In this paper, we present new evidence on the profitability and statistical significance of technical trading rules in the foreign exchange market. We utilize a new data base, currency futures contracts for the period 1976-1990, and we implement a new testing procedure based on bootstrap...

In this paper, we introduce adjusted-range based Kolmogorov-Smirnov (KS) type statisticsto test for structural breaks in the mean of a process and also in a more general setting. We propose a normalization based on the adjusted-range of a partial sum, which is stochastically proportional to the...

This article considers model averaging in the class of the integer-valued autoregressive (INAR) processes. The INAR process is a class of structural models that can be used to model dependent count data in fields such as medicine, economics, finance and marketing. It specifies the data...

Inference and testing in general point process models such as the Hawkes model is predominantly based on asymptotic approximations for likelihoodbased estimators and tests, as originally developed in Ogata (1978). As an alternative, and to improve finite sample performance, this paper considers...

The outbreak of COVID-19 had disruptive effects on China, and in this moment, and is spreading all over the world. The spread of the virus had impacted strongly on global markets and, at the same time, have threatened economic growth. Time-series clustering helps detect the relevant...

This paper considers the problem of assessing the distributional consequences of a treatment on some outcome variable of interest when treatment intake is (possibly) non-randomized but there is a binary instrument available for the researcher. Such scenario is common in observational studies and...

In this paper we present a new asymptotically normal test for out-of-sample evaluation in nested models. Our approach is a simple modification of a traditional encompassing test that is commonly known as Clark and West test (CW). The key point of our strategy is to introduce an independent...