

Introduzione
in Italiano
E' una
famiglia di software che fornisce una integrata soluzione
per coloro che hanno necessità di effettuare analisi econometriche
di serie temporali, modellazione econometrica finanziaria
o analisi statistiche di crosssection e panel data.
Sempre più utilizzatori nel mondo stanno apprezzando la potenza
e la versatilità di OxMetrics, la famiglia di software
che fornisce una integrata soluzione per coloro che hanno
necessità di effettuare analisi econometriche di serie temporali,
modellazione econometrica finanziaria o analisi statistiche
di crosssection e panel data.
I software
OxMetrics possono essere acquistati anche separatamente.
Ox
è un software di sviluppo objectoriented
basato su un potente linguaggio matriciale arricchito da una
completa libreria di funzioni statistiche. I punti di forza
di Ox sono la sua velocità, il ben costruito editor e le sua
funzionalità grafiche. Ox può leggere e scrivere dati in molti
formati, inclusi fogli elettronici; inoltre può utilizzare
direttamente programmi scritti in Gauss.
Cats è un completo software per la cointegrazione di analisi di serie temporali.
PcGive
è un completo software per la modellazione
econometrica. Fornisce agli utilizzatori le più recenti tecniche
econometriche: dai metodi ad equazione singola fino all'analisi
cointegrata avanzata, modelli volatili (tra cui GARCH, EGARCH),
panel data statici e dinamici, serie temporali (come ARFIMA,
X12ARIMA per aggiustamenti stagionali), ecc.
Stamp è un software per la modellazione e il forecast di serie
temporali basato su modelli strutturati di serie temporali.
Questi modelli utilizzano tecniche avanzate, come il Kalman
filtering, ma sono strutturati per poter applicare con estrema
semplicità i concetti base di trend, stagionalità e irregolarità.
G@rch
è il software della famiglia OxMetrics dedicato
alla stima e alla modellazione di modelli G@rch e di tutte
le numerose estensioni. Per operazioni ripetitive i modelli
posso essere stimati utilizzando il Batch Editor di GiveWin
o il linguaggio di programmazione Ox (insieme al software
sono forniti numerosi file di esempio).
G@rch è accompagnato da un manuale cartaceo che raccoglie
i più importanti contributi in questo campo.
TSP/GiveWin è uno dei software econometrici della suite OxMetrics e offre
i seguenti punti di forza:
è dotato di un ottimo sistema di inserimento dei comandi e
dei dati; include tutti i metodi standard per la stima e il
forecasting (incluso il metodo non lineare); include un flessibile
linguaggio di programmazione per la creazione di parametri
di stima personalizzati.

OxMetrics is a family of of software packages
providing an integrated solution for the econometric analysis of time
series, forecasting, financial econometric modelling, or statistical
analysis of crosssection and panel data. OxMetrics consists of a
frontend program called OxMetrics, and individual application modules
such as Ox, CATS, PcGive, STAMP and G@RCH.
OxMetrics Enterprise is a single product that includes all the
important components: OxMetrics desktop, Ox Professional, CATS, PcGive
and STAMP and G@RCH
The new release of OxMetrics 8 contains upgraded versions of Ox Professional, PcGive and G@RCH, a new version of CATS 3 (Cointegration of Time Series
Analysis by Jurgen A Doornik and Katerina Juselius) and several
improvements to the following modules:
OxMetrics Enterprise Edition Version 8.0
OxMetrics Enterprise Edition is a single product that includes and
integrates all the important components for theoretical and empirical
research in econometrics, time series analysis and forecasting, applied
economics and financial time series: Ox Professional, PcGive, G@RCH and
STAMP.
CATS 3 (Cointegration of Time Series Analysis) by Jurgen A Doornik and Katerina Juselius
CATS uses OxMetrics for data input and graphical and text output, and is part of the OxMetrics family.
The third generation of CATS is a complete rewrite in more than one
way. It is now written in Ox for use within OxMetrics, either using the
graphical user interface or programmatically. Furthermore, many
algorithms have been improved or newly invented, in particular for I(2)
models. The new CATs module with I(2) cointegration and many new I(1)
cointegration features includes corrections and is considerably faster.
Ox Professional Version 8.0
An objectoriented matrix programming language. It is an important
tool for statistical and econometric programming with a syntax similar
to C++ and a comprehensive range of commands for matrix and statistical
operations. Ox is at the core of OxMetrics. Most of the
other modules of OxMetrics (such as PcGive, STAMP, G@RCH) are
implemented with the Ox language. Ox Professional belongs to theOxMetrics Enterprise Edition.
PcGive Professional Version 15.0
An essential tool for modern econometric modelling. PcGive Professional is also part of OxMetrics Enterprise Edition.
