Risk Behavior, Country Governance, and Bank Stability in Pakistan

Keeping risk behavior and country governance in observation, this study has investigated the trends in financial stability for a sample of 22 commercial banks in Pakistan while controlling the effect of economic growth. Over the period of 2007 to 2016, the authors have applied OLS, FE, and RE regression methods to investigate which risk and governance factors are influencing the stability measures of the banks. It is found that financial stability in overall banks is affected by credit risk, operational risk, country risk, and financial crisis risk while control of corruption is also affecting ZROA in an adverse way.

Quantifying Economic Uncertainties and Risks in the Oil and Gas Industry

The present economic model is intended to provide an example of how to take into consideration risks and uncertainties in the case of a field that is developed with water injection. The risks and uncertainties are related, on one hand to field operations (drilling time, delays due to drilling problems, rig failures and materials supply, electric submersible pump [ESP] installations failures with the consequences of losing the well), and on the other hand, the second set of uncertainties are related to costs (operational expenditures-OPEX and capital expenditures-CAPEX, daily drilling rig costs), prices (oil, gas, separation, and water injection preparation), production profiles, and discount factor. All the calculations are probabilistic. The authors are intending to provide a comprehensive solution for assessing the business performance of an oil field development.

Market Pricing of Bank M&As and Efficiency in Europe

This study investigates the impact of bank mergers and acquisitions (M&As) on bank efficiency and how such efficiencies are expected to influence bank shareholder value upon merger announcements. It employs stochastic frontier analysis and event study methods along with regression analysis to account for the influences of pre-merger and post-merger efficiencies of bidders and targets in assessing their impact on bidder abnormal returns. Using data for a sample of large commercial bank M&As from 22 European countries, the authors find that bank bidders achieve short-term shareholder value gains from merger announcements, and this could be associated with the perceived efficiencies of bidders and targets. More generally, the evidence supports the view that bank profit efficiency has a positive influence on bidder returns from merger announcements, and therefore markets do take into account the importance of efficiency in value creation. This suggests that stock markets price operational efficiency of banks in predicting value gains from European Bank M&As.

Investigation of the Calendar Effect

This chapter aims to examine calendar anomaly in selected sample countries by using second-order stochastic dominance (SSD) approach. Day-of-the-week and month-of-the-year effects are analysed for a group of 5 developed and 5 developing country indexes to estimate efficient (inefficient) weekdays and months for the period between 1988 and 2016. Then, back-testing procedure is applied for each sample country to compare performance of index returns for 2017-2019 with the strategy arisen by estimation results. Findings suggest that Monday and Friday returns are inefficient and efficient respectively in all developing countries where different results obtained for developed ones. In monthly analysis, December returns found efficient in 8 indexes including S&P 500. However, October is inefficient for all indexes. Positive January effect seems disappeared in most cases. Back-testing results indicate that in a bearish market condition SSD strategy outperforms index returns in general for daily and monthly comparison.

Evaluating the Efficiency of Portfolio-Hedging Strategies by Incorporating Third Degree Stochastic Dominance Criteria and Data Envelopment Analysis

The chapter investigates chosen hedging strategies with options as useful risk hedging instruments. Assuming that average investor prefers greater return, is risk-averse, and prefers greater positive skewness, the performance of different hedged and unhedged portfolios is evaluated using stochastic dominance (SD) criteria and data envelopment analysis (DEA). The SD is examined up to the third degree (TSD) using Davidson-Duclos (DD) test. In the DEA, a super efficiency BCC model is used. It is investigated how these two methodologies can be combined and how the TSD criteria can be integrated into DEA in order to simplify the analysis of determining efficient hedging strategies with options.

Coupon Bond Duration and Convexity Analysis

Coupon bond duration and convexity are the primary risk measures for bonds. Given their importance, there is abundant literature covering their analysis, with calculus being used as the dominant approach. On the other hand, some authors have treated coupon bond duration and convexity without the use of differential calculus. However, none of them provided a complete analysis of bond duration and convexity properties. Therefore, this chapter fills in the gap. Since the application of calculus may be complicated or even inappropriate if the functions in question are not differentiable (as indeed is the case with the bond duration and convexity functions), in this chapter the properties of bond duration and convexity functions by using elementary algebra only are proved. This provides an easier way of approaching this problem, thus making it accessible to a wider audience not necessarily familiar with tools of mathematical analysis. Finally, the properties of these functions are illustrated by using empirical data on coupon bonds.

Riesz Potential With Logarithmic Kernel in Generalized Hölder Spaces

The multidimensional Riesz potential type operators are of interest within mathematical modelling in economics, mathematical physics, and other, both theoretical and applied, disciplines as they play a significant role for analysis on fractal sets. Approaches of operator theory are relevant to researching various equations, which are widespread in financial analysis. In this chapter, integral equations with potential type operators are considered for functions from generalized Hölder spaces, which provide content terminology for formalizing the concept of smoothness, briefly described in the presented chapter. Results on potentials defined on the unit sphere are described for convenience of the analysis. An inverse operator for the Riesz potential with a logarithmic kernel is carried out, and the isomorphisms between generalized Hölder spaces are proven.

Evaluation of Alternative Approaches in Classification Algorithms for Prediction of Stock Market Index

This chapter tackles the problem of automatic recognition of favorable days for intra-day trading. The problem is modeled as a binary classification problem, and several approaches are tested for solving it. Croatian stock index CROBEX data is used and 22 technical indicators are calculated as predictor variables. Performance of five classifiers is evaluated and compared by using Cohen's kappa as evaluation metric: artificial neural network, support network machine, random forest, k-nearest neighbors, and naïve Bayes classifier. The results give insight to effectiveness of technical analysis in predicting the day favorability for CROBEX index and suggest that technical analysis makes sense and might work for this case.

Financial Linkages and Shock Spillovers in the Countries of Central, Eastern, and South-Eastern Europe

At the start of the third decade of the 21st century, the countries of Central, Eastern, and South-Eastern Europe (CESEE) are still lagging behind ‘old' EU Member States in regards to various macroeconomic and social indicators. This is particularly evident when considering the development of the financial sector, especially the non-banking part. This chapter focuses on the stock markets of eleven CESEE countries and analyzes potential macroeconomic factors that contribute to explaining the dynamics of real equity prices. To account for cross-country linkages and potential spillovers, global vector autoregressive (GVAR) methodology is applied. The estimated impact elasticities enabled the pinpointing of CESEE countries with stronger linkages to foreign stock markets. Generalized impulse response functions indicated the existence of statistically significant spillovers, the strongest spillovers coming from the German stock market. The empirical results also showed spillovers from CESEE countries' stock markets, bond markets, as well as from real shocks.

Selected Applications of Grey Models in Stock Price Prediction

This chapter examines the possibilities of utilizing the results of Grey Models (GM) in the portfolio selection. Namely, stock price prediction represents one of the most important steps in the portfolio management. Many different models and methods have been developed for this purpose over the decades. The GM models could be utilized for such purpose. However, this approach is still relatively unknown today although research in the Far East has shown that applications of GM approach have good forecasting capabilities. That is why this chapter aims to popularize the GM approach of modeling stock prices and to combine the estimation results with the portfolio performance measurement. The benefits of using GM models within the portfolio management are empirically confirmed using daily data on the stock market index CROBEX from Zagreb Stock Exchange during the period from September 2, 2019, until February 7, 2020. The GM(2,1) model is the best performing one with respect to out of sample forecasts and based on portfolio performance measures important to the investor.