Overconfidence and Prediction Bias in Political Stock Markets

1
Overconfidence and Prediction Bias in Political
Stock Markets

• Carsten Schmidt
• (joint work with Michael Berleman, ifo Institute
  Dresden)

2
The Puzzle

• US political stock markets were very successful
  in predicting the election results
• IEM predict result of the presidential election
  Bush/Dukakis 1988 with a MAE of 0.2 (Forsythe et
  al., 1992, AER)
• Forsythe et al., 1997, JEBO
• European election markets were not
  (significantly) better than polls. Relatively
  higher MAE compared to US markets.
• Netherlands Jacobsen et al., 2000, EER
• Austria Ortner
• Sweden Bohm and Sonnegard, 1999, ScanJE
• Germany Berlemann und Schmidt (this meta-study)
• MAE PSM 1.394, Polls 1.524, (T1.198, p lt0.126)

3
Driving forces

• Institutions
• Election system
• Proportional representation vs. Winner- takes-all
• Polls
• Adjusted vs. raw data
• Market level market complexity
• Empirical contribution (Berg et al., 1997)
• Number of different contracts (candidates/parties)
  is highly correlated with MAE
• Contract level overconfidence Bias
• Theoretical contribution (Jacobsen et al., 2000,
  EER
• Overvaluation of small contracts, undervaluation
  of relatively large contracts
• Disparity of different contracts
• Bias not significant in US data (Forsythe et al.,
  1999, JEBO)
• Trader level
• Individual mistakes do not bias prediction in US
  data

4
A benchmark poll prediction

• In the US poll data is reported raw
• Prediction error of PSM is significant smaller
• European pollster report corrected data
• Correction is a black box, pollster use different
  approaches
• Prediction error of German PSM is slightly
  smaller (marginal significant)

Party Allensbach raw data Allensbach prediction Election result
CDU/CSU 38,8 43,5 44,5
SPD 46,5 43,5 42,9
FDP 11,1 10,0 10,6
Sunday question, German federal election 1980,
source Allensbach
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Meta study German data

• Method Empirical meta study
• Data Final prediction of all German election
  markets (and all corresponding public polls for
  the election)
• Vote share markets
• Homogeous in the number of contracts (parties)
• CDU,SPD,Grüne,FDP,PDS,Rep,Rest of Field
• Different organizer (academia, commercial)

6
Field data (meta study)
German data 17 Elections, 34 PSM 1990-2003 US data 16 Elections, 16 PSM Berg et al. (1997)
No of contracts K 5 - 7 2 - 6
Theil coefficient 0.41 0.16
No of Presidential or Federal Elections 4 3
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(No Transcript)
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German data contract level
9
Prediction error contract level

• Criterion
• vi true vote share of contract i
• K Number of different contracts

10
Prediction error contract level (2)
11
What makes markets predict well revisited market
level
12
Conclusions

• We find overvaluation of small contracts,
  undervaluation of relatively large contracts in
  German PSM data
• Bias not significant in US data (Forsythe et al.,
  1999 JEBO)
• Market level
• Market complexity in US data (Berg et al., 1997)
• Market complexity constant in German data
• Electoral uncertainty and market efficiency
• Contract level overconfidence bias
• Jacobsen et al. (2000) EER
• Overvaluation of small contracts
• Disparity of different contracts (not
  significant)

13
Implications for PSM

• PSM in Europe predict less successful than in he
  US because of the diversity of the vote shares
  and the complexity of the markets
• Polls in Europe predict more successful than in
  the US by correcting the raw data the poll
  instrument is not biased by diversity of vote
  shares and the complexity of the markets
• Market design implications
• Minimizing number of contracts
• Correcting for the diverse vote share bias

14
Error measures
15
Theory

• Assumption Trade is not driven by different
  preferences, but by individual information of the
  traders about the election result
• v(1-v) is the unknown, true vote share of party
  P1(P2)
• Each trader receives a private signal si ?
  v-e,ve

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Theory (2)

• Definition p p11-p2
• Buy P1 if market price p1ltsi
• Buy P2 if market price p2lt1-si
• In equilibrium p is determined that the demand
  for both parties is equal
• Assumption traders have the same endowment E
• Signal siltp ? buy E/p contracts P1
• Signal sigtp ? buy E/(p-1) contracts P2

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Predictions on contract level

• p(v e)/(12e)
• Winner of the election
• if vgt1/2 that means pgt1/2
• Only if v1v21/2 p is an unbiased estimator
• v1vgt1/2 ? p1pltvv1, p21-pgt1-vv2
• Large parties are undervalued, small parties are
  overvalued

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Predictions

• Market level
• Mean absolute error (MAE) increases with e
  Electoral uncertainty
• MAE increases when the vote shares become more
  unequal diversity of the vote shares
• Contract level

19
Number of contracts K2, e0.025
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Measure for more than 2 contracts

• MAE increases when the vote shares become more
  unequal
• Captured for instance by a Theil coefficient

21
Number of contracts K2, e0.025