Market Dynamics and the Forward Premium Anomaly: A Model of Interacting Agents
By Phillip Hogan and Evan Myer
This paper presents a stochastic model of exchange rates, which is used to explain the forward premium anomaly. In the model, agents switch between four trading strategies, and these changes drive the evolution of the exchange rate. This framework is meant to more realistically represent the important market dynamics of exchange rates, as we suspect these to be the cause of the forward premium anomaly. Our simulations of the model indicate two conclusions: (i) many of the statistical regularities observed in currency markets, including the forward premium anomaly, can be thought of as macro-level scaling laws emerging from micro-level interactions of heterogeneous agents, and (ii) the dynamics of estimates of the beta coefficient in tests of UIP are driven by perceived relationships between changes in interest rates and agents’ aggregate views on the value of the exchange rate, which we call the fundamental value. Section I presents an introduction to the topic and section II reviews the relevant literature. Section III provides the theoretical basis of the forward premium anomaly and our model, then the mathematical definition of the model. Section IV presents the results of a typical simulation which section V compares to relevant stylized facts of the currency markets. Sections VI and VII present our results and a conclusion of what we have drawn from the model.
Advisor: Craig Burnside, Michelle Connolly | JEL Codes: G1, G13, G15 | Tagged: Exchange Rates, Forward Premium Anomaly
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
Variance Risk Premium Dynamics: The Impact of Asset Price Jumps on Variance Risk Premia
By Jackson Pfeiffer
This paper utilizes the high-frequency stock price data and the corresponding daily option price data of several highly capitalized corporations in order to investigate the impact that asset price jumps of individual equities have on the equities’ respective variance risk premia. The findings of this paper describe many characteristics of the variance risk premia of individual equities, supporting some expectations of the characteristics, and refuting others. In the process of investigating these characteristics, this paper proposes a simple estimator for the market price of the variance risk of an individual equity.
Advisor: George Tauchen | JEL Codes: G1, G19, G11 | Tagged: Variance Risk, Variance Swaps, Price Jumps
Enhanced versus Traditional Indexation for International Mutual Funds: Evaluating DFA, Wisdom Tree and RAFI PowerShares
By Heehyun Lim
This paper uses stye analysis to compare the performance of traditional international index funds and enhanced international index funds. It attempts to measure the value added beyond classic indexation by the consideration of fundamentals. By employing Sharpe’s style analysis, I formulate a synthetic portfolio composed of DFA traditional funds to imitate each enhanced index fund portfolio’s performance. Then I compare the return and volatility of each portfolio. The result shows that half of enhanced fund portfolios tested in the paper outperforms their traditional synthetic portfolio, while the other half under-perform.
Advisor: Edward Tower | JEL Codes: G11, G15 | Tagged: Enhanced Index Fund, Fundamental, Indexation, Style Analysis
The Predictability of the Chilean Yield Spread as an Economic Indicator
By Yunze Chen
“Don’t forget that your incredible success in consistently making each move at the right time in the market is but my pathetic failure in making each move at the wrong time. … … I don’t know anyone who can do it successfully, nor anyone who has done so in the past. Heck, I don’t even know anyone who knows anyone who has timed the market with consistent, successful, replicable results.” (John Bogle, quoted in The Finance Buff, 2011).
John C. Bogle, the founder of the Vanguard Group, has long insisted on the superiority of index funds over actively managed mutual funds and the foolishness of attempts to time the market. He published two articles in the Journal of Portfolio Management showing that in eight out of nine style categories, managed mutual funds had lower risk-adjusted returns than the corresponding indexes did. While this demonstrates the failure of stock picking by mutual funds to serve investors well, it says nothing about their ability to time the market by changing styles. Managers of asset allocation funds often use a flexible combination of stocks, bonds, and cash; some, but not all, shift assets frequently based on analysis of business-cycle trends. To test his view of market timing, we evaluated the returns of 82 major asset allocation funds by comparing them with the returns of corresponding baskets of Vanguard’s index funds over a 13-year time span. We find that on average the index funds have higher risk-adjusted returns. We conclude that “simplicity is the ultimate sophistication” applies to mutual fund investments.
Advisor: Edward Tower | JEL Codes: G10, G11, G20 | Tagged: Expense Ratio, Mutual fund families, Performance
Simultaneous Occurrence of Price Jumps and Changes in Diffusive Price Volatility
By Shunting Wei
This paper uses high frequency financial data to study the changes in diffusive stock price volatility when price jumps are likely to have occurred. In particular, we study this effect on two levels. Firstly, we compare diffusive volatility on jump and non-jump days. Secondly, we study the change in diffusive volatility in local windows before and after 5-minute intervals on which price jumps are likely to have occurred. We find evidence that market price jumps occur simultaneously with a change in diffusive volatility with negative dependence in the direction of the jump and the volatility change. However, a similar relationship is not detectable in individual stock price data.
Advisor: George Tauchen | JEL Codes: C22, G1, G19 | Tagged: Diffusive Volatility, Jump Tests, Realized Volatility, Stock Price Jumps
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
Relative Contribution of Common Jumps in Realized Correlation
By Kyu Won Choi
This paper studies common intraday jumps and relative contribution of these common jumps
in realized correlation between individual stocks and market index, using high-frequency price
data. We find that the common jumps significantly contribute in realized correlation at different
threshold cut-offs and both common jumps and realized correlation are relatively consistent across
time period including financial crisis. We also find a weak, positive relationship between relative
contribution of common jumps and realized correlation, when we further sample high-frequency
data into a year. We also observe that the volatility index and market index reveal the strongest
relationship.
Advisor: Geourge Tauchen, Tim Bollerslev | JEL Codes: C40, C58, G10 | Tagged: Diffusive Covariation, Realized Correlation, Relative Contribution of Common Jumps
Motivation and Reasoning Behind Chinese Enterprises Overseas Listing
By Sjing Liang and Xiao Chen
Starting from the early 90s, the number of Chinese firms going public overseas has been increasing rapidly. By running a probit regression, this paper investigates the different factors that affect a Chinese firm’s choice of listing location, either a domestic or a foreign stock exchange. Our data consists of 286 foreign listed companies and 788 domestically listed ones that went public between 2005 and the first quarter of 2011. Our results reveal that, larger firms, in terms of their pre-IPO revenue values, are more likely to go public overseas. In addition, firms in high-tech and capital-intensive industries, namely technology, financials, and real estate, are better represented in overseas markets. We also find that stock markets with lower underpricing levels are more attractive to Chinese firms, who tend to avoid capital markets with high underpricing levels as they do not want to be undervalued at their IPOs.
Advisor: Alon Brav, Edward Tower, Kent Kimbrough | JEL Codes: G10, G15 | Tagged: Chinese Enterprises, Initial Public Offerings, Oversea Listing, Stock Markets
Volatility and Correlation Modeling for Sector Allocation in International Equity Markets
By Melanie Fan and Kate Yuan
Reliable estimates of volatility and correlation are crucial in asset allocation and risk management. This paper investigates Static, RiskMetrics, and Dynamic Conditional Correlation (DCC) models for estimating volatility and correlation by testing them in an asset allocation context. Optimal allocation weights for one year found using estimates from each model are carried to the subsequent year and the realized Sharpe ratio is computed to assess portfolio performance. We also study cumulative risk-adjusted returns over the entire sample period. Our ndings indicate that DCC does not consistently have an advantage over the other two models, although it is optimal in certain scenarios.
Advisor: Aino Levonmaa, Emma Rasiel | JEL Codes: C32, C51, G11, G15 | Tagged: Asset Allocation, Dynamic Correlation, Emerging Markets, Volatilita
