Titlebook: Handbook of Financial Econometrics and Statistics; Cheng-Few Lee,John C. Lee Reference work 2015 Springer Science+Business Media New York

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https://doi.org/10.1007/978-3-0348-5670-6for instantaneously collected massive amounts of tick-by-tick data from financial markets for information analysis and knowledge extraction. Inefficient decomposition of the systematic pattern (the trend) and noises of financial data will lead to erroneous conclusions since irregularities and roughn

FATAL

https://doi.org/10.1007/978-3-658-11296-7pectral analysis and filtering methods. Spectral analysis can be used to identify and to quantify the different frequency components of a data series. Filters permit to capture specific components (e.g., trends, cycles, seasonalities) of the original time series. Both spectral analysis and standard

OVER

Experience, Information Asymmetry, and Rational Forecast Bias,st’s rational bias increases with information asymmetry, but is concavely related with experience. Novice analysts post estimates similar to the consensus but as they become more experienced and develop private information channels, their estimates become biased as they deviate from the consensus. H

Harness

An Appraisal of Modeling Dimensions for Performance Appraisal of Global Mutual Funds,00) provide evidence of short-term performance persistence in high-yield bond mutual funds. In their studies of money market mutual funds, Domian and Reichenstein (.) find that the expense ratio is the most important factor in explaining net return differences. Christoffersen (.) shows that fee waiv

Irascible

白楊

FELON

Nonparametric Bounds for European Option Prices, (2006); calculate the dollar beta of the option and expected payoffs of the index and the option; and eventually obtain our bounds. We discover violations in our lower bound and show that those violations present arbitrage profits. In particular, our empirical results show that out-of-the-money cal

機(jī)密

JUST

Market-Based Accounting Research (MBAR) Models: A Test of ARIMAX Modeling,on, model II (returns on change in earnings divided by beginning-of-period price and prior period with MSE (minimum squared error) loss function in ARIMAX (2,0,2)) is prevalent. These models take place with backward-looking information instead of forward-looking information that recent literature is

LEVER

An Assessment of Copula Functions Approach in Conjunction with Factor Model in Portfolio Credit Riss (Hawkes. .(1), 83–90, 1971). Using the mixture factor-contagious-effect model, Monte Carlo simulation is performed to generate default times of two hypothesized firms..The goodness-of-fit of the joint distributions based on the most often used copula functions in literature including the normal, .