Financial Econometrics Analysis of Coca-Cola HBC AG Share Prices

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Executive Summary
Financial econometrics can be envisaged as a pivotal element in analysing any
company’s financial position based on historical data. Coca-Cola HBC AG , the second
largest anchor bottler company in the world is a revenue spinner and various factors affect its
share prices. Macroeconomic parameters like FTSE 100 index, consumer price index (CPI),
gross debt, 3-months Treasury bill, monthly consumer credit (including student loans), spot
exchange rates with respect to US dollar and against Euro have been taken to harness the
impact on share prices. The time period taken is from January 2013 to January 2018. A time
series approach and modelling techniques have been impregnated here.
Through the application of statistical software Eviews, the descriptive statistics of
share prices will be analysed, then random walk hypothesis will be evaluated, linear
regression modelling will be internalized for analysing the impact of various macroeconomic
variables on share prices and GARCH model of time series for analysing volatility and risk
mitigation.

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I. Introduction
A bird’s eye view
In the world of beverage industry across the globe, the name and brand of ‘Coca-
Cola’ hardly needs any mention. In the current scenario, Coca-Cola HBC AG is the second
largest anchor bottler company with respect to volume sales. In the year 2017, the company
has reached landmark sales of 2.1 billion unit cases and catering to around 600 million people
in 28 countries spanning across three continents (About Us, Coca Cola HBC AG, 2018).
Glimpse of the business
Year 2017 has been of significant progress for the company in terms of core business.
The net sales revenue triggered by 5.9%. The aggregate volume of trade increased by 2.2%
across all industry segments. Momentum has been significant in emerging and developing
countries. In terms of comparable EBIT, there has been a substantial jump of 20%. Robust
growth has been witnessed in the segment of sparkling and still drinks. The free flow of cash
has been € 425.9 million, a significantly higher operating cash flow as compared to the
previous year (Coca-Cola HBC AG, Financial Statement, 2018).
2. Other macroeconomic variables affecting share prices
The main macroeconomic variables affecting the share prices of the company are
FTSE 100 Index, consumer price index (CPI), General government gross debt (Percent of
GDP), Monthly average rate of discount, 3 month Treasury bills, Monthly consumer credit
(including student loans) (seasonally adjusted), Spot exchange rate (Sterling against USD)
(Month average) and Spot exchange rate (Sterling against Euro) (Month average). There are
other macroeconomic variables that affect the share prices of the company. As for instance,
changes in technological factors can be contemplated as one of the significant
macroeconomic factors affecting the share prices of the company. Suppose a new technology
has come in the market and the company has not been able to implement that technology then
that affects the share prices (Kettell, 2002). Other macroeconomic variables that come into
play for affecting share prices are political factors like change in government, wars, strikes in
the country, financial crisis, any international events and so on. Although not
macroeconomic, but micro-economic variables like announcements associated with profits,

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dividends, orders, management changes, issue of new shares and various other happenings
(Mott, 2008).
3. Descriptive statistics of the company’s monthly returns
When we see the mean, it is 16.73 which is well positioned between the minimum
value i.e. 11.066 and 25.85. There is no mode which reflects that there is no share price
occurring twice which is absolutely perfect as the variations are daily basis and then the
average value is taken month-wise and also represents the volatility in the stock prices. The
standard deviation is 3.73 and the skewness is 0.983378 which is right skewed. The
difference between the mean of the distribution and the observations in the frequency
distribution curve is concentrated more towards the right tail. The distribution is also not
normal in nature as the mean and standard deviation are not 0 and 1 respectively.
Fig.1 Variables after importing the dataset