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It is well documented that firms that are neglected by analysts and large institutions provide superior investment performance. This paper studies whether that effect is caused by an upward bias in analyst earnings forecasts. The idea is that the more popular firms are the ones with the greatest earnings estimation bias. It was found that after controlling for earnings estimation bias the neglect effect was considerably weakened. However, it was also found that there was no relation between analyst following and earnings estimation bias.

Since the inception of modern portfolio theory, traditional asset classes have been the standard investment products for portfolio construction. With the introduction of cryptoassets such as cryptocurrencies, tokenized securities, smart contracts, and blockchain-based token assets, the crypto “revolution” has created a new asset class for consideration in a modern portfolio. This chapter explains cryptoassets in a portfolio, including their limitations and parameters as an asset class in a diversified portfolio. Finally, it reports an improvement in a new portfolio’s reward/risk ratio using the Sharpe ratio when adding cryptoassets to simulated equity, bonds, and real estate portfolios. A caveat is that a cryptoasset’s contribution to a well-diversified traditional portfolio differs from the performance of investing in a single and isolated cryptoasset.

The purpose of this study is to evaluate whether the classification of the equity mutual fund depends on the performance measure used.

The sample for this study includes stock mutual funds for the USA, Europe and emerging market economies covering the period 2010 to 2020. Using more than 20 performance measures the results are compared using the Sharpe ratio as the reference.

The results show that performance measures based on absolute reward–risk ratios like Sortino, Treynor, etc. have similar rankings, because in general the numerator (mean excess return) is the same. However, when the authors employ other types of performance measures, results may be significantly different, especially in the case of metrics for “incremental returns”, i.e. alphas. Focussing on markets, their results show that choosing performance measures is more relevant for emerging markets.

The sample is only limited to the USA, Europe and the emerging market, and there are other performance metrics in the literature which have not been covered in this work.

The ordering of equity mutual funds depends on the measure used, specially if investors employ factor models to measure excess returns (alphas). Hence, policy formulation on disclosure of mutual fund performance should encourage the use of several metrics from different families. Investors must be aware of the different rankings made and the most appropriate metrics based on their preferences.

This paper focusses specifically on the effect that performance metrics have on relative fund performance. Previous studies have ignored alpha metrics to rank funds, which are commonly employed by investors. The authors’ study performs an analysis for three different markets considering the two main developed ones (the American and European equity markets), as well as the emerging one, largely ignored until now.

This article urges executives to expand their view of risk. Instead of just defending against bad risk events, leading companies define and anticipate the upside risks that, when well managed, can deliver the maximum rewards. The discipline of strategic risk management allows firms to raise their growth potential in addition to reducing their economic volatility. The author shows executives how to avoid the biggest risk of all – not taking the right growth risks for the business. Businesses today are exposed to greater risks across the board, ranging from political risks to product liability and environmental hazard risks. There also are a set of strategic risks that have become increasingly disruptive. These include not just the obvious high‐probability risks that a new ad campaign or new product launch will fail, but other less‐obvious risks as well in areas such as technology and customer needs. Failure to anticipate and manage this spectrum of strategic risks can expose a company to dramatic decreases in shareholder value and severe swings in stock prices. In today’s risk‐intense environment, firms must manage their economic and risk profiles more actively. The goal is not to eradicate risk, but to deliver the maximum reward for an acceptable level of risk. The author addresses some of the most important forms of strategic risk and the countermeasures that can be used to address them.

Bitcoin’s introduction as the first cryptoasset in 2009 ushered in a new era, representing a seismic shift in the financial markets. Since then, this evolving asset class has generated much interest, excitement, and growth. This chapter begins by providing a brief background of cryptoassets. It then discusses their main types (cryptocurrencies, security tokens, and utility tokens), users (individual investors, major financial institutions, endowments, and hedge funds), and benefits and drawbacks. Next, it sets forth the book’s purpose, distinguishing features, intended audience, and structure. The chapter provides a synopsis of each of the remaining 21 chapters. Although no single book can encompass all changes and iterations of these technologies as they emerge in the marketplace, this book brings together a broad collection of industry expertise and academic analysis to create a book helpful to researchers, academics, and practitioners.

The literature on construction and project risk management published during the period from 1960 to 1997 is reviewed and analysed to identify trends and foci in research and practice. This analysis is used to identify gaps and inconsistencies in the knowledge and treatment of construction and project risk. The findings suggested that political, economic, financial and cultural categories of construction risk deserve greater research attention, as do those associated with quality assurance, and occupational health and safety. Temporal aspects of risk, and risk communication, are also important fields for investigation.

