The Impact of the COVID-19 Pandemic on the Kenyan Stock Market

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By Dr Irene Irungu

A stock market can be likened to a marketplace where demand and supply characterize the price of commodities. When availability is low and demand is high, a commodity’s price is likely to rise. Equally, the price is likely to reduce when there is high availability and low demand. The case is similar for a stock market, in which earnings realized fluctuate almost continuously.

The COVID-19 pandemic has posed challenges to the world at large; presenting opportunities and challenges in various economic sectors. Of keen interest here is the impact of the pandemic on the financial market where a drastic decline in market performance has been observed.

The London Stock Exchange recorded the steepest fall ever of 30% in its Financial Times Stock Exchange (FTSE) indices. So severe has been the situation that it has seen the intervention of securities exchanges to control the effect of this deterioration. For instance, in the USA, the Nasdaq and the New York Stock Exchange agreed to give temporary relief from certain shareholder approval requirements for companies that needed to raise capital. A similar situation was realized in Kenya when trading was halted for half an hour on 13th March 2020, following a decrease of more than 5% of the Nairobi Security Exchange 20 share index.

While this intervention was necessary at the time, fundamental questions remained unanswered. Was the decline uniform across all stocks? What was the market outlook following the opening? What is the current state of the market? What challenges and/or opportunities are posed with this pandemic? This article seeks to answer these questions.

Empirical studies have proved that the observed volatility can be linked to several financial factors. These often include exchange rates, interest rates, inflation rates, monetary policy, commodity price and regional stock market indices. It is, however, important to note that this association is varied in nature and strength as time evolves. As such, investors continuously reference these factors which result to them either realizing a profit or loss. It implies therefore that stocks price correlation presents a positive influence on future stock movement prediction.

This article utilizes Multiple Correlation Analysis to measure how asset prices move in relation to each other, with exchange rates as a reference factor. The reference factor represents the condition that helps us to determine the relationships among stocks as it influences the association between different stocks. Specifically, closing daily prices of stocks that remained actively trading in the first quarter are considered to examine whether the decline was uniform across all stocks. The results of the correlation matrix are displayed in the form a heat-map as displayed below:

A glance at the above correlation heat-map reveals a green colour scheme with varied intensity.  The legend to the left gives the correlation values corresponding to the colour scheme where the green colour indicates a positive correlation. It reveals that the overall nature of the market was highly correlated. On average, the market exhibited an 80% degree of correlation which means that all the stocks are moving in the same direction with each other irrespective of the economic sector.  To examine whether the particular trend is upwards or downwards, the Moving Average is applied to an arbitrary sample of the stocks. A 10-days Moving Average is employed to make the prices more stable, making it easier to measure the trend. The trend line is compared with that of the KES/USD exchange rate and displayed in the following plots.

The trend lines reveal a downward trend in the first quarter for all the stocks across the various economic sectors. It is also observed that a sharp decline in the majority of the stock prices was experienced in March, after the confirmation of the first COVID-19 case in the country.

90% of the stocks experienced a decline on 13th March with East African Cables and Sanlam Insurance accounting for the largest drop that day at 10%, see figure below. As the stock market declined, the Kenya shilling is also observed to weaken against the (US) dollar as the latter steeply soared by 4% between the 16th and 26th March. This indicates that, as the domestic currency weakened, confidence weakened and investors liquidated their shares and invest elsewhere. Equally, when the domestic currency starts to regain strength in the second quarter, it gave investors’ confidence that the country’s economy is also growing, resulting to increased interest from investors and demand to invest in the Kenyan market.  This could further be reinforced by the Goods Market Theory which argues that changes in exchange rates affect the competitiveness of companies and consequently their earnings and stock prices.

The Government has continuously put in place measures to curb the spread of the pandemic. These have evolved from curfews and restricted movement in certain counties to re-opening of some previously closed businesses. This has had a ripple effect on the stock market as revealed by analysis of the closing prices in the second quarter of the year to reveal the current state of the market.  A look at the correlation matrix for this period reveals diversity in the movement of the stock market. Here, unlike in the first quarter, a red colour scheme is observed. This indicates a negative correlation implying that a pair of the stock is moving in the opposite direction, that is when one stock moves upwards the other moves downwards.

