We present a hybrid model for diagnosis and critical time forecasting of real estate bubbles. The model combines two … that the model is able to forecast the end of the bubbles and to identify variables highly relevant during the bubble …

We develop a methodology for detecting asset bubbles using a neural network. We rely on the theory of local martingales … the current estimator, obtaining an improved detection of bubbles. We show the outperformance of our algorithm over the … and build a zero net exposure trading strategy that exploits the risky arbitrage emanating from the presence of bubbles in …

We introduce a novel quantitative methodology to detect real estate bubbles and forecast their critical end time, which … calibration with respect to bootstrapped residuals. We make three main contributions to the literature of real estate bubbles … critical times of historical housing price bubbles in the U.S., Hong Kong, U.K. and Canada. Second, the LPPLS detection methods …

retaining the exponential affine structure of previous approaches, our model allows for an arbitrary number of cointegration … relationships. We show that the cointegration component allows capturing well-known features of commodity prices, i.e., upward … provide compelling evidence of cointegration in the data. Implications for the prices of futures and options written on common …

price dynamics with recurring bubbles in all treatments …

We present a self-consistent model for explosive financial bubbles, which combines a mean-reverting volatility process … correctly identifies the bubbles ending in Oct. 1987, in Oct. 1997, in Aug. 1998 and the ITC bubble ending on the first quarter … diagnostic for the duration of bubbles: applied to the period before Oct. 1987 crash, there is clear evidence that the bubble …