ESSEC METALAB

Expanding Scientific Knowledge

ESSEC’s approach to AI, Data Science and Technology is original and reflects our strengths and tradition of excellence of research in Data Science, Economics, Management, Law and Social Sciences. Through their academic research, the 160 Research Professors at ESSEC improve society's understanding of the profound transformations caused by the advancement of science. They all prove everyday that social, economic and management sciences play a key role in fostering scientific and human progress.

MULTIVARIATE VOLATILITY FORECASTS FOR STOCK MARKET INDICES

MULTIVARIATE VOLATILITY FORECASTS FOR STOCK MARKET INDICES

[ARTICLE] This study forecasts realized variance for major international stock market indices, incorporating jump, continuous, and option-implied variance components, using ...
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DYNAMICS OF VARIANCE RISK PREMIA: A NEW MODEL FOR DISENTANGLING THE PRICE OF RISK

DYNAMICS OF VARIANCE RISK PREMIA: A NEW MODEL FOR DISENTANGLING THE PRICE OF RISK

[ARTICLE] This paper presents a dynamic model for the variance risk premium that separates the continuous component from jump impacts, ...
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MINIMUM COST NETWORK DESIGN IN STRATEGIC ALLIANCES

MINIMUM COST NETWORK DESIGN IN STRATEGIC ALLIANCES

[ARTICLE] This paper investigates the impact of transaction costs on the viability of strategic alliances in service network design, highlighting ...
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PROBABILISTIC FORECASTING OF BUBBLES AND FLASH CRASHES

PROBABILISTIC FORECASTING OF BUBBLES AND FLASH CRASHES

[ARTICLE] This paper proposes a near explosive random coefficient autoregressive model (NERC) to predict probabilities of bubbles and crashes in ...
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DATA-CLONING SMC2: A GLOBAL OPTIMIZER FOR MAXIMUM LIKELIHOOD ESTIMATION OF LATENT VARIABLE MODELS

DATA-CLONING SMC2: A GLOBAL OPTIMIZER FOR MAXIMUM LIKELIHOOD ESTIMATION OF LATENT VARIABLE MODELS

[ARTICLE] This paper proposes a data-cloning SMC2 algorithm for maximum likelihood estimation of models with latent variables, offering broad applicability ...
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FROM DATA TO CAUSES II: COMPARING APPROACHES TO PANEL DATA ANALYSIS

FROM DATA TO CAUSES II: COMPARING APPROACHES TO PANEL DATA ANALYSIS

[ARTICLE] This article compares various panel data methods, highlighting the benefits of the general cross-lagged model (GCLM) over static models ...
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FROM DATA TO CAUSES I: BUILDING A GENERAL CROSS-LAGGED PANEL MODEL (GCLM)

FROM DATA TO CAUSES I: BUILDING A GENERAL CROSS-LAGGED PANEL MODEL (GCLM)

[ARTICLE] This paper introduces a general cross-lagged panel model (GCLM) for causal inference with longitudinal panel data within a structural ...
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THE USE OF PROTOTYPES TO BRIDGE KNOWLEDGE BOUNDARIES IN AGILE SOFTWARE DEVELOPMENT

THE USE OF PROTOTYPES TO BRIDGE KNOWLEDGE BOUNDARIES IN AGILE SOFTWARE DEVELOPMENT

[ARTICLE] This paper explores how software prototypes function as boundary objects in agile development, identifying four effective prototype use practices ...
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