It provides the latest econometric techniques, from single equation
methods to advanced cointegration, volatility models static and dynamic
panel data models, discrete choice models and timeseries models.
PcGive Professional includes Autometrics
Autometrics is the automatic econometric model selection procedure
that is available in PcGive. Autometrics is a revolutionary new approach
to model building, based on recent advances in the understanding of
model selection procedures. Experiments show that Autometrics
outperforms even the most experienced econometrician. Starting from an
initial model, Autometrics will find the best simplified model. Thus
removing the drudgery of model selection, allowing you to concentrate on
the variable choice and interpretation of the model(s).
G@RCH Version 8.0
G@RCH is an OxMetrics module dedicated to the estimation and forecast
of univariate and multivariate ARCHtype models. It also allows the
estimation of univariate and multivariate nonparametric estimators of
the quadratic variation and the integrated volatility. G@RCH provides a
menudriven easytouse interface, as well as some graphical features.
For repeating tasks, the models can be estimated via the Batch Editor of
OxMetrics or using the Ox language together with the ‘Garch’, ‘MGarch’
and ‘Realized’ classes. Version 8.0 is a major update that features many
improvements. G@RCH is also part of OxMetrics Enterprise Edition.
STAMP Version 8.3
Modelling and forecasting time series, based on structural time series models.
These models use advanced techniques, such as Kalman filtering, but are
set to be easy to use. The hard work is done by the program, leaving
the user free to concentrate on formulating models, then using them to
make forecasts. STAMP 8.3 includes both univariate and multivariate
models and automatic outlier detection. STAMP is also part of OxMetrics Enterprise Edition.
SsfPack Version 3.0
SsfPack is a suite of C routines for carrying out computations
involving the statistical analysis of univariate and multivariate models
in state space form and requires Ox 4 or above to run. SsfPack is not a
member of OxMetrics Enterprise Edition.
* OxMetrics 8 and SSfPack users please note: SSfPack
3.0 has been recompiled to be compatible with OxMetrics 8 and requires
users to reinstall a new version of the software.
TSP/OxMetrics
Developed by TSP International, TSP/OxMetrics is an econometric
software package, with convenient input of commands and data, all the
standard estimation methods (including nonlinear), forecasting, and a flexible language for programming your
own estimators. TSP can be installed as a module of OxMetrics 
TSP/OxMetrics. This eases the use of the commandline environment by
providing context sensitive help, syntax highlighting, and a
dialogdriven command builder.
Individual or any combination of OxMetrics modules are available for purchase.
What's New in OxMetrics 8 




OxMetrics 8 (front end)
The following lists the new features and improvements made to the
OxMetrics front end in version 8. Current users of OxMetrics 7 will find
that the user experience remains familiar.
The most important new features are:
 Windows: support for high resolution screens (HiDPI).
 Windows: tabbed user interface.
 All: interface refresh.
 macOS: OxMetrics is now a 64bit program, so client programs are now 64bit as well.
 maxOS: Find replace dialog can remain open while working elsewhere.
 Graphs can be saved as SVG.
>Back to top
CATS 3 (Cointegration of Time Series Analysis) by Jurgen A Doornik and Katerina Juselius
CATS uses OxMetrics for data input and graphical and text output, and is part of the OxMetrics family.
The third generation of CATS is a complete rewrite in more than one
way. It is now written in Ox for use within OxMetrics, either using the
graphical user interface or programmatically. Furthermore, many
algorithms have been improved or newly invented, in particular for I(2)
models. The new CATs module with I(2) cointegration and many new I(1)
cointegration features includes corrections and is considerably faster.
Here is a brief summary of new features in the I(1) part of CATS
 Much more efficient computations (can be several orders of magnitude faster) in Bartlett correction and recursive estimation;
 Bartlett correction always included when valid;
 Improved betaswitching algorithm;
 New alphabetaswitching algorithm allowing linear restrictions on alpha and not requiring identification;
 Bootstrap of rank test;
 Bootstrap of restrictions;
 More Monte Carlo facilities: draw from estimated model, either with estimated or with specified coefficients;
 Generaltospecific CATSmining;
 Automatic generation of Ox code;
 New convenient way to express restrictions;
 Most algorithms QR based.
And for the I(2) part of CATS:
 Improved tauswitching algorithm;
 New deltaswitching algorithm;
 New triangularswitching algorithm allowing linear restrictions on alpha, beta, tau and not requiring identification;
 Estimation with delta=0;
 Bootstrap of rank test;
 Simulation of asymptotic distribution of rank test;
 Bootstrap of restrictions;
 More Monte Carlo facilities: draw from estimated model, either with estimated or with specified coefficients;
 Automatic tests of unit vectors and variables;
 CATSmining;
 Improved computation of standard errors;
 Automatic generation of Ox code;
 All algorithms QR based.
