Tentative Schedule, Homework, Suggested Problem Sets and Links (FINA 4397/7354)

(Slides fec-2a):
Introduction to FINA 4397/7354
Organization of class
Review of Stats: Population & Samples, Statistic, Distribution, Population and Sample Moments
Returns and Yields

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2nd Lecture

(Slides fec-2b)
Review from previous class
Brief R review (bring your computer with R installed)
Expected Returns and the Equity Risk Premium
Hypothesis Testing

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3rd Lecture

(Slides fec-2-c)
Review from previous class
Hypothesis Testing and Confidence Intervals
Application: Are Stock Returns Zero?
Application: Value-at-Risk in FX Markets

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4th Lecture

(Slides fec-2-d)
Review from previous class
Bootstrap: Application to Confindence Intervals
Application: Value-at-Risk in FX Markets

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5th Lecture

(Slides fec-3-a)
Homework R Review
Review from previous class
Introduction: Least Squares Estimation
Review: Linear Algebra
R review of Regression and Linear Algebra (bring your computer with R installed)

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6th Lecture

(Slides fec-3-b)
Review from previous class
Least Squares with Linear Algebra
Testing Hypothesis about Single Parameter
Application: Is IBM Riskier than the Market?
R Examples

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7th Lecture

(Slides fec-3-c)
Homework 1 Review
Goodness of Fit Measures: R^2, Adjusted R^2, IC
Introduction to MLE

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8th Lecture

(Slides fec-3-d)
Review from previous class
MLE
Data Problems

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9th Lecture

(Slides fec-4)
Review from previous class
MLE: Linear Model
Sampling Distribution of OLS
Paired Bootstrap: Correlations

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10th Lecture

(Slides fec-5)
Review from previous class
Testing in the CLM: Single and Multiple Parameter Hypotheses
Wald tests and F-tests

Application: The CAPM or the 3-Factor Fama-French Model?
Non-Nested Models and Tests
Application to FX Models: IFE or PPP?

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11th Lecture

(Slides fec-6-a)
Review from previous class
Testing Remarks: Size of test
Non-Nested Models and Tests
FX Market Application: PPP or IFE?
Functional Form and Specification: Non-linearities and RESET Test

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REVIEW FOR MIDTERM #1

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FIRST MIDTERM


RV Lecture

(Slides fec-Rev1)
Review Post First Exam: Regression & Testing
Forecasting

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13th Lecture

(Slides fec-6-b)
Review from previous class
Functional Form and Specification: Checking assumption (A1)
Testing Model Specification: LM Tests
Functional Form: Intrinsic Linearity and RESET Test
Functional Form: Chow Test
Functional Form: Structural Change Tests
Application: Did the 2008 Financial Crisis affect the 3-Factor F-F Model for IBM?

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14th Lecture

(Slides fec-6-c)
Homework 2 Review
Review from previous class
Evaluation of Forecasts
Testing Forecast Accuracy

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15th Lecture

(Slides fec-6-c)
Review from previous class
Evaluation of Forecasts
Testing Forecast Accuracy
FX Market Application: Fundamental Forecasting (JPY/USD)

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16th Lecture

(Slides fec-6-d & 7-a)
Review from previous class
FX Market Application 2: Fundamental Forecasting (MXN/USD)
Model Selection: General-to-Specific & Specific-to-General
Departures from OLS Assumptions
Stochastic Regressors and Non-normality: Violation of (A2) & (A5)

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17th Lecture

(Slides 7-a)
Review from previous class
Heteroscedasticity and Autocorrelation: Violation of (A3)
Testing for Heteroscedasticity and Autocorrelation

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18th Lecture

(Slides fec-7-b)
Review from previous class
Testing for Autocorrelation
Generalized Regression Model
OLS under Heteroscedasticity and Autocorrelation
White S.E and Newey-West S.E.
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19th Lecture

(Slides 7-c)
Review from previous class
Generalized Least Squares (GLS)
Feasible Generalized Least Squares (FGLS)
FGLS: Heteroscedasticity and AR(1) examples

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21st Lecture

(Slides fec-project-PPP)
Discussion of Project

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22nd Lecture

(Slides fec-8-a)
Time Series: Introduction, AR, MA and White Noise
Stationarity, Non-stationarity, and Ergodictiy
Moving Average & Autoregressive Processes

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REVIEW FOR MIDTERM #2

SECOND MIDTERM

23rd Lecture

(Slides fec-8-b)
Review from previous class
MA, AR and ARMA Processes: Stationarity & ACF
ARMA Processes: Examples

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24th Lecture

(Slides fec-9-a)
Review from previous class
ARMA: Identification: ACF and PACF
Non-stationarity: Deterministic Trend vs Stochastic
ARIMA Processes Identification in Practice

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25th Lecture

(Slides fec-9-a)
Review from previous class
Non-stationarity: Deterministic Trend vs Stochastic
ARIMA Processes Identification in Practice
ARIMA: Estimation
ARIMA: Identification

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26th Lecture

(Slides fec-9-b)
Review from previous class
ARIMA: Review: Identification, Estimation and Diagnostic Testing
ARIMA: Seasonal Models: Deterministic and SARIMA
ARIMA: Forecasting

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27th Lecture

(Slides fec-9-c)
Review from previous class
ARIMA: Forecasting
Exponential Smoothing and Holt-Winters: Forecasting
Comparing Forecasts
Combination of Forecasts

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28th Lecture

(Slides fec-10)
Volatility: Introduction to time-varying volatility
ARCH Models
ARCH Estimation: MLE
GARCH: Forecasting and Persistence
GARCH: VaR Application
GARCH: Variations and Testing
Realized Volatility
Realized Volatility: Forecasting, VIX and VRP
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REVIEW FOR FINAL

FINAL EXAM

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