NumXL 163 SHAMROCK Release

NumXL 1.63 SHAMROCKWhat’s New?

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Spider Financial

New Models ARIMA, SARIMA, ARMAX, and SARIMAX

Support for models with partial sets of lags

Simulation Model-driven simulation scenarios

Monte-Carlo simulation

New Goodness of fit measures Bayesian/Schwarz Information Criterion (BIC)

Hannan-Quinn Information Criterion (HQC)

NumXL 1.63 (SHAMROCK)Overview


Support for ARIMA, Seasonal ARIMA (i.e. SARIMA) , ARMAX, and SARIMAX models

Support for partial-set of lags or coefficients in the model

Revised functionality for calibration and estimating parameters errors

Modeling


Model-driven simulation scenarios

Support for any model (e.g. ARMA/ARIMA, GARCH, etc.)

Option to accept recent observations and/or realized volatility to initialize simulation process

Monte-Carlo Simulation

Designate new cell(s) as the simulation output(s)

Specify a workbook, worksheet or selected cells

range to re-evaluate during each run

Simulation



FAQ

Why did you develop model-based simulation?Answer: In many cases, the underlying ARMA process can be an input to a complex system. Alternately, we might be more interested in the path that the process follows rather than an end-point forecast value.

Examples:

1. Monthly sales process: an analyst wishes to forecast sales commissions for the following quarter.

2. Strategy's returns process: a trader is interested in estimating maximum draw.

What’s next?Answer: In this version, we have completed the key pieces needed for:

1. Model identification – Find the best model that fits the data

2. Model diagnosis – aka backtesting

How can I help?Answer: Let us know what you’d like to see in future NumXL releases:

www.spiderfinancial.com/forums

[email protected]

http://www.spiderfinancial.com/forums

Spider Financial Corp

1507 E 53rd St., Ste. 480

Chicago, IL 60615

(888)427-9486

+1 (312) 324-0367

[email protected]


Thank you!

NumXL 163 SHAMROCK Release

Data & Analytics

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