Automated market-making for CBDCs and stable coins on blockchain.
problem Creating fair exchange rates for digital assets on blockchain.
method Developed an innovative approach for generating fair exchange rates.
result Illustrated the approach's efficacy on G-10 currency exchange rates.
Stablecoins are unstable, but some are more stable than others.
problem Inconsistency in stability of stablecoins and high transaction costs.
method Analysis of market shares, transaction volumes, and exchange activity.
result USD Coin, Tether, and Dai are the most stable, but overall failure rate remains high.
Examines various types of cryptocurrencies and their economic properties.
problem Understanding the economic characteristics of different cryptocurrencies.
method Characterization and analysis of different classes of cryptocurrencies using balance sheet operations.
result Different types of cryptocurrencies have distinct economic properties, ranging from commodities to liabilities of central banks.
Maker Protocol manages Dai stable coin on Ethereum blockchain.
problem Managing decentralized finance applications on blockchain.
method Analyzes Maker Protocol's components and governance.
result Maker Protocol is a significant decentralized finance application.
The paper reveals the hidden costs of digitizing commodity money and proposes a new stable-coin system.
problem Depreciation of banknotes due to high logistics costs after digitization.
method Analyzing the functions of money from a logistics perspective and comparing commodity money to digital currency.
result There is no honest money that is both a store of value and has negligible logistics costs.
Bitcoin draws the highest degree of attention among cryptocurrencies, while coin mining is one of the most important fashion of profiting in the Bitcoin ecosystem. This paper constructs fresh coin circulation networks by tracking the fresh coin transfer routes with transaction referencing in Bitcoin blockchain. This pa…
We present a new Bitcoin coin selection algorithm, "coin selection with leverage", which aims to improve upon cost savings than that of standard knapsack like approaches. Parameters to the new algorithm are available to be tuned at the users discretion to address other goals of coin selection. Our approach naturally fi…
Study reveals strong price correlations between major and alt-coins.
problem Unclear tight relations between cryptocoins trading prices.
method Investigated coin-price correlation trends over two years.
result Strong correlation patterns between main and alt-coins.
We empirically verify that the market capitalisations of coins and tokens in the cryptocurrency universe follow power-law distributions with significantly different values, with the tail exponent falling between 0.5 and 0.7 for coins, and between 1.0 and 1.3 for tokens. We provide a rationale for this, based on a simpl…
New system resists meme coin copy trading bots.
problem Manipulative bots exploit copy trading in illiquid meme coins.
method Multi-agent architecture with LLM and CoT reasoning.
result System outperforms other methods in prediction and economic performance.
Study reveals widespread manipulation of meme coins, leading to significant economic losses.
problem Widespread manipulation of meme coins leading to economic losses.
method Cross-chain analysis of 34,988 tokens across Ethereum, BNB Smart Chain, Solana, and Base.
result 82.8% of high-return tokens show evidence of artificial growth strategies.
The paper analyzes cryptocurrency trading networks using pairwise and high-order dependencies.
problem Understanding information flows and dependencies in cryptocurrency markets.
method Defined a cryptocurrency trading network using weekly log returns, analyzed using Granger causality and O-information.
result High-order dependencies reveal that stable coins play a major role in high-order effects.
Given a mixture between two populations of coins, "positive" coins that each have -- unknown and potentially different -- bias ≥21+Δ and "negative" coins with bias ≤21−Δ, we consider the task of estimating the fraction ρ of positive coins to within additive error ε. We achieve an upper a…
A decentralized online quantum cash system, called qBitcoin, is given. We design the system which has great benefits of quantization in the following sense. Firstly, quantum teleportation technology is used for coin transaction, which prevents from the owner of the coin keeping the original coin data even after sending…
New coin sampling method for Bayesian inference without learning rates.
problem Scalable Bayesian inference with learning rate tuning issues.
method Coin sampling for gradient-based Bayesian inference.
result Comparable performance to other ParVI algorithms without learning rate tuning.
Cryptocurrency prices predicted using LSTM, SVM, and polynomial regression.
problem Uncertainty in crypto coin values.
method Long Short Term Memory, Support Vector Machine, Polynomial Regression models.
result Support Vector Machine with linear kernel had the smallest mean square error.
