Modelling earnings moves.

[TheBigShort]

https://www0.gsb.columbia.edu/faculty/mjohannes/PDFpapers/Earnings_2006.pdf

This is out dated but the models are still useful. It also gives you some interesting ideas to include into your own model. Reading it for the second time if any one cares to talk about it i'll be here

 

[mushinseeker]

gonna read it as I plow thru my machine learning course this term... one possible avenue for my thesis in January. THANKS!

 

[ironchef]

https://www0.gsb.columbia.edu/faculty/mjohannes/PDFpapers/Earnings_2006.pdf

This is out dated but the models are still useful. It also gives you some interesting ideas to include into your own model. Reading it for the second time if any one cares to talk about it i'll be here

Thank you for the link.

Regards,

 

[pipeguy]

Thanks for the link? Do you need this in trading and how it can help you. Still have no clue on clear-cut application of this.

 

[ironchef]

Thanks for the link? Do you need this in trading and how it can help you. Still have no clue on clear-cut application of this.

Here is the summary of the study:

This paper uses option prices to learn about the uncertainty surrounding firm fundamentals. When firms announce earnings every quarter, they reveal current fundamentals (earnings, cash flows, sales, taxes, etc.) which were, to varying extents, unknown to investors prior to the announcement. This information revelation is why stock prices often react violently after earnings announcements. This paper develops estimators of the uncertainty associated with information revealed in earnings announcements and investigates. On the theoretical side, we develop no-arbitrage option pricing models in the presence of earnings announcements; and we develop and justify estimators of the earnings uncertainty using option prices. Empirically, we first nonparametrically test for the importance of earnings announcements on option prices and then implement the estimators. We analyze their time series behavior and test for the presence of risk premia. Finally, we quantify the impact that earnings annoucements have on formal option pricing models.

If you are a mom and pop amateur retail like me and have no formal training, how to price options around earnings and events, the interplays between various parameters on option prices and how they relate to convexity.... this is very useful.

 

[ironchef]

Thanks for the link? Do you need this in trading and how it can help you. Still have no clue on clear-cut application of this.

And I am particularly interested in the estimators they tried to develop.

 

[TheBigShort]

gonna read it as I plow thru my machine learning course this term... one possible avenue for my thesis in January. THANKS!

Masters or PHD? What are you getting your degree in?

 

[TheBigShort]

Thanks for the link? Do you need this in trading and how it can help you. Still have no clue on clear-cut application of this.

Well from reading a few of your posts it looks like you trade linear products. That is why you see no use of this paper.

 

[mushinseeker]

MS in Comp Sci.

 

[ironchef]

https://www0.gsb.columbia.edu/faculty/mjohannes/PDFpapers/Earnings_2006.pdf

This is out dated but the models are still useful. It also gives you some interesting ideas to include into your own model. Reading it for the second time if any one cares to talk about it i'll be here

Read the paper a few times, the math is beyond my ability but the concept is simple enough. I now understand the relationships between IV and earning uncertainty from a probability and option pricing model points of view.

As a trader of options, for each underlying, I need to calculate the historical behaviors of prior earning periods, use them to predict the pricing outcome for the upcoming period and find those potentially under/over price options to trade. For a retail like me, to do that, I need access to historical IV, earning performance and modeling software. I have none of those.

On the other hand, perhaps I don't need to be so precise. Worth thinking about it some more.

Welcome any coaching or comments.