Method detects and visualizes changes in financial markets' asset relationships.
problem Detecting and explaining changes in financial markets' asset relationships.
method Construct co-occurrence networks, calculate Graph-Based Entropy, apply Differential Network.
result Visualization of changes in financial markets with high interpretability.
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.
SVAR-LiNGAM reveals causal order in crypto-asset markets.
problem Understanding the causal relationships between spot rates and crypto-assets.
method Applied SVAR-LiNGAM to analyze spot exchange rates and crypto-asset exchange rates.
result Causal order found: EUR_USD spot rate -> Bitcoin -> Ethereum -> Ripple.
Examines how central bank policies affect stock markets and asset prices.
problem Understanding the impact of monetary policy on stock markets and asset prices.
method Used Taylor rule equations to analyze data from 1990 to 2020 for US and UK, testing with various econometric methods.
result Monetary policy can explain asset price volatility and output gap better than just inflation rate.
The value of an asset in a financial market is given in terms of another asset known as numeraire. The dynamics of the value is non-stationary and hence, to quantify the relationships between different assets, one requires convenient measures such as the means and covariances of the respective log returns. Here, we dev…
New process explains asset volatility patterns.
problem Explains statistical relationship between asset volatility and returns.
method Uses multiplicative Langevin process with adjustable coherence time.
result Exactly equivalent to Inverse Gamma distribution for volatility.
Proposes neural model for stock embeddings to capture nuanced asset correlations.
problem Lack of research on modelling financial asset correlations.
method Neural model using historical returns data to learn nuanced relationships.
result Outperforms benchmarks in two real-world financial analytics tasks.
Transformer model improves asset allocation by unifying forecasting and optimization.
problem Separation of forecasting and optimization leads to suboptimal portfolios.
method Signature Informed Transformer using path signatures and specialized attention.
result Direct minimization of Conditional Value at Risk improves performance.
Study uses MTD model to optimize portfolios by capturing complex financial asset relationships.
problem Capturing nonlinear and directional relationships in financial markets.
method Directed and weighted financial networks using Mixture Transition Distribution (MTD) model.
result Portfolio optimization with network-based assortativity measures outperforms classical methods.
We propose a novel estimation procedure for scale-by-scale lead-lag relationships of financial assets observed at high-frequency in a non-synchronous manner. The proposed estimation procedure does not require any interpolation processing of original datasets and is applicable to those with highest time resolution avail…
A new contrastive learning method extracts asset embeddings from financial time series.
problem Extracting meaningful latent features from noisy financial data.
method Contrastive learning framework using hypothesis testing for positive and negative samples.
result Effective asset embeddings significantly outperform existing methods on financial tasks.
We investigate financial market correlations using random matrix theory and principal component analysis. We use random matrix theory to demonstrate that correlation matrices of asset price changes contain structure that is incompatible with uncorrelated random price changes. We then identify the principal components o…
Study examines the impact of employment benefit costs on firm profitability.
problem Impact of employment benefit costs on firm profitability.
method Panel data regression analysis using E-Views.
result There is a significant positive relationship between employment benefit costs and firm profitability.
Study introduces a new copula-based measure for financial asset cointegration.
problem Traditional correlation coefficient's limitations in measuring financial asset relationships.
method Utilizes copulas to measure dependence among financial asset returns.
result Enhanced stability and informativeness in measuring financial asset relationships.
We present an overview of the broad class of financial models in which the prices of assets are Lévy-Ito processes driven by an n-dimensional Brownian motion and an independent Poisson random measure. The Poisson random measure is associated with an n-dimensional Lévy process. Each model consists of a pricing kerne…
TGNN combines GNN and SMM for better trading network predictions.
problem Predicting asset prices in trading networks with structural impact factors.
method Combines GNN and SMM for asset price prediction.
result TGNN outperforms existing methods in prediction accuracy.
This research improves asset life prediction by integrating deep learning with mixture distributions.
problem Predicting residual useful life for assets with multiple failure modes.
method Integrates mixture (log)-location-scale distribution with deep learning.
result Proposed models outperform existing methods in predicting residual useful life.
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.
