Volatility persistence in asset markets long memory in high/low prices by J. D. Byers

Cover of: Volatility persistence in asset markets | J. D. Byers

Published by Cardiff Business School, Financial and Banking Economics Research Group in Cardiff .

Written in English

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StatementJ.D. Byers and D.A. Peel.
SeriesFinancial and banking economics discussion paper series / Cardiff Business School, Financial and Banking Economics Research Group -- no.96:031, Financial and banking economics discussion paper (Cardiff Business School, Financial and Banking Economics Research Group) -- no.96:031.
ContributionsPeel, D. 1950-
ID Numbers
Open LibraryOL20831736M

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Abstract We introduce extensions of the Realized Exponential GARCH model (REGARCH) that capture the evident high persistence typically observed in measures of financial market volatility in a tractable fashion.

The extensions decompose conditional variance into a short-term and a long-term by: 6. This paper examines the potential influence of changing volatility in stock market prices on the level of stock market prices.

It demonstrates that volatility is only weakly serially correlated, implying that shocks to volatility do not by: Downloadable (with restrictions).

This study addresses the issue of volatility persistence in asset markets by analysing the behaviour of daily ratios of highest and lowest prices for a number of different assets both inter-war and post-war.

These series include sterling exchange rates, S&P futures prices, the FT30 and the price of gold. It is found that each of these series can be. However, when the volatility persistence is interacted with negative shocks, it cause the EREIT returns to decline. The negative volatility persistence effects fit the story of inter-temporal asset substitution, which explain why risk-averse REIT investors substitute risky REIT assets by risk-less assets in periods of prolong negative by: 2.

Stochastic Volatility in Financial Markets presents advanced topics in financial econometrics and theoretical finance, and is divided into three main parts. The first part aims at Volatility persistence in asset markets book an empirical regularity of financial price changes: the occurrence of sudden and persistent changes of financial markets volatility.

This phenomenon, technically termed `stochastic volatility', or 4/5(1). This paper investigates volatility persistence in Southern and East African stock markets taking into account the rate of volatility decay. Generalised autoregressive conditional heteroscedaticity. where E is the market value of the firm’s equity and X is the book value of short term debt plus half of the book value of long term debt (e.g., Bharath and Shumway, ).

Our second estimate of historical asset volatility. Consequently, a stock with anti-persistent volatility can earn average annualized returns of up to % higher than a stock with long memory volatility.

16 Models 2 to 6 additionally include one of the firm characteristics in the cross-sectional regression. The magnitude and significance of the memory risk premium is slightly reduced when. 1. Introduction.

Financial market instabilities have become more frequent and acute Volatility persistence in asset markets book the era of globalisation (Bordo et al., ), and have raised concerns about the benefits of traditional portfolio diversification involving instruments based on the VIX volatility index (which is negatively correlated to equity returns) are thought to be particularly effective during.

Persistence in volatility of stock returns is one of the common 'stylized facts' when it comes to analyzing time series. However, I am wondering for theoretical arguments why (estimated) volatility should have a long memory.

Charles and Darn e [17] considered volatility persistence in the three crude oil markets (WTI, Brent and OPEC) between and and identified significant structural changes where the. Downloadable. We show that volatility movements have first-order implications for consumption dynamics and asset prices.

Volatility news affects the stochastic discount factor and carries a separate risk premium. In the data, volatility risks are persistent and are strongly correlated with discount-rate news. This evidence has important implications for the return on aggregate wealth and the.

Abstract. We examine long memory volatility in the cross-section of stock returns. We show that long memory volatility is widespread in the United States and that the degree of memory can be related to firm characteristics, such as market capitalization, book-to-market. In empirical finance, it is well-known that the volatility of asset returns is highly persistent.

The persistence of the volatility process may be checked by testing for a unit root on stochastic volatility models. In this paper, a Bayesian test statistic based on decision theory is developed for testing a unit root on multivariate stochastic volatility models.

Thus, in these models, persistence in the information arrival process generates persistence in asset price volatility and trading volume. Market Volatility, vol 1. Robert Shiller (). in MIT Press Books from The MIT Press. Abstract: Market Volatility proposes an innovative theory, backed by substantial statistical evidence, on the causes of price fluctuations in speculative markets.

It challenges the standard efficient-markets model for explaining asset prices by emphasizing the significant role that popular opinion or. where y t is the continuously compounded return on the relevant asset at time t, T is the total number of observations and the sample mean \(m = \frac{1}{T}\sum\nolimits_{t = 1}^T {yt} \) A practical question that arises is what the length of the sample should be when volatility changes over time.

Conventional wisdom would suggest that the sample should consist of a large number of. 1,edReturns,andStockPriceFluctuations ThissectiondiscuBBestherelationshipbetweenchangesinvolatilityand changesinthelevelofstockmarketprices.

The Book value of a company is typically it's assets minus liabilities. This can differ from market value (which is the share price * number of shares outstanding).

The picture you provided looks like an option calculator, with inputs: Stock price, Volatility, Risk Free Rate, and Dividends (top left). Stochastic Volatility in Financial Markets presents advanced topics in financial econometrics and theoretical finance, and is divided into three main parts.

The first part aims at documenting an empirical regularity of financial price changes: the occurrence of sudden and persistent changes of financial markets volatility.

Volatility defines both the size and frequency of changes in the price of an asset. An asset is considered to be riskier if it has a high level of volatility, since its valuation could be spread across a substantial range.

