Economic/Statistic Problems

Big Data in Commercial
Shipping & Trading
The Signal Group I Coursework 2022
Module 1 I Introduction to Shipping Analytics
Semiramis Assimakopoulou
Consider that you have received the following information for a specific vessel. Do not use The Signal
Platform.
Data received Source Information
10/06/2022 AIS Current position from Lat, Lon Red Sea
12/6/2022 Email Signal Alpa subs Ceyhan- Med 22/06 80k WS 92.5
12/6/2022 AIS AIS destination : Suez canal
23/06/2021 AIS AIS destination: Ceyhan
24/06/2021 Line up Fos
What should be the current position and the latest forecasted position for Signal Alpha be forecasted at all
the timestamps above based on all the information received at any point in time. Generate a small table with
timestamps ?
Module 2 I Commercial Management
Semiramis Assimakopoulou
Imagine you are on a Chartering desk and you have an Aframax to work. You are presented with two options
to choose from:
1. A short TC, delivery in the US Gulf redelivery Singapore, for a minimum of 20 days and a maximum
of 60 days at $25,000/day
2. A local voyage in the USG for a period of 30 days with a TCE of $17,000/day
To help you assess which is the better option, you should note the following:
1. The position value of Singapore is -$550,000 and the position value of the US GULF is 0
2. You are in a position to hedge the market for the second month forward at $18,500/day
Which of the two scenarios is more profitable considering that you would like to compare both options
based on the same duration and end position?
What additional premium would you need to ask for, in order to make the less profitable scenario equally
equivalent to the other one ?
Module 3 I Making Commercial Decisions
Stella Saridou
The Cass Pool for May 2022 includes 4 vessels with the following rating elements:
Vessel WAF EAF Israel Libya Sikka Deadweight
Vessel 1 0.020000 0.010000 0.005000 0.005000 0.010000 0.036730
Vessel 2 0.020000 0.010000 0.005000 0.005000 0.010000 0.023700
Vessel 3 0.020000 0.010000 0.005000 0.005000 0.010000 0.024010
Vessel 4 0.020000 0.010000 0.005000 0.005000 0.010000 0.049970
These vessels perform the following voyages (see link below) along with the PnL information provided for
each voyage.
Cass 2022 Module 3 Coursework Data
1) Calculate the Rating of each vessel.
2) Calculate the Bunker Adjustment of each vessel based on the Bunker Performance per vessel that is
included in the Coursework Data
3) Calculate the Monthly Distribution for each vessel assuming full onhire days (i.e. 31 days) for all vessels
in May 2022 assuming 300$/day Admin Fees and no Other Fees. Please note the unfixed days (i.e. not in
a voyage) within the month for any vessels need to be adjusted to 0 $/day in terms of their contribution
into the Pool.
Module 4 I The Signal Ocean Platform
Semiramis Assimakopoulou
Your goal is to optimise your fleet using The Signal Ocean Platform running Voyage Calculations:
You have three vessels under commercial management with the following positions :
1. Minerva Alexandra, opening 2nd June, Taragona
2. Songa coral opening, opening 5th June, Pachi
3. Philotimos opening, 11th June, New York
You have been quoted the following cargoes with the below descriptions:
1. Arzew -Trieste 12th of June
2. Es Sider-Fos 7th June
3. Sidi-Burgas – 13th June , but requires a vessel with DWT >110kt
4. Ceyhan-Augusta -13th June
Market conditions:
● Consider the market is stable at 80kt and at ws 130 for all cargoes
● Consider that all ending positions are of equivalent value
● Run all voyages and use $15,000/ day for the remaining days of each voyage
Present a table matching each vessel to the optimum cargo in order to maximize profits for all three vessels
What is the estimated amount of CO2 emissions for each vessel basis the selected voyage
Module 5 I Data & Analytics in Paper Trading
Dimitris Tasoulis
1. Correlation:
a. You have two assets A and B, both have the same standard deviation equal to 30%. If the
correlation between them is 0.8, what is the covariance between A and B? Which asset is
more volatile?
b. If assets A and C have a correlation equal to -0.4, would you prefer building a portfolio out
of A and B or rather A and C? Why?