The Special Issue reprint book "Recent Developments in Cointegration"
has been published online and is freely accessible on the MDPI Books
platform here
>Back to top
Ox
Ox is an objectoriented matrix programming language with a
comprehensive mathematical and statistical function library. Matrices
can be used directly in expressions, for example to multiply two
matrices, or to invert a matrix. The major features of Ox are its speed,
extensive library, and welldesigned syntax, which leads to programs
which are easier to maintain.
Running Ox programs
There are two versions under Windows:
Ox Professional
oxl.exe for use in a command prompt (console) window, oxrun.exe for
full graphical functionality in conjunction with OxMetrics. The oxrun
and oxli programs have an interactive and debug mode. Executables are in
ox\bin.
Ox Console
oxl.exe for use in a command prompt window.
New Features and enhancements in Ox Version 8.0
 Changes to
Modelbase mean that oxo files of Modelbase derived classes need to be recompiled:
GetOx* functions have additional sClass argument; also introduced GetOxDecl,GetOxDatabase .
Y_VAR
constants have been moved into the class (derived classes should do the
same with their constants). This avoids clashes when using multiple
classes in one project. So we need to write (e.g.)
model.Select(Arfima::Y_VAR, ...
instead of
model.Select(Y_VAR, ...
For convenience a mechanism has been added to use strings instead of constants:
model.Select("Y", ...
model.SetMethod("NLS");
To support this, Modelbase has two new virtual functions FindGroup,FindMethod which rely on the new virtual functions GetGroupLabels,GetMethodLabels . The derived class should override GetGroupLabels,GetMethodLabels to return the correct array of strings.
 Can save graphs as SVG file.
savesheet to save twodimensional array as Excel file (counterpart to loadsheet)
 Improved handling of array entries with no value
(.Null) :
 when created using new, array elements will be
.Null
 can test
.Null equality (only) using arr[i] == .Null
 can assign
arr[i] = .Null
 but using a variable with a
.Null value in an expression remains a runtime error.
 The three dots in a function header, indicating variable number of arguments, can now be followed by a variable name. E.g:
func(...args)
{
decl a = 1;
}
is convenient shorthand for
func(...)
{
decl args = va_arglist();
decl a = 1;
}
(Unless used in main, as in main(...args), in which case arglist is called to get the command line arguments.)
 Three dots in a function call spreads an array, so
func1(...a) equals func1(a[0], a[1], a[2]) if a is an array with three elements. The array cannot have more than 256 elements.
 Read Stata 13 and 14 .dta files.
 Can skip items in multiple assignment, as well as use it in decl, e.g.
decl [a, b, c] = {1, 2, 3};
[a,,c] = {1, 3};
 %#v on array of strings: omit top level {} (useful for generating code)
fwrite/fread can have a filename as the first argument. E.g.,
fread("filename", &s, 's') reads an entire file into one string,
fwrite("filename", s) saves a string as a file.
diagcat(a, b, ...); to concatenate more than two matrices.
 Added pvalue format for printing: e.g.
print("%9.3P", 1e6) prints
"[0.000]***" . The format is three stars for significance below 0.001, two for below 0.01, one for below 0.05.
 The default line length for output is now 1024 (was 80 before). This can be changed using the
format function.
 using G,E,F format to print . for .NaN.
 Added %rs and %cs to matrix format to specify row and column separator
Fixed Problems in Ox version 8.0
 confusion with norm: using 'F' on vector computes l_70 instead of l_2, now using l_2 for 'F' (assuming l_70 is never needed).
 continue in switch can lead to stack overflow (missing a pop).
 It is safe to redeclare constants within a class (provided they
don't change value), but that symbol was counted eventhough not added,
resulting in NULL symbol at the end of the list of class symbols, which
crashed.
>Back to top
G@RCH 8.0
 The G@RCH book is now available in pdf accessed from within the software.
 G@RCH 8.0 comes along with Ox Professional. This major change
allows G@RCH users, who previously did not purchase OxMetrics
Enterprise, to run ox programs and in particular the numerous example
files provides with G@RCH as well as the codes generated with ‘ALT+o’
after the estimation of a model with the rolling menus.
 A new option is available for the Lee and Mykland (2008) and Lee
and Hannig (2010) tests for jumps. This option allows both tests to have
better finite sample properties when the underlying process deviates
from the random walk hypothesis (with and without jumps). The correction
has been proposed by Laurent and Shi (2018).
 Following the simulation method advocated by Blasques, Lasak,
Koopman, and Lucas (2016), insample confidence bands for the
conditional mean and conditional variance of univariate GARCHtype
models are now available. This allows to visually investigate the
precision of the estimates of the first two conditional moments.
