Market efficiency of the crude palm oil: Evidence from quantum harmonic oscillator

Abstract

This study examines the weak-form efficient market hypothesis of the crude palm oil market by adopting the quantum harmonic oscillator. This approach allows us to analyze market efficiency by estimating one parameter: the probability of finding the market in a ground state. Our results confirm that the crude palm oil market is more efficient than the West Texas Intermediate crude oil market. We explain the greater market efficiency comes from a small proportion of speculative transactions, resulting from tight market operation policies.

Stationarity in the Prices of Energy Commodities. A Nonparametric Approach

“…Our conclusions also agree with Lean and Smyth [21], who studied monthly spot and futures prices, finding little evidence to support the efficient market hypothesis. However, our findings would diverge from results by Lee et al [24], who (for daily data) reported more efficiency in palm oil than in the West Texas Intermediate crude oil market, possibly explained by the smaller proportion of speculative transactions in the former as a consequence of relatively strict trading policies.…”

“…More recently, Lean and Smyth [21], who analyzed palm oil spot and futures markets by employing a GARCH unit root test with structural breaks, concluded that a large percentage of the palm oil series they analyzed are stationary, with only a weak evidence of efficiency being found in that market. Efficiency in the palm oil market has also been addressed by Liu [22], and more recently by Snaith et al [23], whose results suggested an efficiency skew in the market, and Lee et al [24], who concluded that the crude palm oil market is more efficient than that of the West Texas Intermediate crude oil. Chen et al [25], employing unit root Augmented Dickey-Fuller (ADF) testing with no changes allowed for, found significant evidence of unit roots in both palm and soybean oils.…”

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“…The notes in a song are analyzed through a mean-reverting process, in particular using the Vasicek model [4][5][6][7][8], which is a one-factor model widely adopted to describe the interest rate movements in finance. According to this model, the progression of a note at time 𝒕 is defined as…”

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“…2 An increasing number of quantum finance models have been used to describe the stochastic dynamics of risk assets [23,25,[42][43][44][45]. 3 Ahn et al [23] reported that the null hypothesis of the Cramér goodness-of-fit test, log return data of S&P 500 comes from the Gaussian distribution, can be rejected in the sampling frequency of 1-day, 1-week, and 1-month.…”