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The information content of analysts recommendations. V a dim Surin International Financial Laboratory. The plan. Importance Buy-side/sell-side difference Typical research questions Prior evidence Our dataset and method Why our method is better Results Discussion What’s next?.

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the information content of analysts recommendations

The information content of analysts recommendations


International Financial Laboratory

the plan
The plan
  • Importance
  • Buy-side/sell-side difference
  • Typical research questions
  • Prior evidence
  • Our dataset and method
  • Why our method is better
  • Results
  • Discussion
  • What’s next?
why it s important
Why it’s important
  • The goal of market is timely and accurate reflection of relevant information in prices
  • Market is efficient, if it manages with it (efficient-market hypothesis)
  • Market manages, if there are a lot of self-dependent members, whose
    • careful exanimate information about assets.
    • quickly translate results of researches in transactions.
  • There are sell- and buy-side analysts on the stock market.
buy side sell side difference
Buy-side/sell-side difference
  • Buy-side analyst gives closed recommendations for institutional investors
    • reward is directly dependent on the success of the recommendations
    • there is no motivation to report recommends to the market
  • Sell-sideanalyst gives recommendations to buy-side investor. Buy-side analyst has executeda trade with this recommendations.
    • reward is directly dependent on the volume of transactions
    • an indirect motivation to do qualitative research
    • agreat motivation to report recommendations to the market
  • Buy-side data are closed, sell-side – are opened
  • But for the effective market are important both
typical research questions
Typical research questions
  • Do analysts add value on individual and aggregated value?
  • Do analysts add value in excess of publicly available information?
  • Is there any asymmetry in value, added by foreign/local, developed/emerging, buyside/sellsideanalysts?
  • Is there any signof price manipulation?
  • Are analysts biased?
  • What determines [un]successful recommendation?
prior evidence 2000 2013
Prior evidence: 2000-2013
  • “glamour” stock effect
    • P/B ratio is the indicator for Buy and Strong Buy recommendation regressions
  • information in recommendations is largely orthogonal to the information in 8 other variables with proven ability to predict future stock returns
  • aggregated analyst recommendation relates to subsequent aggregate market change.
  • strategies, which combine the full analyst report and specific analytical outputoutperform the comparable
prior evidence 2000 20131
Prior evidence: 2000-2013
  • reaction to sell is greater than to buy
  • foreign analysts’ buy recommendations more informative than local (opposite held for sell recommendations)
our dataset and method
Our dataset and method
  • opinions are encoded and aggregated
    • strong buy = 5, strong sell = 1
  • quantile portfolios, rebalanced monthly
  • differential “abnormal” monthly return,
    • no a priori assumption about market model
  • KS-test on statistical significance of differences between return distributions of opinion portfolios
  • T-Student and Welsh tests on difference of returns between opinion portfolios and Q-Spread
  • “Sharpe ratio” rule of thumb
why our method is better
Why our method is better
  • Test analysts aggregated ability to predict individual stocks outperformance
  • Test just significance of difference between aggregated opinion portfolios,
    • no implied assumption, e.g. “positive = buy, negative = sell”
  • Minimum assumptions = robust
    • any market model, any distribution law
  • Relative = free from positive bias
  • Useful in practice, as can be directly replicated to profit from any pattern
  • Strong evidence of excess return, “earned” by analyst recommendation, is rare
  • Evidence of no difference in opinion portfolios returns is quite frequent
  • “opinion portfolios” serve rare free lunch to the market by providing diversification venue
  • Possible reason for insignificance of “opinion portfolios” profits
    • market doesn’t respond to analyst recommendation
    • responds too fast to be captured by our method
      • marked is liquid and profit is arbitraged away before the end of the month
        • participants are “too rational”: well-informed, well-equipped
      • low liquidity: arbitraged away by one or two rational participants, others abstain due to high prices
what s next
What’s next?
    • the speed of price adjustment
    • daily? high-frequency?
    • “trading” back-test
  • what makes market “efficient”
    • liquidity impact
    • capital flows impact
  • the level of the consensus adds value only among stocks with positive quantitative characteristics
    • perhaps, markets that failed in our research had negative characteristics prevailing all the time
  • How to measure “closeness” of opinion portfolios returns
    • slightly positively skewed, almost-normal (with several negative outliers)
    • any distance metrics, like Mahalanobis?