 The tool introduced in version 7.0 to convert a date of the format
yyyymmdd, yyyyddmm, ddmmyyyy or mmddyyyy into a proper OxMetrics format
is now also accessible via the rolling menus in Category ‘Other Models’
and Model Class ‘Convert Date using G@RCH’.
 A bug has been corrected in MGarch on the inclusion of explanatory variables in the mean and variance of DCCtype of models.
 The G@RCH classes (Garch, MGarch and Realized) uses enumerations,
i.e., lists of integer constants like enum { HESS, CROSSPRODUCT, QMLE
};. By default, the first member has value 0, and each successive member
has a value of one plus that of the previous member. In order to avoid
clashes with other classes imported in the same project, enumerations
have been moved into the classes as public members. Therefore, they can
still be accessed from outside of the class but using the following
convention: mgarchobj.MLE(MGarch::HESS); (where MGarch is the class
name) instead of mgarchobj.MLE(HESS); like in the previous versions.
Note that this is equivalent to using mgarchobj.MLE(0); because HESS is
the first element of the enumeration.
 The test for additive jumps in ARGARCH/GJR models proposed by
Laurent, Lecourt, and Palm (2016) is available in Category ‘Other
Models’ and Model Class ‘Descriptive Statistics using G@RCH’ and by
calling the new class function Run Test Additive Jumps of the Garch
class or the RGARCH class directly (which is available in the same
folder as Garch.oxo). Several example files are also provided to
estimate a BIPARGARCH/GJR model and to extract the detected jumps in
ox.
 Several minor bugs have been corrected.
>Back to top
PcGive 15
Fixed and Improved in PcGive 15
 Easier desktop layout with additional direct access to recursive graphs, forecasts and tests
 Trend indicator saturation (TIS) (we have undertaken research using
TIS on GPs speed of takeup of generics, which yielded useful results,
but still in progress, as is the technical paper)—note this as PcGive
being at the frontier implementing powerful new approaches
 Recursive graphs can be implemented after conventional estimation
rather than needing a separate implementation, and can be undertaken
with or without indicator saturation (IS)
 Additional diagnostic plots are available
 Easy choice of form of estimated parameter standard errors (SEs) including HCSE and HACSE.
 Multivariate robust Hedgehog plots had variables scrambled.
 Hedgehog plots use a different color in the forecast period.
 Hedgehog Levels forecasts beyond estimation sample: not integrated
 Levels forecasts with gap: created cGap extra forecasts Also used wrong levels if cGap > 0.
 Recursive hedgehog would omit early part when there are dummies
 Fixed Ox issue with find, affecting forecasting
Unique to PcGive 15
 Hedgehog graphs where a sequence of forecasts for say 1 through 8
steps ahead starting at successive horizons T, T+1, etc. are plotted
against outcomes looking like the spins of a hedgehog.
 Easily computed forecasts by a robust device as an additional choice
to avoid that problem: an illustration is attached showing how much
better the robust device is after a shift.
>Back to top
STAMP 8.3
New Features
 STAMP 8.3 works under OxMetrics 6.1.
 The Ox code generator is introduced and fully supported by STAMP.
This new facility can generate Ox code for the model that is estimated
in STAMP. It complements the Batch code generator in STAMP. It is
particularly useful for those who use Ox for time series analysis in a
production environment.
 The online help facility of STAMP is updated. In particular, the
online help for the Batch language and the new Ox code generator are
rewritten.
Solved problems
 All weights and related computations in the Test/Weights dialog can be carried out, also for time series with missing data.
 The Write forecasts option is combined with a Store forecasts
option in the Test/Forecasting dialog. The observations forecasts are
stored after confirmation as a new variable with the forecasts attached
at the end of the sample. When necessary, the database sample is
automatically extended such that the forecast window is included. The
insample values of the new variable are the same as in the original
series.
 The Edit/Save forecasts option in the Test/Forecasting dialog is reactivated for model without explanatory variables.
 The Batch code options for Forecasting is extended; see Batch documentation.
 Variables and components in the Batch code need to be written
between accolades. Specifically, in the setcmp batch command we have
"level", "slope", "seasonal", "cycle", "ar" and "irregular".
 Inclusion of lagged dependent variables is discouraged. A new
facility will be built in for the next version. In this version it is
best to treat and to have it as an exogenous variable.
>Back to top
The current OxMetrics software family
supports the latests versions of Microsoft Windows, Mac OS and Linux.
See below to see if your machine is compliant with the latest version:
 32bit: Windows 10, 8, 7, Vista, XP; Linux (i386); OS X
 64bit: Windows 10, 8, 7, Vista, XP; Linux (x86_64); OS X
