Essays on Financial Market Volatility PDF Download
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Author: Mehmet Sahiner
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ISBN:
Category :
Languages : en
Pages : 0
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Author: Mehmet Sahiner
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Category :
Languages : en
Pages : 0
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Author: Otis Scott Mixon
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Category : Foreign exchange rates
Languages : en
Pages : 254
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Author: Emily B. Johnston
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ISBN: 9781303738654
Category :
Languages : en
Pages : 258
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This dissertation examines time-variation in asset volatility surrounding periods of financial market distress. In the first chapter we give a brief introduction of the overall theme of the project, and we outline the models used. The next chapters individually focus on the application of time-varying volatility to important themes in the literature. These include: the behavior of investor risk preferences across periods of stability and distress; inconsistencies in options pricing with regard to the behavior of the underlying asset; and the characterization of time-varying volatility dynamics in equity returns. The second chapter of this dissertation examines the impact of changing asset volatility on the estimation of investor risk preferences. We ask whether prior findings of time-varying behavior for risk preferences may be due in part to a failure to account for changes in volatility. This is an important issue, because there is evidence in the existing literature that suggests a contributing role of risk preferences during periods of crisis and contagion. We use a regime-switching GARCH model for pricing kernel estimation to show that much of the variation in estimated investor risk preferences can be explained by changing volatility instead. In the third chapter we examine stochastic volatility as an additional uncertainty factor regarding the future state of the market. We explore whether this inclusion affects prior findings of options pricing inconsistencies in the literature. Options mispricing is an important topic in debates concerning the role of investor sentiment in market behavior and asset pricing. Results from our investigation indicate that including this additional uncertainty factor does not fully explain away the inconsistencies. Our findings thus appear to support the existing evidence of options mispricing with respect to the behavior of the underlying asset. In the fourth and final chapter of this dissertation, we examine asset volatility dynamics over a long historical time frame from 1871-2013. We demonstrate best fit for the number of distinct volatility regimes and characterize these separate dynamics. There is growing evidence that some economic relationships themselves may change between periods of high and low volatility - understanding changing volatility dynamics is crucial for understanding these economic relationships as well. We also show in this chapter how the estimated high-volatility state matches up with well-documented historical financial market events.
Author: Srideep Ganguly
Publisher:
ISBN:
Category : Finance
Languages : en
Pages : 310
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Author: Ai Jun Hou
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Category : Interest rates
Languages : en
Pages : 131
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Author: Kwanho Kim
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Category : Euro-dollar market
Languages : en
Pages : 312
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Author: Sang Yup Choi
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ISBN:
Category :
Languages : en
Pages : 130
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This dissertation studies how financial market volatility or uncertainty in the U.S. economy affects real economic activity both in the U.S. and other open economies. Chapter 1 critically examines a stylized fact about the effects of uncertainty shocks on the U.S. economy. A link between uncertainty and firms' investment, hiring, and production decisions has drawn much attention in contemporary discussions after the 2008 financial crisis. Bloom (2009) showed that uncertainty events, identified by spikes in stock market volatility, triggered immediate falls in output and employment, followed by rapid rebounds. I show that such stock market volatility shocks failed to produce this same pattern of responses after 1983. Chapter 2 studies the effects of risk aversion shocks, measured by increases in the VIX, on emerging market economies (EMEs). By estimating a structural vector autoregression (VAR) model, I find that, although risk aversion shocks do not have much impact on U.S. output, they do have a noticeable impact on the output of EMEs. To explain the contrast between the impact of risk appetite shocks on EMEs and the impact on the U.S. economy, a credit channel is proposed as a propagation mechanism. In the model, an increase in the VIX is translated to a risk-aversion shock that generates a "flight to quality." As international investors pull their money from EMEs, borrowing costs increase and domestic credit falls as a consequence of credit market imperfections. Higher borrowing costs, in turn, lead to a fall in investment that causes a real depreciation and a decline in total output through sectoral linkages. Finally, Chapter 3, which is co-authored with Prakash Loungani, studies the effect of uncertainty shocks on unemployment dynamics by separating out the role of aggregate and sectoral channels. Using SP500 data from the first quarter of 1963 through the third quarter of 2014, we construct a separate index to measure sectoral uncertainty and compare its effects on the unemployment rate with that of aggregate uncertainty in a standard VAR model, augmented by a local projection method. We find that aggregate uncertainty shocks lead to an immediate increase in unemployment, followed by swift reversals. In contrast, sectoral uncertainty shocks have a long-lasting impact on unemployment, with the peak impact occurring after two years. Our findings highlight an additional channel through which uncertainty shocks have persistent effects on unemployment by requiring substantial inter-industry labor reallocation.
Author: Alessandro Castaldo
Publisher:
ISBN:
Category :
Languages : en
Pages : 336
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Author: Yajun Xiao
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ISBN:
Category :
Languages : en
Pages : 133
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Author: Chengbo Fu
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Category :
Languages : en
Pages : 0
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This dissertation consists of three essays on stock market volatility. In the first essay, we show that investors will have the information in the idiosyncratic volatility spread when using two different models to estimate idiosyncratic volatility. In a theoretical framework, we show that idiosyncratic volatility spread is related to the change in beta and the new betas from the extra factors between two different factor models. Empirically, we find that idiosyncratic volatility spread predicts the cross section of stock returns. The negative spread-return relation is independent from the relation between idiosyncratic volatility and stock returns. The result is driven by the change in beta component and the new beta component of the spread. The spread-relation is also robust when investors estimate the spread using a conditional model or EGARCH method. In the second essay, the variance of stock returns is decomposed based on a conditional Fama-French three-factor model instead of its unconditional counterpart. Using time-varying alpha and betas in this model, it is evident that four additional risk terms must be considered. They include the variance of alpha, the variance of the interaction between the time-varying component of beta and factors, and two covariance terms. These additional risk terms are components that are included in the idiosyncratic risk estimate using an unconditional model. By investigating the relation between the risk terms and stock returns, we find that only the variance of the time-varying alpha is negatively associated with stock returns. Further tests show that stock returns are not affected by the variance of time-varying beta. These results are consistent with the findings in the literature identifying return predictability from time-varying alpha rather than betas. In the third essay, we employ a two-step estimation method to separate the upside and downside idiosyncratic volatility and examine its relation with future stock returns. We find that idiosyncratic volatility is negatively related to stock returns when the market is up and when it is down. The upside idiosyncratic volatility is not related to stock returns. Our results also suggest that the relation between downside idiosyncratic volatility and future stock returns is negative and significant. It is the downside idiosyncratic volatility that drives the inverse relation between total idiosyncratic volatility and stock returns. The results are consistent with the literature that investor overreact to bad news and underreact to good news.
