This document describes a financial transaction simulator that allows users to model different transaction scenarios over time. It includes built-in scenarios like single transfers as well as customizable scenarios like constant, linear, seasonal, and interrupted transfers. The simulator allows running the scenarios with different parameters and displays the results either as a chart or table. Jupyter notebooks are used for interactive exploration and customization of the scenarios.

1. Simulator Sandbox
Notebook setup
In [1]:
Built-in scenarios
Scenarios included in simulator configuration. Curently available 2 simple scenarios: 'Scenario 1' and 'Scenario 2'.
In [2]:
Dynamic scenarios
Single transfer
Simplest scenario to simulate single transfer.
Executed with default values (5000EUR at 12:00).
Full syntax: $single(amount, hour)
12:00
Jan 1, 2019
00:00
Jan 2, 2019
12:00 00:00
Jan 3, 2019
12:00 00:00
Jan 4, 2019
12:00 00:00
Jan 5, 2019
12:00
0
20
40
60
80
100
Scenario name with parameters:"Scenario 1", start date: 2019-01-01
Simulation day
EUR
%run Setup.ipynb
run_scenario('Scenario 1')

2. In [3]:
Single scenario execution with parameters:
Full syntax: $single(amount, hour)
In [4]:
Constant transfers scenario
With default arguments it generates 53 wekly transfers of 5000EUR at noon.
23:59:59.9996
Dec 31, 2018
23:59:59.9998 00:00:00
Jan 1, 2019
00:00:00.0002 00:00:00.0004
0
1000
2000
3000
4000
5000
Scenario name with parameters:"$single()", start date: 2019-01-01
Simulation day
EUR
amount 1000
Start date 01.01.2019
Display result as table
23:59:59.9996
Dec 31, 2018
23:59:59.9998 00:00:00
Jan 1, 2019
00:00:00.0002 00:00:00.0004
0
200
400
600
800
1000
Scenario name with parameters:"$single(100000)", start date: 2019-01-01
Simulation day
EUR
run_scenario('$single()')
@interact(amount=(1,10000),
start_date=widgets.DatePicker(description='Start date', value= date(2019, 1, 1)),
as_table=widgets.Checkbox(description='Display result as table',indent=True))
def single_demo(amount=1000, start_date=date(2019, 1, 1), as_table=False):
name = '$single({})'.format(amount*100)
run_scenario(name, start_date.strftime("%Y-%m-%d"), as_table)

3. Full syntax: $constant(amount, number, hour, period)
In [5]:
Constant scenario can be customized by providing arguments:
Full synatx: $constant(amount, number, hour, period)
Jan 2019 Mar 2019 May 2019 Jul 2019 Sep 2019 Nov 2019 Jan 2020
0
1000
2000
3000
4000
5000
Scenario name with parameters:"$constant()", start date: 2019-01-01
Simulation day
EUR
run_scenario('$constant()')

4. In [6]:
Parameters that will be probably not changed are placed at the end, so they can be skipped:
Full syntax: $constant(amount, number, hour, period)
can be invoked in shorter form, e.g.:
$constant(amount, number)
Also parameters in the middle can be skipped: $constant(amount,number,, period)
amount 1000
number 20
hour 12
period 7
Start date 01.01.2019
Display result as table
Jan 6
2019
Jan 20 Feb 3 Feb 17 Mar 3 Mar 17 Mar 31 Apr 14 Apr 28 May 12
0
200
400
600
800
1000
Scenario name with parameters:"$constant(100000,20,12:00,7)", start date: 2019-01-01
Simulation day
EUR
@interact(amount=(100,10000,100),
number=(1,100),
hour=(0,23),
period=(1,30),
start_date=widgets.DatePicker(description='Start date', value=date(2019, 1, 1)),
as_table=widgets.Checkbox(description='Display result as table',indent=True))
def constant_demo(amount=1000, number=20, hour=12, period=7, start_date=date(2019, 1, 1), as_table=False):
time = '{}:00'.format(hour)
name = "$constant({},{},{},{})".format(amount*100, number, time, period)
run_scenario(name, start_date.strftime("%Y-%m-%d"), as_table)

5. In [7]:
Linear changing transactions
With default arguments generates 53 weekly transactions at 12:00 with amount staring from 5000EUR and growing by 30EUR every transaction.
Full syntax: $linear(amount, delta, number, hour, period)
In [8]:
amount 1000
number 20
Start date 01.01.2019
Display result as table
Jan 6
2019
Jan 20 Feb 3 Feb 17 Mar 3 Mar 17 Mar 31 Apr 14 Apr 28 May 12
0
200
400
600
800
1000
Scenario name with parameters:"$constant(100000,20)", start date: 2019-01-01
Simulation day
EUR
Jan 2019 Mar 2019 May 2019 Jul 2019 Sep 2019 Nov 2019 Jan 2020
0
1000
2000
3000
4000
5000
6000
Scenario name with parameters:"$linear()", start date: 2019-01-01
Simulation day
EUR
@interact(amount=(100,10000,100),
number=(1,100),
start_date=widgets.DatePicker(description='Start date', value=date(2019, 1, 1)),
as_table=widgets.Checkbox(description='Display result as table',indent=True))
def constant_demo2(amount=1000, number=20, start_date=date(2019, 1, 1), as_table=False):
name = "$constant({},{})".format(amount*100, number)
run_scenario(name, start_date.strftime("%Y-%m-%d"), as_table)
run_scenario('$linear()')

