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日期：2023-10-19 07:41

Financial Modelling - Final Assessment

Market Bubble Burst Test

Background

The first financial market bubble can be well traced back to the 17th the Netherlands,

during which demand for the cheerful tulip bulbs caused farmers to experiment with species

and colouring so that the tulip became an object of speculation. In fact, they were so prized,

people literally mortgaged their houses during that period in order to buy and then resell

tulip bulbs. Suddenly, consumer confidence eroded, resulting in the tulips market crash.

They became all but worthless. It is believed that the bubble burst led to a year’s-long

economic decline.

Exhibit 1. Market Bubble Formation and Burst

As shown in Exhibit 1, when a market bubble bursts, demand falls, and prices decline

quickly. Investors who established positions near the top could see their profits erode

completely. Depending on its size, a deflating bubble can have short-term effects to an

industry or market niche, but it could also prompt large scale consequences [1], such as the

recent Global Financial Crisis, triggered by the deflation of the US housing market during

2007–2008. The downturn in the U.S. housing market snowballed into a national recession

and led to a global monetary crisis. Therefore, a close examination of market bubbles and

the assessment of economic and financial after effects of the bubbles bursting has become

an integral part of the asset management.

Market Bubble

In this exercise, a bubble is characterized by an increase in the price of assets at a rate which

is not sustainable, shortly after, if a bubble has formed the price will decrease at a high rate,

leading to a large potential loss if the asset is not sold quickly enough.

Momentum

The momentum of an asset relates to the acceleration of its price. It can be determined by

simply calculating the rate of change of the asset’s price over a certain period of time.

Random Search

A brute force numerical method used to search for local minima that increases efficiency by

checking every ‘nth’ value, with the assumption that the elements located close to every

‘nth’ value will not deviate too far from it. A smaller sample is then extracted from the data

set and these values are checked individually to find the minimum value.

The company you are working for currently uses an in-house VBA function to identify

bubbles in the market by analysing the asset’s momentum. Currently, local minima of the

asset’s momentum are found utilizing a random search to boost efficiency, the momentum

of the asset around these local minima are then analysed to check if they are too low, which

could indicate a bubble has burst. You are given this function by your supervisor and she

wishes you to demonstrate that you understand how the code works and make the function

more generic (Sheet 1) and would like you to improve upon it (Sheet 2), if applicable.

Sheet 1

You must alter the function Bubble_Finder (Module 1) so that it takes inputs

Bubble_Finder(StockPrices, Dates, BigStep, NoBubbles) in that order. You must then

analyze the assets given and place the results, starting in the top left corner in the green

cells provided next to each asset’s name. Exhibit 2 is an example given in the sheet of what

the output should look like for an analysis of 2 potential bubbles for Z1P.

Exhibit 2. Market Bubble Formation and Burst

Z1P Average Momentum Momentum Std Dev Local Min Momentum Local Min Location Bubble Burst Found

0.017255565 0.103020374 -0.369458128 16/03/2020 Large Bubble Burst

-0.1 03/06/2019 No Bubble/No Burst

For each other three assets, you must use the parameters below:

1. CBA

? Step size of 5 weeks

? Analyse 3 potential bubbles

2. QAN

? Step size of 3 weeks

? Analyse 2 potential bubbles

3. AIZ

? Step size of 4 weeks

? Analyse 2 potential bubbles

Additionally, the date of the local minima must display the date, not the numeric code for

the date, as shown in the 5

th column of Exhibit 2.

Please only make the required changes to the code which relates to the above mentioned

inputs and output. Do not alter the method used to search for minima or the decision rule

which is used to classify if a bubble has burst in this sheet.

Sheet 2

This is a copy of Sheet 1 and will not be marked as part of your spreadsheet submission,

instead it is to be used to present what your changes to the code supplied do. You are free

to make any changes you would like at all to the code in the Bubble_Finder_Exp() function

(Module 2) that you believe will improve the code supplied.

The Assessment

The sample code to create the required function for this task is already provided to you in

Module1, but it was very poorly written and unable to proceed effectively straightaway.

Your job is to fix and improve it (if applicable). You will be assessed across Week 11 and

Week 12.

1. Week 11 Assessment Q&A (5 Minutes)

The focus of the assessment in this week is on the understanding of the idea (like a code

plan), including but not limited to:

i. Discuss and demonstrate a code plan for the functions;

ii. Identify and discuss some of the bugs and issues with the code;

iii. Suggest methods/ideas to improve the efficiency of the codes;

iv. Recommend on how to optimise the functions;

2. Week 12 Assessment, Presentation (5 Minutes Max)

The focus of the assessment in this week is on the code and solution quality, including but

not limited to:

i. Efficiency;

ii. User interface (user friendly wise);

iii. Accuracy of bubble detection;

iv. Bubble detection rules;

v. And general usability and improvements you have made/proposed.

3. Spreadsheet Submission in Week 11 and 12

As previously, the automatic marking software marks your work.

i. It will only mark Sheet 1 worksheet and the function;

ii. You must not modify the structure of Sheet 1, change the function name or the

order of its input parameters.

I couldn’t wait to meet you in Week 10 and Week 11 assessment. Please ‘think outside the

box’ and let your wild imagination lead you while tackling this challenge.

Good luck!

Bob

Reference

[1]. Pavlidis, E., Yusupova, A., Paya, I. et al. Episodes of Exuberance in Housing Markets: In

Search of the Smoking Gun. J Real Estate Finan Econ 53, 419–449 (2016).