Modern economics was born in the Marginal revolution and the Keynesian revolution. These
revolutions led to the emergence of fundamental concepts and methods in economic theory …

This paper gives an account of some of the recent work on structural breaks in time series
models. In particular, we show how procedures based on the popular cumulative sum …

Long-memory, or more generally fractal, processes are known to play an important role in
many scientific disciplines and applied fields such as physics, geophysics, hydrology …

In this study, we forecast the realized volatility of the S&P 500 index using the
heterogeneous autoregressive model for realized volatility (HAR-RV) and its various …

This study reconsiders the role of jumps for volatility forecasting by showing that jumps have
a positive and mostly significant impact on future volatility. This result becomes apparent …

Volatility has been one of the most active and successful areas of research in time series
econometrics and economic forecasting in recent decades. This chapter provides a selective …

In recent years, with the availability of high-frequency financial market data modeling
realized volatility has become a new and innovative research direction. The construction of …

Given that policy uncertainty shocks in the economic environment can exacerbate financial
market volatility and pose financial risks, this paper utilizes a smooth transition version of the …

Considering nonlinear and highly persistent dynamics of realized volatility, we introduce
Markov regime switching models to the Heterogeneous Autoregressive model of the …

Mathematical economics is a theoretical and applied science in which economic objects,
processes, and phenomena are described by using mathematically formalized language. In …