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EVENTS

RESEARCH

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 financial asset prices.

by Guillaume Chevillon, Marie Kratz (ESSEC Business School), Anurag Narayan Banerjee

We propose a near explosive random coefficient autoregressive model (NERC) to obtain predictive probabilities of the apparition and devolution of bubbles. The distribution of the autoregressive coefficient of this model is allowed to be centred at an O(T−α) distance of unity, with α ∈ (0, 1). When the expectation of the autoregressive coefficient lies on the explosive side of unity, the NERC helps to model the temporary explosiveness of time series and obtain related predictive probabilities. We study the asymptotic properties of the NERC and provide a procedure for inference on the parameters. In empirical illustrations, we estimate predictive probabilities of bubbles or flash crashes in financial asset prices.

[Please read the research paper here]

Research list
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 ...
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, ...
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 ...
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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