Word-of-Mouth Effects in the Holdings and Trading Activities among Canadian Mutual Fund Managers
By Chang Liu
The study tests the word-of-mouth effects among mutual fund managers in Canada with methodology based on a previous study (Hong et al., 2005), with multiple modifications to it such as the method to locate the mutual fund managers. The results confirm the original findings yet with unexpected outcomes. This study demonstrates smaller word-of-mouth effects compared to the original study and reverse word-of-mouth effects in the largest financial city of Canada. The possible interpretations are further discussed in detail, among which a dynamic model of word-of-mouths effects and product differentiation is introduced. The study also discusses the market structure’s possible implications on such dynamic models.
Advisor: Jia Li | JEL Codes: G02, G15, G20, G21 | Tagged: Word-of-Mouth, Product Differentiation, Herding Behavior
Conditional Beta Model for Asset Pricing By Sector in the U.S. Equity Markets
By Yuci Zhang
In nance, the beta of an investment is a measure of the risk arising from exposure to general market movements as opposed to idiosyncratic factors. Therefore, reliable estimates of stock portfolio betas are essential for many areas in modern nance, including asset pricing, performance evaluation, and risk management. In this paper, we investigate Static and Dynamic Conditional Correlation (DCC) models for estimating betas by testing them in two asset pricing context, the Capital Asset Pricing Model (CAPM) and Fama-French Three Factor Model. Model precision is evaluated by utilizing the betas to predict out-of-sample portfolio returns within the aforementioned asset-pricing framework. Our findings indicate that DCC-GARCH does consistently have an advantage over the Static model, although with a few exceptions in certain scenarios.
Advisor: Andrew Patton, Michelle Connolly | JEL Codes: C32, C51, G1, G12, G17 | Tagged: Beta, Asset Pricing, Dynamic Correlation, Equity, U.S. Markets
Market Dynamics and the Forward Premium Anomoly: A Model of Interacting Agents
By Phillip Hogan
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
Market Dynamics and the Forward Premium Anomoly: A Model of Interacting Agents
By 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 | JEL Codes: G1,G13, G15 | Tagged: Exchange Rates, Forward Premium Anomoly
The Impact of Macroeconomic Surprises on Mergers & Acquisitions for Real Estate Investment Trusts
By 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.
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
Are Asset Allocation Funds Good at Market Timing?
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
