Essays on Asset Pricing and Asset Allocation PDF Download
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Author: Xiangrong Jin
Publisher:
ISBN:
Category :
Languages : en
Pages : 128
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Author: Xiangrong Jin
Publisher:
ISBN:
Category :
Languages : en
Pages : 128
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Book Description
Author: Huacheng Zhang
Publisher:
ISBN:
Category :
Languages : en
Pages : 282
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Book Description
This dissertation consists of two essays in asset allocation. In the first essay, I measure the value of active money management. I explore this issue by comprehensively examining the parametric rule proposed by Brandt, Santa-Clara and Valkanov (2009) (the BSV rule) out-of-sample for portfolio selection among 3516 stocks in CRSP and comparing this rule to the mean-variance (MV) rule and the naïve 1/N rule recently advocated by DeMiguel, Garlappi and Uppal (2009). The BSV rule outperforms both the MV and 1/N rules and the outperformance is robust to investment horizons and stock market states. The BSV rule is effective for investors with different preferences or investment opportunities. The effectiveness of the BSV rule is robust to data screening criteria, estimation periods, portfolio performance evaluation models, the business cycle, and stock market states. In the second essay, I explore the question of whether macroeconomic state variables are able to predict cross-sectional stock returns from the perspective of asset allocation. I find that conditioning on macroeconomic state variables leads to optimal portfolios with a Carhart alpha that is 125 basis points per month higher than unconditional optimal portfolios out-of-sample. Unfortunately, conditioning on macroeconomic states is subject to an "overfitting" problem and can lead investors to experience unexpected huge losses. My results suggest that macroeconomic state variables mare able to predict cross-sectional stock returns but risk-averse investors need to combine other funds (e.g. market portfolio) to take advantage of this predictability.
Author: Xin Gao
Publisher:
ISBN:
Category : Commodity exchanges
Languages : en
Pages :
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This dissertation consists of two essays in asset allocation. In the first essay, I explore the question of how investors should optimally incorporate commodities in their multi-asset portfolios, or even if they should at all. To tackle this problem, I conduct a comprehensive out-of-sample assessment on the economic value of commodities in multi-asset investment strategies for both mean-variance and non-mean-variance investors who exploit the predictability of time-varying asset return moments. With both monthly and quarterly rebalancing frequencies, I find that predictability makes the addition of commodities profitable even when short-selling and high leverage are not permitted. For instance, a mean-variance (non mean-variance) investor rebalancing quarterly, with moderate risk aversion and leverage, would be willing to pay up to 108 (155) basis points per year after transaction cost for adding commodities into her stock, bond and cash portfolio. In the second essay, I study the economic value generated by active equity mutual funds from an investor’s perspective. I employ an optimization-based portfolio approach to construct a composite investment strategy of U.S. active equity mutual funds. The strategy jointly exploits the conditioning information conveyed by multiple fund characteristics and macroeconomic variables about the cross-section of fund performance. Based on an extensive out-of-sample performance evaluation, I find that the proposed strategy consistently outperforms a large set of passive investments that rely on index funds as well as the strategies that exploit the fund characteristics on an individual basis. The outperformance is net of fees and expenses and after precluding short-sales and leverage. I further show that the proposed strategy’s superior performance derives from effectively exploiting the predictive power of distinct fund characteristics to shift portfolio allocation toward (away from) funds with future outperformance (underperformance) as market conditions evolve over time. The findings indicate that investing in active equity mutual funds can add significant economic value for investors if the time-varying predictability in fund performance is properly taken into account and if an optimal portfolio approach, as opposed to simpler strategies based on sorting or on equal-weighted schemes, is adopted.
Author: Chen Cao
Publisher:
ISBN:
Category : Asset allocation
Languages : en
Pages : 137
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Author: Ka Chun Ma
Publisher:
ISBN:
Category :
Languages : en
Pages : 222
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Author: Ehud Peleg
Publisher: ProQuest
ISBN:
Category : Capital assets pricing model
Languages : en
Pages : 356
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Author: Eva Schneider
Publisher:
ISBN:
Category :
Languages : en
Pages : 134
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Author: Sébastien Coupy
Publisher:
ISBN:
Category :
Languages : en
Pages : 85
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Author: Ken-Shih Lin
Publisher:
ISBN:
Category :
Languages : en
Pages : 186
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Author: Alberto Gianluca Paolo Rossi
Publisher:
ISBN: 9781124703749
Category : Asset allocation
Languages : en
Pages : 155
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Book Description
This dissertation presents three stand-alone contributions to the fields of theoretical and empirical asset pricing. The first chapter presents a theoretical model in which the attention investors pay to the stock market varies over time. This feature is obtained by introducing information costs into a continuous-time model of asset allocation with time-varying investment opportunities. My model explains why investors do not trade uniformly through time. It also rationalizes why agents do not modify their portfolio allocations gradually with the arrival of new information, but rather alternate extended periods of inertia (no-trade) with brief moments of action where asset allocations are updated according to the current state of the economy. The second chapter analyzes the role of information in the context of financial market predictions. I employ a novel semi-parametric method known as Boosted Regression Trees (BRT) to forecast stock returns and volatility at the monthly frequency. The framework allows me to generate forecasts on the basis of a large set of predictor variables without incurring over-fitting related problems. My results indicate that expanding the conditioning information set results in greater out-of-sample predictive accuracy compared to the standard models proposed in the literature and that the forecasts generate profitable portfolio allocations even when market frictions are considered. The third chapter (co-authored with Allan Timmermann) analyzes the limitations of parametric models in evaluating the relation between risk and return. By taking advantage of the flexible and semi-parametric nature of Boosted Regression Trees, we find evidence of a nonmonotonic relation between conditional volatility and expected stock market returns. At low and medium levels of conditional volatility there is a positive risk-return trade-off, but this relation is inverted at high levels of volatility. This finding helps explain the absence of a consensus in the empirical literature on the sign of the risk-return trade-off. We propose a new measure of risk based on the conditional covariance between observations of a broad economic activity index and stock market returns. Using this broader covariance-based risk measure, we find clear evidence of a positive and monotonic risk-returns trade-off.
