The recent slowdown in global economic activity has shown that macroeconomic models without a well-structured representation of the financial sector will fail to provide understanding of the way that disruptions in credit markets, capital markets and banking can affect the rest of the economy. An investigation of foreign exchange speculation is used to get a better knowledge of the interaction between the financial sector and the economy as a step towards improving macroeconomic models and policy. The first part of this research looks at speculation at the macroeconomic level by using a structured vector auto regression (SVAR) to assess the relationship between capital flows and the US real exchange rate. The second assesses whether speculation can be used to identify price reversals in foreign exchange markets. The final section seeks to understand more about speculative risk with a detailed analysis of uncovered interest parity and the speculative attempt to take advantage of times when it does not hold. Speculative activity is a significant contributor to changes in the real exchange rate. No informational content is found in the extremes of speculative activity but it is shown that speculators are compensated for taking crash risk and that their activity may increase the amount of crash risk in the markets where they are operating. The main contributions of this work are applying a microstructure approach at the macro level; adding speculation to a model of international capital flows; the use of a unique series of options data to identify speculative sentiment; using a carry trade model to understand more about uncovered interest parity and the returns to speculation; using the event study method to investigate speculative extremes; and using all this to suggest ways to improve macroeconomic models and policy.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:608318 |
Date | January 2013 |
Creators | Hayward, Rob |
Publisher | University of Brighton |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Source | https://research.brighton.ac.uk/en/studentTheses/28e195b4-7c9d-4a0a-b4e5-6bc2d5878407 |
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