No feature ranking can be faithful, stable, and complete when features are collinear.
problem The impossibility of creating a feature ranking that is simultaneously faithful, stable, and complete when features are collinear.
method Proving the impossibility, quantifying it for four model classes, resolving it via ensemble averaging (DASH), and machine-verifying it with Lean 4 theorems.
result No method lies outside the dichotomy of faithful-complete methods (unstable, with rankings that flip up to 50% of the time) and ensemble methods (stable, reporting ties for symmetric features).
Quantum walks blend patterns into splines when averaged.
problem Understanding the asymptotic patterns of quantum random walks.
method Averaging over quantum coins using the Haar measure.
result Patterns blend into splines, showing a unified behavior.
New algorithm closes empirical gap in PFSGD performance.
problem Empirical performance gap between tuned SGD and PFSGD.
method Parameter-free algorithm based on Coin-Betting ODE updates.
result New algorithm outperforms tuned baselines and matches optimal performance.
We study capital process behavior in the fair-coin game and biased-coin games in the framework of the game-theoretic probability of Shafer and Vovk (2001). We show that if Skeptic uses a Bayesian strategy with a beta prior, the capital process is lucidly expressed in terms of the past average of Reality's moves. From t…
COIN++ compresses multiple data types efficiently.
problem Handling diverse data modalities in neural compression.
method Implicit neural representations and modulations quantization.
result Significant compression gains with reduced encoding time.
We discuss several uses of blockchain (and, more generally, distributed ledger) technologies outside of cryptocurrencies with a pragmatic view. We mostly focus on three areas: the role of coin economies for what we refer to as data malls (specialized data marketplaces); data provenance (a historical record of data and …
Paper tightens PAC-Bayes bounds using coin-betting for better estimates.
problem Estimating mean of random elements with possibly S-dependent parameters.
method Refined PAC-Bayes proof strategy based on coin-betting framework.
result Derives tighter concentration inequalities for all sample sizes.
Predicts cryptocurrency pump probability using sequence-based neural networks.
problem Detecting pump-and-dump schemes in cryptocurrency markets.
method Developed a sequence-based neural network (SNN) that encodes historical P&D events into sequences for prediction.
result SNN improves prediction accuracy by leveraging positional attention to extract useful information.
SFC aims to protect the Amazon with a digital currency and smart contracts.
problem Protecting the Amazon's ecosystem and ensuring resource credibility.
method Blockchain, digital contracts, smart contracts with oracles.
result Ensures credibility and security for financial resources invested in Amazon projects.
We study multistep Bayesian betting strategies in coin-tossing games in the framework of game-theoretic probability of Shafer and Vovk (2001). We show that by a countable mixture of these strategies, a gambler or an investor can exploit arbitrary patterns of deviations of nature's moves from independent Bernoulli trial…
We study a coin-tossing model used by a ratings agency to justify the sale of constant proportion debt obligations (CPDOs), and prove that it was impossible for CPDOs to achieve in a finite lifetime the Cash-In event of doubling its capital. In the best-case scenario of a two-headed coin, we show that the goal of attai…
This paper discusses the potential impacts of the so-called `initial coin offerings', and of several developments based on distributed ledger technology (`DLT'), on corporate governance. While many academic papers focus mainly on the legal qualification of DLT and crypto-assets, and most notably in relation to the pote…
Randomness is crucial for stability in learning and statistics, especially for differential privacy.
problem Quantifying the amount of randomness needed for algorithmic stability.
method Weak-to-strong boosting theorem for stability, characterizing randomness complexity of PAC Learning.
result Randomness complexity is tightly controlled by the best replication probability of any deterministic algorithm solving the task.
Optimizes cryptocurrency trading pairs for efficiency and decentralization.
problem Finding optimal trading pairs among many cryptocurrencies without direct volume data.
method Two-stage process: 1) Fill missing values using eigenvalue decomposition with regularization, 2) Optimize pairs using branch and bound with pruning.
result Optimal trading pairs lead to more decentralized markets and better liquidity.
We derive some results on contrarian and one-sided strategies by Skeptic for the fair-coin game in the framework of the game-theoretic probability of Shafer and Vovk \cite{sv}. In particular, concerning the rate of convergence of the strong law of large numbers (SLLN), we prove that Skeptic can force that the convergen…
New algorithms learn latent variable models without tuning, outperforming existing methods.
problem Learning latent variable models without manual tuning.
method Two particle-based algorithms using free energy minimization and coin betting.
result Learning algorithms are entirely tuning-free and competitive with existing methods.
