Robert W. McLeod

DSSALM: A decision support system for asset and liability management

Abstract The following paper discusses the development of a decision support system for asset and liability management (ALM) in financial institutions. The system utilizes historical data to develop algorithms that can forecast the amounts of these assets and liabilities. Simulation models are used to identify the crests and troughs of the primary interest rate, and to forecast interest rates for future cycles of interest. The outputs of the algorithms are utilized to calculate the gap position and interest rate risk of the institution. “What-if” analysis features are incorporated into the system to determine the favorable alternatives in changing market environments.

An Analysis of Nondeductible IRA Contributions and Roth IRA Conversions

On average investors have an income replacement rate of 64 percent of their pre-retirement income, which in many cases results in a lower tax rate in retirement. We analyze the impact of declining withdrawal tax rates on the choice between taxable mutual fund investments and nondeductible IRAs. The relative attractiveness of the taxable mutual fund option declines significantly when withdrawal tax rates decline. Converting existing IRAs to Roth IRAs is generally beneficial for investors who remain in the same tax bracket upon withdrawal. For short (long) time horizons and low (high) expected returns, the marginal value of conversion in 1998 is greater (less) than the marginal value of optimal conversion. For investors dropping into the 15 percent tax bracket, conversion is generally not beneficial unless the conversion is done optimally, the time horizon is long, and the expected return is high. Investors in the 15 percent tax bracket should convert existing IRA assets.

An expert system for financial ratio analysis

Financial analysis interprets a companys past and present financial health and predicts its future condition. Although company financial statements contain a wealth of information to support this analysis, their interpretation may be complicated. Experts in this field are limited. This research focuses on automating the current practice of financial ratio analysis to identify the various features that need to be incorporated into the system. This involves calculating the ratios, establishing the relationships between the ratios, determining the technique for accurately forecasting the financial statements and/or ratios, developing heuristics for analysing the ratios and providing a system for recommendations. A prototype expert system was then developed. The system is capable of performing five types of analysis: liquidity, leverage, turnover, profitability, and past performance. The output of the system is a list of conclusions and recommendations based on these analyses.

The risks of pension plans

Abstract This paper identifies and describes the risks to which the prospective pensioner is exposed. An understanding of the types of plans and the risks associated with each will assist the individual pensioner with making a proper analysis of the safety of his/her plan and acquaint the pensioner with the role of the Employee Retirement Income Security Act (ERISA) and the Pension Benefit Guaranty Corporation (PBCG) in safeguarding pension assets.

The effect of rule 12b-1 on bond fund expense ratios

This paper presents empirical evidence that bond mutual funds which have adopted the use of 12b-1 fees have not achieved the goal of lowering expense ratios. Using a model specific to bond funds, as opposed to generic models used in previous studies on equity funds, the analysis confirms that the 12b-1 fee is an additional cost borne by shareholders of the fund without any additional benefit. However, this cost as a percent of the net asset value of the fund has decreased from 1991 through 1994. This reduction coincides with the submission of a proposed rule change by the National Association of Security Dealers concerning maximum sales charges imposed by mutual funds on December 28, 1990 and the implementation of limits on 12b-1 fees which became effective in July of 1993.

Bad news bears: Effects of expected market volatility on daily tracking error of leveraged bull and bear ETFs

Purpose - – This study aims to look into how volatility significantly impacts the tracking error for daily-rebalanced leveraged bull and bear ETFs. Design/methodology/approach - – Using Morningstar return data and Chicago Board Options Exchange (CBOE) volatility index (VIX) data, the paper examines the daily tracking error for leveraged bull and bear ETFs. Tracking error is defined as the difference between the daily returns for a leveraged bull or bear ETF and the multiple of the daily return for that ETFs respective underlying benchmark index. Findings - – Changes in the market VIX of the CBOE have a significant and opposite effect on the daily returns for both leveraged bull and bear ETFs. Furthermore, these effects are more pronounced for bear ETFs than similarly leveraged bull ETFs. Research limitations/implications - – The sample period (June 19, 2006 to September 22, 2009) contains periods of extraordinarily high volatility. Considering that the VIX reached an all-time high during this period, the results may be time-period specific and may not translate to other time periods. Practical implications - – The implication is that market timing may be feasible for enhancing daily returns for both leveraged bull and bear ETFs. However, any specific timing strategies go beyond the scope of this paper. Originality/value - – In this study, the paper examined the effects of expected market volatility on the daily tracking error of leveraged bull and bear ETFs. Specifically, the paper performed multiple linear regression analysis using Morningstar return data for the ETFs and their underlying benchmark and CBOE VIX data. The findings suggest that market timing could be beneficial for increasing daily yields for leveraged and inverse ETFs.

