On aspects of inflation in the context of commodity and futures market

HB Economic Theory;HG Finance

Mao, Yixiao ; Ewald, Christian

University:University of Glasgow

Department:Adam Smith Business School

关键词: inflation-linked derivatives, commodity futures, state-space model, Kalman filter, inflation forecasting, commodity futures options, Monte Carlo simulation, implied volatility, inflation risk premium.;   

Others  :  http://theses.gla.ac.uk/30878/1/2018MaoPhD.pdf

来源: University of Glasgow

【 摘 要 】

This thesis has developed alternative approaches for inflation forecasting and analysed the inflation risk premium in the context of commodity futures and options markets.Chapter 1 proposes an approach to tackle the non-availability of exchange-traded inflation futures price data. The composition of the consumer price index enables us to recognise the commodities which correspond to the consumption goods in the CPI. By averaging the commodity futures prices in the same way as the CPI is composed, we construct a synthetic futures contract written on the consumer price index, i.e. a futures on the CPI proxy, based on which we derive a ‘point’ forecast of inflation rate.Chapter 2 analyses the term structures of futures on the CPI proxy using the Schwartz (1997) method. Inspired by the Schwartz (1997)’s framework, we develop a two-factor valuation model filtering the spot consumer price index and the instantaneous real interest rate. The Kalman filter is applied to estimate the two-factor valuation model parameters. The filtered spot consumer price index may help alleviate the publication lag in the U.S. CPI-U index. What’s more, the two-factor valuation model is capable of forecasting the downward trend in the U.S. CPI inflation rate during May 2014 to December 2014.Chapter 3 forecasts the inflation rate from the perspective of commodity futures option market. We construct a synthetic option contract written on the futures on the CPI proxy. Based on a synthetic option implied volatility surface, we derive an interval estimate for the one-year ahead expected inflation rate. Moreover, the fact that commodity futures option market data is high-frequency enables our method of inflation forecasting to theoretically capture the market expectation of price level evolution in the real time.Chapter 4 estimates the inflation risk premium using commodity market data. We derive a link between the inflation risk premium and the risk premium associated with the futures on the CPI proxy. The negative inflation risk premium estimates in our result are consistent with the recent inflation risk premium estimates in the macroeconomic inflation risk premium literature.