2. Time series analysis part 1
a. Get access to the time series called “JohnsonJohnson”’ in the “dataset” package
https://stat.ethz.ch/R-manual/R-devel/library/datasets/html/00Index.html
to carry out the following exploratory time series analysis in R.
This time series contains the quarterly earnings in dollars per Johnson & Johnson share
during the period 1960–80. Produce a time plot of the data
b. Plot the aggregated annual series and a boxplot that summarises the observed values for
each quarter, and comment on each plot. Any evident trend or seasonality in the data?
c. Which are the reasons or the generating mechanisms for trend and seasonality in this kind
of economic data?
d. Decompose the time series into the components trend, seasonal effect, and residuals, and
plot the decomposed series. Produce a plot of the trend with a superimposed seasonal
effect.
e. Plot the correlogram of the original time series and then the one for the residuals (random
component) after decomposition. Comment on the plot, with particular reference to any
statistically significant correlations.
3. Time series analysis part 2
a. Get access to the time series called “nottem” from the same dataset mentioned above. This
time series contains average monthly air temperatures at Nottingham Castle in degrees
Fahrenheit for 20 years between 1920 and 1939. Produce a time plot of the data.
b. Plot the aggregated annual series and a boxplot that summarises the observed values for
each month, and comment on each plot. Any evident trend or seasonality in the data?
Would you expect these data to have a substantial seasonal component?If yes, why?
c. Compare the standard deviation of the original time series with the deseasonalized one.
How can you judge the effectiveness of the seasonal adjustment?
d. Do these temperature data show any trend? Would you expect to find any?If yes, due to
which causing root or factor?
e. After appropriately decomposing the time series into the components trend, seasonal
effect and residuals, plot all relevant components and comment.
f. Plot the correlogram of the original time series and then the one for the residuals (random
component) after decomposition. Comment on the plot, with particular reference to any
statistically significant correlations.
4. Supply and index prices
a. Download the supply data from:
https://drive.google.com/file/d/10aUbw6gzb7VylpJs0gNze8j1iEtrk8op/view?usp=sharing
b. Download the index data (spot) from:
https://drive.google.com/file/d/1Q4DIItuauxTr0SifYdj8sIgUtvvpw_u-/view?usp=sharing
c. Download the FFA data from:
https://drive.google.com/file/d/1ktcW2W-13S5-6SibHFPcTkXM0cdeo92c/view?usp=shari
ng
○ What do these time series represent?
○ Would you expect any seasonality of the supply data based on your domain
knowledge of the shipping business? Why? Does data support this evidence?
○ Compute the correlation between the supply and the spot prices. Please comment
on everything you may notice.
○ Evaluate the volatility of each time series. What do they represent?
○ Imagine you can have all kinds of shipping data you may ask for. Describe the
datasets you would select and use to design a profitable trading strategy in the FFA
market. Which would be your strategy? Which rules would you use to
algorithmically enter and exit a position? How would you test the profitability of
your strategy?
Module 6 I Analytics & Technology in Oil Trading
Florian Thaler / Juan Carlos Rodriguez Arguelles
Based on historical information obtained from JODI
http://www.jodidb.org/TableViewer/tableView.aspx?ReportId=93904) produce an oil analyst forecast for
the Crude Oil Supply Demand Balance of Angola until December 2022.
Consider the following:
● Period: monthly data for each segment
● Unit of measurement: thousand barrels per day (kb/d)
● Country: Angola
● Segments to be completed (Jan – Dec ):
○ Crude Oil Production
○ Crude Oil Imports
○ Crude Oil Exports
○ Refinery Intake
In three bullet points also answer the following questions:
a) Do you observe any seasonality or trend in the data?
b) Is the country an importer/exporter of crude oil?
c) What role do geopolitics play? Angola is currently in a deal with OPEC to reduce oil production
which is gradually getting relaxed. What would happen to your forecast if there were no deal?
Sample Format: