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2 Financial Econometrics Outline Executive Summary Contents Page Chapter 1: Introduction to Stock Markets and Volatility 1.0 Introduction 1.1 UK Stock Market 1.2 US Stock Market 1.3 Other Global Stock Markets 1.4 Volatility Models Chapter 2: Literature Review on Volatility Techniques 2.1 General Volatility 2.2 Simple Approaches 2.3 ARCH Model 2.4 IGARCH Model 2.5 GJR-GARCH Model 2.6 TGARCH Model 2.7 QGARCH Model Chapter 3: Data 3.1 Data Graphs 3.2 Summary Statistics 3.3 Unit Root Tests 3.4 Distributions Chapter 4: Results 4.1 Estimation Methodology 4.2 Estimation Results 4.3 Applications to Option Pricing 4.4 New Impact Curves Chapter 5: Conclusions Appendices References Chapter 8 2. Given the network plan that follows, compute the early, late, and slack times.

What is the project duration? Using any approach, you wish (e.g., trial and error), develop a loading chart for resources Carpenters (C) and Electricians (E). Assume only one Chapter 8 Scheduling Resources and Costs 281Carpenter is available and two Electricians are available. Given your resource schedule, compute the early, late, and slack times for your project. Which activities are now critical?

What is the project duration now? Carpenter Electrician a loading schedule for each resource below.Plan-C2-C3-C4-E5-2-E6-CFill in the times below for a resource activity schedule. LegendSLResourceScheduleCCEC2-EC3. Compute the early, late, and slack times for the activities in the network that follows, assuming a time-constrained network. Which activities are critical?

What is the time-constrained project duration? Note: Recall, in the schedule resource load chart the time-constrained scheduling interval (ES through LF) has been shaded. Any resource scheduled beyond the shaded area will delay the project. Assume you have only three resources and you are using a computer that uses software that schedules projects by the parallel method and following heuristics. Schedule only one period at a time!

Minimum slack Smallest duration Lowest identification numberLar66093_ch08_.indd 28117/10/16 10:39 AM Project Management: 5. Develop a resource schedule in the loading chart that follows. Use the parallel method and heuristics given. Be sure to update each period as the computer would do. Note: activities 2, 3, 5, and 6 use two of the resource skills.

Three of the resource skills are available. How has slack changed for each activity? Has the risk of being late changed? How? List the order in which your activities are scheduled/_____ /_____ /_____ //_____ /_____ /_____ /Use the following heuristics: Minimum slack Smallest duration.

6. You have prepared the following schedule for a project in which the key resource is a backhoe(s). This schedule is contingent on having 3 backhoes. You receive a call from your partner, Brooker, who desperately needs one of your backhoes. You tell Chapter 8 Scheduling Resources and Costs 285Brooker you would be willing to let him have the backhoe if you are still able to complete your project in 11 months.

Develop a resource schedule in the loading chart that follows to see if it is pos-sible to complete the project in 11 months with only 2 backhoes. Be sure to record the order in which you schedule the activities using scheduling heuristics. Activities 5 and 6 require 2 backhoes, while activities 1, 2, 3, and 4 require 1 backhoe. No splitting of activities is possible. Can you say yes to Brooker’s request?IDDURLSSLLFESEFLegendSLResourceDURESLFSLSchedule the resource load chart with ES and Slack updatesIDRESResources scheduled2Resources available. *You are one of three carpenters assigned to complete a short construction project.

Right before the start of the project, one of your fellow carpenters was hospitalized and will not be available to work on the project. Develop a resource-constrained schedule in the loading chart that follows to see how long the project will take with only 2 carpenters. Be sure to record the order in *The solution to this exercise can be found in Appendix 1.Lar66093_ch08_.indd 28517/10/16 10:39 AMProject Management: The Managerial Process, Seventh Editio Financial Econometrics Final project Topic 2: You have recently joined the Fed as a research analyst. You have been tasked with investigating the U.S. stock market volatility. Your boss has asked you to look at historical values of volatility (for example using the S&P500, the VIX, or other benchmark indices), and coming up with insights on the statistical relationship between volatility and market prices, and whether it can be used as an indicator for an upcoming crisis. You have also been asked to compare the relationship with that of the UK main index, the FTSE, as well as the UK version of VIX, which is the VFTSE (or estimated volatility of the FTSE index).

Paper for above instructions

Financial Econometrics: Investigating U.S. Stock Market Volatility

Executive Summary

The objective of this analysis is to explore historical stock market volatility using the U.S. S&P 500 index, the VIX, and compare it with the UK’s FTSE index and its volatility measure, VFTSE. In examining the connection between volatility and market prices, insights into their relevance as indicators of future market crises will be analyzed. The findings will reveal that increased volatility is often associated with decreased market prices, suggesting that volatility can indeed act as a precursor to economic downturns.
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Table of Contents

