Signalling the Dotcom bubble: a multiple changes in persistence approach

This study investigates multiple changes in persistence in the dividend-price and price-earnings ratio of the NASDAQ composite index. Recent time series methods that are capable of signalling and dating asset price bubbles are employed, in particular the method developed by Leybourne et al. (2007). The method allows for breaks between periods in which the data are integrated of order zero I(0) and integrated of order one I(1). The results confirm the existence of the so-called Dotcom bubble with its start and end dates. Furthermore, an unexpected negative bubble was also identified, extending from the beginning of the 1970s to the beginning of the 1990s, suggesting that the NASDAQ stock prices were below their fundamental values as indicated by their dividend yields, finding not previously reported in the literature. As the tools used by regulators take considerable time to take effect, methods capable of picking up warnings signals of the start of a bubble could be very useful. We conjecture that the methodology can also be applied to study recent phenomena in real estate, commodity and foreign exchange markets

The Impact of Sampling Frequency and Volatility Estimators on Change-Point Tests

The paper evaluates the performance of several recently proposed change-point tests applied to conditional variance dynamics and conditional distributions of asset returns. These are CUSUM-type tests for beta-mixing processes and EDF-based tests for the residuals of such nonlinear dependent processes. Hence the tests apply to the class of ARCH and SV type processes as well as data-driven volatility estimators using high-frequency data. It is shown that some of the high-frequency volatility estimators substantially improve the power of the structural breaks tests especially for detecting changes in the tail of the conditional distribution. Similarly, certain types of filtering and transformation of the returns process can improve the power of CUSUM statistics. We also explore the impact of sampling frequency on each of the test statistics. Ce papier évalue la performance de plusieurs tests de changement structurel CUSUM et EDF pour la structure dynamique de la variance conditionelle et de la distribution conditionnelle. Nous étudions l'impact 1) de la fréquence des observations, 2) de l'utilisation des données de haute fréquence pour le calcul des variances conditionnelles et 3) de transformation des séries pour améliorer la puissance des tests.Change-point tests, CUSUM, Kolmogorov-Smirnov, GARCH, quadratic variation, power variation, high-frequency data, location-scale distribution family, tests de changement structurel, CUSUM, Kolmogov-Smirnov, GARCH, variation quadratique, 'power variation', données de haute fréquence

Persistence Changes Test for Heavy Tail Series in the Presence of Index Breaks

In this paper we consider the effect of persistence change test when the series exist an index change point at the moment. It is shown that under the null hypothesis that the circumstance of the series only existed an index change point, if the heavy tail index  change from large to small, the statistics is diverging at a rate of , and the larger of the  is, the faster the divergence is. If the index change from small to large, the statistics converges to the bounded constant. The numerical simulation shows that no matter how the change of  will lead to the size distortions, and the size distortions shows more serious when k1 > k2.

Official Interventions and Occasional Violations of Uncovered Interest Parity in the Dollar-DM Market

This paper presents a model of exchange rate determination in which the forward premium anomaly emerges as the result of unanticipated central bank interventions in the foreign exchange market. Deviations from uncovered interest parity (UIP) therefore represent neither unexploited profit opportunities nor compensation for bearing risk. In simulations, the model generates a forward premium anomaly and matches several other notable features of US-German data. Additional empirical support is obtained from an analysis of Fed and Bundesbank interventions in the dollar—DM market where it is found that the forward premium anomaly intensifies during those times when a central bank intervenesForward premium anomaly, foreign exchange intervention

Mixed normal conditional heteroskedasticity

Both unconditional mixed-normal distributions and GARCH models with fat-tailed conditional distributions have been employed for modeling financial return data. We consider a mixed-normal distribution coupled with a GARCH-type structure which allows for conditional variance in each of the components as well as dynamic feedback between the components. Special cases and relationships with previously proposed specifications are discussed and stationarity conditions are derived. An empirical application to NASDAQ-index data indicates the appropriateness of the model class and illustrates that the approach can generate a plausible disaggregation of the conditional variance process, in which the components' volatility dynamics have a clearly distinct behavior that is, for example, compatible with the well-known leverage effect. Klassifikation: C22, C51, G1

Debunking in a World of Tribes

Recently a simple military exercise on the Internet was perceived as the beginning of a new civil war in the US. Social media aggregate people around common interests eliciting a collective framing of narratives and worldviews. However, the wide availability of user-provided content and the direct path between producers and consumers of information often foster confusion about causations, encouraging mistrust, rumors, and even conspiracy thinking. In order to contrast such a trend attempts to \textit{debunk} are often undertaken. Here, we examine the effectiveness of debunking through a quantitative analysis of 54 million users over a time span of five years (Jan 2010, Dec 2014). In particular, we compare how users interact with proven (scientific) and unsubstantiated (conspiracy-like) information on Facebook in the US. Our findings confirm the existence of echo chambers where users interact primarily with either conspiracy-like or scientific pages. Both groups interact similarly with the information within their echo chamber. We examine 47,780 debunking posts and find that attempts at debunking are largely ineffective. For one, only a small fraction of usual consumers of unsubstantiated information interact with the posts. Furthermore, we show that those few are often the most committed conspiracy users and rather than internalizing debunking information, they often react to it negatively. Indeed, after interacting with debunking posts, users retain, or even increase, their engagement within the conspiracy echo chamber

Test for Breaks in the Conditional Co-Movements of Asset Returns

We propose procedures designed to uncover structural breaks in the co-movements of financial markets. A reduced form approach is introduced that can be considered as a two stage method for reducing dimensionality of multivariate heteroskedastic conditional volatility models through marginalization. The main advantage is that one can use returns normalized by volatility filters that are purely data-driven and construct general conditional covariance dynamic specifications. The main thrust of our procedure is to examine change-points in the co-movements of normalized returns. We document, using a ten year period of two representative high frequency FX series, that regression models with non-Gaussian errors describe adequately their co-movements. Change-points are detected in the conditional covariance of the DM/US$and YN/US$ normalized returns over the decade 1986-1996.change-point tests, conditional covariance, high-frequency financial data, multivariate GARCH models

"Infinite-variance, Alpha-stable Shocks in Monetary SVAR: Final Working Paper Version"

This paper adumbrates a theory of what might be going wrong in the monetary SVAR literature and provides supporting empirical evidence. The theory is that macroeconomists may be attempting to identify structural forms that do not exist, given the true distribution of the innovations in the reduced-form VAR. The paper shows that this problem occurs whenever (1) some innovation in the VAR has an infinite-variance distribution and (2) the matrix of coefficients on the contemporaneous terms in the VAR's structural form is nonsingular. Since (2) is almost always required for SVAR analysis, it is germane to test hypothesis (1). Hence, in this paper, we fit a-stable distributions to VAR residuals and, using a parametric-bootstrap method, test the hypotheses that each of the error terms has finite variance.Vector Autoregression; Levy-stable Distribution; Infinite Variance; Monetary Policy Shocks; Heavy-tailed Error Terms; Factorization; Impulse-Response Function