Titlebook: High Frequency Financial Econometrics; Recent Developments Luc Bauwens,Winfried Pohlmeier,David Veredas Book 2008 Physica-Verlag Heidelberg

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書目名稱High Frequency Financial Econometrics影響因子(影響力)




書目名稱High Frequency Financial Econometrics影響因子(影響力)學(xué)科排名




書目名稱High Frequency Financial Econometrics網(wǎng)絡(luò)公開度




書目名稱High Frequency Financial Econometrics網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱High Frequency Financial Econometrics被引頻次




書目名稱High Frequency Financial Econometrics被引頻次學(xué)科排名




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書目名稱High Frequency Financial Econometrics讀者反饋




書目名稱High Frequency Financial Econometrics讀者反饋學(xué)科排名

一瞥

盲信者

引起

Liquidity supply and adverse selection in a pure limit order book market,deling framework regarding marginal zero profit order book equilibrium and the parametric market order size distribution. We show that using average zero profit conditions considerably increases the empirical performance while a nonparametric specification for market order size combined with margina

刻苦讀書

Tidious

Order aggressiveness and order book dynamics,n order classification scheme, we model the most aggressive market orders, limit orders as well as cancellations on both sides of the market employing a sixdimensional autoregressive conditional intensity model. Using order book data from the Australian Stock Exchange, we find that market depth, the

旅行路線

Modelling financial transaction price movements: a dynamic integer count data model,relies on an autoregressive multinomial component for the direction of the price change and a dynamic count data component for the size of the price changes. Since the model is capable of capturing a wide range of discrete price movements it is particularly suited for financial markets where the tra

字謎游戲

The performance analysis of chart patterns: Monte Carlo simulation and evidence from the euro/dollant chart patterns: one built on 5-min close prices only, and one based on both 5-min low and high prices. We look for twelve types of chart patterns and we study the detected patterns through two criteria: predictability and profitability. We run a Monte Carlo simulation to compute the statistical s

Bouquet

Semiparametric estimation for financial durations,on generalized profile likelihood, which allows for joint estimation of the parametric—anACD type of model—and nonparametric components, providing consistent and asymptotically normal estimators. It is possible to derive the explicit form for the nonparametric estimator, simplifying estimation to a

GULP