This paper focuses on two methods for optimum portfolio selection. We compare Mean-Variance method with Mean-VaR method by the means of investment simulation, based on Czech financial market data from turbulent market periods of the year 2007 and the year 2008. We compare both strategies, basing...

This paper investigates investment performance of microfinance investment funds. The examined funds have recorded lower total risk than global stocks and bonds (measured by four benchmark indices) with moderate but stable returns. The analysis revealed that investment in microfinance investment...

Investors reveal a tendency to prefer domestic over foreign equities despite the financial losses. From institutional perspective the factors that cause home biasness are the barriers to entry the foreign markets, transaction costs, illiquidity, asymmetric information and information costs,...

Equity home bias is a situation on equity market where domestic investors prefer invest too much into domestic equities despite the possible gains from diversification into foreign equities. Equity home bias can arise as a result of institutional or behavioral factors. In this paper I will...

This paper deals with the risk management of savings accounts. Savings accounts are non-maturing accounts bearing a relatively attractive rate of return and two embedded options: a customer's option to withdraw money at any time and a bank's option to set the deposit as it wishes. The risk...

Cryptoassets, particularly Bitcoin, have attracted the attention of institutional investors during the latest price rallies of 2020 and 2021. The need for cryptoassets apart from Bitcoin in their portfolios is mostly unexplored in the current literature, and the general perception of...

This article presents a new approach for building robust portfolios based on stochastic efficiency analysis and periods of market downturn. The empirical analysis is done on assets traded on the Brazil Stock Exchange, B3 (Brasil, Bolsa, Balcão). We start with information on the assets from...

We develop a four-factor model intended to capture size, value, and credit rating transition patterns in excess returns for a panel of predominantly mid- and large-cap entities. Using credit transition matrices and rating histories from 48 US issuers, we provide evidence to support a...

We study the role of the choice of a fundamental database on the portfolio returns of a set of 74 fundamental anomalies. We benchmark Compustat by comparing it to Datastream in the US and find systematic differences in the raw financial statements across the databases. These differences only...

We examine the predictability of expected stock returns across horizons using machine learning. We use neural networks, and gradient boosted regression trees on the U.S. and international equity datasets. We find that predictability of returns using neural networks models decreases with longer...