This paper examines the high frequency multiscale relationships and nonlinear multiscale causality between Bitcoin, Ethereum, Monero, Dash, Ripple, and Litecoin. We apply nonlinear Granger causality and rolling window wavelet correlation (RWCC) to 15 min-data. Empirical RWCC results indicate...

Cryptocurrency markets exhibit periods of large, recurrent arbitrage opportunities across exchanges. These price deviations are much larger across than within countries, and smaller between cryptocurrencies, highlighting the importance of capital controls for the movement of arbitrage capital....

This paper aims to find the effectiveness of Cryptocurrency on well-formed portfolio with assets like Commodities, Exchange Traded Fund (ETFs), Stock assets and currency value of INR. There are several ways to determine the effectiveness in diversification. In this paper we use SOLVER, Modern...

Since the launch of Bitcoin in 2009, the spectacular rise and fall of cryptocurrencies and the underlying blockchain technology have attracted global attention. While the application of distributed ledger technology presents great economic and business potential, significant volatility and...

This paper documents and characterizes the time-varying structure of U.S. and international asset co-movements. Although some of the time variation could be genuine, the sampling uncertainty and time series properties of the series can distort significantly the underlying signal dynamics. We...

This paper studies intraday time-series momentum (ITSM) in an international setting by employing high-frequency data of 16 developed markets. We show that ITSM is economically sizable and statistically significant both in- and out-of-sample in most countries. Based on existing theories of...

A novel dynamic asset-allocation approach is proposed where portfolios as well as portfolio strategies are updated at every decision period based on their past performance. For modeling, a general class of models is specified that combines a dynamic factor and a vector autoregressive model and...

In this work we focus on the application of wavelet-based methods in volatility modeling. We introduce a new, wavelet-based estimator (wavelet Whittle estimator) of a FIEGARCH model, ARCH-family model capturing long-memory and asymmetry in volatility, and study its properties. Based on an...