A new wavelet method for analyzing lead-lag effects between financial assets.
problem Analyzing lead-lag relationships between financial assets.
method Wavelet-based framework bridging continuous-time and discrete-time models.
result Developed an asymptotic theory for multi-scale analysis of lead-lag effects.
NAPLES resolves lead-lag analysis challenges in non-synchronous high-frequency data.
problem Challenges in analyzing lead-lag effects due to non-synchronous observations and high-frequency data.
method NAPLES (Negative And Positive lead-lag EStimator) resolves these challenges.
result NAPLES has a strong correlation with actual lead-lag effects, including those triggered by macroeconomic announcements.
The study examines network analysis for predicting stock market performance.
problem Understanding lead-lag relationships in the NYSE.
method Network analysis of the NYSE to identify lead-lag effects.
result Network analysis reveals valuable insights for investors and analysts.
Estimates lead-lag relationships in high-frequency financial markets without interpolation.
problem Lag relationships in high-frequency financial markets with non-synchronous data.
method Proposes a novel estimation procedure for scale-by-scale lead-lag relationships.
result Identifies two types of lead-lag relationships at different time scales.
Algorithm detects lead-lag relationships in multivariate time series.
problem Understanding temporal dependencies between time series.
method Cluster-driven methodology based on dynamic time warping.
result Robust detection of lead-lag relationships in lagged multi-factor models.
This study examines lead-lag relationships in Chinese futures markets using high-frequency data.
problem Understanding high-frequency trading dynamics and information flow in futures markets.
method High-frequency tick-by-tick data analysis of lead-lag relationships between different maturity futures contracts.
result The near-month futures lead longer-dated contracts by one tick, with a negative feedback effect on the leading asset.
Recently the interest of researchers has shifted from the analysis of synchronous relationships of financial instruments to the analysis of more meaningful asynchronous relationships. Both of those analyses are concentrated only on Pearson's correlation coefficient and thus intraday lead-lag relationships associated wi…
Detects lead-lag clusters in US equity market time series.
problem Identifying lead-lag relationships in multivariate time series.
method Directed network clustering of lead-lag relationships.
result Validated on US equity market data, detects statistically significant lead-lag clusters.
Study reveals lead-lag patterns between onshore and offshore RMB exchange rates.
problem Understanding the lead-lag relationship between onshore and offshore RMB exchange rates.
method Employed the thermal optimal path method to analyze daily and minute-scale data.
result Lead-lag patterns are influenced by market factors and US dollar appreciation.
New method for estimating lead-lag times between non-synchronously observed point processes.
problem Estimating lead-lag relationships between non-synchronously observed point processes.
method Formulate lead-lag estimation as CPCF shape estimation; propose kernel density estimation-based lead-lag time estimator.
result Proposed method delivers superior numerical performance and effective lead-lag time estimation.
No arbitrage found with market frictions for time-lagged asset returns.
problem Existence of time-lagged cross-correlations in financial returns.
method Introduced market frictions like minimal waiting time or transaction costs.
result No arbitrage possible with market frictions.
According to the leading models in modern finance, the presence of intraday lead-lag relationships between financial assets is negligible in efficient markets. With the advance of technology, however, markets have become more sophisticated. To determine whether this has resulted in an improved market efficiency, we inv…
New method selects stock pairs for pairs trading considering lead-lag relationship.
problem Identifying best stock pairs for pairs trading considering lead-lag relationship.
method Proposes a new distance measure incorporating lead-lag relationship.
result Selected pairs consistently generate best profit compared to other measures.
Clusters asset classes to identify lead-lag relationships in market regimes.
problem Understanding lead-lag relationships between different asset classes.
method Defining macroeconomic regimes by clustering indices and investigating lead-lag relationships.
result Unravels market features and highlights informative market trends or risks.
Novel framework detects lead-lag relationships in Chinese A-share market.
problem Detecting lead-lag relationships in the Chinese A-share market.
method Two-stage framework: long-term coupling via correlation, dynamic time warping, and rank-based metrics; high-frequency data analysis via cross-correlation, Granger causality, and regression models.
result Strongly coupled stock pairs often exhibit lead-lag effects, especially at finer time scales.
