Evaluating Stock and Bond Portfolio Allocations using CAPER and Tobin’s Q
By Jayanth Ganesan
I test whether an investor can increase the returns on their portfolio over the long-term by timing the market using measures of market value, such as the Tobin’s q ratio and the Cyclically Adjusted Price Earnings (CAPE or Shiller-CAPE). To test this proposition, I examine contrarian investor strategies proposed by Smithers and Wright (2000) and investor strategies based on different equity-fixed income combination portfolios. I seek to determine whether these strategies produce higher risk-adjusted returns than buy-and-hold equity strategies such as those proposed by Siegel (2014) for long-term portfolios. I also examine whether Siegel’s theory that stocks are better investment vehicles than bonds for investment horizons greater than 20 years. In my study, buy-and-hold portfolios composed of the S&P 500 have additional annualized returns of 1.5% than portfolios which reallocate funds in alternative securities based on CAPE and q thresholds. I conclude that for long-term investment horizons, an investor is unlikely to increase portfolio returns by reallocating funds to an alternative asset class when stocks are overvalued. However, I do not find that stocks are better investment vehicles compared to bonds as portfolio with bonds have a lower portfolio risk in my sample. I believe that the effectiveness q ratios for market timing is likely to be independent of how the q ratio is calculated. As suggested by Asness (2015), I find that portfolios that utilize both value and trend investing principles with CAPE and q may outperform portfolios that utilize only value-based market timing strategies. I conclude that CAPE and q based timing strategies are difficult to implement without detailed knowledge of future stock valuations.
Advisor: Edward Tower | JEL Codes: G11, G14 Tagged: Information on Market Efficiency, Investment Decisions, Portfolio Choice
Google Search Volume Index: Predicting Returns, Volatility and Trading Volume of Tech Stocks
By Rui Xu
This paper investigates the efficacy of using Google Search Volume Index (SVI), a publicly available tool Google provides via Google Trends, to predict stock movements within the tech sector. Relative changes in weekly search volume index are recorded from April 2004 to March 2015 and correlated with weekly returns, realized volatility and trading volume of 10 actively traded tech stocks. Correlations are drawn for three different time periods, each representing a different stage of the financial business cycle, to find out how Search Volume Index correlates with stock market movements in economic recessions and booms. Google SVI is found to be significantly and positively correlated with trading volume and weekly closing price across 2004 to 2015, and positively correlated with realized volatility from 2009-2015. There exists a positive correlation between weekly stock returns and SVI for half of the stocks sampled across all 3 periods. The regression model was a better fit before and during the recession, suggesting the possibility of stronger “herding” behavior during those periods than in recent years.
Advisor: Edward Tower | JEL Codes: G1, G14, G17 | Tagged: Analysis, Information, market efficiency, Stock Returns
Multiples Valuation and Abnormal Returns
By Joon Sang Yoon
I investigate whether three commonly used valuation multiples—the Price-to-Earnings Ratio, the EV-to-EBITDA multiple, and the EV-to-Sales multiple—can be used to identify mispriced securities. I find that multiples are successful in identifying mispricing in both the equal and value weighted portfolios relative to the One-Factor CAPM. I further find, after controlling for size and value effects, that the bulk of the abnormal returns are concentrated in smaller firms. Moreover, the Sales multiple seems to outperform the other two multiples in the equal weighted design. In the value weighted design, however, the P/E ratio outperforms the others.
Advisor: Per Olsson, Michelle Connolly | JEL Codes: G12, G14, M4 | Tagged: Equity Valuation, Long-run Abnormal Returns, Market Efficiency, Multiples Valuation
The Impact of Macroeconomic Surprises on Mergers & Acquisitions for Real Estate Investment Trusts
By John Battinelli and John Reid
This paper examines the impact of various macroeconomics and real estate specific surprises on M&A transactions involving Real Estate Investment Trust. The 2008 financial crisis drastically affected merger & acquisitions activity, especially within the real estate market. The number of M&A transactions involving Real Estate Investment Trusts were very volatile during this period of economic turmoil and it appeared that several economic factors contributed to changing patterns in M&A activity. Our study uses time series data to draw a connection between REIT-related M&A activity and quantifiable factors. From or results we find there to be a relationship between the macroeconomic environment and REIT-related M&A activity.
Advisors: Connel Fullenkamp, Kent Kimbrough, Marjorie McElroy,
JEL Codes: G10, G14, G34 | Tagged: Macroeconomic Surprises, Mergers & Acquisitions, Real Estate Investment Trust
Examination of Time-Variant Asset Correlations Using High-Frequency Data
By Mingwei Lei
Drawing motivation from the 2007-2009 global financial crises, this paper looks to further examine the potential time-variant nature of asset correlations. Specifically, high frequency price data and its accompanying tools are utilized to examine the relationship between asset correlations and market volatility. Through further analyses of this relationship using linear regressions, this paper presents some significant results that provide striking evidence for the time-variability of asset correlations. These findings have crucial implications for portfolio managers as well as risk management professionals alike, especially in the contest of diversification.
Advisor: George Tauchen | JEL Codes: G, G1, G10, G11, G14 | Tagged: Asset correlations, Diversification, Financial Crisis, High-Frequency Data, Market Volatility, Time-Variant Correlations, Time-Variant Volatility
Auctions as an Alternative to Book Building in the IPO Process: An Examination of Underpricing for Large Firms in France
By John Mekjian
A relevant factor in determining the quality of an initial public offering (IPO) mechanism is the level and variability of underpricing that occurs. The percentage difference between the IPO price and the closing price after one day of trading is a common way to define the “underpricing” of the stock. Although companies may value a small amount of positive underpricing, they certainly want this to be controlled. Both extreme positive and extreme negative underpricing are undesirable for a company. Building off of a paper that found a lower mean and variability of underpricing for firms that use the auction IPO mechanism as opposed to the book building IPO mechanism, this paper argues that auctions are not disadvantaged when only large firms are considered. Although this paper finds that the book building mechanism controls underpricing better than the auction mechanism, the advantage disappears when considering only large firms. This analysis is relevant because, aside from two companies, only small companies have used the auction IPO mechanism in the United States. Due to the lack of auction IPOs in the United States, this paper uses French data in its analysis. By showing that large firms using the auction mechanism are not disadvantaged when compared to large firms using the book building mechanism, this paper attempts to encourage large firms in the United States to consider using the auction method for their IPOs.
Advisor: James Roberts, Marjorie McElroy | JEL Codes: G12, G14, G20, G30 | Tagged: Auction, IPO, Underpricing
Taming the Dragon: The Modernization of the Chinese Equity Markets and its Effects on IPO Underpricing
By William Benesh
The extreme underpricing of Chinese Initial Public Offerings in the early days of the Chinese equity markets was reduced by several reforms instituted by the Chinese government from around 2000 to 2002. These reforms reduced 1-day returns on IPOs from 295% to 72%. The reforms reduced IPO underpricing by decreasing the inequality between IPO supply and demand. These reforms, while announced between 2000 and 2002, likely took until around 2004 to take full effect. In addition to inequality between supply and demand, other factors such as information asymmetry and government/quality signaling contributed to underpricing both before and after the reforms.
Advisors: Francesco Bianchi, Kent Kimbrough | JEL Codes: G14, G15, G28, G30 | Tagged: China, Initial Public Offerings, Regulation, Stock Markets, Underpricing
