873 resultados para Volatility premium
Resumo:
A existência e o sinal do prêmio de volatilidade têm causado controvérsias dentro da literatura especializada. Este trabalho propôs, criticou e aplicou uma nova metodologia com a natalidade de testar estatisticamente a existência do prêmio de volatilidade, com as vantagens de testar para um conjunto de ações, e não para séries individuais, e de não depender de uma forma funcional específica para e relação entre o retorno e a volatilidade esperados. Os resultados da aplicação para um conjunto selecionado de ações negociadas na Bovespa foram favoráveis à existência do prêmio.
Resumo:
Numerous studies have documented the failure of the static and conditional capital asset pricing models to explain the difference in returns between value and growth stocks. This paper examines the post-1963 value premium by employing a model that captures the time-varying total risk of the value-minus-growth portfolios. Our results show that the time-series of value premia is strongly and positively correlated with its volatility. This conclusion is robust to the criterion used to sort stocks into value and growth portfolios and to the country under review (the US and the UK). Our paper is consistent with evidence on the possible role of idiosyncratic risk in explaining equity returns, and also with a separate strand of literature concerning the relative lack of reversibility of value firms' investment decisions.
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In this paper, we study the role of the volatility risk premium for the forecasting performance of implied volatility. We introduce a non-parametric and parsimonious approach to adjust the model-free implied volatility for the volatility risk premium and implement this methodology using more than 20 years of options and futures data on three major energy markets. Using regression models and statistical loss functions, we find compelling evidence to suggest that the risk premium adjusted implied volatility significantly outperforms other models, including its unadjusted counterpart. Our main finding holds for different choices of volatility estimators and competing time-series models, underlying the robustness of our results.
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The value premium is well established in empirical asset pricing, but to date there is little understanding as to its fundamental drivers. We use a stochastic earnings valuation model to establish a direct link between the volatility of future earnings growth and firm value. We illustrate that risky earnings growth affects growth and value firms differently. We provide empirical evidence that the volatility of future earnings growth is a significant determinant of the value premium. Using data on individual firms and characteristic-sorted test portfolios, we also find that earnings growth volatility is significant in explaining the cross-sectional variation of stock returns. Our findings imply that the value premium is the rational consequence of accounting for risky earnings growth in the firm valuation process.
Resumo:
Forecasts of volatility and correlation are important inputs into many practical financial problems. Broadly speaking, there are two ways of generating forecasts of these variables. Firstly, time-series models apply a statistical weighting scheme to historical measurements of the variable of interest. The alternative methodology extracts forecasts from the market traded value of option contracts. An efficient options market should be able to produce superior forecasts as it utilises a larger information set of not only historical information but also the market equilibrium expectation of options market participants. While much research has been conducted into the relative merits of these approaches, this thesis extends the literature along several lines through three empirical studies. Firstly, it is demonstrated that there exist statistically significant benefits to taking the volatility risk premium into account for the implied volatility for the purposes of univariate volatility forecasting. Secondly, high-frequency option implied measures are shown to lead to superior forecasts of the intraday stochastic component of intraday volatility and that these then lead on to superior forecasts of intraday total volatility. Finally, the use of realised and option implied measures of equicorrelation are shown to dominate measures based on daily returns.
Resumo:
The price formation of financial assets is a complex process. It extends beyond the standard economic paradigm of supply and demand to the understanding of the dynamic behavior of price variability, the price impact of information, and the implications of trading behavior of market participants on prices. In this thesis, I study aggregate market and individual assets volatility, liquidity dimensions, and causes of mispricing for US equities over a recent sample period. How volatility forecasts are modeled, what determines intradaily jumps and causes changes in intradaily volatility and what drives the premium of traded equity indexes? Are they induced, for example, by the information content of lagged volatility and return parameters or by macroeconomic news, changes in liquidity and volatility? Besides satisfying our intellectual curiosity, answers to these questions are of direct importance to investors developing trading strategies, policy makers evaluating macroeconomic policies and to arbitrageurs exploiting mispricing in exchange-traded funds. Results show that the leverage effect and lagged absolute returns improve forecasts of continuous components of daily realized volatility as well as jumps. Implied volatility does not subsume the information content of lagged returns in forecasting realized volatility and its components. The reported results are linked to the heterogeneous market hypothesis and demonstrate the validity of extending the hypothesis to returns. Depth shocks, signed order flow, the number of trades, and resiliency are the most important determinants of intradaily volatility. In contrast, spread shock and resiliency are predictive of signed intradaily jumps. There are fewer macroeconomic news announcement surprises that cause extreme price movements or jumps than those that elevate intradaily volatility. Finally, the premium of exchange-traded funds is significantly associated with momentum in net asset value and a number of liquidity parameters including the spread, traded volume, and illiquidity. The mispricing of industry exchange traded funds suggest that limits to arbitrage are driven by potential illiquidity.
