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.

169,291 papers · 148 categories

Trend · papers per month

69138207276 · Jun 202019922001200920182026
48 results for DJIA dynamics

Forecast predicts US recession in 2017, global economic slowdown, and eventual growth.

problem Short-term economic forecast and potential recession in developed countries.
method Analysis of log-periodic oscillations in DJIA dynamics and historical economic cycles.
result Predicts a recession in the second half of 2017 for developed countries.

An original method, assuming potential and kinetic energy for prices and conservation of their sum is developed for forecasting exchanges. Connections with power law are shown. Semiempirical applications on S&P500, DJIA, and NASDAQ predict a coming recession in them. An emerging market, Istanbul Stock Exchange index IS…

2005-06-10abs ↗pdf ↗

In high-frequency financial data not only returns, but also waiting times between consecutive trades are random variables. Therefore, it is possible to apply continuous-time random walks (CTRWs) as phenomenological models of the high-frequency price dynamics. An empirical analysis performed on the 30 DJIA stocks shows …

2005-05-31abs ↗pdf ↗

In high-frequency financial data not only returns, but also waiting times between consecutive trades are random variables. Therefore, it is possible to apply continuous-time random walks (CTRWs) as phenomenological models of the high-frequency price dynamics. An empirical analysis performed on the 30 DJIA stocks shows …

2003-10-14abs ↗pdf ↗

Predicting absolute magnitude of fluctuations of price, even if their sign remains unknown, is important for risk analysis and for option prices. In the present work, we display our predictions about absolute magnitude of daily fluctuations of the Dow Jones Industrials Average (DJIA), utilizing the original theory of c…

2006-02-08abs ↗pdf ↗

In recent publications, the authors have considered inverse statistics of the Dow Jones Industrial Averaged (DJIA) [1-3]. Specifically, we argued that the natural candidate for such statistics is the investment horizons distribution. This is the distribution of waiting times needed to achieve a predefined level of retu…

2005-11-10abs ↗pdf ↗

We present a systematic algorithm testing for the existence of collective self-organization in the behavior of agents in social systems, with a concrete empirical implementation on the Dow Jones Industrial Average index (DJIA) over the 20th century and on Hong Kong Hang Seng composite index (HSI) since 1969. The algori…

2003-04-26abs ↗pdf ↗

The inverse statistics is the distribution of waiting times needed to achieve a predefined level of return obtained from (detrended) historic asset prices \cite{optihori,gainloss}. Such a distribution typically goes through a maximum at a time coined the {\em optimal investment horizon}, τρτ^*_ρ, which defines the most…

2006-01-02abs ↗pdf ↗

It is demonstrated that the US economy has on the long-term in reality been governed by the Keynesian approach to economics independent of the current official economical policy. This is done by calculating the two-point correlation function between the fluctuations of the DJIA and the US public debt. We find that the …

2011-07-15abs ↗pdf ↗

The Indian IT sector is strongly linked to global markets, while CG sector reflects domestic growth.

problem Analyzing the structural characteristics of Indian IT and CG sectors.
method Time series analysis and forecasting using R programming.
result The IT sector is strongly associated with global markets (DJIA and USD/INR), while CG sector is linked to domestic growth (NIFTY).

Dynamics of the major USA market indices DJIA, S&P, Nasdaq, and NYSE is analyzed from the point of view of the random walking problem with two-step correlations of the market moves. The parameters characterizing the stochastic dynamics are determined empirically from the historical quotes for the daily, weekly, and mon…

2001-12-16abs ↗pdf ↗

We study power-law correlations properties of the Google search queries for Dow Jones Industrial Average (DJIA) component stocks. Examining the daily data of the searched terms with a combination of the rescaled range and rescaled variance tests together with the detrended fluctuation analysis, we show that the searche…

2015-02-01abs ↗pdf ↗

Study confirms financial bubbles' common patterns in isolated markets.

problem Testing universal dynamics of financial bubbles in isolated markets.
method Log-Periodic Power Law Singularity (LPPLS) model analysis of two major bubble episodes.
result Tehran Stock Exchange shows clear LPPLS hallmarks, supporting bubble universality.

Modeling price clustering in financial markets using discrete distributions.

problem Price clustering phenomenon in financial markets.
method Discrete price model based on mixture of double Poisson distributions with dynamic volatility and proportions.
result Higher instantaneous volatility weakens price clustering at ultra-high frequencies.

