Explosive Behavior in the 1990s Nasdaq : When Did Exuberance Escalate Asset Values?

A recursive test procedure is suggested that provides a mechanism for testing explosive behavior, date-stamping the origination and collapse of economic exuberance, and providing valid conOdence intervals for explosive growth rates. The method involves the recursive im- plementation of a right-side unit root test and a sup test, both of which are easy to use in practical applications, and some new limit theory for mildly explosive processes. The test procedure is shown to have discriminatory power in detecting periodically collapsing bubbles, thereby overcoming a weakness in earlier applications of unit root tests for economic bubbles. An empirical application to Nasdaq stock price index in the 1990s provides conOrmation of ex- plosiveness and date-stamps the origination of Onancial exuberance to mid -1995, prior to the famous remark in December 1996 by Alan Greenspan about irrational exuberance in Onancial market, thereby giving the remark empirical content.Explosive root, irrational exuberance, Mildly explosive process, Nasdaq bubble, periodically collapsing bubble, sup test, unit root test

Explosive Behavior in the 1990s Nasdaq: When Did Exuberance Escalate Asset Values?

A recursive test procedure is suggested that provides a mechanism for testing explosive behavior, date-stamping the origination and collapse of economic exuberance, and providing valid con?dence intervals for explosive growth rates. The method involves the recursive im- plementation of a right-side unit root test and a sup test, both of which are easy to use in practical applications, and some new limit theory for mildly explosive processes. The test procedure is shown to have discriminatory power in detecting periodically collapsing bubbles, thereby overcoming a weakness in earlier applications of unit root tests for economic bubbles. An empirical application to Nasdaq stock price index in the 1990s provides con?rmation of ex- plosiveness and date-stamps the origination of ?nancial exuberance to mid -1995, prior to the famous remark in December 1996 by Alan Greenspan about irrational exuberance in ?nancial market, thereby giving the remark empirical content.Explosive root, irrational exuberance, mildly explosive process, Nasdaq bubble, periodically collapsing bubble, sup test, unit root test

Explosive Behavior in the 1990s Nasdaq: When Did Exuberance Escalate Asset Values?

A recursive test procedure is suggested that provides a mechanism for testing explosive behavior, date-stamping the origination and collapse of economic exuberance, and providing valid confidence intervals for explosive growth rates. The method involves the recursive implementation of a right-side unit root test and a sup test, both of which are easy to use in practical applications, and some new limit theory for mildly explosive processes. The test procedure is shown to have discriminatory power in detecting periodically collapsing bubbles, thereby overcoming a weakness in earlier applications of unit root tests for economic bubbles. An empirical application to Nasdaq stock price index in the 1990s provides confirmation of explosiveness and date-stamps the origination of financial exuberance to mid -1995, prior to the famous remark in December 1996 by Alan Greenspan about irrational exuberance in financial markets, thereby giving the remark empirical content.Explosive root, Irrational exuberance, Mildly explosive process, Nasdaq bubble, Periodically collapsing bubble, Sup test, Unit root test

Generalized Points-to Graphs: A New Abstraction of Memory in the Presence of Pointers

Flow- and context-sensitive points-to analysis is difficult to scale; for top-down approaches, the problem centers on repeated analysis of the same procedure; for bottom-up approaches, the abstractions used to represent procedure summaries have not scaled while preserving precision. We propose a novel abstraction called the Generalized Points-to Graph (GPG) which views points-to relations as memory updates and generalizes them using the counts of indirection levels leaving the unknown pointees implicit. This allows us to construct GPGs as compact representations of bottom-up procedure summaries in terms of memory updates and control flow between them. Their compactness is ensured by the following optimizations: strength reduction reduces the indirection levels, redundancy elimination removes redundant memory updates and minimizes control flow (without over-approximating data dependence between memory updates), and call inlining enhances the opportunities of these optimizations. We devise novel operations and data flow analyses for these optimizations. Our quest for scalability of points-to analysis leads to the following insight: The real killer of scalability in program analysis is not the amount of data but the amount of control flow that it may be subjected to in search of precision. The effectiveness of GPGs lies in the fact that they discard as much control flow as possible without losing precision (i.e., by preserving data dependence without over-approximation). This is the reason why the GPGs are very small even for main procedures that contain the effect of the entire program. This allows our implementation to scale to 158kLoC for C programs

Forecasting euro area inflation: Does aggregating forecasts by HICP component improve forecast accuracy?

Monitoring and forecasting price developments in the euro area is essential in the light of the second pillar of the ECB's monetary policy strategy. This study analyses whether the forecasting accuracy of forecasting aggregate euro area inflation can be improved by aggregating forecasts of subindices of the Harmonized Index of Consumer Prices (HICP) as opposed to forecasting the aggregate HICP directly. The analysis includes univariate and multivariate linear time series models and distinguishes between different forecast horizons, HICP components and inflation measures. Various model selection procedures are employed to select models for the aggregate and the disaggregate components. The results indicate that aggregating forecasts by component does not necessarily help forecast year-on-year inflation twelve months ahead. JEL Classification: E31, E37, C53, C32Euro Area Inflation, HICP subindex forecast aggregation, linear time series models

Hot Money Inflows and Monetary Stability in China: How the People's Bank of China Took up the Challenge

Non-foreign direct investment capital inflows in China were particularly strong in 2003 and 2004. They were even stronger than current account surpluses or net foreign direct investment inflows. As a result, the pace of international reserves accumulation in China increased significantly. This paper investigates if the rapid build up of international reserves in 2003 and 2004 was a source of monetary instability in China. The relationship between international reserves and domestic credit is examined with a Vector Error Correction Model (VECM), estimated on monthly data from March 1995 to December 2005. Empirical results show that this relationship was stable and consistent with monetary stability. Direct and indirect Granger causality tests are implemented to show how the People's Bank of China (PBC) achieved this monetary stabilityhot money inflows, international reserves, VECM, Granger causality

On nonparametric estimation of a mixing density via the predictive recursion algorithm

Nonparametric estimation of a mixing density based on observations from the corresponding mixture is a challenging statistical problem. This paper surveys the literature on a fast, recursive estimator based on the predictive recursion algorithm. After introducing the algorithm and giving a few examples, I summarize the available asymptotic convergence theory, describe an important semiparametric extension, and highlight two interesting applications. I conclude with a discussion of several recent developments in this area and some open problems.Comment: 22 pages, 5 figures. Comments welcome at https://www.researchers.one/article/2018-12-

Cross sectional efficient estimation of stochastic volatility short rate models

We consider the problem of estimation of term structure of interest rates. Filtering theory approach is very natural here with the underlying setup being non-linear and non-Gaussian. Earlier works make use of Extended Kalman Filter (EKF). However, the EKF in this situation leads to inconsistent estimation of parameters, though without high bias. One way to avoid this is to use methods like Efficient Method of Moments or Indirect Inference Method. These methods, however, are numerically very demanding. We use Kitagawa type scheme for nonlinear filtering problem, which solves the inconsistency problem without being numerically so demanding. \u