Research
On-device research index

arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,695 papers · 148 categories

Trend · papers per month

3877115153 · May 202619922001200920172026
48 results for market phases

The paper models market crashes as phase transitions, finding dynamic transitions offer better predictions.

problem Understanding and predicting extreme financial events like market crashes.
method Employing phase transition theory, focusing on endogenous crashes, and comparing DPT, CPT, and SPT.
result Dynamic phase transitions provide more accurate predictions of market crashes compared to critical and stochastic models.

We analyze the linear response of a market network to shocks based on the bipartite market model we introduced in an earlier paper, which we claimed to be able to identify the time-line of the 2009-2011 Eurozone crisis correctly. We show that this model has three distinct phases that can broadly be categorized as "stab…

2016-09-19abs ↗pdf ↗

New model explains market dynamics with phase transitions and non-linear interactions.

problem Understanding complex multi-asset market dynamics with phase transitions.
method Developed a Multi-Asset Non-Equilibrium Skew (MANES) model based on Langevin dynamics and McKean-Vlasov equation.
result The model accurately predicts market returns and phase transitions in both benign and distressed markets.

Paper predicts cryptocurrency bull and bear phases using Bitcoin's moving averages.

problem Determining cryptocurrency bull and bear phases based on Bitcoin performance.
method Employing predictive algorithms to forecast Bitcoin's 50 Day and 200 Day Moving Averages.
result Predicted data from Bitcoin's moving averages helps identify potential bull and bear phases.

Moon phases added to stock market analysis for better pattern recognition.

problem Finding meaningful patterns in stock market data using irregular time sampling.
method Incorporating Moon phases into the Gregorian calendar time sampling methods for stock market analysis.
result Moon phases provide unique, irregular sampling features for stock market pattern recognition.

We examine the out-of-equilibrium phase reported by Plerou {\it et. al.} in Nature, {\bf 421}, 130 (2003) using the data of the New York stock market (NYSE) between the years 2001 --2002. We find that the observed two phase phenomenon is an artifact of the definition of the control parameter coupled with the nature of …

2005-02-15abs ↗pdf ↗

Modeling financial markets as gas molecules, the paper predicts phase transitions similar to water and steam.

problem Understanding the dynamics of financial markets through phase transitions.
method Developed a lattice gas model equivalent to the Ising model on a social network, analyzing critical exponents and auto-correlations.
result Financial market dynamics exhibit phase transition-like behavior, with critical exponents analogous to water and steam.

AlphaMLDigger predicts excess returns in fluctuating markets.

problem Mining effective information for investment decisions in a volatile market.
method Two-phase approach using deep NLP for sentiment analysis and ensemble ML models.
result Ensemble models achieve 0.984 accuracy, significantly outperforming baseline.

We analyze the stock prices of the S&P market from 1987 until 2012 with the covariance matrix of the firm returns determined in time windows of several years. The eigenvector belonging to the leading eigenvalue (market) exhibits in its long term time dependence a phase transition with an order parameter which can be in…

2013-06-11abs ↗pdf ↗

Applicability of the concept of financial log-periodicity is discussed and encouragingly verified for various phases of the world stock markets development in the period 2000-2010. In particular, a speculative forecasting scenario designed in the end of 2004, that properly predicted the world stock market increases in …

2008-02-27abs ↗pdf ↗

Modeling financial markets with memory using fractional calculus and Brownian motion.

problem Capturing memory effects in financial markets using stochastic models.
method Fractional Langevin equation with colored noise generated by fractional Brownian motion.
result Anomalous marginal glass phase observed in some regions of the system.

We study the emergence of instabilities in a stylized model of a financial market, when different market actors calculate prices according to different (local) market measures. We derive typical properties for ensembles of large random markets using techniques borrowed from statistical mechanics of disordered systems. …

2012-07-02abs ↗pdf ↗

Study finds a phase transition in flash crashes involving large and liquid stocks.

problem Systemic risk and propagation of shocks in high frequency trading.
method In-depth investigation of co-crashes in high frequency trading.
result Large co-crashes involve mostly illiquid stocks, while small crashes involve a mix of liquid and illiquid stocks.

We study the market impact of a meta-order in the framework of the Minority Game. This amounts to studying the response of the market when introducing a trader who buys or sells a fixed amount h for a finite time T. This perturbation introduces statistical arbitrages that traders exploit by adapting their trading strat…

2011-12-16abs ↗pdf ↗

Cryptocurrencies are increasingly correlated with traditional financial markets.

problem Determining the independence of cryptocurrencies from traditional financial markets.
method High-frequency detrended cross-correlation analysis over various time scales and market periods.
result Cryptocurrencies have become more aligned with traditional financial markets, especially during bear phases.

The present paper analyses the formal parallelism existing between the laws of thermodynamics and some economic principles. Based on previous works, we shall show how the existence in Economics of principles analogous to those in thermodynamics involves the occurrence of economic events that remind of well-known phenom…

2015-05-03abs ↗pdf ↗

Study uses LSTM models to detect Wyckoff patterns in currency trading.

problem Understanding market dynamics and identifying trading opportunities.
method Dissecting Wyckoff Phases, using CNNs for spatial data and LSTM for temporal data.
result Deep learning models enhance pattern recognition in financial markets.

