limiting behaviour of the statistic under a multivariate fads model and under a moderately explosive bubble process: these … linear predictability in the most recent period, for small and medium cap stocks. The main findings are not substantially …

limiting behaviour of the statistic under a multivariate fads model and under a moderately explosive bubble process: these … linear predictability in the most recent period, for small and medium cap stocks. The main findings are not substantially …

We propose an alternative Ratio Statistic for measuring predictability of stock prices. Our statistic is based on … actual returns rather than logarithmic returns and is therefore better suited to capturing price predictability. It captures … multiperiod portfolio gross returns. We apply our methodology to test the gross return predictability of various financial series. …

substantially improve both the statistical and economic out-of-sample performance of multivariate models for return predictability …

expectations equilibria, we argue that this carries over to the finite time “strict local martingale”-approach to bubbles. Our …At odds with the common “rational expectations” framework for bubbles, economists like Hyman Minsky, Charles … essential drivers for bubble phenomena and financial crises. Following this understanding that asset price bubbles are generated …

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 …

are common among them. Having established the conditions under which common bubbles are present within the class of mixed …