Dataset and Initial Analysis

For each stock index the continuously compounded return is estimated as 𝑟𝑟_𝑖𝑖=

ln (𝑝𝑝𝑖𝑖⁄𝑝𝑝𝑖𝑖−1), where 𝑝𝑝𝑖𝑖 is the price at the end of the day 𝑡𝑡.8 Tables 1-4 report key

descriptive statistics for the full, pre-crisis, crisis and post-crisis periods. For the definition of the crisis we have used the official timelines provided by the Bank for International Settlements (BIS, 2009) and the Federal Reserve Board of St. Louis (2009), which separate the Global Financial Crisis into four phases. Phase 1 starts on the 1st of August 2007 and ends on the 15th of September 2008 and is termed the “initial financial turmoil”. Phase 2, spanning from 16th September 2008 until 31st

8 _{To remove excessive spikes, we winsorise at the 99.9% of the return series, a standard practice in this}

December 2008, is a period of “sharp financial market deterioration”. Phase 3 is

termed as “macroeconomic deterioration” (1st January 2009 – 31st March 2009) and

Phase 4 as “stabilization and tentative signs of recovery” from 1st April 2009 onwards. Therefore, the crisis can be defined as running from August 2007 until March 2009 covering the first three phases. In our analysis, we term this period as “Crisis”, while every observation preceding and following this period is termed as pre-crisis and post-crisis respectively

All stock markets featured gains during the pre-crisis period, with most markets exceeding the S&P 500 global benchmark. This finding is in line with the risk-return doctrine whereby developing markets compensate investors that are willing to take on greater risk. For example, Dubai recorded the highest daily gain (0.156 %) in the pre- crisis period but also the second largest loss during the crisis period (-0.230%). Interestingly, Bahrain shows the lowest volatility across all sub-periods. This is quite important, given that the Kingdom relies mostly on financial services.

Financial returns of all stock market indices exhibit the usual characteristics of excess kurtosis and skewness across all periods. Interestingly, autocorrelation is strongly present for most of these developing markets but at a varying extent. For instance, the GCC countries show lower coefficients than the remaining oil exporting economies, a potential sign of a more developed financial system. The US, as proxied by the S&P 500, does not show any evidence of stock returns predictability across all periods but the post-crisis. Lastly, the two commodity prices remain unpredictable across all market periods. In terms of volatility in the financial markets of the respective countries, there are a few cases, namely Kuwait, Dubai and Bahrain, which are more stable than the S&P 500 over the full sample and during the crisis period. Others, such

as Saudi Arabia and Qatar are either of comparable or of slightly higher volatility during the same periods. In terms of stock market development, the efficient market hypothesis holds for the S&P 500 across the full sample and the pre-crisis period, while it collapses under crisis and post-crisis. In the GCC the findings are mixed. Some of the most developed financial markets (in terms of market capitalisation and openness) such as Bahrain and Dubai are not weak form efficient pre-crisis. However, Dubai shows evidence that the weak form efficiency holds during the crisis and post crisis times. Conversely, for the Bahraini stock market, the efficient market hypothesis holds only in the post-crisis period.

[Tables 1 – 4 around here]

Figures 3-4 show the evolution of the stock market price and returns for the sample under investigation. As most of these are either developing or frontier markets, the existence of pronounced spikes or evidence of a stock market developing in the last few years is evident. For all stock markets the impact of the global financial crisis is clear around the 2007-2009 period with an upward trend leading to the start of the crisis and a sustained price drop onwards. Some countries show more than one crisis experiences. For example, Saudi Arabia experienced a stock market crisis from around the late 2005- to early 2006, which is evident in the specific graph. Similarly, the stock market in Venezuela reflects the dire economic situation in the country where the local currency (bolivar) has collapsed and rampant inflation (above 100% annually) has been recorded. As a market response, investors are using the stock market to hedge their risks, as it is preferable to hold stocks than bolivars. As a result, the main equity index (which also consists of just 11 stocks) has been recording phenomenal growth (around 600% in 12 months). However, this growth should be

reflective of the fear in the Venezuelan economy rather than promising investment opportunities. Likewise, the US in the early 2001-2002 shows evidence of the dot.com bubble (see Figure 3-4). However, to understand how oil may affect the financial sector of these countries it suffices to compare the spikes in the oil prices with the evolution of the Nigerian stock exchange.

[Figures 3-4 around here]

Table 5 presents the bi-variate correlation coefficients for the full sample. A quick inspection of the figures gives evidence of positive interrelations across all the stock markets. For example, in the GCC, correlation between Kuwaiti and Bahraini stock markets is around 0.22, while correlation between two of the oil exporting countries (e.g., Venezuela and Nigeria) is much lower at around 0.012. Most countries are quite unrelated to the US stock market, as evidenced by the very low correlations to the SP500. The only exception is Saudi Arabia, with a correlation coefficient around 0.142. Correlation with the oil is also quite low, particularly for the non-GCC oil producers. Still Saudi Arabia shows the largest correlation coefficient, at 0.142, possibly due to the large reliance of the country to on oil exports and its size (as a producer) among both the GCC and the OPEC.

[Table 5 around here]