In financial time series there are periods in which the value increases or decreases monotonically. We call those periods elemental trends and study the probability distribution of their duration for the indices DJIA, NASDAQ and IPC. It is found that the trend duration distribution often differs from the one expected u…

2012-11-13abs ↗pdf ↗

We have applied the Zipf method to extract the ζζ' exponent for seven financial indices (DAX, FTSE; DJIA, NASDAQ, S&P500; Hang-Seng and Nikkei 225), after having translated the signals into a text based on two letters. We follow considerations based on the signal Hurst exponent and the notion of a time dependent Zipf …

2002-10-22abs ↗pdf ↗

This paper illustrates a procedure for fitting financial data with αα-stable distributions. After using all the available methods to evaluate the distribution parameters, one can qualitatively select the best estimate and run some goodness-of-fit tests on this estimate, in order to quantitatively assess its quality. I…

2006-08-23abs ↗pdf ↗

This study uses moving average cluster entropy to analyze financial market dynamics.

problem Understanding long-range dependence in financial markets.
method Moving average cluster entropy approach applied to ARFIMA and FBM processes.
result Long-range positive correlation in financial markets is linked to the cluster entropy behavior.

Symmetry analysis of financial trends returns reveals bi-modality and multi-scale behavior.

problem Analyzing distributional symmetry in financial trends returns.
method Statistical procedure based on symmetry statistic, applied to daily financial trends returns.
result Daily financial trends returns exhibit bi-modality and multi-scale behavior.

3S-Trader uses LLMs to optimize stock portfolios by scoring, strategizing, and selecting stocks.

problem Lack of multi-LLM frameworks for adaptive stock scoring, strategy, and selection in portfolio optimization.
method 3S-Trader incorporates scoring, strategy, and selection modules for stock portfolio construction, using historical strategies and market conditions to generate optimized selections.
result 3S-Trader achieves the highest accumulated return of 131.83% on DJIA constituents with a Sharpe ratio of 0.31 and Calmar ratio of 11.84.

Using a metric related to the returns correlation, a method is proposed to reconstruct an economic space from the market data. A reduced subspace, associated to the systematic structure of the market, is identified and its dimension related to the number of terms in factor models. Example were worked out involving sets…

2002-11-06abs ↗pdf ↗

In this work, the time chart of Dow Jones Industrial Average (DJIA) index is analyzed and approach of recession time term is predicted, which may be hallmark of a worldwide economic crisis. However, the methods used for the prediction will be disclosed a few years from now. On the other hand, this work will be updated …

2010-08-11abs ↗pdf ↗

DRL improves ESG financial portfolio management by regulating returns based on ESG scores.

problem Improving ESG financial portfolio management through market regulation.
method Used Advantage Actor-Critic (A2C) agent and adapted OpenAI Gym environments for comparative analysis.
result DRL agent outperforms standard market conditions in ESG-regulated market.

Study reveals 2020 stock crashes were mostly endogenous, not exogenous.

problem Identifying the cause of the 2020 global stock market crash.
method Applied log-periodic power law singularity (LPPLS) methodology to analyze stock market indexes.
result The 2020 stock market crashes were mostly endogenous, driven by systemic instability.

The paper integrates behavioral distortions into portfolio optimization using implied probability weighting functions.

problem Behavioral distortions in probability weighting affect portfolio optimization under different return distributions.
method Developed a unified framework to extract probability weighting functions from optimal portfolios modeled under Gaussian and NIG distributions.
result Increasing tail fatness amplifies behavioral distortions, and shifts in risk-free rates alter the curvature of these distortions.

RACORN-K improves portfolio selection by penalizing risk in pattern matching.

problem Challenges in portfolio selection, especially risk-aversion in pattern matching methods.
method Risk-aversion CORN-K algorithm (RACORN-K) that penalizes risk in pattern matching.
result Significant improvements in return, Sharp ratio, and maximum drawdown on volatile markets.

We apply two non-parametric methods to test further the hypothesis that log-periodicity characterizes the detrended price trajectory of large financial indices prior to financial crashes or strong corrections. The analysis using the so-called (H,q)-derivative is applied to seven time series ending with the October 1987…

2002-05-25abs ↗pdf ↗

A framework uses attention mechanisms to optimise financial portfolios by reducing noise and balancing returns.

problem Balancing investment returns and risks in noisy financial markets.
method Multi-agent framework with attention mechanisms and time series analysis.
result MASAAT framework produces more balanced portfolios with enhanced performance.

This paper presents an exclusive classification of the largest crashes in Dow Jones Industrial Average (DJIA), SP500 and NASDAQ in the past century. Crashes are objectively defined as the top-rank filtered drawdowns (loss from the last local maximum to the next local minimum disregarding noise fluctuations), where the …

2004-01-13abs ↗pdf ↗

The paper introduces eigen-portfolios using PCA to improve portfolio construction in finance.

problem Overfitting and poor generalization in selecting a single eigen-portfolio.
method Principal Component Analysis (PCA) to derive eigen-portfolios from asset return correlation matrices.
result An ensemble strategy combining multiple top-performing eigen-portfolios significantly improves out-of-sample performance.

Entropy measure quantifies volatility correlation and risk diversity in asset portfolios.

problem Quantifying volatility correlation and risk diversity in asset portfolios.
method Kullback-Leibler cluster entropy DC[PQ]\mathcal{D_{C}}[P \| Q] for empirical and model probability distributions of realized volatility.
result Portfolio built on diversity indexes derived from Kullback-Leibler entropy measure of realized volatility exhibits better performance.