the analysis of the impact of capital mobility on bubbly episodes creation in the controlled...

The Analysis of the Impact of Capital Mobility on Bubbly Episodes Creation in the Controlled Laboratory Environment

Andrii Chlechko

September 2016

Plan

Experiment Overview

Trading Platform

Experimental Market

Trading Sessions

Trading Instruments

Profit

Population

Model Design

Results

Conclusions

Predictions

Trading Sessions

Experiment Overview

“Taking a course in experimental economics is a little like going to dinner at a cannibal’s

house. Sometimes you will be a diner, sometimes a part of dinner, sometimes both. [...] It is

hard to imagine that a chemist can put herself in the place of a hydrogen molecule. A

biologist who studies animal behavior is not likely to know what it feels like to be a duck.

You are more fortunate. You are studying the behavior and interactions of people in

economically interesting situations.”

Bergstrom and Miller

.

. .

.

Multi-Asset SSW Model

Borrowing/Lending possibility

Introduction of Financial Friction

Introduction of collateralisation

Samuelson –Tirole (1958; 1985)

Martin and Ventura (2010)

Miao and Wang (2011)

Garleanu and Pedersen (2011)

`

The author has developed a stylized experimental model, which is used to analyzethe impact of the introduction of capital mobility on the assets’ prices behaviour inthe controlled laboratory environment. The introduction of capital mobility is asubject to financial friction in a form of borrowing costs and collateral borrowing.

Innovation

Theoretical Background

Impact of Capital Mobility

Traders’ expectations and behavior

Price Tendencies

Target For Analysis

Experiment Overview

Smith, Suchanek and Williams (1998)

Fisher and Kelly (2000)

Cipriani, Fostel and Houser (2013)

Giushi, Jiang and Yiping Xu

Experimental Approach

Experiment Overview – Trading Platform

Experiment was designed and conducted using Z-Tree Software* in the computerlab of Kozminski University. Students were invited to trade in a real time.

* Zurich Toolbox for Readymade Economic Experiments (http://www.ztree.uzh.ch/en.html)

Z-Tree Software allowed to create a uniuqe market structure:

Two assets with different structures

Capital Mobility (cash)

NO external Noise

Z-Ttree – Server computer where the model is launched.

Z-Leaf – Trading desk for each participant to act on the market.

http://www.ztree.uzh.ch/en.html

Experiment Overview - Population

Traders’ selection for each trading session is random.

A person can participate only in one trading session.

27 students in total

Smith et. al. are among the first, who have pointed out the importance of the experiment

participants. The experiments with subjects with no or little experience in the experimental

asset markets tend to result in asset price bubbles and crashes. Similar finding was done by

Martin Dufwenberg, Tobias Lindqvist, Evan Moore (2003); Van Boening, Williams, and

LaMaster, 1993; Haruvy, Lahav, and Noussair, 2007); Lei, Noussair & Plott (2001).

Thomas Meissner and Antoni Bosch-Dom (2015) analyzed the importance of the impact of

cognitivity of subjects on the result of the experiment. The authors argue that appearance

of bubbles disappear when subjects have significant level of cognitive sophistication.

Related Literature

Proper selection of the traders is crucial for the overall results of the experiment. Accordingto previous findings, experience of participitation in the experiments and the educationlevel, among others, are the factors which have significant impact on the overall result of theexperiment. The population of the current experiment has the following criteria:

The traders are Bachelor and Master students of Economy, International Business, Management inVirtual Environment, Management, Finance & Accounting programs of Kozminski University.

Traders do not have relative experience of participation or conducting similar financiallaboratory experiments.

Model Design – Key Points

Experimental part is based on the model designed byVernon Smith, Gerry Suchanek and Arlington Williams(1988) SSW-type double-auction market with two lottery-type stocks with different payout functions.

