Predictability is time and frequency dependent. We propose a new forecasting method - forecast combination in the frequency domain - that takes this fact into account. With this method we forecast the equity premium and real GDP growth rate. Combining forecasts in the frequency domain produces...

In this paper we augment the Bayesian unobserved components model of the EU Commission to estimate the cyclical component of total factor productivity (TFP gap) with a factor structure to include a wide array of business cycle indicators. We demonstrate that this model extension considerably...

This study investigates the relationship between investor sentiment and leading equity market indices from the U.S., Europe, Asia, and globally between January 2020 and June 2022. The results of wavelet coherence analysis highlighted that, at lower frequency bands, Google Search Volume moves in...

Wavelet power spectrum (WPS) and wavelet coherence analyses (WCA) are used to examine the co-movements among oil prices, green bonds, and CO2 emissions on daily data from January 2014 to October 2022. The WPS results show that oil returns exhibit significant volatility at low and medium...

We consider an observation-driven location model where the unobserved location variable is modeled as a random walk process and where the error variable is from a mixture of normal distributions. The mixed normal distribution can approximate many continuous error distributions accurately. We...

China has accelerated its banking sector reform in recent years, paying particular attention to non-performing loans (NPLs). The paper's scope is to analyse the relationship between NPLs and macroeconomic variables in China using quarterly data from 2008/Q1 to 2021/Q1 applying wavelet analysis,...

This study proposes a wavelet procedure for estimating partial correlation coefficients between stock market returns over different time scales. The estimated partial correlations are subsequently used in a cluster analysis to identify, for each time scale, groups of stocks that exhibit distinct...

In this paper, we estimate trend inflation in Sweden using an unobserved components stochastic volatility model. Using data from 1995Q4 to 2021Q4 and Bayesian estimation methods, we find that trend inflation has been well-anchored during the period - although in general at a level below the...

We conduct a Monte Carlo experiment using an ad-hoc New Keynesian model and a tractable agent-based model to generate artificial credit cycle episodes. We show that fluctuations in the implicit measures of the natural rate of interest obtained using a conventional trivariate Kalman filter on...

Using data from the Borsa İstanbul (BIST), this study analyzes whether derivatives market operations have a volatility spillover effect on stock indexes using multivariate GARCH models and wavelet methods. We use the DVECH method, with variables for the daily BIST 30 index and BIST 30 index...

This paper develops a novel and tractable empirical approach to estimate the cycle in schooling participation decisions, which we denominate the schooling cycle. The estimation procedure is based on unobserved components time series models that decompose higher education enrollment rates into a...

Climate change will potentially bring about important macroeconomic effects for all countries in the world and especially for emerging economies. I perform a counterfactual analysis to estimate the potential effect of global warming on the natural interest rate using a state-space...

During the past two decades, financial markets across the globe have experienced sporadic waves of crashes. Such waves raise concerns about the vulnerability of global financial markets and the transmission mechanisms of shocks beyond borders. The current study examines the co-movement of stock...

We examine the relationship between oil as a major export for the member countries of the Gulf Cooperation Council (GCC) and the forward levels of all GCC currencies using wavelet analysis. We find that oil and GCC forward markets have significant but weak relationships at high frequencies. We...

It is a widely known fact that the intraday seasonality of trading intervals for financial transactions such as stocks is short at the beginning of business hours and long in the middle of the day. In this paper, we extend the stochastic conditional duration (SCD) model to capture the pattern of...

We present a multi-scale and time-frequency analysis of the degree of integration and the lead-lag relationship between six cryptocurrencies (i.e., Bitcoin, Bitcoincash, Ethereum, Litecoin, Ripple, and Tether) and the cryptocurrency-implied volatility index (VCRIX). As a result, the wavelet...

Dynamic factor models (DFMs), which assume the existence of a small number of unobserved underlying factors common to a large number of variables, are very popular among empirical macroeconomists. Factors can be extracted using either nonparametric principal components or parametric Kalman...

The Central Bank of Algeria has announced a managed float of the Algerian dinar since 1994. Yet, there are some substantial differences between various de facto classifications of Algeria's exchange rate regime. This study looks into the exchange rate regime of Algeria, aiming to identify de...

A multivariate, non-Bayesian, regression-based, or feasible generalized least squares (GLS)-based approach is proposed to estimate time-varying VAR parameter models. Although it has been known that the Kalman-smoothed estimate can be alternatively estimated using GLS for univariate models, we...

Most factor-based forecasting models for the term structure of interest rates depend on a fixed number of factor loading functions that have to be specified in advance. In this study, we relax this assumption by building a yield curve forecasting model that learns new factor decompositions...

The present study analyses BRICS (Brazil, Russia, India, China, South Africa) capital markets in both time and frequency domain using wavelets. We used artificial neural network techniques to forecast the co-movement among BRICS capital markets. Wavelet coherence and clustering estimates uncover...

This study investigates the dynamic mechanism of financial markets on volatility spillovers across eight major cryptocurrency returns, namely Bitcoin, Ethereum, Stellar, Ripple, Tether, Cardano, Litecoin, and Eos from November 17, 2019, to January 25, 2021. The study captures the financial...

Assessing potential output and the output gap is essential for policy-making and fiscal surveillance. The European Commission proposes a production function methodology that involves the estimation of two classes of Gaussian state space models. This paper presents the R package RGAP which...

Among cryptocurrencies (CC), Bitcoin has received much attention in the media and by investors, although there remains skepticism and a lack of understanding of this cryptocurrency. Some studies have found strong evidence of long-memory (long range dependence (LRD)) characteristics in the...

Background and objectives: Atrial fibrillation (AF) is a common and extremely harmful arrhythmia disease that leads to stroke and death. Several kinds of AF exist as paroxysmal AF, persistent AF, and permanent or chronic AF. Based on electrocardiograms (ECG), wavelet transform (WT), and...

Improving the accuracy of cash flow forecasting in the TSA is the key to fulfilling government payment obligations, minimizing the cost of maintaining the cash reserve, providing the absence of outstanding debt accumulation, and ensuring investment in various financial instruments to obtain...

We propose a modified version of the augmented Kalman filter (AKF) to evaluate the likelihood of linear and time-invariant state-space models (SSMs). Unlike the regular AKF, this augmented steady-state Kalman filter (ASKF), as we call it, is based on a steady-state Kalman filter (SKF). We show...

In this paper, the relationship between some selected stocks in the Nigerian Capital Market was investigated using wavelet analysis. The selected stocks are Dangote Cement (Dans) representing the housing sector, Julius Berger (Jbger) representing the Construction industry, Nestle Nigerian Plc...

In this study, we apply the Kalman filter to estimate the set of reduced-form Phillips curves for different types of inflation in Ukraine. Based on the estimated models, we derive a number of series of non-accelerating inflation rate of unemployment (NAIRU) that provide information about the...

We examine the time-frequency lead-lag relationships and the degree of integration between the US financial stress index and global commodity prices (i.e., oil, gold, silver, and cocoa) with data covering over 47 decades (January 1975 to December 2021). For this purpose, we resort to the bi- and...