The paper tests stock return models and uses LSTM to predict stock returns.
problem Validating stock return models and predicting stock returns.
method Used Fama-French three-factor, four-factor, and five-factor models; also used LSTM model.
result Fama-French five-factor model shows better validity for stock returns.
Through a long-period analysis of the inter-temporal relations between the French markets for credit default swaps (CDS), shares and bonds between 2001 and 2008, this article shows how a financial innovation like CDS could heighten financial instability. After describing the operating principles of credit derivatives i…
Study analyzes Disney stock market performance using machine learning.
problem Forecasting stock market performance of Disney.
method Exploratory data analysis, feature engineering, model selection (linear regression).
result Linear regression model performed best.
Study tests if equity factors explain Bitcoin's risk and returns.
problem Explaining Bitcoin's risk and return with equity factors.
method Applied statistical methods to test Fama-French factors on Bitcoin's excess returns.
result Fama-French factors have explanatory power on Bitcoin's risk and returns.
This study revisits Fama-French models using sample innovations to address misinterpretation of high R-squared values.
problem Misinterpretation of high R-squared values in Fama-French models due to serial dependence and volatility clustering.
method Use of sample innovations to derive standard econometrics time series models to overcome misinterpretation.
result Suggests the Fama-French model should consider heavy-tail distributions due to relevant tail behavior in financial data.
Paper introduces a specialized text classification system for French Open Banking transactions.
problem Classifying specialized banking text data with high accuracy and efficiency.
method Data collection, labeling, preprocessing, modeling, and evaluation stages with language-specific techniques.
result Enhanced performance and efficiency compared to generic approaches.
Study examines stock price reactions to Texas winter storm power outages.
problem Impact of natural disasters on stock market values.
method Used four benchmark models to measure abnormal returns.
result Firms experienced significant stock price drops after the Texas winter storm.
Empirical study of CAPM and Fama-French model in Chinese A-share market.
problem Testing and validating CAPM and Fama-French model in Chinese A-share market.
method Used Fama-MacBeth regression and Fama-French three-factor model to analyze Chinese A-share trading data from 2000 to 2019, adjusting for IPO shell value contamination.
result Fama-French model captures most of A-share market returns, with adjusted R-squared > 0.88.
The paper examines the stability of Fama-French multi-factor models over time.
problem Stability of Fama-French multi-factor models over time.
method Rolling window method, Fama and MacBeth's two-step estimation, generalized GRS statistics.
result The effectiveness of Fama-French factors is not stable over time in all countries.
The article prices exchange options using variance gamma-like models.
problem Pricing exchange options under specific stochastic processes.
method Derives formulas for variance gamma and variance gamma++ processes, constructs multidimensional versions, calibrates parameters with real data.
result Closed formulas and numerical methods for evaluating exchange options.
Study on time-zero efficiency of European power derivatives markets using statistical tests and trading rules.
problem Assessing time-zero efficiency in European power derivatives markets.
method Statistical tests based on the law of one price and trading rules based on price differentials and no-arbitrage violations applied to daily data of three European power markets.
result Definite conclusions on time-zero efficiency are not possible for French and Spanish markets due to liquidity and representativeness challenges.
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…
Market trade-routes can support infectious-disease transmission, impacting biological populations and even disrupting causal trade. Epidemiological models increasingly account for reductions in infectious contact, such as risk-aversion behaviour in response to pathogen outbreaks. However, market dynamics clearly differ…
Examines how extending home loan durations affects French households financially.
problem Financial implications for households with extended home loan durations.
method Analysis of French and international home loan systems, including bullet loans and Japanese home loans.
result Extending home loan durations can reduce monthly payments but raises financial risks.
We find that the CAPM fails to explain the small firm effect even if its non-parametric form is used which allows time-varying risk and non-linearity in the pricing function. Furthermore, the linearity of the CAPM can be rejected, thus the widely used risk and performance measures, the beta and the alpha, are biased an…
We present extensive evidence that ``risk premium'' is strongly correlated with tail-risk skewness but very little with volatility. We introduce a new, intuitive definition of skewness and elicit an approximately linear relation between the Sharpe ratio of various risk premium strategies (Equity, Fama-French, FX Carry,…
Thurston's influence on French math traced and problems solved.
problem Major problems in French math traced back to Thurston.
method Overview and survey of Thurston's influence and results.
result French math problems rooted in Thurston's work.
