Excel add-in for time series and statistics

	NumXL 1.68.7.1 Author: Spider Financial Corp Supported languages: English, Spanish Supported OS: Win2000 / WinXP / Win7 x32 / Win7 x64 / Windows 8 / Windows 10 / WinServer / WinOther / WinVista / WinVista x64 Price: $625.00

NumXL is a Microsoft Excel add-in for econometrics and data analysis, designed to make finance modeling and time series easier to manage. You can perform all of your data work right in Excel. NumXL allows you to apply advanced econometric analysis quickly and easily via an intuitive user interface. You can track and make changes to your data and share your analysis, modeling and results with just one file. In just a few clicks, you can analyze, build, validate, back-test and forecast your models. NumXL Functions are organized into 11 categories: - Descriptive Statistics - histogram, Q-Q plotting and autocorrelation function - Statistical Tests - mean, standard deviation, skew, kurtosis, normality, serial correlation (white-noise), ARCH effect, stationary and ADF unit root test. - Transformation - BoxCox, difference, integral operators - Smoothing - weighted moving average, exponential smoothing and trend - ARMA Analysis - conditional mean modeling (ARMA/ARIMA/ARMAX), AirLine, U.S. Census X-12-ARIMA support - ARCH/GARCH Analysis - conditional volatility and heteroskedacity modeling (ARC/GARCH/E-GARCH/GARCH-M) - Combo Models - log-likelihood, AIC, residuals diagnosis, parameters' constraints check, forecast, etc. - Factor Analysis - Generalized Linear Model - Date/Calendar - weekday and holiday calculations - Utilities - interpolation, statistical functions - Spectral Analysis - Discrete Fourier Transform NumXL Pro is compatible with all Excel versions from '97 to 2013 (34-bit and 64-bit) and with Windows 9x through Windows 8 systems.

Free NumXL download - 609 Kb numxl.exe

Keywords: numxl, excel, data analysis, time series analysis, econometrics, X-13ARIMA-SEATS, X-12ARIMA, seasonal adjustment, interpolation, DFT, FFT, discrete fourier transform, hurst exponent, smoothing, volatility, forecasting, KDE, Portfolio statistics