RiskTRACK: the five-factor model for measuring risk tolerance

Purpose Currently, few academics agree on a standard and scientific way to measure risk tolerance. This paper aims to create a unique model for empirically measuring risk tolerance and to make a strong contribution to the growing literature in risk tolerance and risk management. Design/methodology/approach The authors use factor analysis and regression analysis to identify relevant factors for measuring risk tolerance. Findings The risk tolerance model is based on the acronymed model riskTRACK, which includes the five significant factors this paper identifies for measuring risk tolerance: traditional risk factor, reflective risk factor, allocation risk factor, capacity risk factor and knowledge risk factor. Research limitations/implications Uses for future research streams devoted to risk tolerance and risk management. Practical implications The results also have practical applications for the financial services industry, particularly risk management, portfolio management and financial planning. Originality/value In sum, this research expands previous research in risk tolerance and also adds to the growing literature in risk management. Once again, this paper is unique in that the authors develop a valid and reliable risk tolerance model based on five specific factors for measuring risk tolerance.

Performance of Dividend Exchange-Traded Funds during Bull and Bear Markets

This study investigates the performance of dividend exchange-traded funds (ETFs) during both bull and bear markets. The authors compare their performance to a proxy for the U.S. market as measured by the S&P 500 ETF (IVV). Using data from Morningstar Direct, they construct equally weighted portfolios of dividend ETFs and compute their absolute and risk-adjusted returns for the period 2004 through 2014. The study finds that dividend ETFs are much more expensive than IVV and are highly correlated with IVV. Over the entire period of study, the performance of the dividend ETF portfolio was marginally better than that of IVV; the portfolio marginally outperformed IVV during two bull markets (January 2004 to September 2007 and April 2009 to December 2014), but it also marginally underperformed IVV during the most recent bear market (October 2007 to March 2009), which means that dividend ETFs are more volatile than IVV. The sample period is limited because the first dividend ETF was created in late 2003. Investors in dividend ETFs, who were expecting to receive superior returns during volatile markets, would not have achieved the results that they anticipated.

An Empirical Examination of the Performance of Commodity Mutual Funds

The use of commodities to hedge inflation risk and diversify portfolios is generally thought to be an important consideration for portfolio management. Direct investment in commodities or commodity derivatives requires that investors have significant assets and/or expertise in these commodities or their respective derivatives markets. As an alternative to direct investment, investors in recent years have increasingly resorted to the use of commodity-based mutual funds. In this article we evaluate the performance, persistence, market timing, and selectivity of four categories of mutual funds whose returns are based on commodity prices. Our period of analysis begins with each fund’s inception and ends in December of 2012. Our results indicate that these funds have not been able to create positive alphas for their investors, have negative or insignificant performance persistence, and have no market timing ability. Some of the categories of funds, however, do exhibit some selectivity. We did find that when these commodity-based funds’ performance was evaluated during specific time periods of market downturns (e.g., the 2000 stock market downturn and the financial crisis that began in late 2007), their performance was significantly positive, which indicates that these funds provide a good hedge during bear markets/financial crises.

Sustainable competitive advantage and stock performance: the case for wide moat stocks

ABSTRACT ‘In business, I look for economic castles protected by unbreachable “Moats”’. Warren Buffett Companies that have sustainable competitive advantages should be able to create a barrier (Moat) to prevent or lessen competition from other firms. The wider the Moat the greater the barrier and the more secure the company’s profitability. Using the Morningstar classification of ‘Wide Moat’ stocks, we construct annually rebalanced equal- and value-weighted portfolios to analyse their performance in order to determine if they deliver superior performance relative to standard benchmark portfolios. The period for our analysis extends from June 2002 through May 2014. We find that the ‘Wide Moat’ portfolios outperform both the S&P 500 and Russell 3000 indices generating higher average monthly and annualized returns, Sharpe Ratio, Sortino Ratio, Treynor Ratio, Omega Ratio, Upside Potential Ratio, M2, M2 Alpha, and cumulative returns. When we compute alpha using Carhart four-factor and Fama–French five-factor models, we find that ‘Wide Moat’ portfolios had significantly positive risk-adjusted alphas with both the models. ‘Wide Moat’ portfolios also lost less value during the 2007–2009 financial crisis compared to both S&P 500 and Russell 3000. In conclusion, we find that ‘Wide Moat’ stocks have created significant value for their investors over the course of our study.