed-seed model runs and deterministic simulators; human-supervised AI agents supported the July 20 evidence-integrity revision through literature retrieval, separately tasked critique, artifa…
Bitcoin Dominance (Crypto).
ETH BTC Ratio (Crypto).
Perpetual Funding Rate (Crypto).
Open Interest Crypto (Crypto).
Liquidation Cascade (Crypto).
Stablecoin Supply (Crypto).
Exchange Netflow (Crypto).
Hash Rate Bitcoin (Crypto).
Miner Capitulation (Crypto).
ETF Bitcoin Flows (Crypto).
Basis Trade Crypto (Crypto).
Cross Exchange Arb (Crypto).
On Chain Active Addresses (Crypto).
Stablecoin Depeg Risk (Crypto).
Bitcoin Hashrate (Crypto).
Bitcoin Difficulty Adjustment — Periodic retarget of mining difficulty to stabilize block times.
Crypto Perpetual Funding Rate — Periodic payment between longs and shorts that anchors perp to spot.
Crypto Basis Trade (Crypto).
Crypto Liquidation Cascade — Forced closes amplifying moves when leverage clusters breach.
Tether Reserve Opacity — Uncertainty around reserve composition and redemption capacity.
Crypto ETF Flow Impact — Spot ETF creations/redemptions as a structural demand channel.
On Chain Exchange Reserves — Coins on exchanges as a potential sell-pressure gauge.
Crypto Market Maker Inventory — Dealer inventory and hedge needs shaping crypto microstructure.
Layer Two Rollup Risk — Sequencer, bridge, and finality risks in L2 architectures.
MEV Extraction (Crypto).
Crypto Options Skew (Crypto).
Crypto Realized Vol Regime — Shifts in realized volatility that redefine sizing and carry.
Stablecoin Market Cap (Crypto).
Spot ETF Flow BTC — Digital-asset market structure, leverage, or on-chain concept.
Spot ETF Flow ETH — Digital-asset market structure, leverage, or on-chain concept.
Spot ETF Flow SOL — Digital-asset market structure, leverage, or on-chain concept.
Spot ETF Flow BNB — Digital-asset market structure, leverage, or on-chain concept.
Spot ETF Flow XRP — Digital-asset market structure, leverage, or on-chain concept.
Spot ETF Flow perp — Digital-asset market structure, leverage, or on-chain concept.
Spot ETF Flow spot — Digital-asset market structure, leverage, or on-chain concept.
Spot ETF Flow options — Digital-asset market structure, leverage, or on-chain concept.
Adverse Selection crypto — Execution quality, book dynamics, or venue microstructure concept.
Alt Season Beta BNB (Crypto).
Alt Season Beta BTC (Crypto).
Alt Season Beta CEX (Crypto).
Alt Season Beta DeFi (Crypto).
Alt Season Beta DEX (Crypto).
Alt Season Beta ETH (Crypto).
Alt Season Beta options (Crypto).
Alt Season Beta perp (Crypto).
Alt Season Beta SOL (Crypto).
Alt Season Beta spot (Crypto).
Alt Season Beta XRP (Crypto).
Arrival Price Slippage crypto — Execution quality, book dynamics, or venue microstructure concept.
Auction Imbalance crypto (Microstructure).
Basis Cash Carry BNB (Crypto).
Basis Cash Carry BTC (Crypto).
Basis Cash Carry CEX (Crypto).
Basis Cash Carry DeFi (Crypto).
Basis Cash Carry DEX (Crypto).
Basis Cash Carry ETH (Crypto).
Basis Cash Carry options (Crypto).
Basis Cash Carry perp (Crypto).
Basis Cash Carry SOL (Crypto).
Basis Cash Carry spot (Crypto).