The Extreme Value Method for Estimating the Variance of the Rate of Return

Parkinson, Michael

doi:10.1086/296071

Cited by 1,535 publications

(1,009 citation statements)

References 4 publications

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“…Parkinson (1980). As shown in both panels, with and without control variables, the risk aversion parameter (β) is estimated to be positive but statistically insignificant, except for the marginal significance of β for the Canadian dollar in Panel B.…”

Section: Resultsmentioning

confidence: 78%

“…Panel C of Table 8 shows the parameter estimates and their Newey-West t-statistics from the riskreturn regressions with the daily range variance of Parkinson (1980). With LIBOR rates and the lagged return, the risk aversion parameter (β) is estimated to be positive for all currencies, but statistically significant only for the Canadian Dollar.…”

Section: Resultsmentioning

confidence: 99%

“…where range t VAR is the Parkinson's (1980) range-based estimator of the daily integrated variance defined in eq. (4).…”

Section: Estimation Methodsologymentioning

confidence: 99%

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The Intertemporal Relation between Expected Return and Risk on Currency

Bali

Yılmaz

2009

SSRN Journal

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in ABSTRACTThe literature has so far focused on the risk-return tradeoff in equity markets and ignored alternative risky assets. This paper examines the presence and significance of an intertemporal relation between expected return and risk in the foreign exchange market. The paper provides new evidence on the intertemporal capital asset pricing model by using high-frequency intraday data on currency and by presenting significant time-variation in the risk aversion parameter. Five-minute returns on the spot exchange rates of the U.S. dollar vis-à-vis six major currencies (the Euro, Japanese Yen, British Pound Sterling, Swiss Franc, Australian Dollar, and Canadian Dollar) are used to test the existence and significance of a daily risk-return tradeoff in the FX market based on the GARCH, realized, and range volatility estimators. The results indicate a positive, but statistically weak relation between risk and return on currency.

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Section: Resultsmentioning

confidence: 78%

Section: Resultsmentioning

confidence: 99%

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The Intertemporal Relation between Expected Return and Risk on Currency

Bali

Yılmaz

2009

SSRN Journal

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“…With the unobserved terms, the expected ranges of daily and two-day midprices can be eliminated, allowing us to extract the bid-ask spread. Parkinson (1980) shows that if the mid-price follows a one-dimensional Wiener process, its expected range is an increasing function of the sampling time interval and its diffusion. A long sampling time interval or large diffusion will lead to a wider range.…”

Section: The Basic High-low Estimator (The Bhl Model)mentioning

confidence: 99%

New bid-ask spread estimators from daily high and low prices

Lambe

Adegbite

2018

International Review of Financial Analysis

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In this paper, we introduce two low frequency bid-ask spread estimators using daily high and low transaction prices. The range of mid-prices is an increasing function of the sampling interval, while the bid-ask spread and the relationship between trading direction and the mid-price are not constrained by it and are therefore independent. Monte Carlo simulations and data analysis from the equity and foreign exchange markets demonstrate that these models significantly out-perform the most widely used low-frequency estimators, such as those proposed in Corwin and Schultz (2012) and most recently in Abdi and Ranaldo (2017). We illustrate how our models can be applied to deduce historical market liquidity in NYSE, UK, Hong Kong and the Thai stock markets. Our estimator can also effectively act as a gauge for market volatility and as a measure of liquidity risk in asset pricing.

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“…The BS model adopts the assumption that the volatility is constant (Black and Scholes, 1973;Merton, 1973). In order to obtain it, the historical volatility of the underlying was proposed as proxy and several methods to calculate it has been developed (Rogers and Satchell, 1991;Rogers et al, 1994;Parkinson, 1980). The option prices using the historical volatility mismatch with the real market option prices since the assumptions of the BS model do not satisfy the real market properties.…”

Section: Introductionmentioning

confidence: 99%

Implied Volatility Function Approximation with Korean ELWs (Equity-Linked Warrants) via Gaussian Processes

Han

2014

Management Science and Financial Engineering

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A lot of researches have been conducted to estimate the volatility smile effect shown in the option market. This paper proposes a method to approximate an implied volatility function, given noisy real market option data. To construct an implied volatility function, we use Gaussian Processes (GPs). Their output values are implied volatilities while moneyness values (the ratios of strike price to underlying asset price) and time to maturities are as their input values. To show the performances of our proposed method, we conduct experimental simulations with Korean Equity-Linked Warrant (ELW) market data as well as toy data.

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The Extreme Value Method for Estimating the Variance of the Rate of Return

Cited by 1,535 publications

References 4 publications

The Intertemporal Relation between Expected Return and Risk on Currency

The Intertemporal Relation between Expected Return and Risk on Currency

New bid-ask spread estimators from daily high and low prices

Implied Volatility Function Approximation with Korean ELWs (Equity-Linked Warrants) via Gaussian Processes

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