In all investment decisions it is important to determine the degree of uncertainty associated with the valuation of a company. We propose an original and robust methodology to company valuation which replaces the traditional point estimate of the conventional Discounted Cash Flow (DCF) with a...

We analyse the behaviour of a non-linear model of coupled stock and bond prices exhibiting periodically collapsing bubbles. By using the formalism of dynamical system theory, we explain what drives the bubbles and how foreshocks or aftershocks are generated. A dynamical phase space...

This paper develops a method to improve the estimation of jump variation using high frequency data with the existence of market microstructure noises. Accurate estimation of jump variation is in high demand, as it is an important component of volatility in finance for portfolio allocation,...

This paper proposes a new method for estimating continuous-time stochastic volatility (SV) models for the S&P 500 stock index process using intraday high-frequency observations of both the S&P 500 index and the Chicago Board Options Exchange (CBOE) implied (or expected) volatility index (VIX)....

We propose a novel intraday instantaneous volatility measure which utilises sequences of drawdowns and drawups non-equidistantly spaced in physical time as indicators of high-frequency activity of financial markets. The sequences are re-expressed in terms of directional-change intrinsic time...

The empirical literature of stock market predictability mainly suffers from model uncertainty and parameter instability. To meet this challenge, we propose a novel approach that combines the documented merits of diffusion indices, regime-switching models, and forecast combination to predict the...

Because implied volatility is essential for pricing options, analyzing derivative strategies and measuring risk in investment portfolios containing derivatives, understanding variations in implied volatility also becomes vital. Aside from a secular trend, volatility clustering and calendar...

Most existing studies conclude that the accuracy of analysts' target prices is questionable. In forecasting target prices, analysts estimate a future stock price under the constraint of a time frame of usually 12 months. We exclude this source of uncertainty by focusing on valuations in takeover...

We examine the relative forecast accuracy of expected returns for individual stocks sourced from analyst target prices, earnings per share estimates, management forecasts, earnings yields, stock yields, historical averages and the random walk model. In doing so, we avoid the use of predictive...

We identify all return leader-follower pairs among individual stocks using Granger causality regressions. Thus-identified leaders can reliably predict their followers' returns out of sample, and the return predictability works at the level of individual stocks rather than industries. Our results...