Study on asset price dynamics in OLG economies with and without a bubbly asset.
problem Analyzing asset price dynamics and optimality in OLG economies with an asset that yields dividends.
method Deriving conditions for three scenarios of equilibrium existence, providing a complete characterization of the equilibrium set, and investigating the relationship between asset price behaviors and optimality.
result A bubbly equilibrium exists if and only if the interest rate is lower than the population growth rate and the sum of per capita dividends is finite.
The existence of time-lagged cross-correlations between the returns of a pair of assets, which is known as the lead-lag relationship, is a well-known stylized fact in financial econometrics. Recently some continuous-time models have been proposed to take account of the lead-lag relationship. Such a model does not follo…
Enhances thematic investing with stock embeddings from textual data.
problem Challenges in constructing thematic portfolios due to overlapping sector boundaries and evolving market dynamics.
method Introduces THEME, a framework that fine-tunes embeddings using hierarchical contrastive learning, aligning themes and stocks using their hierarchical relationship and incorporating stock returns.
result Theme-aligned portfolios demonstrate compelling performance, significantly outperforming large language models in thematic asset retrieval.
Paper uses news data to model asset correlations without market data.
problem Traditional risk models rely on market data; this paper offers an alternative.
method Uses encoder-only language models to embed news data, then calculates asset return distributions and covariance through Energy Distance.
result Established connections between distributional differences and excess returns co-movements using Energy Distance.
Bayesian model reduces stock volatility by identifying key cointegrated relationships.
problem Constructing low volatility stock portfolios from a large number of stocks.
method High dimensional Bayesian cointegration estimation.
result Portfolios with reduced volatility and persistence of cointegration relationships.
In power systems, an asset class is a group of power equipment that has the same function and shares similar electrical or mechanical characteristics. Predicting failures for different asset classes is critical for electric utilities towards developing cost-effective asset management strategies. Previously, physical ag…
We study risk-sharing economies where heterogenous agents trade subject to quadratic transaction costs. The corresponding equilibrium asset prices and trading strategies are characterised by a system of nonlinear, fully-coupled forward-backward stochastic differential equations. We show that a unique solution generally…
This paper proposes a new clustering method based on Stochastic Dominance for asset allocation.
problem Traditional clustering methods fail to capture risk dominance relationships among assets.
method Integrates Stochastic Dominance theory with machine learning algorithms to construct a Stochastic Dominance Coefficient Matrix and modify clustering algorithms.
result The proposed method effectively facilitates customized asset allocation for investors.
The Capital Asset Pricing Model (CAPM) is one of the original models in explaining risk-return relationship in the financial market. However, when applying the CAPM into reality, it demonstrates a lot of shortcomings. While improving the performance of the model, many studies, on one hand, have attempted to apply diffe…
Investigates the relationship between US money supply and asset indices over 2001-2019.
problem Determining the relationship between US money supply and asset indices growth.
method Information entropy methodology applied to US asset indices (Property, Russell 2000, S&P 500, NASDAQ) over 2001-2019.
result Growth in US broad money supply is the main determinant of US asset indices growth, especially the NASDAQ and Russell 2000.
Development of stock networks is an important approach to explore the relationship between different stocks in the era of big-data. Although a number of methods have been designed to construct the stock correlation networks, it is still a challenge to balance the selection of prominent correlations and connectivity of …
Novel risk matrix for optimal portfolio choice with tail risk considerations.
problem Optimal portfolio choice with tail risk events.
method Risk matrix with Value-at-Risk and Delta-CoVaR measures, derived conditions for closed-form solution, examination of portfolio risk and centrality, demonstration of asset centrality's impact on optimal weight allocation.
result Portfolio risk is not necessarily increasing with stock centrality and can be improved by high connectivity.
Optimal strategy for liquidating portfolios under discrete time intervals.
problem Optimizing liquidation of portfolios with discrete time constraints and impact effects.
method Modeling portfolio liquidation with N risky assets, using VaR for cost measurement, and deriving an optimal liquidation time.
result The optimal liquidation time is only influenced by temporary price impacts, not permanent ones.
Study asset pricing under model uncertainty with discrete time and states.
problem Asset pricing under model uncertainty with discrete time and states.
method Novel definition of arbitrage, investigation of no-arbitrage conditions, expansion to multi-period securities model.
result Necessary and sufficient conditions for no-arbitrage asset pricing under model uncertainty.