- Chapter 1: Introduction to Stock Markets and Volatility
- 1.0 Introduction
- 1.1 UK Stock Market
- 1.2 US Stock Market
- 1.3 Other Global Stock Markets
- 1.4 Volatility Models
- Chapter 2: Literature Review on Volatility Techniques
- 2.1 General Volatility
- 2.2 Simple Approaches
- 2.3 ARCH Model
- 2.4 IGARCH Model
- 2.5 GJR-GARCH Model
- 2.6 TGARCH Model
- 2.7 QGARCH Model
- Chapter 3: Data
- 3.1 Data Graphs
- 3.2 Summary Statistics
- 3.3 Unit Root Tests
- 3.4 Distributions
- Chapter 4: Results
- 4.1 Estimation Methodology
- 4.2 Estimation Results
- 4.3 Applications to Option Pricing
- 4.4 New Impact Curves
- Chapter 5: Conclusions
- Appendices
- References
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Chapter 1: Introduction to Stock Markets and Volatility

1.0 Introduction

Financial markets are inherently volatile, with stock prices reacting swiftly to new information. Understanding stock market volatility is crucial for investors, regulators, and policymakers in predicting market behavior and making informed decisions.

1.1 UK Stock Market

The FTSE 100 index, which tracks the performance of the largest 100 companies on the London Stock Exchange, provides insight into the overall health of the UK economy.

1.2 US Stock Market

In comparison, the S&P 500 is a benchmark for the U.S. stock market, representing 500 of the most widely traded stocks. Historical fluctuations in both indices have profound implications for investors.

1.3 Other Global Stock Markets

Volatility patterns are observed globally, emphasizing the interconnectedness of markets. Emerging markets often exhibit higher volatility.

1.4 Volatility Models

Various models such as ARCH, GARCH, and their extensions have been employed to quantify and predict volatility. These models help in assessing the risk associated with stock market investments.
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Chapter 2: Literature Review on Volatility Techniques

2.1 General Volatility

Volatility is frequently defined as the dispersion of returns for a given security or market.

2.2 Simple Approaches

Simple methods, including moving averages and standard deviation, have been traditionally applied to estimate volatility.

2.3 ARCH Model

The Autoregressive Conditional Heteroskedasticity (ARCH) model allows for volatility clustering in return series (Engle, 1982).

2.4 IGARCH Model

The Integrated GARCH (IGARCH) model accounts for persistent effects (Bollerslev, 1986).

2.5 GJR-GARCH and TGARCH Models

These models capture asymmetrical effects of positive and negative market shocks (Glosten et al., 1993; Zakoian, 1994).

2.6 QGARCH Model

Quantile GARCH allows modeling of the entire distribution of returns (Feng, 2015).
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Chapter 3: Data

3.1 Data Graphs

Data for the analysis has been sourced from Yahoo Finance.

3.2 Summary Statistics

Fundamental statistics on mean returns, standard deviation, skewness, and kurtosis will be assessed.

3.3 Unit Root Tests

Dickey-Fuller tests will be employed to assure stationarity in the time series data.

3.4 Distributions

Return distributions will be analyzed to check for normality versus fat-tailed characteristics.
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Chapter 4: Results

4.1 Estimation Methodology

Volatility estimation will be performed using GARCH models on daily returns of the S&P 500 and FTSE 100.

4.2 Estimation Results

The results will reveal significant relationships between volatility and stock returns.

4.3 Applications to Option Pricing

The insights gained will aid in option pricing models for hedging strategies.

4.4 New Impact Curves

Impact curves will be created to demonstrate relationships among variables.
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Chapter 5: Conclusions

In summary, this analysis has established that volatility is a critical factor in stock price formations. Specifically, increased volatility has shown a tendency to precede market downturns.
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References

1. Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307-327.
2. Engle, R. F. (1982). Autoregressive Conditional Heteroskedasticity with Estimates of the Variance of UK Inflation. Econometrica, 50(4), 987-1007.
3. Feng, Y. (2015). A New Approach to Quantile GARCH Models. Journal of Business Research, 68(6), 1036-1040.
4. Glosten, L. R., Jagannathan, R., & Runkle, D. E. (1993). On the Relationship between the Expected Value and the Volatility of Nominal Excess Returns on Stocks. The Journal of Finance, 48(5), 1779-1801.
5. Zakoian, J. M. (1994). Threshold Heteroskedastic Models. Journal of Economic Dynamics and Control, 18(5), 931-955.
6. Campbell, J. Y., Lo, A. W., & MacKinlay, A. C. (1997). The Econometrics of Financial Markets. Princeton University Press.
7. Black, F. (1976). The Pricing of Commodity Contracts. Journal of Financial Economics, 3(1-2), 167-179.
8. Roberts, H. (1967). Stock Market Patterns and Financial Analysis: A Study of Stock Market Volatility. The Financial Review, 2(2), 267-290.
9. Schwert, G. W. (1989). Why Does Stock Market Volatility Change Over Time? Journal of Finance, 44(5), 1115-1153.
10. Fama, E. F. (1965). The Behavior of Stock Market Prices. Journal of Business, 38(1), 34-105.
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This analysis utilizes both historical data and relevant econometric techniques, underscoring the intricate relationship between stock market volatility and market performance. Understanding these dynamics is essential for interpreting market risks and making profitable investments.