Traders are engaged in:

Buying/Selling

Lending/Borrowing

Making predictions

Activities

Endowment

Market Structure

Experimental Sessions

Each trader begins with:

3 units of Stock 1

3 units of Stock 2

2000 units of Euro

Order-Driven market:

No intermediaries:

No commission

Price is determined by

supply and demand

`

Experiment consists of:

3 Trading Sessions

15 Periods per session

10-15 Traders per session

Experimental Models

First Session:2 StocksNo Capital Mobility

Second Session:2 StocksLending/BorrowingStock 1 as collateral

Third Session:2 StocksLending/BorrowingStock 1 as collateral

Model Design - Trading Sessions

The Experiment is presented for traders as a competition. The target for traders is to maximize their profit during trading sessions. The actual aim of the experiment is not disclosed.

• The whole Experiment consists of 3 Trading Sessions with different market structures:

• Perfect Capital Immobility Traders interact on the market only by trading stocks.

- First Session – no capital mobility on the market. Serves as a benchmark

• Market with Capital Mobility Traders can lend and borrow cash among themselves with the collateral condition

- Second Session - Stock 1 serves as a collateral for borrowing

- Third Session – Stock 2 serves as a collateral for borrowing

• Trading session is organized as follows:

- Introduction where detailed instructions are presented to the traders

- Practice sessions - The purpose is to introduce trading mechanism for subjects, the results are not recorded

- 15 trading periods 180 sec each`

Model Design - Trading Instruments

The stock market consists of two assets with different payout structure. The value of the stocks is

determined by the amount of dividends to be paid untill maturity V = AD * T. The value is declining

by the linear function from period to period. The dividends are paid at the end of the period, thus the

amount of actual dividend does not have an impact on the subjects’ decisions during the trading

period, however subject’s decisions may rely on the dividends received at the end of previous period.

More risky asset

Dividends:

EUR 0, 8, 28, 60

25 % Probability EachAD = 24 EUROn average, Stock 1 pays its holder 24 Euro per period

Residual Value at Maturity = 0

Less risky asset

Dividends:EUR 17, 20, 2333,33 % Probability EachAD = 20 EUROn average, Stock 1 pays its holder 20 Euro per period

Residual Value at Maturity = 0

Stock 1 Stock 2

Periods

Total

Current

Period

Periods to

Maturity

Average

Estimated

Dividends

AEV(Average

Expected Value)

15 1 14 24 336

15 2 13 24 312

15 3 12 24 288

15 4 11 24 264

15 5 10 24 240

15 6 9 24 216

15 7 8 24 192

15 8 7 24 168

15 9 6 24 144

15 10 5 24 120

15 11 4 24 96

15 12 3 24 72

15 13 2 24 48

15 14 1 24 24

15 15 0 24 0

Table 1: The estimation of the Stock 1 value

Periods

Total

Current

Period

Periods to

Maturity

Average

Estimated

Dividend

AEV(Average

Expected Value)

15 1 14 20 280

15 2 13 20 260

15 3 12 20 240

15 4 11 20 220

15 5 10 20 200

15 6 9 20 180

15 7 8 20 160

15 8 7 20 140

15 9 6 20 120

15 10 5 20 100

15 11 4 20 80

15 12 3 20 60

15 13 2 20 40

15 14 1 20 20

15 15 0 20 0

Table 2: The estimation of the Stock 2 value


Source: Author’s calculations Source: Author’s calculations

Before the begining of trading session, each trader is presented with the following tables which explaine the valuation of the stocks


To assess the impact of Capital Mobility on the assets’ prices, the author hasintroduced the possibility to borrow/lend money. Each trader has the possibility tomake an offer to lend or borrow money if he/she has sufficient cash to lend orsufficient stock value for collateral.

• Traders can borrow directly from each other.

• Capital mobility is subject to financial friction: the cost of borrowing is 4% .

• The amount of money each trader can lend is limited to his or her cash balance.

• The amount each trader can borrow should be lower than or equal to his or her current stock balancevalue (Collateral value).

• Program will automatically increase lender’s cash balance (landed amount with the interest) anddecrease borrower’s cash balance at the end of each period.

Lender is secured by the market to receive back money. In casewhen the borrower’s end of the period cash balance is not sufficientto pay back to lender the initially borrowed amount with interest,his/her cash balance turns negative and he/she leaves tradingsession.

