This study examines the predictability of three major cryptocurrencies-bitcoin, ethereum, and litecoin-and the profitability of trading strategies devised upon machine learning techniques (e.g., linear models, random forests, and support vector machines). The models are validated in a period...

Volatility is a fundamental parameter for option valuation. In particular, real options models require project volatility, which is very hard to estimate accurately because there is usually no historical data for the underlying asset. Several authors have used a method based on Monte Carlo...

This paper proposes a new way to measure and deal with risk within the portfolio selection problem using a skewness/semivariance biobjective optimization framework. The solutions of this biobjective optimization problem allow the investor to analyse the efficient trade-off between skewness and...

Project volatility is an essential parameter for real options analysis, and it may also be useful for risk analysis. Many volatility estimation procedures only consider the volatility in the first year of the project. Others consider that different years may have different values of the project...

In this study we analyse the link between stock returns and results in national league matches for 13 clubs of six different European countries. We assume that the stock prices should only respond to the unexpected component of match results, and we use betting odds to separate the expected...

Most of the studies about the Foreign Exchange market (Forex) analyse the behaviour of currencies that are allowed to float freely (or almost freely), but some currencies are still bounded by bandwidths (either disclosed or undisclosed). In this paper, I try to find out whether two...

When a project either generates or suppresses traffic, fuel taxes and tolls should be considered in the cost-benefit analysis. In this paper we present a simple partial equilibrium model showing that under linear demand, if factor costs are the unit of account and transfer payments are netted...

Traditional approaches to the study of technical analysis (TA) often focus on the performance of a single indicator, which seems to fall short in scope and depth. We use a genetic algorithm (GA) to optimize trading strategies in the three major Forex markets, in order to verify the adequacy of...

This study examines the predictability of three major cryptocurrencies-bitcoin, ethereum, and litecoin-and the profitability of trading strategies devised upon machine learning techniques (e.g., linear models, random forests, and support vector machines). The models are validated in a period...