The purpose of this paper is to focus on the empirical dimension of financial integration among the five newest members of the European Monetary Union (Cyprus, Estonia, Malta, Slovakia and Slovenia) and the euro area. The main objective is to study the level and the speed of integration between the stock markets of those European Union (EU) member states and the rest of the euro area, assessing in this way the role that the EU enlargement, the drive towards European Monetary Union and the actual adoption of the euro play in the process of European financial market integration.

This study will exclusively test the integration of the stock markets of EU member states that joined in 2004, when the EU expanded, but are already members of Economic and Monetary Union (EMU). Since there is limited evidence on the effects of EU and EMU enlargements or their announcements, it will be a useful addition to the examination of this issue. Given the small size of those emerging stock markets and the fact that they are part of a stable and well-regulated system, the degree to which they are integrated has implications for investors' portfolio allocation decisions, as they may offer diversification benefits without extreme risks. The case of integration will be examined using various econometric methodologies, two of which (beta- and sigma-convergence) have been given less formal attention and their application is rare, so as to detect both long- and short-run interdependencies and achieve robust results.

The findings indicate an increasing degree of integration for Malta and Slovenia, while Estonia appears segmented. Cyprus and Slovakia exhibited a degree of integration after their accession into EU but this trend changes after they adopted the euro. Overall, the integration process accelerated after the accession in the EU but EMU does not seem to have the same positive impact on it.

Compared with previous studies, the authors' apply the concept of beta- and sigma-convergence, a methodology that will help us identify the speed of integration. Moreover, the period under study includes the recent crisis: this allows us to see if the worsened economic environment has had effect on the level and speed of integration of the countries under study. In the end, it is worth noting that previous studies focused on either advanced markets or neighbouring countries or states with a common history. This alone can create a level of interdependence between the countries under study and bias the results. In this paper, the markets under study have almost nothing in common except their small size and the fact that they are members of the EMU.

In the search for alternative income-generating assets, the paper addresses the following question, one that the literature has yet to answer: what is a reasonable allocation, if any, to asset-backed securities within a 60–40% stock-bond balanced portfolio of mutual funds?

The authors apply the Black–Litterman model of Modern Portfolio Theory to test the efficacy of adding asset-backed securities to the classic 60–40% stock-bond portfolio of mutual funds. The authors use out-of-sample tests of one, three, five, and ten years to determine a reasonable asset allocation. The data are monthly and range from January 2000 through September 2021.

The statistical evidence indicates a modest reward-risk added value from the addition of asset-backed securities, as measured by the Sharpe “reward-to-variability” ratio, in holding periods of three, five, and ten years. Based on the findings, the authors conclude that a reasonable asset allocation for income-seeking, risk-averse investors who follow the classic 60%–40% stock-bond allocation is 8%–10%.

The findings apply to a stock-bond balanced portfolio of mutual funds. Other fund combinations could produce different results.

Investors and money managers can use the findings to improve portfolio performance.

For investors seeking higher income-generating securities in the current record-low interest rate environment, the authors determine a reasonable asset allocation range on asset-backed securities. This study is the first to provide such direction to these investors.

The authors apply their method to analyze which portfolios are capable of providing superior performance to those based on the Sharpe ratio (SR).

In this paper the authors illustrate the use of conditional copulas for identifying differences in alternative portfolio performance strategies. The authors analyze which portfolios are capable of providing superior performance to those based on the SR.

The results show that under the Gaussian copula, both expected tail ratio (ETR) and skewness-kurtosis ratio portfolios exhibit remarkably low correlations respecting the SR portfolio. This means that these two portfolios are different respecting the SR one. The authors also find that copulas which focus on either the upper tail (Gumbel) or the lower tail (Clayton) render significant differences. In short, the copula analysis is useful to understand what kind of equity-screening strategy based on its corresponding performance measure (PM) performs better in relation to the SR portfolio.

Copula methods for evaluating relative tail forecasting performance provide an alternative tool when forecast differences are very small or found non statistically significant through standard tests.

Our copula methods to evaluate models' performance differences are significant because when models' performance is rather similar, conclusions on statistical differences, can be defective as they may hinge on the subsample type or size used, leading to inefficient investment decisions. Our method based in copula is novel in this research topic.