We present the symmetric thermal optimal path (TOPS) method to determine the time-dependent lead-lag relationship between two stochastic time series. This novel version of the previously introduced TOP method alleviates some inconsistencies by imposing that the lead-lag relationship should be invariant with respect to …
New technique identifies lead-lag relationships in FX market during pandemic.
problem Identifying lead-lag relationships in financial markets, especially during crises.
method Dynamic Programming technique for finding optimal lead-lag path, using a loose metric.
result The proposed technique gives the best results in identifying statistically significant paths and closest forecasts.
Method detects lead-lag relationships in multivariate time series.
problem Discovering lead-lag relationships in multivariate time series.
method Clustering-driven methodology using sliding window and various clustering techniques.
result Robust lead-lag estimates across clusters enhance consistent relationships identification.
Study examines lead-lag relationships between VIX and VIX futures markets over time.
problem Understanding dynamic interaction patterns between VIX and VIX futures markets.
method Utilized the symmetric thermal optimal path (TOPS) method to analyze time-dependent lead-lag relationships.
result Observed alternate lead-lag relationship instead of dominance between VIX and VIX futures markets.
Modeling lead-lag relationship between two text corpora for improved topic modeling.
problem Recognizing the relationship between multiple text corpora for better topic modeling.
method Proposed a jointly dynamic topic model and embedding extension for large-scale text corpus.
result The proposed model can well recognize the lead-lag relationship between two text corpora and improve topic learning.
New method speeds up lead-lag detection between asynchronous time series.
problem Slow inference of lead-lag networks between long time series.
method Derive asymptotic distribution of Transfer Entropy and introduce time-shifted time series.
result Statistically validated lead-lag networks between time series.
Study lead-lag relationships in foreign exchange markets using three approaches.
problem Lack of research on lead-lag relationships in foreign exchange markets.
method Three approaches: lagged correlations, lagged partial correlations, and Granger causality.
result Statistically significant lead-lag relationships found in some exchange rate pairs.
Method infers trader lead-lag networks to reveal market dynamics.
problem Understanding herding and liquidity in financial markets.
method Kinetic Ising model and inference algorithm to reconstruct trader opinions.
result Identifies leading players and links herding to liquidity.
The intermarket analysis, in particular the lead-lag relationship, plays an important role within financial markets. Therefore a mathematical approach to be able to find interrelations between the price development of two different financial underlyings is developed in this paper. Computing the differences of the relat…
Lead/lag relationships are an important stylized fact at high frequency. Some assets follow the path of others with a small time lag. We provide indicators to measure this phenomenon using tick-by-tick data. Strongly asymmetric cross-correlation functions are empirically observed, especially in the future/stock case. W…
Hybrid method uses LLM to filter lead-lag relationships in prediction markets.
problem Challenges in discovering robust lead-lag relationships in prediction markets due to spurious correlations.
method Two-stage approach: statistical Granger causality followed by LLM semantic re-ranking.
result LLM-based method outperforms statistical baseline, increasing win rate and reducing average loss magnitude.
Study reveals asymmetry in market dynamics across different timescales.
problem Understanding asymmetry in market dynamics across different timescales.
method Infer lead-lag networks for multiple timescales to capture causal structure.
result Strong and complex asymmetric influence of timescales on lead-lag networks.
In our previous study we have presented an approach to studying lead--lag effect in financial markets using information and network theories. Methodology presented there, as well as previous studies using Pearson's correlation for the same purpose, approached the concept of lead--lag effect in a naive way. In this pape…
Proposes C2RM to mine cross-cryptocurrency relationships for better Bitcoin price prediction.
problem Limited consideration of historical relationships and interactions between cryptocurrencies for Bitcoin price prediction.
method C2RM module using Dynamic Time Warping for lead-lag relationship extraction and aggregation.
result Improves existing price prediction methods by significant performance improvement.
We introduce a method to infer lead-lag networks of agents' actions in complex systems. These networks open the way to both microscopic and macroscopic states prediction in such systems. We apply this method to trader-resolved data in the foreign exchange market. We show that these networks are remarkably persistent, w…
Study examines how economic policy uncertainty impacts stock markets.
problem Dynamic relationship between economic policy uncertainty and stock markets.
method Used symmetric thermal optimal path (TOPS) method.
result Different interaction patterns observed in emerging and developed markets.
Enhanced trend-following strategy using network momentum for commodity futures.
problem Improving systematic trend-following in commodity futures markets.
method Combines univariate and cross-sectional trend indicators, including network momentum.
result Statistically significant improvements in portfolio performance metrics.
