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Investing

FDI: Your Passport to Stock Market Stardom!

iStock 1147352052 - Global Banking | Finance

FDI: Your Passport to Stock Market Stardom!

Picture1 - Global Banking | FinanceBy Mehul Gupta, an analyst at Fischer Jordan, with an interest in data science, number crunching, and storytelling for business and economic case studies.

Purab Jain, an intern at Fischer Jordan, helping organizations to exchange complexity for clarity by combining strategy and analytics

Introduction

Foreign Direct Investment (FDI) is a term used by business gurus and politicians alike, often as a way to show promise of a bright future of an economy. Over time, investment paradigms have shifted and so have investor preferences, always being on the lookout for better and less risky returns. Before talking about FDI, let us talk about the wider realm of international equity investing, in which FDI falls. What makes international investing so lucrative is its ability to help investors diversify their holdings by accessing different markets, industries, and currencies. Investing in stocks from various countries can potentially reduce risk by spreading it across different economies and market conditions.

FDI involves the investment by companies or individuals in foreign business ventures, allowing them to acquire assets or establish subsidiaries. On the other hand, portfolio investment offers investors the ability to diversify their holdings across countries and asset classes without actively managing the invested assets. Both FDI and portfolio investment contribute significantly to international economic activities, providing avenues for businesses and investors to expand their presence and minimize risks.

While the past few years were all about easy money flowing due to low interest rates, many budding startup ecosystems around the world, like India, benefited from money flowing in from investor countries like USA, Singapore, and others. This helped many businesses reach enormous valuations and made many people rich via, but not limited to, lucrative IPO exits.

While not every one of us might have the circumstances, resources and capabilities to make it big as a startup founder or investor, we still can leverage the FDI data to our benefit to make bets against the stock market. We cover this in depth in the next section.

Our Study

We aim to explore the impact of inward FDI (the money flowing in a given country) and outward FDI (money flowing out of a given country) on the stock market performance across international markets and whether these indicators can be used to drive an enhanced internationally diversified portfolio strategy.

The reason behind choosing FDI inflows comes intuitively, as more money flowing into the economy translates to more technology transfer, job creation, increase in market capitalization and other spillover effects as the money trickles down the economy. Countries with stable political environments, robust financial institutions and propensity towards growth, attract investments from other countries. The reason behind choosing FDI outflows seems counter-intuitive, but is based on sound reasoning.

While developed nations park their funds in new, upcoming developing markets to get a higher return than their home markets, developing nations are not far away in the race.  From 1995 to 2014, the OFDI (outward FDI) from developing nations has increased from just four percent of global FDI flows, to a record 27 percent. As a result, the number of developing countries engaged in OFDI has notably increased.  OFDI can be used to source knowledge and technology not present in the home market. These knowledge effects can benefit not only outwardly invested firms, but also domestic firms in the home economy. OFDI can boost home country exports through complementary relationships, for instance by opening new export markets or increasing the demand for intermediate exports. All these reasons contribute to our rationale to use both FDI outflows and inflows to build and test our theory.

To do the same, we collected 22 nations from the top quartile by gross GDP numbers, as these were the economies deemed rich and stable enough to bet against. We then segmented these in 4 buckets, them being:

  1. Bottom 25% Nations in GDP Per capita: Egypt, India, Vietnam, Philippines, South Africa
  2. Median Nations in GDP Per capita: Brazil, China, Turkey, Poland, Malaysia
  3. Top 25% Nations in GDP Per capita: Germany, UK, USA, France, South Korea
  4. Other nations: UAE, Italy, Australia, Israel, Netherlands, Canada, Japan

These buckets were made using GDP per capita as a metric and the ‘Other nations’ bucket was added to make the list geographically diverse and to encompass more countries.

Next, we used FDI (both inflows and outflows) as leading indicators to calculate correlations of FDI with market capitalization of domestic companies. The data for the same we sourced through the World Bank database. We collected data of nearly 30 years (1991-2022) to perform our correlation analysis, by calculating the correlation of market capitalization of domestic companies with one-year lagged FDI.

The correlations we observed were close to 0.4 for FDI outflows and 0.35 for FDI inflows. Seeing a good enough correlation with FDI outflows, we first started building out our portfolio investment theory using only FDI outflows.  The procedure we followed to make this model is as below:

1. We collected the following data from 30 years for each country:

    • FDI outflows as a percentage of total GDP of the country (FDI outflows/GDP)
    • Annual stock market return percentage of the country’s stock index
    • Exchange rate percentage change of the country against USD

2. The next step was to calculate the 5-year average and standard deviation for the FDI outflows. This step is carried out to assign weights by comparing the previous year FDI outflow to the 5-year average and SD, and assigning weights accordingly. The logic for applying weights is as follows.