The MAXFLAT low-pass filter improves factor adjustment for better portfolio performance in China's stock market.
problem Improving factor adjustment for better portfolio performance in China's stock market.
method Using MAXFLAT low-pass volatility model to adjust factors and construct portfolios.
result Adjusted factors by MAXFLAT volatility model show better performance in both large and small cap universes.
In the standard equilibrium and/or arbitrage pricing framework, the value of any asset is uniquely specified from the belief that only the systematic risks need to be remunerated by the market. Here, we show that, even for arbitrary large economies when the distribution of the capitalization of firms is sufficiently he…
The study compares VaR and ES models for tail risk of electricity futures, finding AR(1)-GARCH(1,1) with Student-t distribution best.
problem Modeling tail risk of electricity futures contracts in various markets.
method Comparison of VaR and ES models using AR(1)-GARCH(1,1) with Student-t distribution, historical simulation, and quantile regression.
result AR(1)-GARCH(1,1) with Student-t distribution is the best-performing model for tail risk estimation.
In Biology, all motor enzymes operate on the same principle: they trap favourable brownian fluctuations in order to generate directed forces and to move. Whether it is possible or not to copy one such strategy to play the market was the starting point of our investigations. We found the answer is yes. In this paper we …
Measuring information value in markets using covariance of price changes and order flow.
problem Determining the value of information in financial markets.
method Using high-frequency data on US equities, the covariance between price changes and order flow is estimated to measure information value.
result The aggregate value of information is about 0.04% of market cap, significantly lower than fees investors pay.
We introduce a new system of stochastic differential equations which models dependence of market beta and unsystematic risk upon size, measured by market capitalization. We fit our model using size deciles data from Kenneth French's data library. This model is somewhat similar to generalized volatility-stabilized model…
Nostradamus links climate and stock market performance.
problem Understanding the impact of climate on stock prices.
method Analyzing historical data, climate indicators, and natural disasters.
result Significant correlation between climate and stock price fluctuations.
This paper investigates the time-varying risk-premium relation of the Chinese stock markets within the framework of cross-sectional momentum and contrarian effects by adopting the Capital Asset Pricing Model and the French-Fama three factor model. The evolving arbitrage opportunities are also studied by quantifying the…
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.
A new model decomposes equity returns and volatilities into memory components.
problem Understanding long-term equity dynamics and volatility patterns.
method Proposes a multivariate generalization of the variance ratio to decompose long-horizon equity dynamics.
result Identifies a five-factor model capturing persistent, antipersistent, and multi-scale memory in returns and volatility.
The paper presents a neural machine translation system for Wolof.
problem Low-resource conditions for translating French to Wolof.
method Developed a bidirectional LSTM-based encoder-decoder architecture with attention mechanisms.
result Best model achieved a 47% BLEU score for French-Wolof translation.
We propose and investigate two model classes for forward power price dynamics, based on continuous branching processes with immigration, and on Hawkes processes with exponential kernel, respectively. The models proposed exhibit jumps clustering features. Models of this kind have been already proposed for the spot price…
Motivated by the increasing integration among electricity markets, in this paper we propose two different methods to incorporate market integration in electricity price forecasting and to improve the predictive performance. First, we propose a deep neural network that considers features from connected markets to improv…
The paper models battery valuation in intraday electricity markets, incorporating liquidity costs.
problem Valuing batteries in intraday electricity markets considering liquidity costs.
method Stochastic model for mid-prices combined with a deterministic model for liquidity costs, using dynamic programming for optimization.
result Liquidity costs significantly impact battery valuation, especially with multiple batteries.
Unified model combines shrinkage, views, and factor models for better portfolio selection.
problem Limitations of mean-variance analysis, estimation errors, and reliance on historical data.
method Bayesian approach integrating shrinkage estimation and Black-Litterman model with Fama-French factor models.
result The model outperforms simple and sample-based optimal portfolios in US equity market.
