Modeling and Forecasting Trend (FRM Part 1 2025 – Book 2 – Chapter 10)
Level up your FRM Part 1 (Book 2 – Quantitative Analysis, Chapter 10) skills with a clear walkthrough of modeling and forecasting trend. We compare linear vs. nonlinear trends, fit trend models with least squares, and show how to pick the best model using MSE, adjusted MSE, AIC, and SIC/BIC. Includes step-by-step examples and exam-style insights.
What you’ll learn:
Identify linear vs nonlinear trends
Transform to log-linear where helpful
Fit and forecast trend models (h-step ahead)
Select models via MSE, AIC, SIC
Understand consistency conditions
For FRM (Part I & Part II) video lessons, study notes, question banks, mock exams, and formula sheets covering all chapters of the FRM syllabus, click on the following link: https://analystprep.com/shop/unlimite...
AnalystPrep is a GARP-Approved Exam Preparation Provider for FRM Exams
After completing this reading you should be able to:
Describe linear and nonlinear trends.
Describe trend models to estimate and forecast trends.
Compare and evaluate model selection criteria, including mean squared error (MSE), s2, the Akaike information criterion (AIC), and the Schwarz information criterion (SIC).
Explain the necessary conditions for a model selection criterion to demonstrate consistency.
0:00 Introduction
0:38 Learning Objectives
1:13 What is Trend?
3:28 What Causes Trend?
7:15 Identify: Linear or Nonlinear?
8:28 Nonlinear Trend
9:09 Fitting Trend Models
13:08 Forecasting Trend
16:07 Model Selection: Mean Squared Error
18:28 Other Model Selection Criteria
20:13 Example
20:38 Consistency
21:23 Book 2 - Quantitative Analysis Chapter 10
#FRM #GARP #QuantitativeAnalysis #TimeSeries #TrendForecasting #LinearRegression #ModelSelection #AIC #BIC #ExamPrep #AnalystPrep