Economic perception is that stocks are categorized into homogeneous groups based on their industrial affiliation so that companies in the same industry share high return correlations compared to companies in different industries.

In the Agricultural sector, for instance, we continue to observe a positive correlation between Sasini Tea and Williamson Tea, where unlike in the first quarter, the prices of these stocks is now increasing.  However, this is not always the case as displayed in the second quarter where Bamburi Cement and East Africa Cables are negatively correlated, where the former continues to dip as the latter soars. These two companies classified in the manufacturing sector may not necessarily experience a strong co-variation over short horizons, as their co-movement may be drowned out by non-economic forces such as investor sentiment.

The Banking, Energy and Petroleum sectors are also seen to improve, although the increase is at a slow and varied rate. The Commercial and Services sector depicts mixed fortunes as some positively correlated stocks improve like WPP Scangroup and Kenya Airways while others continue to decrease, such as the Nation Media Group and Longhorn Publishers. This is also observed in the Insurance sector where only two stocks, Britam and CIC, have shown an upward trend. The Construction sector reveals a negative correlation between Bamburi Cement and East Africa Cables, where the former continues to dip as the latter soars.

Even for companies not invested in the stock market, the measures put in place to curb the spread of the pandemic such as curfews and lockdowns have resulted into slowed economic activities and a decline in the overall spending.

The effect on the stock market is likely to trickle down to all and sundry, posing challenges and opportunities in some cases.  It is likely that short-term investors cut their losses by liquidating their stocks and shifting to fixed income assets such as T-bills following the first quarter results.

However, results for the second quarter indicate that it is prudent for long-term investors to continue holding their portfolios as there is an opportunity for recovery.

There are instances where some companies have invested in the stock market. These have also been impacted through loss of the capital invested which may affect their ability to pay their employees remuneration and eventually affect their job security.

Even for companies not invested in the stock market, the measures put in place to curb the spread of the pandemic such as curfews and lockdowns have resulted into slowed economic activities and a decline in the overall spending. This has resulted in a reduction of companies’ profits which may cause such companies to resort to downsizing to reduce their expenses. Others may halt any expansion plans that may have been underway thus reducing any job opportunity prospects. Consequently, both situations would result in an increase in unemployment, burdening an already struggling informal economy workforce.

For a country that heavily relies on imports to support the economy for machinery, transport equipment, manufactured goods, chemicals, food, animals and vegetable oils & fats and crude materials, the situation is aggravated by the depreciation of the Kenyan currency. Traders are likely to find it more expensive to stock up and for those who afford it, the increased costs are transmitted to the consumers.

It is not all gloom, though. In fact, this difficult environment presents a good opportunity for a long-term investor to buy into the market.

The slow upward movement observed in the second quarter indicates that the market is likely to recover in no time. The plot above reveals companies whose stock grew by more than 10% between 27th March and 30th June 2020. We can depict the trading opportunity by considering a hypothetical investor who bought 100 shares each of two correlated stock, say Williamson Tea and Sasini tea. These were respectively trading at KES 94.75 and KES 15.50 on 27th March, representing a portfolio worth KES 11,025. By 30th June, these stocks were respectively trading at KES 130 and KES 17.8, indicating that the portfolio was worth KES 14,780. This represents a short-term pay-off of KES 3,755 accounting for a 34% growth of this portfolio. With the observed upward trend for these stocks, a long-term investor is likely to make greater profit margins by maintaining this position. This can be replicated for a portfolio composed of other stocks.


Dr Irene Irungu is a lecturer of Actuarial Science in the Department of Mathematics, Statistics and Actuarial Science at Karatina University, Kenya. She holds a BSc Actuarial Science and MSc Applied Statistics from the Jomo Kenyatta University of Agriculture and Technology (JKUAT) and a PhD Financial Mathematics from the Pan African University Institute for Basic Sciences Technology and Innovation (PAUISTI). 

Additional contribution by Purity Mukami

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