) risk premia in different frequency ranges. To achieve the identification, I employ the long-run projections and the … consumption risk premia in different frequency bands. I then perform the method on the US data across different asset classes. My …

Generalized Method of Moments (GMM) estimation procedure to cope with the documented difficulties of previous methodologies. We … foreign exchange markets. -- Random Lognormal cascades ; GMM estimation ; best linear forecasting ; volatility of financial …

objective of this work is to develop statistical inference tools, such as parameter estimation and linear hypothesis tests in … asset pricing models, with an emphasis on the Capital Asset Pricing Model (CAPM). An extension of the CAPM, the Multifactor …

has for the selection of pairs of cointegrated stock prices and for the estimation and prediction of the spread between … estimation and prediction of the spread - the deviation from the equilibrium relationship - which leads to better results in … terms of profit per capital engagement and risk than using a standard linear normalization …

risk and return of two pairs trading strategies: a conditional statistical arbitrage method and an implicit arbitrage one … model. Using this class of models and the proposed inferential technique, we are able to connect estimation and model … uncertainty with risk and return of stock trading. In terms of methodology, we show the effect that using an encompassing prior …

study---the first in the context of long-run risk modeling---we delineate the pitfalls associated with SMM estimation of LRR …The long-run consumption risk (LRR) model is a convincing approach towards resolving prominent asset pricing puzzles … model solubility and weak identification. We propose a two-step estimation strategy that combines GMM and SMM, and for which …

regularizing appropriate groups of coefficients. The second pass delivers risk premia estimates to predict equity excess returns …