Conversely, a low rate of volatility equates to minimal or moderate pricing changes over a period of time. The purpose of this paper is to analyze the existence of volatility spillover effect in frontier markets.

This study also examines whether any linkages exist among these markets or not.,Monthly data of regional frontier markets, from toare analyzed using Multivariate GARCH (BEKK and Dynamic Conditional Correlation (DCC)) models.,The result of cointegration test shows that the.

the dynamics of domestic sectors markets in asset allocation decisions. In this study, we attempt to answer a number of questions: First, do sector retur ns volatility exhibit persistence. The persistence of volatility embodies the extent to which.

Since the values of the growth options increase with volatility, all else equal, a –rm with a higher ratio of growth options to book value will serve as a better hedge against volatility risk in the market and should earn a lower variance risk premium.

This channel therefore generates a value premium. The Federal Reserve Board Discussion Paper "What drives volatility persistence in the foreign exchange market?" published May analyses the factors driving the widely-noted persistence in asset return volatility using a unique dataset on global euro-dollar exchange rate trading.

5 Tips to Handle (persistent) Market Volatility. In today’s digitally connected world, short-term market volatility can be more prevalent thanks (P/B Ratio) is a ratio used to compare a stock's market value to its book value (the company's assets minus liabilities).

It is calculated by dividing the price of the stock. Keyword: Bivariate GJR-GARCH, Trading volume, Volatility, Stock return, Volatility Persistence, Asymmetry in markets JEL Classification: C12, C32, G12 1.

Introduction In financial markets volatility is an important risk factor. Asset pricing models and portfolio. volatility is stochastic, and, if the representative household has Epstein and Zin preference, the asset and return premium will be a linear function of conditional consumption and market volatility.

The Euler condition is given by [, 1]=1 (1) 1, 1 E t G t R a t R i t (1). Purpose – The purpose of this paper is to estimate time‐varying conditional volatility, and examine the extent to which trading volume, as a proxy for information arrival, explain the persistence of futures market volatility using National Stock Exchange S&P CRISIL NSE Index Nifty index futures.

Design/methodology/approach – To estimate the volatility and capture the stylized facts of. In market equilibrium, then, assets which hedge against persistent volatility risk should require lower average returns, all else equal.2 Campbell, Giglio, Polk, and Turley () formally model this point, constructing an intertemporal capital asset pricing model (ICAPM) incorporating stochastic volatility.

It is now widely accepted that expected returns, volatility, and broader financial risk measures all vary over time. In particular, there is a pronounced clustering in return volatility; occasional extreme return outliers--especially on the negative for equities; and an increase in return correlations during market.

The present study adds to the sparse published Australian literature on the size effect, the book to market (BM) effect and the ability of the Fama French three factor model to account for these effects and to improve on the asset pricing ability of the Capital Asset Pricing Model (CAPM).

Expected volatility is a strong indicator of the risks of an asset. Volatility can be measured in different ways, but most often it involves tracking the standard deviation of returns over some sample period and capturing the dispersion – or potential dispersion of returns – over time.

The news component of volatility is not positively autocorrelated on these dates, since the news is released at a specific moment in time. We find that (1) expected returns on the short end of the bond market are significantly higher on these announcement dates, and (2) the persistence pattern of daily volatility is quite different around these.

by corresponding characteristic of the stocks (blue lines and red lines). The characteristics tested are market capitalization, book-to-market ratio, volatility, past performance and serial correlation.

We also display the rebalancing premium (black dashed lines) when the N = 30 stocks are randomly selected from the base S&P universe. This book shows how current and recent market prices convey information about the probability distributions that govern future prices.

Moving beyond purely theoretical models, Stephen Taylor applies methods supported by empirical research of equity and foreign exchange markets to show how daily and more frequent asset prices, and the prices of option contracts, can be used to construct and. Some market participants believe that active managers with successful track records should have the skills to benefit from different market environments.

However, volatility in the one-year period ending September did not help their persistence scores. Persistence of volatility in futures markets Persistence of volatility in futures markets Chen, Zhiyao; Daigler, Robert T.; Parhizgari, Ali M.

This article examines the characteristics of key measures of volatility for different types of futures contracts to provide a better foundation for modeling volatility behavior and derivative values. The presence of long persistence asset returns as discussed in Baillie (), Baillie, et al.

(), Ding, et al. (), Granger and Joyeux () and Mandelbrot () has further improved the model specification in volatility modelling. French() show that size and book-to-market ratio are better able to capture the cross-sectional variation in average stock t() adds a momentum factor, and more recently,Fama & French() extend their three-factor model by.

perspective, the financial econometric volatility literature (see Andersen, Bollerslev and Diebold,for a recent survey) has provided extensive evidence of wide fluctuations and high persistence in asset market conditional variances, and in individual equity conditional covariances with the market.Persistent, idiosyncratic cash flow shocks that hit firms are an important source of undi- differences in average returns on book-to-market, size, earning-to-price, and corporate bond market return volatility for explaining asset pricing stylized facts.4 We focus on exposure to idiosyncratic volatility instead, which in our model is.The Reg s/A fixed rate note was priced at bp over the US treasuries to yield %.

The offering attracted a large order book for a new Asian issuer reaching US$ billion – or an x oversubscription ratio, which reflects the market’s confidence in Xiaomi’s credit strength and future growth.

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