Gary van Vuuren

Increasingly, in the last decade, largely due to perceived greater shareholder pressures for more profitable performance, compensation maximization has taken center stage in some segments of the banking industry. Banks need to establish board governance committees with explicit responsibilities to monitor corporate ethics and culture. This paper aims to measure the correlation between dire economic conditions, competition, banking profitability, and misconduct. This is done by means of GDP comparisons to determine economic conditions, calculating z-scores to determine bank risk taking, and analysis of variance of return on assets, return on equity and z-scores, to determine profitability, and fines comparisons to determine misconduct. Analysis finds that dire economic conditions may lead to increased competition, increased competition may lead to increased risk taking, increased risk taking may have an impact on a bank’s financial performance, and decreased financial performance may lead to increase in misconduct.

Keywords: banking competition, banking behavior, economic conditions.
JEL Classification: C21, G01, G21, G32

The banking industry plays a significant role in both the financial system and economy as a whole. By 2012, the US banking system owned US $14.45 trillion in assets. However, the importance of the banking system stretches beyond its mere size. Numerous studies have indicated that the health of this sector has significant effects on overall economic activity, as well as the size and persistence of economic cycles. For the purposes of this paper, the researchers measured the correlation between current legislation, risk-taking, market value, and reputation. This was performed by calcula-ting Z-scores to determine bank risk-taking. The Z-scores were correlated to market value to determine its impact. Reputable firm behavior was used to determine the correlation between market value and reputation. The statistical package for Social Sciences was used to perform ANOVA analysis of share value and Z-scores. A literature review was conducted to determine the reputational impact. It was determined that current legislation might have a desired result on risk-taking, that risk-taking might not have an impact on market value, and that reputation might have an impact on market value.

Keywords: reputation, banking industry, financial system, economic activity, Z-scores, legislation, risk-taking.
JEL Classification: C21, G18, G21, G32, G38, K23

The investment nous of active managers is judged on their ability to outperform specified benchmarks while complying with strict constraints on, for example, tracking errors, β and Value at Risk. Tracking error constraints give rise to a tracking error frontier – an ellipse in risk/return space which encloses theoretically possible (but not necessarily efficient) portfolios. The β frontier is a parabola in risk/return space and defines the threshold of portfolios subject to a specified β requirement. An α - TE frontier is similarly shaped: portfolios on this frontier have a specified TE for a maximum TE. Utility and associated risk aversion have also been explored for constrained portfolios. This paper contributes by establishing the impossibility of satisfying more than two constraints simultaneously and explores the behavior of these constraints on the maximum risk-adjusted return portfolio (defined arbitrarily here as the optimal portfolio).

As a risk measure, Value at Risk (VaR) is neither sub-additive nor coherent. These drawbacks have coerced regulatory authorities to introduce and mandate Expected Shortfall (ES) as a mainstream regulatory risk management metric. VaR is, however, still needed to estimate the tail conditional expectation (the ES): the average of losses that are greater than the VaR at a significance level These two risk measures behave quite differently during growth and recession periods in developed and emerging economies. Using equity portfolios assembled from securities of the banking and retail sectors in the UK and South Africa, historical, variance-covariance and Monte Carlo approaches are used to determine VaR (and hence ES). The results are back-tested and compared, and normality assumptions are tested. Key findings are that the results of the variance covariance and the Monte Carlo approach are more consistent in all environments in comparison to the historical outcomes regardless of the equity portfolio regarded. The industries and periods analysed influenced the accuracy of the risk measures; the different economies did not.

Recent (2018) evidence identifies the increased need for active managers to facilitate the exploitation of investment opportunities found in inefficient markets. Typically, active portfolios are subject to tracking error (TE) constraints. The risk-return relationship of such constrained portfolios is described by an ellipse in mean-variance space, known as the constant TE frontier. Although previous work assessed the performance of active portfolio strategies on the efficient frontier, this article uses several performance indicators to evaluate the outperformance of six active portfolio strategies over the benchmark – subject to various TE constraints – on the constant TE frontier.

Behavioral components of Kahneman and Tversky’s (1979) prospect theory (PT) were applied to derive an adjusted Capital Asset Pricing Model (CAPM) in the estimation of merger and acquisition-intensive firms’ expected returns. The premise was that the CAPM – rooted in expected utility theory – is violated by the behavioral biases identified in prospect theory. Kahneman and Tversky’s prospect theory (1979) has demonstrated that weaknesses abound in the viability of classical utility theory predictions. For mergers and acquisitions, firms appear to be isolated from and immune to human error, yet decisions which involve the undertaking of capital-intensive projects are delegated to senior management. These individuals are prone to cognitive biases and personalized risk appetites that may (and often do) compromize attitudes and behavior when it comes to pricing risky ventures. Having established that beta estimates using linear regression are inferior, the CAPM was implemented utilizing beta estimates obtained from the Kalman filter. The results obtained were assessed for their long-term market price predictive accuracy. The authors test the reliability of the CAPM as a predictor of price, observe the rationality of human behavior in capital markets, and attempt to model premiums to adjust CAPM returns to a level that more appropriately accounts for firm specific risk. The researchers show that market participants behave irrationally when assessing M&A firms’ specific risk. Logistic regression coupled with the development of a risk premium was implemented to correct the original Kalman filter returns and was tested for improvements in predictive power.

The mean-variance framework coupled with the Sharpe ratio identifies optimal portfolios under the passive investment style. Optimal portfolio identification under active investment approaches, where performance is measured relative to a benchmark, is less well-known. Active portfolios subject to tracking error (TE) constraints lie on distorted elliptical frontiers in return/risk space. Identifying optimal active portfolios, however defined, have only recently begun to be explored. The Ω – ratio considers both down and upside portfolio potential. Recent work has established a technique to determine optimal Ω – ratio portfolios under the passive investment approach. The authors apply the identification of optimal Ω – ratio portfolios to the active arena (i.e., to portfolios constrained by a TE) and find that while passive managers should always invest in maximum Ω – ratio portfolios, active managers should first establish market conditions (which determine the sign of the main axis slope of the constant TE frontier). Maximum Sharpe ratio portfolios should be engaged when this slope is > 0 and maximum Ω – ratios when < 0.