Reassessing Export Diversification Strategies: A Cross-Country Comparison

Gouvea, Raul; Vora, Gautam

doi:10.4236/me.2015.61009

Cited by 6 publications

(4 citation statements)

References 64 publications

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“…On the other hand, countries with a higher share of manufactured products shows a much lower level of volatility, although again there are substantial differences among countries. Moreover, it is important to mention that the "what you export matters", i.e., manufactured exports with a larger global market and higher value-added tend to also benefit nations with betas closer to the global market beta ( [35]). Figure 1 illustrates the Sharpe ratio for the LAS countries, the portfolio of all countries and the world index.…”

Section: Resultsmentioning

confidence: 99%

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The Arab League: Export Earnings and Economic Development

Gouvea¹,

Vora²

2017

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The countries of the Arab League paint a diverse picture of economic (and social) performance and export-earnings performance. While Arab countries have formed numerous alliances for one reason or another, the League of Arab States, more popularly known as the Arab League, is the dominant one. One can, however, see a social, political, economic development divide among them. Focusing on the export performance of these countries during the period from 1988 through 2012, we examine stability of export earnings as well as exports' risk-return profile. The single index model from the modern portfolio theory is used for empirical examination. The results indicate that these countries exhibit a corresponding performance divide for export-earnings. The oil and natural gas exporters show a much higher sensitivity than non-oil exporters. Exporters with a higher proportion of manufactured products show a much lower sensitivity. Examination of risk-return tradeoff reveals a more complicated picture: Qatar, UAE and Bahrain show the highest Sharpe ratio which is a measure of performance based on total fluctuations whereas Lebanon, Jordan and Tunisia show the highest Treynor ratio which is a measure of performance based on market-fluctuations. The study concludes that different socioeconomic development policies are needed for developed and developing countries of the Arab League. Several structural challenges facing these countries are pointed out and discussed to improve economic and export performances. These challenges can be overcome only with sustained resolute action emanating from the highest level of political control.

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Section: Resultsmentioning

confidence: 99%

“…We refer the interested reader to Gouvea and Vora ( [35]) who provide numerous citations to the application of SIM in various fields to demonstrate that the use of SIM to explore the topic of this study is well-established. We use SIM…”

Section: Methodsmentioning

confidence: 99%

The Arab League: Export Earnings and Economic Development

Gouvea¹,

Vora²

2017

Self Cite

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“…Following this idea, these authors and others, like Tóth et al [31], address systematic risk in agriculture. Other examples of applications of the single-index model to economics are, for instance, Finn [32], who investigates the systematic risk of marketing projects, Wu et al [33], who focus on the study of the oil import risk from portfolio theory, and Gouvea and Vora [34], who use Markowitz and Sharpe models to assess countries' export diversification strategies.…”

Section: Imentioning

confidence: 99%

Assessing Sustainability-Related Systematic Reputational Risk through Voting Results in Corporate Meetings: A Cross-Industry Analysis

2019

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This research uses Sharpe’s single-index model to analyze voting results in corporate meetings, thus assessing whether voting results at the corporate level are influenced by aggregated voting results at the industry level. We use a sample of votes regarding managerial proposals concerning executive election and compensation. The companies involved are included in the five most represented industries in NASDAQ, and the analysis focuses on the 2003–2017 period. The votes were disclosed by institutional investors who are especially concerned with corporate governance and sustainability issues, so we consider that they reflect sustainability-driven decisions. Based on previous research linking voting results to reputational consequences, we assess the systematic component of sustainability-related reputational risk within these five industries, finding significant differences among them. Thus, although the systematic component of sustainability-related reputational risk appears to be strong for financial and technological companies, it is weak for healthcare, consumer services, and capital goods companies. Implications for researchers and practitioners are reported.

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“…unsystematic risk (also known as unique risk or idiosyncratic risk), the difference between total risk and systematic risk, can be significantly reduced through portfolio diversification, but complete elimination is not possible. Reducing market-based risk is more challenging and requires risk-management instruments and methods Fu (2009); Gouvea et al (2015); Mangram (2013).…”

Section: Introductionmentioning

confidence: 99%

Predicting Idiosyncratic Volatility from Stock Market Trade Records: A Machine Learning Approach

Seifi¹,

Shavarani²

2023

Preprint

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Financial markets require a great deal of decision making from the investors and market makers. One metric that can help ease the process of decision making is investment risk which can be measured in two parts; systematic risk and idiosyncratic risk. Clear understanding of the volatilities in each risk component can be a powerful signal in recognizing the right assets to maximize the investment returns. In this paper, we focus on the idiosyncratic volatility values and pre-calculate the idiosyncratic volatility values for 31,198 members of NYSE, Amex and Nasdaq markets for the trades occurring between January 1963 and December 2019. Utilizing a subset of dataset, limited to Nasdaq100 index, we consider the application of machine learning techniques in predicting the idiosyncratic volatility values using the raw trade data to explore a data extension option for the future market trade records that have not yet occurred. We offer a deep learning based regression model and compare it with traditional tree-based methods on a small subset of our per-calculated idiosyncratic volatility dataset. Our analytical results show that the performance of the deep learning techniques is much more robust in comparison to that of the traditional tree-based baselines.

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Reassessing Export Diversification Strategies: A Cross-Country Comparison

Cited by 6 publications

References 64 publications

The Arab League: Export Earnings and Economic Development

The Arab League: Export Earnings and Economic Development

Assessing Sustainability-Related Systematic Reputational Risk through Voting Results in Corporate Meetings: A Cross-Industry Analysis

Predicting Idiosyncratic Volatility from Stock Market Trade Records: A Machine Learning Approach

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