This dissertation considers a range of topics on the use of range-based risk estimators for financial markets (with the exception of Chapter 5 discussed below). Chapter 1 provides an introduction to the existing literature and the research objectives of the dissertation. Chapter 2 uses time series of daily high-low ranges of national equity market indices to analyse daily volatility dynamics and volatility spillover across four European markets. Chapter 2 is based on the joint research with Gregory Connor. We develop a dynamic linear model of expected daily range which is a variant of Chou’s conditional autoregressive range model. We find significant, but not uniform, range-based volatility spillovers. During the crisis period (after July 2007) we find significant increases in daily range, increases in contemporaneous correlation, and increases in the influence of previous-day US market range on the conditional expected range of these European markets. A gamma-distribution-based model of realized daily range fits more closely than one based upon a Feller distribution, but it sacrifices the link to a specific distribution for underlying returns. In Chapter 3 we use information on the daily opening, close, high, and low prices of individual stocks to estimate range-based correlation and to construct a new estimator of market betas. We create a measure called “range-beta”, which is based on the daily range-based volatility and covariance estimators of Rogers and Zhou (2008). These range-based betas reflect the current day’s intra-day price movements. They avoid a weakness of return based betas, which typically are based on close-to-close returns. Our approach yields competitive estimates compared with traditional methodologies, and outperforms other methodologies when analysing highly liquid assets. Chapter 4 studies the relationship between options-implied and realized-range-based volatility estimates for Euro area countries. When both implied volatility and historical range-based volatility are used to forecast realized range-based volatility, we find that implied volatility outperforms historical range-based volatility. We also find that the stochastic volatility is priced with a negative market price of risk. The volatility implied from option prices is higher than the realized range-based volatility under the objective measure due to investor risk aversion. Chapter 5 considers financial market risk from a different perspective. Chapter 5 analyses the tone and information content of the two external policy reports of the Internal Monetary Fund (IMF), the IMF Article IV Staff Reports and Executive Board Assessments, for Euro area countries. In particular, we create a tone measure denoted WARNING, based on the existing DICTION 5.0 Hardship dictionary. We find that in the run-up to the current credit crises, average WARNING tone levels of Staff Reports for Slovenia, Luxembourg, Greece, and Malta are one standard deviation above the EMU sample mean; and for Spain and Belgium, they are one standard deviation below the mean value. Furthermore, on average for Staff Reports over the period 2005-2007, there are insignificant differences between the EMU sample mean and Staff Reports’ yearly averages. We also find the presence of a significantly increased level of WARNING tone in 2006 for the IMF Article IV Staff Reports. There is also a systematic bias of WARNING scores for Executive Board Assessments versus WARNING scores for the Staff Reports.