Novel method calculates complex correlation for high-frequency financial data.
problem Analyzing lead-lag relations in high-frequency financial data.
method Hilbert transform based complex correlation for unevenly spaced data.
result Identifies market components with small but significant delays.
This study compares price discovery in ETH and BTC markets between centralized and decentralized exchanges.
problem Understanding price discovery dynamics in cryptocurrency markets.
method Comparative analysis of centralized and decentralized exchanges, using econometric tools.
result Centralized exchanges lead in ETH price discovery, while futures markets lead in BTC.
Study reveals how correlation matrix eigenvalues change with time scale in U.S. stocks.
problem Understanding how correlation structure of securities changes with time scale.
method Aggregated one-minute returns of 533 U.S. stocks at different time scales, estimated correlation matrix, lead-lag factor model.
result Emergence of several dominant eigenvalues as time scale increases.
We have recently introduced the ``thermal optimal path'' (TOP) method to investigate the real-time lead-lag structure between two time series. The TOP method consists in searching for a robust noise-averaged optimal path of the distance matrix along which the two time series have the greatest similarity. Here, we gener…
Enhances time-series regression trees with latent factors for robust financial analysis.
problem Handling predictors with measurement error, trends, seasonality, and missing data.
method Integrates latent stationary factors extracted via state-space methods into time-series regression trees.
result Factor-augmented trees provide a reliable approach for macro-finance problems, exemplified by the lead-lag effect between equity volatility and the business cycle.
The Epps effect, the decrease of correlations between stock returns for short time windows, was traced back to the trading asynchronicity and to the occasional lead-lag relation between the prices. We study pairs of stocks where the latter is negligible and confirm the importance of asynchronicity but point out that al…
Using a recently introduced method to quantify the time varying lead-lag dependencies between pairs of economic time series (the thermal optimal path method), we test two fundamental tenets of the theory of fixed income: (i) the stock market variations and the yield changes should be anti-correlated; (ii) the change in…
Paper detects intensity bursts in financial data using Hawkes processes.
problem Detecting and analyzing intensity bursts in high-frequency financial data.
method Proposes a novel Hawkes process-based method for detecting intensity bursts in financial data.
result Demonstrates the effectiveness of the method in detecting intensity bursts in FX markets.
This study examines how economic policy uncertainty impacts commodity prices across different crises.
problem Impact of economic policy uncertainty on commodity prices during various crises.
method Wavelet coherence analysis of time series data.
result Commodity prices are more correlated during global financial and Covid-19 crises.
A novel signature method improves sequential data prediction accuracy.
problem Improving prediction accuracy for sequential and temporal data.
method Signature method based on rough path theory, with a specific embedding called lead-lag.
result Lead-lag embedding consistently outperforms other embeddings across various datasets and algorithms.
Study examines oil and US stock market interactions during coronavirus crisis.
problem Understanding the impact of coronavirus on oil and stock markets.
method Wavelet analysis of daily data from February 18, 2020 to August 15, 2020.
result Oil prices lead US stock prices at 3-5-day cycles during the first and second parts of March and April 2020.
We analyse the temporal changes in the cross correlations of returns on the New York Stock Exchange. We show that lead-lag relationships between daily returns of stocks vanished in less than twenty years. We have found that even for high frequency data the asymmetry of time dependent cross-correlation functions has a d…
We study historical correlations and lead-lag relationships between individual stock risk (volatility of daily stock returns) and market risk (volatility of daily returns of a market-representative portfolio) in the US stock market. We consider the cross-correlation functions averaged over all stocks, using 71 stock pr…
Path signatures reveal community structure in coupled oscillators' dynamics.
problem Detecting communities in multivariate dynamical processes from time series data.
method Path signatures, a mathematical framework encoding geometric and temporal properties of continuous paths.
result Achieved exact recovery of structural communities from observed time series in multiple KSBM instances.
Proposes a diagnostic method to evaluate factor models using cap-axis integrals.
problem Improving factor model evaluation in low-dimensional spaces.
method Lifts pricing errors into a bridge-alpha curve along the market-capitalization rank axis.
result The cap-axis norm is distinct from Sharpe gain and size exposure.
Proposes a diagnostic method to evaluate factor models using cap-axis integrals.
problem Improving factor model evaluation for low-dimensional models.
method Lifts pricing errors into a bridge-alpha curve along the market-capitalization rank axis.
result The cap-axis norm is distinct from Sharpe gain and size exposure.