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May I Have Your Attention, Please: The Market Microstructure Of Investor Attention

May I Have Your Attention, Please: The Market Microstructure Of Investor Attention. Christopher Fink and Thomas Johann Discussion by Georges Hübner 7th Financial Risks International Forum BIG DATA IN FINANCE AND INSURANCE, Paris March 20-21, 2014. Summary and contributions.

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May I Have Your Attention, Please: The Market Microstructure Of Investor Attention

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  1. May I Have Your Attention, Please:The Market Microstructure Of Investor Attention Christopher Fink and Thomas Johann Discussion by Georges Hübner 7th Financial Risks International Forum BIG DATA IN FINANCE AND INSURANCE, Paris March 20-21, 2014

  2. Summary and contributions • The paper adapts and extends the Easley et al. (1996) model of market microstructure to add two states related to investors’ attention. • A measure of Financial Google Insights Search Volume Index (SVI) is introduced to refine the way investor’s attention is measured • Based non this extension, the PIN measure is estimated for high and low attention stocks • Further tests on other classical liquidity measures show that F-SVI captures some element of investors’ attention. When applicable, the F-SVI provides information on investor attention that dominates the classical SVI variable • The results are unfortunately not yet very supportive at this moment • Results are significant only for small stocks. The PIN measure is very close for high and low attention stocks • Significance of F-SVI in regressions can only be tested for a limited set of firms 2 May I Have Your Attention, Please: The Market Microstructure of Investor Attention Discussion at BIG DATA IN FINANCE AND INSURANCE, Paris, March 20

  3. Comments - 1 Theoretical setup • The extension to the Easley et al. model is too narrow and straightforward. • It does not provide a rationale for the coexistence of two opposite hypotheses: • H2a: High attention  higher liquidity because MM covers info asym losses with gains from uninformed traders • H2b: High attention  lower liquidity because informed traders hide between order flows • As the results are inconclusive to validate either H2a or H2b then there are three possibilities (non exclusive) • The model is incomplete: it should identify situations favoring H2a and H2b, e.g. by capturing situations or stocks for which information asymmetry is highest • The period and/or sample of firms pools contrasted situations, therefore drowning the information. For instance, the effect might be different for value and growth stocks beyond the market cap criterion • The variable measuring investor attention features too much noise. A possibility would be to use a moving average or a relative F-SVI 3 May I Have Your Attention, Please: The Market Microstructure of Investor Attention Discussion at BIG DATA IN FINANCE AND INSURANCE, Paris, March 20

  4. Comments - 2 Data & models • The data is too old (but the authors know it) but also the period 2003-07 is not particularly exciting. • There is obviously a timeline effect, and a strong impact of HFT in the extent of noise trading capture • Is it possible to integrate a mean-reverting component of the prices of high attention stocks? Consistent with prospect theory, one would expect the underreaction effect to be stronger • In general, where’s the causality? • Do highly skewed stocks behave very differently from other ones? Writing style • Avoid being to assertive and relying too much on conjectures. 4 May I Have Your Attention, Please: The Market Microstructure of Investor Attention Discussion at BIG DATA IN FINANCE AND INSURANCE, Paris, March 20

  5. The Impact of Media on Corporate Social Responsibility Jingoo Kang & Andy Kim Discussion by Georges Hübner 7th Financial Risks International Forum BIG DATA IN FINANCE AND INSURANCE, Paris March 20-21, 2014

  6. Summary and contributions • The paper discusses the relation between negative public opinion and subsequent firm CSR efforts, mostly related to the Philantropic Contributions • Two hypotheses are tested: • The shareholder value maximization hypothesis (ShMax): PC is an agency problem, so this behavior is mostly observable amongst firms with poorer governance • The stakeholder value maximization hypothesis (StMax): PC shows a commitment towards all the firm’s stakeholders, so this should improve long term performance • The results are consistent with the StMax • Positive and significant impact of article negativity on PC spending • Even though the event study on PC announcements show no significant AR on average, the event-specific level of AR also supports the StMax • Various other metrics (proba of appointment as indep director, market share change, Tobin’s Q) also confirm the previous results 6 The Impact of Media on Corporate Social Responsibility Discussion at BIG DATA IN FINANCE AND INSURANCE, Paris, March 20

  7. Major comments • This is not really a horse race, as there is no discriminant model setup. In the main model [equation (2)], the StMax is tested directly while the ShMax is tested only through indirect indicators of CG. • Perhaps the ShMax could be further developed to yield an alternative testable hypothesis. The agency issue could be only one amongst the many manifestations of a behavior that leads to shareholder value reduction • The contrast between StMax and ShMax might not be the proper one. • Looking at ShMax, the consequence is a long-term improvement of all stakeholders’s satisfaction, including shareholders  LTSh+ • Looking at ShMax, the agency issue might not be the CEO vs the shareholders, but the Board vs the stakeholders (PC=diversion), leading to a short term improvement of equity but a l.t. damage LTSh- • This calls for a longer horizon in the measurement of the variables. Why not looking for the DV at the EWMA of subsequent PC spending, and for the IV at the evolution of shareholder value? 7 The Impact of Media on Corporate Social Responsibility Discussion at BIG DATA IN FINANCE AND INSURANCE, Paris, March 20

  8. Othercomments • This is a static approach: negative coverage  subsequent CSR reaction. Then what can happen? • Will the firm react similarly the next time negative news is again conveyed? • Will the probability of having negative subsequent media coverage be altered? • Will the impact of negative news change? • Does the destination (in terms of sector), trend and length of PC matter? • Is the R&D relative to sales really a control? Again, the destination of the funds matter as R&D intensive firms get potentially better links with the research community if philanthropic actions help fundamental research, for instance 8 The Impact of Media on Corporate Social Responsibility Discussion at BIG DATA IN FINANCE AND INSURANCE, Paris, March 20

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