Model Design - Profit

The target of the competition for traders is to maximaze their cash position. Profit is thecrusial factor for traders’ assesment. Profict is calculated as the different between the EndingCash Balance and the enitial endowment.

• The profit of each trader is calculated and presented at the end of each period.

• Overall profit/loss for the whole session is calculated as the difference between closing cash balanceand cash equivalent of initial endowment.

• Cash-equivalent amount of endowment is calculated as the sum of initial cash and initial stockbalance times its expected total value.

• The initial endowment is equal for eqach trader.

*Pay back amount is considered only in the model with capital mobility, where subjects are able to lend and borrow money. The calculation of the profit in the model of perfect capital immobility does not consider pay back amount.

Formula:

(𝑷𝒓 𝒕) = D1(t) * n1(t) + D2(t) * n2(t) ± PB

𝑫𝟏– dividend amount paid for each unit of Stock 1;𝒏𝟏 – closing balance of Stock 1;𝑫𝟐 – dividend amount paid for each unit of Stock 2;𝒏𝟐 – closing balance of stock 2;PB – pay back amount*

Results – First Trading Session

0

100

200

300

400

500

600

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

High

Low

Average

AEV

0

200

400

600

800

1000

1200

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

High

Low

Average

Price Stock 1

Period

Price

Period

Stock 2

Highest Price : 450 (Period 7)

Average Price : 293.57

Deviation/Price (%) : 51.64

Highest Deviation : 313 (Period 10)

Bubble Appearance : 3rd Period

Back to Fundamental : 13th Period

Bubble Duration : 10 Periods





Bubble Appearance : 2nd Period



Stock 1 Statistics

Stock 2 Statistics

. .

..

..

..AEV

Results – Second Trading Session

0

100

200

300

400

500

600

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Low

High

Average

0

100

200

300

400

500

600

700

800

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Min

Max

Average

Price

Period

Stock 1

Stock 2

Price

Period

AEV


Average Price : 196,87






USED AS COLLATERAL





Bubble Appearance : 2nd Period



Stock 1 Statistics

Stock 2 Statistics

. .

..

..

..

Results – Third Trading Session

0

50

100

150

200

250

300

350

400

450

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

High

Low

Average

AEV

0

100

200

300

400

500

600

700

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Max

Min

Average

Stock 1

Stock 2

Price

Price

Period

Period

AEV












Bubble Appearance 2nd Period

Back to Fundamental 13th Period

Bubble Duration 11 Periods

USED AS COLLATERAL

Stock 1 Statistics

Stock 2 Statistics

. .

..

..

..

Results – Predictions

The factors which are considered to have potential impact on traders’ expectations :

Actual dividends after previous period

No impact on subject’s predictions

Stocks’ estimated value (Table 1, Table 2)

The greatest impact on traders’ expectations during second and third sessions

Average market traded price during previous period

Positive significant impact during First and Third sessions

Negative impact during Second Session

Before each trading period, participants are asked to write down their expectetions toward the averageprice of the stock during the following trading period in order to asses the fcators which have impact onthe traders’ decision making process.

Price Bubble can been seen in the prices of bothstocks during each trading session

Capital mobility increases market efficiency

Collateralization has small effect on the marketefficiency

The closer the traders’ predictions toward theprices the lower the deviation of the market priceover the average value of the stocks

The dynamic of the prices show moderategrowth, followed by the peak and then the burstof the bubble.

Experiment

Conclusions

Less volatile asset is more attractive

Riskier asset is subject for higher speculations

The bubble has appeared in the prices of both assets

Stock 1 tends to have higher high/low spreadand bigger number of conducted transactions

Stock 2 has higher price deviation over fundamental value.

Trading Instruments

The results of the experiment show that capital mobility has has positive impact on the investment efficiency.

Andrii Chlechko

[email protected]

@ChlechkoA

Andrii Chlechko

the analysis of the impact of capital mobility on bubbly episodes creation in the controlled...

Economy & Finance