The recent liberalization of the electricity and gas markets has resulted in the growth of energy exchanges and modelling problems. In this paper, we modelize jointly gas and electricity spot prices using a mean-reverting model which fits the correlations structures for the two commodities. The dynamics are based on Or…
Study shows how 'crowding' in equity trading affects performance and costs.
problem Deterioration of strategy performance, increased trading costs, and systemic risk due to equity factor crowding.
method Direct metrics of crowding based on imbalances of trades executed on the market, analyzing U.S. equity market data.
result Significant signs of crowding in well-known equity signals, especially Momentum, affecting order flow and portfolio rebalancing.
The paper introduces a machine learning method to forecast market direction using efficient frontier coefficients.
problem Improving asset return estimation for portfolio optimization.
method Monthly directional market forecast using an online decision tree trained on efficient frontier coefficients.
result The method outperforms baseline portfolios and other feature sets.
Modeling financial crises and cryptocurrency shocks using copulae clustering.
problem Detecting financial crises and shock events in stock and cryptocurrency markets.
method Copulae clustering based on probability distribution distances.
result Successfully detected all past crises and shock events in stock and cryptocurrency markets.
Decomposes financial networks to reveal cause-effect hierarchies during crises.
problem Complex financial networks are hard to interpret due to Granger causality.
method Helmholtz-Hodge-Kodaira decomposition to separate networks into rotational and gradient components.
result Precious metals and pharmaceutical products are identified as causal drivers during crises.
The objective of this article is to analyze the impact of capital structure on profitability. This impact can be explained by three essential theories: signaling theory, tax theory and the agency costs theory. A sample of 1846 French industrial firms are taken over the period 1999-2006, as a dynamic panel study by usin…
Study examines market reactions and spillovers in Japanese bank mergers using multiple methods.
problem Understanding valuation and spillover effects of bank mergers in the Japanese banking sector.
method Combines event study, VAR models, IRFs, and PSM to analyze two M&A events.
result Significant positive market reaction and prolonged positive spillovers detected.
OT domain adaptation improves aphasia detection across languages.
problem Detecting aphasia in low-resource languages with limited data.
method Utilized OT domain adaptation to map linguistic features across multiple languages.
result OT domain adaptation significantly improved F1 scores for French and Mandarin aphasia detection.
Study assesses additional factors for identifying persistent alpha in pension funds.
problem Identify persistent alpha in pension funds using additional factors.
method Reproduces Fama and French's (2010) experiment with additional features and compares results to 3-factor model.
result Additional factors improve persistence of alpha assessment in pension funds.
A limit order book provides information on available limit order prices and their volumes. Based on these quantities, we give an empirical result on the relationship between the bid-ask liquidity balance and trade sign and we show that liquidity balance on best bid/best ask is quite informative for predicting the futur…
Intangible investment becomes a strong predictor of stock returns over time.
problem Understanding the role of intangible investment in stock returns over different periods.
method Comparing intangible investment's predictive power over two distinct periods (1963-1992 and 1993-2022) using orthogonal factors.
result Intangible investment's predictive power for stock returns has significantly increased over time, becoming a main predictor for recent periods.
Current study aims to provide new empirical evidence on the impact of debt on corporate profitability. This impact can be explained by three essential theories: signaling theory, tax theory and the agency cost theory. Using panel data sample of 2240 French non listed companies of service sector during 1999-2006. By uti…
Model shows government incentives boost green bond investment.
problem Increasing green investments through government incentives.
method Optimal incentives indexed on bond prices and covariation, applied to a portfolio of bonds.
result Method outperforms current tax-incentives systems in green investments.
The object of this contribution is to present the ideas behind the thinking of the French economist Pierre-Joseph Proudhon (1809-1865) in relation to the causes and effects of Stock market speculation. It is based upon the works of this author but particularly on his "Manuel du spéculateur à la Bourse" (Stock Market Sp…
Improved language model for French clinical reports achieves state-of-the-art performance in medical NLP tasks.
problem Lack of specialized language models for French clinical reports.
method Adapted a general pre-trained language model (CamemBERT) to French clinical reports using a corpus of 21M reports.
result Pretrained and fine-tuned models improved F1-score by 3 percentage points on APMed task.