With the exception of Bitcoin, there appears to be little or no literature on GARCH modelling of cryptocurrencies. This paper provides the first GARCH modelling of the seven most popular cryptocurrencies. Twelve GARCH models are fitted to each cryptocurrency, and their fits are assessed in terms...

We analyze statistical properties of the largest cryptocurrencies (determined by market capitalization), of which Bitcoin is the most prominent example. We characterize their exchange rates versus the U.S. Dollar by fitting parametric distributions to them. It is shown that returns are clearly...

With the exception of Bitcoin, there appears to be little or no literature on GARCH modeling of cryptocurrencies. This paper provides the first GARCH modeling of the seven most popular cryptocurrencies. Twelve GARCH models are fitted to each cryptocurrency and their fits are assessed in terms of...

This paper studies a dynamic market microstructure model, in which a strategic market maker competes with an informed trader. We include the presence of noise traders and limit order traders in our setup. Our model is a N-period model. We give necessary and sufficient conditions for an...

Convolutional neural networks (CNN) and long short-term memory (LSTM) networks have become a staple of sequence learning. Due to the well-established fact that financial time series data exhibit exceptionally noisy characteristics, capital market anomalies are virtually impossible to detect. We...

Monte Carlo simulation methods for the valuation of financial instruments have become a staple of empirical economic analysis. A specific focus is dedicated to the feasibility of the stock price losses and barrier options as well as the sensitivity of partial time barrier options in dependence...

Momentum trading strategies are thoroughly described in the academic literature and used in many trading strategies by hedge funds, asset managers, and proprietary traders. Baz et al. (2015) describe a momentum strategy for different asset classes in great detail from a practitioner's point of...

Since the early beginning of investing as it was commonly seen as a form of gambling for the rich and wealthy, the idea of Harry Markowitz was revolutionising the way of thinking and how portfolios should be constructed. However, today the traditional mean-variance portfolios are still not fully...

Is there an informational gain by training a Deep Reinforcement Learning agent for automated stock trading using other time series than the one to be traded? In this work, we implement a DRL algorithm in a solid framework within a model-free and actor-critic approach and learn it with 21 global...