The price volatility of cryptocurrencies is often cited as a major hindrance to their wide-scale adoption. Consequently, during the last two years, multiple so called stablecoins have surfaced---cryptocurrencies focused on maintaining stable exchange rates. In this paper, we systematically explore and analyze the stabl…
The paper examines stability of shares in Proof of Stake protocol, identifying different investor behaviors and phase transitions.
problem Stability of shares in Proof of Stake protocol.
method Identification of large, medium, and small investors under various rewarding schemes; dynamical population model analysis.
result Phase transitions and thresholds for stability are characterized; chaotic centralization leads to concentration of shares.
Cryptofinance generates yield through innovative decentralized finance.
problem Lack of intrinsic yield in crypto-assets.
method Analysis of yield-generating mechanisms in cryptofinance.
result Cryptofinance innovations enable yield generation through various decentralized and centralised mechanisms.
Study sets a nontrivial upper limit on return forecasting accuracy.
problem Establishing a practical upper limit for return forecasting accuracy.
method Defined a coin-flip oracle model to theoretically outperform practical models and used its RextOOS2 as an upper bound. result Theoretical upper bound on RextOOS2 is a quadratic function of directional accuracy. This paper provides a set of sensitivity analysis and activity identification results for a class of convex functions with a strong geometric structure, that we coined "mirror-stratifiable". These functions are such that there is a bijection between a primal and a dual stratification of the space into partitioning sets…
A crypto coin designed to provide a stabilization instrument backed up by minded like financial investments instruments to maintain the purchase value of savings across time, in order to construct new tools for unstable economies.
We study data-driven representations for three-dimensional triangle meshes, which are one of the prevalent objects used to represent 3D geometry. Recent works have developed models that exploit the intrinsic geometry of manifolds and graphs, namely the Graph Neural Networks (GNNs) and its spectral variants, which learn…
This paper explores using nonlinear control for robust logarithmic growth in coin flipping games.
problem Tackles the use of nonlinear control in recursive betting games with logarithmic growth.
method Formulates a robust nonlinear control problem for a simple coin flipping game, considering a probability range for the coin's bias.
result Provides a closed-form description of the optimal robust nonlinear controller, which outperforms linear controllers.
New digital currency aims for equal wealth distribution.
problem Inequality in cryptocurrency wealth distribution.
method Egalitarian coin minting and joint minting across communities.
result Achieves global distributive justice in wealth distribution.
Deep learning methods achieve state-of-the-art performance in many application scenarios. Yet, these methods require a significant amount of hyperparameters tuning in order to achieve the best results. In particular, tuning the learning rates in the stochastic optimization process is still one of the main bottlenecks. …
Study reveals RL game's embedding space is stratified, not a manifold.
problem Understanding the structure of RL game embeddings.
method Adapted Robinson's volume growth transform for RL setting.
result Token embedding space is stratified, not a manifold.
New algorithms for sampling in constrained domains without learning rates.
problem Sampling in constrained domains with fairness constraints and post-selection inference.
method Coin betting ideas from convex optimisation and a unifying framework for constrained sampling.
result Our algorithms achieve competitive performance without hyperparameter tuning.
New convergence rates for SGD under heavy-tailed noise with infinite variance.
problem Convergence analysis of SGD under heavy-tailed noise with infinite variance.
method Identifying a condition on the Hessian and providing a convergence rate for the distance to the global optimum.
result SGD can converge to the global optimum under heavy-tailed noise with infinite variance.
Study replicability in high-dimensional statistics, resolving open problems.
problem Ensuring consistent results in high-dimensional statistical tasks.
method Introduced replicable learning algorithms and established computational and statistical equivalence with high-dimensional isoperimetric tilings.
result Matching sample complexity upper and lower bounds for replicable mean estimation and coin problem.
In this article, I will present a paradox whose purpose is to draw your attention to an important topic in finance, concerning the non-independence of the financial returns (non-ergodic hypothesis). In this paradox, we have two people sitting at a table separated by a black sheet so that they cannot see each other and …
Cryptocurrencies are ranked for efficiency using a new Complexity-Entropy Plane.
problem Evaluating the efficiency of cryptocurrencies using traditional financial metrics.
method Developed a Binary Complexity-Entropy Plane (BiCEP) to analyze daily price fluctuations of major cryptocurrencies.
result Only Shiba Inu (SHIB) is significantly inefficient, while most cryptocurrencies operate in close-to-efficient conditions.