The Analysis of the Impact of Capital Mobility on Bubbly Episodes Creation in the Controlled...
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Transcript of 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.
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
Model Design - Trading Instruments
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
Model Design - Trading Instruments
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
Highest Price : 490 (Period 8)
Average Price : 322.13
Deviation/Price (%) : 60.72
Highest Deviation : 350 (Period 8)
Bubble Appearance : 2nd Period
Back to Fundamental : 13th Period
Bubble Duration : 11 Periods
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
Highest Price : 345 (Period 5)
Average Price : 196,87
Deviation/Price (%) : 23.19
Highest Deviation : 105 (Period 5)
Bubble Appearance : 3rd Period
Back to Fundamental : 13th Period
Bubble Duration : 10 Periods
USED AS COLLATERAL
Highest Price : 408 (Period 4)
Average Price : 191.93
Deviation/Price (%) : 31.57
Highest Deviation : 188 (Period 4)
Bubble Appearance : 2nd Period
Back to Fundamental : 13th Period
Bubble Duration : 11 Periods
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
Highest Price : 321 (Period 1)
Average Price : 214.87
Deviation/Price (%) : 23.79
Highest Deviation : 137 (Period 11)
Bubble Appearance : 3rd Period
Back to Fundamental : 13th Period
Bubble Duration : 10 Periods
Highest Price : 326 (Period 2)
Average Price : 202.93
Deviation/Price (%) : 31.99
Highest Deviation : 153 (Period 11)
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.