Resumo:
This article describes a maximum likelihood method for estimating the parameters of the standard square-root stochastic volatility model and a variant of the model that includes jumps in equity prices. The model is fitted to data on the S&P 500 Index and the prices of vanilla options written on the index, for the period 1990 to 2011. The method is able to estimate both the parameters of the physical measure (associated with the index) and the parameters of the risk-neutral measure (associated with the options), including the volatility and jump risk premia. The estimation is implemented using a particle filter whose efficacy is demonstrated under simulation. The computational load of this estimation method, which previously has been prohibitive, is managed by the effective use of parallel computing using graphics processing units (GPUs). The empirical results indicate that the parameters of the models are reliably estimated and consistent with values reported in previous work. In particular, both the volatility risk premium and the jump risk premium are found to be significant.
Resumo:
This article examines the role of idiosyncratic volatility in explaining the cross-sectional variation of size- and value-sorted portfolio returns. We show that the premium for bearing idiosyncratic volatility varies inversely with the number of stocks included in the portfolios. This conclusion is robust within various multifactor models based on size, value, past performance, liquidity and total volatility and also holds within an ICAPM specification of the risk–return relationship. Our findings thus indicate that investors demand an additional return for bearing the idiosyncratic volatility of poorly-diversified portfolios.
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We develop an affine jump diffusion (AJD) model with the jump-risk premium being determined by both idiosyncratic and systematic sources of risk. While we maintain the classical affine setting of the model, we add a finite set of new state variables that affect the paths of the primitive, under both the actual and the risk-neutral measure, by being related to the primitive's jump process. Those new variables are assumed to be commom to all the primitives. We present simulations to ensure that the model generates the volatility smile and compute the "discounted conditional characteristic function'' transform that permits the pricing of a wide range of derivatives.
Resumo:
We present empirical evidence using daily data for stock prices for 17 real estate companies traded in the Sao Paulo, Brazil stock exchange. from August 26, 2006 to March 31, 2010. We use the U.S. house price bubble, financial crisis and risk measures to instrument for momentums and reversals in the domestic real estate sector. We find evidence of conditional premium persistence and conditional volatility persistence in the market. We find that the conditional risk-return relationship in the sector is consistent with the prospect theory of risk attitudes in this period. Certain companies seem to be operating on a perceived potential industry return above the target, while most others are below the target, and the whole sector is below target on average. (C) 2011 Elsevier Inc. All rights reserved.
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Using a Markov switching unobserved component model we decompose the term premium of the North American CDX index into a permanent and a stationary component. We establish that the inversion of the CDX term premium is induced by sudden changes in the unobserved stationary component, which represents the evolution of the fundamentals underpinning the probability of default in the economy. We find evidence that the monetary policy response from the Fed during the crisis period was effective in reducing the volatility of the term premium. We also show that equity returns make a substantial contribution to the term premium over the entire sample period.
Resumo:
Particle emissions, volatility, and the concentration of reactive oxygen species (ROS) were investigated for a pre-Euro I compression ignition engine to study the potential health impacts of employing ethanol fumigation technology. Engine testing was performed in two separate experimental campaigns with most testing performed at intermediate speed with four different load settings and various ethanol substitutions. A scanning mobility particle sizer (SMPS) was used to determine particle size distributions, a volatilization tandem differential mobility analyzer (V-TDMA) was used to explore particle volatility, and a new profluorescent nitroxide probe, BPEAnit, was used to investigate the potential toxicity of particles. The greatest particulate mass reduction was achieved with ethanol fumigation at full load, which contributed to the formation of a nucleation mode. Ethanol fumigation increased the volatility of particles by coating the particles with organic material or by making extra organic material available as an external mixture. In addition, the particle-related ROS concentrations increased with ethanol fumigation and were associated with the formation of a nucleation mode. The smaller particles, the increased volatility, and the increase in potential particle toxicity with ethanol fumigation may provide a substantial barrier for the uptake of fumigation technology using ethanol as a supplementary fuel.