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…
By decomposing asset returns into potential maximum gain (PMG) and potential maximum loss (PML) with price extremes, this study empirically investigated the relationships between PMG and PML. We found significant asymmetry between PMG and PML. PML significantly contributed to forecasting PMG but not vice versa. We furt…
Study shows environmental spending positively impacts company profitability.
problem Impact of environmental spending on company profitability.
method Panel data regression analysis using E-Views.
result Environmental spending positively impacts profitability metrics.
The conventional wisdom of mean-variance (MV) portfolio theory asserts that the nature of the relationship between risk and diversification is a decreasing asymptotic function, with the asymptote approximating the level of portfolio systematic risk or undiversifiable risk. This literature assumes that investors hold an…
This research introduces dynamic portfolio cuts using a spectral approach for graph-theoretic diversification.
problem Traditional methods for estimating asset-return covariance assume statistical time-invariance, failing to capture the nonstationary nature of asset price movements.
method Introduces graph spectral estimators that account for nonstationarity, partitioning the market graph into time-evolving clusters for dynamic portfolio cuts.
result Demonstrates the advantages of the proposed framework over traditional methods through numerical case studies using real-world price data.
Deep learning model optimizes portfolios by integrating news sentiment, stock relationships, and price data.
problem Optimizing portfolio weights using traditional methods introduces instability.
method Combines LSTM, GAT, and sentiment analysis in a unified pipeline.
result Delivers higher cumulative returns and Sharpe ratios compared to benchmarks.
This paper investigates the risk-return relationship in determination of housing asset pricing. In so doing, the paper evaluates behavioral hypotheses advanced by Case and Shiller (1988, 2002, 2009) in studies of boom and post-boom housing markets. The paper specifies and tests a multi-factor housing asset pricing mode…
By exploiting a bipartite network representation of the relationships between mutual funds and portfolio holdings, we propose an indicator that we derive from the analysis of the network, labelled the Average Commonality Coefficient (ACC), which measures how frequently the assets in the fund portfolio are present in th…
Complex contagion model explains financial fire sales through continuous asset prices.
problem Modeling financial fire sales with a continuum of asset prices.
method Developed a threshold model of continuous-state cascades using real values for asset prices.
result Discretization approach accurately replicates the distribution of defaulted banks and asset prices.
Two-cycle GEILA equilibria are OLG equilibria and vice versa, with applications to indeterminacy and bubbles.
problem Relationship between GEILA and OLG models.
method Proof of equilibrium equivalence and application to indeterminacy and bubbles.
result GEILA and OLG models are equivalent under certain conditions.
Randomized control methods improve asset pricing and performance analysis.
problem Challenges in drawing inferences from traditional random portfolios in performance evaluation.
method Geometric random walks and Markov chain Monte Carlo methods to construct flexible control groups.
result Captured premia associated with size, value, quality, and momentum in a constrained setting.
We analyze the size dependence and temporal stability of firm bankruptcy risk in the US economy by applying Zipf scaling techniques. We focus on a single risk factor-the debt-to-asset ratio R-in order to study the stability of the Zipf distribution of R over time. We find that the Zipf exponent increases during market …
A network-based approach identifies financial factors from asset interactions, explaining market dynamics.
problem Characterizing joint financial asset behavior through underlying drivers.
method Modeling market as coupled iterated maps, where asset returns depend on past returns and interactions.
result Stable patterns of co-movement (financial factors) emerge from asset interactions, explaining asset variance.
Study evaluates profitability of Islamic banks in Bangladesh using ROA, ROE, and ROD.
problem Evaluating profitability of Islamic banks in Bangladesh.
method Used ROA, ROE, and ROD as measures, analyzed relationships with AU and OE.
result ROD significantly associated with ROA, but not with OE and AU.
In common finance literature, Black-Scholes partial differential equation of option pricing is usually derived with no-arbitrage principle. Considering an asset market, Merton applied the Hamilton-Jacobi-Bellman techniques of his continuous-time consumption-portfolio problem, deriving general equilibrium relationships …
ETF approval boosts Bitcoin's correlation with equities, stabilizes with gold, and maintains negative correlation with fiat currencies.
problem Impact of Bitcoin ETF approval on Bitcoin's relationships with traditional assets.
method Rolling correlation analysis, Chow tests, and DCC-GARCH models.
result Bitcoin's correlation with equities increased significantly post-ETF approval, while its relationship with gold stabilized and remained negatively correlated with fiat currencies.