We study the phase transition of dynamical herd behaviors for the yen-dollar exchange rate in the Japanese financial market. It is obtained that the probability distribution of returns satisfies the power-law behavior with three different values of the scaling exponent 3.11 (one time lag ττ = 1 minute), 2.81 (30 minut…

2004-08-28abs ↗pdf ↗

In the spirit of behavioral finance, we study the process of opinion formation among investors using a variant of the 2D Voter Model with a tunable social temperature. Further, a feedback acting on the temperature is introduced, such that social temperature reacts to market imbalances and thus becomes time dependent. I…

2012-12-19abs ↗pdf ↗

We study the inter-stock correlations for the largest companies listed on Warsaw Stock Exchange and included in the WIG20 index. Our results from the correlation matrix analysis indicate that the Polish stock market can be well described by a one factor model. We also show that the stock-stock correlations tend to incr…

2008-03-01abs ↗pdf ↗

New algorithms reduce matching market regret to log(T) with improved stability.

problem Minimizing regret in two-sided matching markets with bandit feedback.
method Phase-based algorithm with local arm deletion to improve stability.
result Achieves Θ(log(T)) regret for markets with uniqueness consistency.

We consider models of financial markets in which all parties involved find incentives to participate. Strategies are evaluated directly by their virtual wealths. By tuning the price sensitivity and market impact, a phase diagram with several attractor behaviors resembling those of real markets emerge, reflecting the ro…

2007-08-01abs ↗pdf ↗

The study analyzes aftershocks of stock market crashes using statistical methods.

problem Understanding the aftershocks of stock market crashes during crises.
method Structural break analysis and statistical methods applied to 1987 crash, 2008 financial crisis, and 2020 COVID-19 pandemic.
result The recovery of stock price during the COVID-19 pandemic may be faster than the financial crisis of 2008.

Study uses topological signatures to quantify financial market complexity.

problem Capturing temporal organization beyond volatility measures.
method Null validated topological approach using L1L^1 norm of persistence landscapes.
result Persistence landscape norms reveal dynamical structure during market stress.

We analyze the statistics of daily price change of stock market in the framework of a statistical physics model for the collective fluctuation of stock portfolio. In this model the time series of price changes are coded into the sequences of up and down spins, and the Hamiltonian of the system is expressed by spin-spin…

2001-10-06abs ↗pdf ↗

The stability of money value is an important requisite for a functioning economy, yet it critically depends on the actions of participants in the market themselves. Here we model the value of money as a dynamical variable that results from trading between agents. The basic trading scenario can be recast into an Ising t…

2001-10-10abs ↗pdf ↗

We present a model that investigates the spontaneous emergence of randomness in equity market microstructure. The phase space analysis of our model exposes an endogenous source of fluctuation in price and volume. We formulate a control problem for maximizing price regularity and stability while minimizing entanglement …

2004-06-03abs ↗pdf ↗

The paper analyzes debt recycling strategies for mortgage repayment, revealing complex phases of success and failure.

problem Evaluating the effectiveness of debt recycling strategies compared to standard mortgage repayment.
method Developed a dynamical model to study the time evolution of equity and mortgage balance under various conditions.
result The model identifies four phases: strongly successful, weakly successful, default, and permanent re-mortgaging, with sensitivity to initial conditions.

The two phase behavior in financial markets actually means the bifurcation phenomenon, which represents the change of the conditional probability from an unimodal to a bimodal distribution. In this paper, the bifurcation phenomenon in Hang-Seng index is carefully investigated. It is observed that the bifurcation phenom…

2007-12-30abs ↗pdf ↗

Paper uses TDA to assess cryptocurrency risk by measuring phase space instability.

problem Traditional risk measures fail to capture market dynamics' geometric structure.
method Applied Takens' Delay Embedding Theorem to generate point cloud, computed persistent homology groups, defined Topological Persistence Norm.
result Proposed leverage calibration heuristic based on persistence of 1-dimensional cycles.

Study analyzes price change patterns across different market capitalizations using Markov chains.

problem Understanding price dynamics in limit order markets across various market capitalizations.
method Discrete-time Markov chain analysis of intraday price changes in NASDAQ100 tick data.
result Systematic patterns in price inertia and stability across market capitalizations are identified.

We study a class of heterogeneous agent-based models which are based on a basic set of principles, and the most fundamental operations of an economic system: trade and product transformations. A basic guiding principle is scale invariance, which means that the dynamics of the economy should not depend on the units used…

2009-02-23abs ↗pdf ↗

An artificial stock market is established based on multi-agent . Each agent has a limit memory of the history of stock price, and will choose an action according to his memory and trading strategy. The trading strategy of each agent evolves ceaselessly as a result of self-teaching mechanism. Simulation results exhibit …

2004-06-07abs ↗pdf ↗

We introduce a probabilistic model of labor markets for university graduates, in particular, in Japan. To make a model of the market efficiently, we take into account several hypotheses. Namely, each company fixes the (business year independent) number of opening positions for newcomers. The ability of gathering newcom…

2013-09-20abs ↗pdf ↗

The paper analyzes liquidity in decentralized finance, deriving impact functions and de-pegging risks.

problem Understanding and quantifying market impact and de-pegging risk in decentralized finance.
method Derives market impact functions for optimal-growth liquidity providers, views Constant Product Market Maker as a Carnot engine, and links de-pegging risks to catastrophe bonds.
result New insights into liquidity models and de-pegging risks in decentralized finance.