    • If previous year FDI outflow is below 1SD from the mean, weight assigned=1
    • If previous year FDI outflow is between, 1SD below from the mean and the mean, weight assigned=2
    • If previous year FDI outflow is between, the mean and 1SD above from the mean, weight assigned=3
    • If previous year FDI outflow is above 1SD from the mean, weight assigned=4
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Fig 1: Formula description for assigning weights using FDI as leading indicator

3. The weighted stock market return is calculated by multiplying the weights by the stock return of that year.

4. To consider the exchange rate changes, we added the ER percent change to the stock market return percentage and multiply the whole quantity with the weights assigned. This gives us weighted returns taking into account the ER changes.

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Fig 2: Formula description for calculating weighted return

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Fig 3: Weighted return using ER change

 

 

 

 

 

 

 

 

 

 

 

While this theory performed well with developing nations, beating the stock index return by more than a percent greater return, it failed to beat the normal returns for developed nations with higher GDP per capita.

Return World Average Bottom 25% Nations Median Nations Top 25% Nations Other Nations
Weighted Return Stock Market 10.39% 13.65% 14.50% 7.14% 6.26%
Normal Return Stock Market 9.99% 13.40% 12.21% 7.50% 6.83%
Weighted Return Including ER Changes 8.01% 10.07% 9.44% 6.40% 6.15%
Normal Return Including ER Changes 7.62% 9.11% 7.43% 7.04% 6.91%

Fig 4: Returns table with FDI outflows as leading indicator

We then repeated the same procedure with FDI inflows, and this time we were able to beat the market consistently with all our buckets. FDI inflows work better as a leading indicator in a diverse set of countries, giving us a higher return than the normal stock index return.

Return World Average Bottom 25% Nations Median Nations Top 25% Nations Other Nations
Weighted Return Stock Market 11.59% 14.98% 15.01% 9.74% 6.65%
Normal Return Stock Market 10.34% 13.40% 12.21% 9.54% 6.21%
Weighted Return Including ER Changes 9.14% 10.15% 10.47% 9.13% 6.81%
Normal Return Including ER Changes 7.96% 9.11% 7.43% 8.99% 6.30%

Fig 5: Returns table with FDI inflows as leading indicator

While this is consistent with existing literature on the topic, our study is a step forward to actively leverage FDI as a driver of international investment allocation strategy. Here are some reasons proposed in the literature for why inbound FDI could be a driver for stock market performance:

  • FDI inflows contribute to the liquidity and efficiency of stock markets, leading to increased trading volumes and improved market performance.
  • Stable economic and political environments with a propensity towards growth attract FDI inflows and positively contributes to the stock market.
  • Increased FII inflows lead to higher stock market returns, indicating the positive sentiment and confidence of foreign investors in the Indian market.

We simulated the returns based on 30 years of data, with a base amount of $100 in the year 1995, and it can be seen that our weighted investment strategy performs well and beats the normal stock index return across all the buckets, putting the findings to practical use.

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Fig 6: Returns chart for overall world

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Fig 7: Returns chart for top 25% nations as per GDP per capita

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Fig 8: Returns chart for median 25% nations as per GDP per capita

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Fig 9: Returns chart for bottom 25% nations as per GDP per capita

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Fig 10: Returns chart for ‘other nations’ as per GDP per capitaA point to note here is that our theory proves to be slightly more volatile in nature owing to the higher investment size, it also gives us higher returns. A natural addition in this study would be to inculcate risk control measures and to try to improve the returns.

Conclusion

From our study, we can conclude that our weighted returns model is able to beat the normal stock index returns consistently with FDI inflows as a leading indicator, across various geographies, thus proving to be a viable internationally diversified portfolio investment theory.

The next steps in this study could be to look for solutions to mitigate the risks associated with recessionary periods as in the 2008 stock market crisis. This would involve solutions like setting up a stop loss and inculcating it in the model. Furthermore, the study could be expanded to take more countries into account and hence calculate the correlations and returns.

 

 

References

  1. Claessens, S., & Rhee, M.W. (1993). “The effect of equity barriers on foreign investment in developing countries”
  2. Jeffus, W.M. (2005). “FDI and stock market development in selected Latin American Countries”. Latin American Financial Markets: Developments in FinancialInnovations (International Finance Review).
  3. Malik, I.A., & Amjad, S. (2013). “Foreign direct investment and stock market development in Pakistan”. Journal of International Trade Law and Policy
  4. Sekhri, V., & Hague, M. (2015). “Impact of Foreign Investments on Indian Stock Market: AnEmpirical Study
  5. Bhanumurthy, N. R., & Das, A. (2007). “FDI inflows and the stock market: an empirical investigation.” Applied Economics, 39(13), 1611-1622.
  6. Li, X., & Selover, D. D. (2008). “Foreign direct investment and stock market development: A panel data analysis.” International Review of Financial Analysis, 17(4), 818-830.
  7. Gorgulu, M. E., & Aydin, O. (2016). “Foreign direct investment and stock market development: Evidence from emerging market countries.
  8. https://blogs.worldbank.org/psd/outward-foreign-direct-investment-new-channel-development
  9. Issouf Soumare´ and Fulbert Tchana Tchana (2015). “CAUSALITY AND EXTERNAL VALIDITY Causality between FDI and Financial Market Development: Evidence from Emerging Markets”

 

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