*international econometric journal
in Russian language*

*This jubilee issue
is dedicated to the 20th anniversary*

*of the New Economic
School*

Hill, Jonathan. Dependence and stochastic limit theory

In this essay we
provide the basic asymptotic theory that serves as background theory for
estimators in time series. We outline concepts of dependence used for
stochastic limit theory, covering mixing, mixingale and near epoch dependence
properties. We then detail some of the most general probability and
distribution limit theorems for these processes popularly employed for time
series theory and applications.

Marmer, Vadim. Linear processes: properties and asymptotic results

This
essay surveys results for linear time series including Wold decomposition,
properties of spectral density functions and lag operators, autoregressive
moving average models, Beveridge–Nelson decomposition, and Phillips–Solo device
for deriving asymptotics.

Anatolyev, Stanislav; Gospodinov, Nikolay. Asymptotics of near unit roots

Sometimes
the conventional asymptotic theory yields that the limiting distribution
changes discontinuously, or that the asymptotic distribution does not approximate
accurately the actual finite-sample distribution. In such situations one finds
useful an asymptotic tool of drifting parameterizations where certain
parameters are allowed to depend explicitly on the sample size. It proves
useful, among other things, for impulse response analysis and forecasting of
strongly dependent processes at long horizons. This essay provides a review of
these alternative asymptotic approximations in the context of time series
models.

We investigate
properties of the volatility estimator, which is proportional to the square of
oscillations of the bridge formed by the logarithm of the incremental price of
a financial instrument at a specified time interval. In the framework of the
geometric Brownian motion model for price increments we show by analytical
computations and statistical simulations that the proposed volatility estimator
by the bridge is much more efficient than the well-known Parkinson and
Garman–Class estimators. We also discuss possible usages of the estimators for
estimation of integrated volatility.

Rafalson, Andrey. Bootstrap inference about integrated volatility

We
extend the work of Gonçalves & Meddahi (2009) who suggest using the
iid and wild bootstrap for realized volatility instead of the asymptotic
approach in order to estimate integrated volatility. We propose the block
bootstrap and GARCH residual bootstrap approaches motivated by the persistence
of the intraday term structure of returns. Using

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