Option Implied Dividends Predict Dividend Cuts: Evidence from the Financial Crisis

Fodor, Andy; Stowe, David L.; Stowe, John D.

doi:10.1111/jbfa.12249

Cited by 6 publications

(5 citation statements)

References 68 publications

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“…Following the financial crisis, the average frequency of omissions increases to 4.29%, suggesting some moderation of dividend smoothing in crisis years (2007–2012). The evidence is consistent with findings in Fodor, Stowe, and Stowe (), who document a larger number of dividend cuts and omissions, albeit during a much narrower window (2008–2009) and only for large US banks with traded options. In post‐crisis years (2013–2016), dividend omissions appear to decrease significantly, suggesting a return to greater dividend smoothing.…”

Section: Resultssupporting

confidence: 90%

What factors determine dividend smoothing by US and EU banks?

Koussis

Makrominas

2019

Business Fin & Account

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Using a relatively large sample of European and US banks for the period 1998-2016, we investigate the determinants of bank dividend smoothing based on agency, asymmetric information and risk-shifting theories. We show that dividend payout ratio smoothing practices were implemented on both continents before and after the crisis of 2007 and were more strongly pronounced for EU banks. Our findings mostly support agency-based explanations of bank dividend behavior as evidenced by higher payout ratio smoothing for banks with higher (initial) dividend payouts, lower ownership concentration, public banks, and banks with lower growth opportunities and weaker investor protection. Evidence in favor of asymmetric information explanations is stronger for EU countries, where smaller (more opaque) banks appear to smooth more. In both continents, banks that rely more heavily on equity issuances are found to smooth dividend payout ratios more, suggesting that banks aim at improving access to equity markets. We also provide evidence in support of risk-shifting, as evidenced by the persistence of dividend payout ratio smoothing in the crisis years and higher dividend smoothing for banks under greater regulatory pressure.Additional analysis using a time series partial adjustment model for dividend levels provides evidence supporting the prevalence of dividend smoothing and the suggested theoretical explanations. K E Y W O R D Sagency, asymmetric information, bank dividend policy, bank regulation, legal origin, risk-shifting

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Section: Resultssupporting

confidence: 90%

What factors determine dividend smoothing by US and EU banks?

Koussis

Makrominas

2019

Business Fin & Account

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“…For American-style options, the put-call parity does not hold. In certain works [17,18] the authors employ Formula (12) to roughly estimate the implied dividend yield for American options.…”

Section: Implied Dividendmentioning

confidence: 99%

“…Moreover, a hedging process involves frequent updating of the position in the underlying asset, and one may choose a specific trading strategy according to the difference between market implied and announced actual dividends, see [17]. The authors in [18,19] give evidence for the fact that implied dividends are a significant factor for forecasting actual dividend changes. Implied dividend is shown to have a more predictive power than historical dividends.…”

Section: Introductionmentioning

confidence: 99%

“…A popular way to estimate implied dividend is by means of the put-call parity. The putcall parity holds, however, only for European-style options, and does no longer hold in the case of American-style options due to the early-exercise premium [17,18]. Alternatively, an option pricing model including a dividend yield model can be inverted to determine the implied dividend, as in [21] where a known implied volatility was assumed.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

On Calibration Neural Networks for extracting implied information from American options

Liu¹,

Leitao²,

Borovykh³

et al. 2020

Preprint

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Extracting implied information, like volatility and/or dividend, from observed option prices is a challenging task when dealing with American options, because of the computational costs needed to solve the corresponding mathematical problem many thousands of times. We will employ a data-driven machine learning approach to estimate the Black-Scholes implied volatility and the dividend yield for American options in a fast and robust way. To determine the implied volatility, the inverse function is approximated by an artificial neural network on the computational domain of interest, which decouples the offline (training) and online (prediction) phases and thus eliminates the need for an iterative process. For the implied dividend yield, we formulate the inverse problem as a calibration problem and determine simultaneously the implied volatility and dividend yield. For this, a generic and robust calibration framework, the Calibration Neural Network (CaNN), is introduced to estimate multiple parameters. It is shown that machine learning can be used as an efficient numerical technique to extract implied information from American options.

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“…Specifically, we examine the impact of option transaction costs on two types of informed trading: directional information trading and volatility information trading. By directional and volatility information trading, we mean using option market‐related measures to predict future stock returns and future stock return volatility, respectively (Cairney & Swisher, 2004; Cao et al., 2005; Cremers & Weinbaum, 2010; Doran, Fodor, & Krieger, 2010; Fodor, Stowe, & Stowe, 2017; Truong, 2012; Truong & Corrado, 2014; Xing et al., 2010).…”

Section: Introductionmentioning

confidence: 99%

The effect of option transaction costs on informed trading in the options market around earnings announcements

Govindaraj

Zhao

2020

Business Fin & Account

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We investigate the effect of option market transaction costs (a form of market imperfection) on the ability of option implied volatility‐based measures to predict future stock returns and volatility around quarterly earnings announcements. We find that the predictability is significantly stronger for firms with lower option relative bid‐ask spreads. The effect is more pronounced around positive rather than negative earnings news. We find no significant effect of option transaction costs around randomly chosen dates when there is no clustering of major information events. Trading strategies based on option market predictors and transaction costs earn monthly abnormal returns of 1.39% to 1.91%.

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Option Implied Dividends Predict Dividend Cuts: Evidence from the Financial Crisis

Cited by 6 publications

References 68 publications

What factors determine dividend smoothing by US and EU banks?

What factors determine dividend smoothing by US and EU banks?

On Calibration Neural Networks for extracting implied information from American options

The effect of option transaction costs on informed trading in the options market around earnings announcements

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