6. Customizing by using scenario arguments:
$linear(amount, delta, number, hour, period)
In [9]:
Seasonal scenario
Simulates periodic changes in tenant income resulting from seasonal changes.
Full syntax: $seasonal(amount, amplitude, season_cycle_days, max_at_day, number, hour, period)
With default arguments generates 53 weekly transactions simulating seasonal changes with mean value 5000EUR, yearly season cycle,
seasonal changes amplitude of 2000EUR and maximum at start of simulation.
amount 1000
delta -5
Start date 01.01.2019
Display result as table
Jan 2019 Mar 2019 May 2019 Jul 2019 Sep 2019 Nov 2019 Jan 2020
0
200
400
600
800
1000
Scenario name with parameters:"$linear(100000,-500)", start date: 2019-01-01
Simulation day
EUR
@interact(amount=(100,10000,100),
delta=(-100,100,1),
start_date=widgets.DatePicker(description='Start date', value=date(2019, 1, 1)),
as_table=widgets.Checkbox(description='Display result as table',indent=True))
def linear_demo(amount=1000, delta=-5, start_date=date(2019, 1, 1), as_table=False):
name = "$linear({},{})".format(amount*100, delta*100)
run_scenario(name, start_date.strftime("%Y-%m-%d"), as_table)

7. In [10]:
Customizing by using scenario arguments:
$seasonal(amount, amplitude, season_cycle_days, max_at_day, number, hour, period)
Jan 2019 Mar 2019 May 2019 Jul 2019 Sep 2019 Nov 2019 Jan 2020
0
1000
2000
3000
4000
5000
6000
7000
Scenario name with parameters:"$seasonal()", start date: 2019-01-01
Simulation day
EUR
run_scenario('$seasonal()')

8. In [11]:
Interrupted scenario
Simulates periods of none or other income values that standard ones.
Full syntax: $interrupted(amount, interruption_amount, interruption_spec, number, hour, period)
With default arguments generates 53 weekly transactions of 5000EUR at 12:00, with no transactions between days 90 and 120.
In [12]:
Customizing by using scenario arguments:
Full syntax: $interrupted(amount, interruption_amount, interruption_spec, number, hour, period)
amount 6000
amplitude 2000
cycle_len 355
max_day 180
Start date 01.01.2019
Display result as table
Jan 2019 Mar 2019 May 2019 Jul 2019 Sep 2019 Nov 2019 Jan 2020
0
10
20
30
40
50
60
70
80
Scenario name with parameters:"$seasonal(6000,2000,355,180)", start date: 2019-01-01
Simulation day
EUR
2000
3000
4000
5000
Scenario name with parameters:"$interrupted()", start date: 2019-01-01
EUR
@interact(amount=(100,10000,100),
amplitude=(0,6000,100),
cycle_len=[7,30,90,182,355],
max_day=(0,355),
start_date=widgets.DatePicker(description='Start date', value=date(2019, 1, 1)),
as_table=widgets.Checkbox(description='Display result as table',indent=True))
def seasonal_demo(amount=6000, amplitude=2000, cycle_len=355, max_day=180, start_date=date(2019, 1, 1), as_table=Fal
name = "$seasonal({},{},{},{})".format(amount, amplitude, cycle_len, max_day)
run_scenario(name, start_date.strftime("%Y-%m-%d"), as_table)
run_scenario('$interrupted()')

9. y p ( , p _ , p _ p , , , p )
In [13]:
Place for experimens
amount 6000
interruption… 2000
interruption… 50-100|150-280
Start date 01.01.2019
Display result as table
Jan 2019 Mar 2019 May 2019 Jul 2019 Sep 2019 Nov 2019 Jan 2020
0
10
20
30
40
50
60
Scenario name with parameters:"$interrupted(6000,2000,50-100|150-280)", start date: 2019-01-
Simulation day
EUR
@interact(amount=(100,10000,100),
interruption_amount=(100,10000,100),
start_date=widgets.DatePicker(description='Start date', value=date(2019, 1, 1)),
as_table=widgets.Checkbox(description='Display result as table',indent=True))
def seasonal_demo(amount=6000, interruption_amount=2000, interruption_spec='50-100|150-280', start_date=date(2019, 1
name = "$interrupted({},{},{})".format(amount, interruption_amount, interruption_spec)
run_scenario(name, start_date.strftime("%Y-%m-%d"), as_table)

10. In [14]:
name $seasonal(500000,300000,50,10)
Start date 01.01.2019
Display result as table
Jan 2019 Mar 2019 May 2019 Jul 2019 Sep 2019 Nov 2019 Jan 2020
0
1000
2000
3000
4000
5000
6000
7000
8000
Scenario name with parameters:"$seasonal(500000,300000,50,10)", start date: 2019-01-01
Simulation day
EUR
@interact(start_date=widgets.DatePicker(description='Start date', value=date(2019, 1, 1)),
as_table=widgets.Checkbox(description='Display result as table',indent=True))
def free_demo(name='$seasonal(500000,300000,50,10)', start_date=date(2019, 1, 1), as_table=False):
run_scenario(name, start_date.strftime("%Y-%m-%d"), as_table)