Use this URL to cite or link to this record in EThOS: | https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.260482 |
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Title: | Anomalies on the London Stock Exchange : the influence of the bid-ask spread and nonsynchronous trading | ||||||
Author: | Batty, Richard Andrew |
ISNI:
0000 0001 3451 4315
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Awarding Body: | Brunel University | ||||||
Current Institution: | Brunel University | ||||||
Date of Award: | 1994 | ||||||
Availability of Full Text: |
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Abstract: | |||||||
This thesis tests for seasonal anornalies and daily predictability on the UK stock market and investigates how mispricing caused by the bid-ask spread, known as the 'touch' and nonsynchronous trading in portfolio returns may explain these anomalies. By using constructed portfolios within a th-ne-series regression framework, I show that seasonality, in the first instance, is prominent in returns around the turn of the week and the turn of the year. However, this seasonal returns behaviour disappears when the touch is accounted for. Indeed, seasonality seerns to occur in the touch rather than returns. Despite this touch explanation, lagged returns remain significant, suggesting return predictability. In fact, when using a price adjustment model returns are predictable across portfolios. This predictability, while to some extent dependent upon firm size and the touch, may be accounted for by nonsynchronous trading. First-order autocorrelation and cross-autocorrelation found in returns proves more indicative of infrequent trading than return predictability. Thus, these results confirm that mismeasurernent in portfolio returns caused by market microstructure and nonsynchronous trading can create false inferences about the extent of stock market anornalies in the UK and subsequently, market efficiency.
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Supervisor: | Garrett, I. | Sponsor: | Not available | ||||
Qualification Name: | Thesis (Ph.D.) | Qualification Level: | Doctoral | ||||
EThOS ID: | uk.bl.ethos.260482 | DOI: | Not available | ||||
Keywords: | Seasonal anornalies ; Daily predictability ; Mispricing ; Portfolio returns ; Time-series regression framework | ||||||
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