Predicting the Australian equity risk premium

Jurdi, Doureige J.

doi:10.1016/j.pacfin.2021.101683

Cited by 6 publications

(3 citation statements)

References 36 publications

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“…On a more specific basis, θ * is the Sharpe measure of the ex post efficient portfolio (ratio of expected excess return to the standard deviation of the excess return), while θp is the Sharpe measure of the test portfolio. Jurdi [45] and Agrrawal et al [46] note that investors rely on the ex-post performance of portfolios to assess the economic utility of their asset allocation and guide the portfolio rebalancing decision. Bazhutov et al [47] further note that no market portfolio is clearly defined in CAPM testing.…”

Section: Table 2 These Represent a Range Of Actual Grs-w Test Statist...mentioning

confidence: 99%

The Gibbons, Ross, and Shanken Test for Portfolio Efficiency: A Note Based on Its Trigonometric Properties

Agrrawal

2023

Mathematics

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This study is intended as a note and provides an extension to a much-used and established test for portfolio efficiency, the Gibbons, Ross, and Shanken GRS-Wald test. Tests devised to measure portfolio efficiency are crucial to the theoretical issues related to CAPM (Capital Asset Pricing Model) testing and have applications for the fund manager who seeks to rank portfolio performance. This study looks at the GRS-Wald test for portfolio efficiency and extends it to make it visually more interpretive without any loss of generality in its structure. The geometrically recast statistic draws upon the trigonometric properties of a portfolio in the mean-variance space and a mathematical proof of the equivalence of the two statistics is provided. The GRS-Wald test is a widely used statistic in studies addressing the issue of portfolio efficiency and CAPM deviations. A simulation demonstrates the use of the recast GRS-Wald test in testing for the mean-variance efficiency of a test portfolio. The study also provides a table of the GRS-Wald test, based on a range of mean-variance locations (cosine of portfolio angles) at which the test portfolio and the efficient market portfolio can be placed.

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Section: Table 2 These Represent a Range Of Actual Grs-w Test Statist...mentioning

confidence: 99%

The Gibbons, Ross, and Shanken Test for Portfolio Efficiency: A Note Based on Its Trigonometric Properties

Agrrawal

2023

Mathematics

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“…Futures contracts for this meat may be traded on the Bolsa de Mercadorias & Futuros (BM&F, Stock Exchange of Commodities and Futures) market and other international markets such as the Chicago Mercantile Exchange or the Australian Securities Exchange. Notably, the Australian Securities Exchange and its dynamics have been extensively researched in recent studies, such as the work by [15] that examines the predictive performance of various financial, economic and sentiment variables for the Australian All Ordinaries index equity risk premium spanning the last 28 years. Commodities' purchase and sale are made through 'futures' contracts that stipulate the quantities and quality of commodities to be traded.…”

Section: Bgi and Futures Pricesmentioning

confidence: 99%

Modelling Risk for Commodities in Brazil: An Application for Live Cattle Spot and Futures Prices

Alcoforado,

Egídio dos Reis,

Bernardino

et al. 2023

Commodities

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This study analyses a series of live cattle spot and futures prices from the Boi Gordo Index (BGI) in Brazil. The objective is to develop a model that best portrays this commodity’s behaviour to estimate futures prices more accurately. The database created contains 2010 daily entries in which trade in futures contracts occurs, as well as BGI spot sales in the market, from 1 December 2006 to 30 April 2015. One of the most important reasons why this type of risk needs to be measured is to set loss limits. To identify patterns in price behaviour in order to improve future transaction results, investors must analyse fluctuations in asset values for longer periods. Bibliographic research reveals that no other study has conducted a comprehensive analysis of this commodity using this approach. Cattle ranching is big business in Brazil given that in 2021, this sector moved BRL 913.14 billion (USD 169.29 billion). In that year, agribusiness contributed 26.6% of Brazil’s total gross domestic product. Using the proposed risk modelling technique, economic agents can make the best decision about which options within these investors’ reach produce more effective risk management. The methodology is based on Holt–Winters exponential smoothing algorithm, autoregressive integrated moving-average (ARIMA), ARIMA with exogenous inputs, generalised autoregressive conditionally heteroskedastic and generalised autoregressive moving-average (GARMA) models. More specifically, five different methods are applied that allow a comparison of 12 different models as ways to portray and predict the BGI commodity behaviours. The results show that GARMA with order c(2,1) and without intercept is the best model. Investors equipped with such precise modelling insights stand at an advantageous position in the market, promoting informed investment decisions and optimising returns.

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“…Goldsticker and Agrrawal (1999) find that the dilutive effect of executive stock options on EPS growth rates is not trivial and that it persists. Jurdi (2022) finds that alpha opportunities across various markets remain for investors from forecasting the risk premium, resulting from the inefficient market pricing of predictors; and misestimation of betas as seen on finance web portals (Waggle et al, 2010). Moreover, studies highlight the existence of other anomalies which prevent new information to be processed in an unbiased way.…”

Section: A Review Of Supporting Literaturementioning

confidence: 99%

A Longer-Term Evaluation of Information Releases by Influential Market Agents and the Semi-Strong Market Efficiency

Agrrawal,

Agarwal

2023

Journal of Behavioral Finance

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This paper is an evaluation of long-term cumulative returns (CAR's) based on Twitter broadcasts by highly influential market agents. We look at the information content of Elon Musk, CEO of SpaceX, Tesla and Twitter Inc. and the former US President Donald Trump. The principal objectives of this research are twofold: 1.) To assess whether markets are semi-strong form efficient and consequentially whether or not returns can be derived from strategies based on such sporadic tweet releases (abstracting from 'news'). For this purpose, event studies are conducted on multiple companies which were targeted by Musk and Trump tweets. A control group of all Dow Jones companies with earnings releases on Twitter is utilized. We find there appears to be a "pre-post-Twitter-drift" when the release is by exceedingly influential market personalities. The cumulative abnormal returns remain significant over long durations. This indicates that markets are not entirely semi-strong form efficient regarding social media releases and that trading on such tweets may be profitable (even after factoring in varying market phases). 2.) The paper introduces a new theme: long term CAR's of market information events. The paper also notes whether the tweet was during regular market hours or after-market hours.Forthcoming: "A Longer-Term evaluation of Information releases by Influential market Agents and the Semi-strong market Efficiency.

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Predicting the Australian equity risk premium

Cited by 6 publications

References 36 publications

The Gibbons, Ross, and Shanken Test for Portfolio Efficiency: A Note Based on Its Trigonometric Properties

The Gibbons, Ross, and Shanken Test for Portfolio Efficiency: A Note Based on Its Trigonometric Properties

Modelling Risk for Commodities in Brazil: An Application for Live Cattle Spot and Futures Prices

A Longer-Term Evaluation of Information Releases by Influential Market Agents and the Semi-Strong Market Efficiency

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