US Portfolio Research Articles

Hedging global currency risk: A dynamic machine learning approach

We propose a dynamic method to hedge foreign exchange risk of international equity portfolios. The method is based on the currency return forecasts derived from a set of alternative machine learning models, built on the main factor components of the currency return time series. To illustrate our method, we take the perspective of a US portfolio manager investing in a global equity portfolio of developing and developed economies. The analysis of several model performance indicators, back-tested on data from 27 October 2008 to 30 December 2022, allows to conclude that accurate predictions of global currency factor returns, such as those obtained with non linear machine learning models, can improve currency risk hedging of global equity portfolios.

Risk Analysis of Nvidia Corporation Stock and Equally-Weighted US Portfolio

Risk Analysis of Nvidia Corporation Stock and Equally-Weighted US Portfolio

Market overreaction, firm-specific information and macroeconomic variables in US and Chinese markets during COVID-19

PurposeThis study examines the impact of firm-specific information and macroeconomic variables on market overreaction of US and Chinese winner and loser portfolio before and during COVID-19.Design/methodology/approachThe firm-specific information includes firm size, volume, volatility, return of asset (ROA), return of equity (ROE), earning per share (EPS) and quick ratio while the macroeconomic variables are export rate, import rate, real GDP, nominal GDP, FDI, IPI and unemployment rate. Besides, one-third of the top performance stocks are categorized as winner portfolio while one-third of lowest performance stocks are categorized as loser portfolio. This study uses AECR to indicate stock return and measure market overreaction. GAECR is used to determine contrarian profit. The data range of pre-COVID-19 is from 1-Jan-2015 to 31-Dec-2019 while the period of COVID-19 is from 1-Jan-2020 to 31-Dec-2020.FindingsIn pre-COVID-19, firm-specific information (volatility, ROA, ROE and EPS) and macroeconomic variables are found to be correlated to stock return in US and Chinese portfolios except Chinese winner portfolio. Nonetheless, the impact of firm-specific information has vanished and macroeconomic variables are significant to stock return in COVID-19. It shows that investors rely on the economic indicators to trade in turbulent period due to emergence of COVID-19 as a disruption in market. Furthermore, US and Chinese portfolios are overreacted during COVID-19. Chinese loser portfolio has higher tendency of overreaction than US loser portfolio while US winner portfolio has higher tendency of overreaction than Chinese winner portfolio.Originality/valueThe results of this study assists academician, practitioners and investors on understanding and create awareness to the existence of market overreaction and the determinants that can cause the phenomenon.

Nonlinear spillover and portfolio allocation characteristics of energy equity sectors: Evidence from the United States and Canada

AbstractWe investigate the nonlinear spillover and portfolio allocation characteristics of the US and Canadian energy equity portfolios. Our empirical study based on directional spillover index and non‐convex portfolio optimization show that the spillover effects in the aggregate are smaller for the US portfolio across time. However, when only the largest spillover transmitters and receivers are considered, the total spillover effects are lower for the Canadian portfolio relative to the US portfolio. These portfolio optimization results indicate lower portfolio allocation risk for the Canadian energy equities during the global financial crisis of 2008 and for the full sample period.

Are herding transmissions in the gulf cooperation council stock markets regional or international?

PurposeThe authors aim to assess whether herding in GCC stock markets is more responsive to global dynamics than its response to regional developments. To do so, they use the largest equity market in the region which is Saudi Arabia as the benchmark, and then they examine if herding crosses from this large regional market to the rest of equities in the neighboring markets during various time periods. To compare the importance of global influences on herding, the authors investigate and compare the impact of the information flow from the US equity market on the herding of equities in the GCC markets.Design/methodology/approachTo investigate herding in GCC markets the authors use the relationship between the squared market return and the cross-section absolute deviation that does not covary with market styles and/or fundamentals. In order to do that we follow Galariotis et al. (2015) and account for four styles: market-oriented, small-cap, value and momentum. As these factors have been shown to be associated with the economic fundamentals, filtering the covariance of deviation with these factors is expected to remove the style and the fundamental herding influence from the value of the dispersion.FindingsThe results show significant herding behavior that persists across various independent periods. This evidence stands even when the authors control for the well- known factor structures in stock returns. Importantly, the authors find that the few herding crossovers that occurred during the sample period are more likely to originate from the Saudi market rather than from the US. Therefore, the authors conclude that behavioral inefficiencies in the GCC equity markets are likely to be regional and that the sentiment-based trading in the US has essentially a minimal role to play.Practical implicationsThe empirical findings are useful for policymakers who aim at preventing market manipulation in order to preserve the integrity of financial markets. Policymakers in the GCC should disclose more information to aid investors so they do not rely on other investors' trades. The portfolio managers should be aware that the correlation of GCC equities can be higher in the short term due to common market herding in these countries. As the US market does not play an important role in triggering behavioral irrationalities in these markets, investing in GCC equities is a good hedge in a US portfolio. Finally, the results have also important implications for active funds that aim to exploit short-term trending in markets in order to enhance performance.Originality/valueThe authors’ contribution in this paper is to investigate herding in GCC markets by using the relationship between the squared market return and the cross-section absolute deviation that does not covary with market styles and/or fundamentals. Another contribution of our paper is to investigate any cross herding from the Saudi market to the rest of the markets in the area. The previous literature on GCC equity market herding is silent on this issue and it is typically restricted to the level of the single market.

Biden should rethink US policy on low-yield nuclear weapons

ABSTRACT In 2020, the Trump administration deployed a low-yield nuclear weapon aboard US submarines. President-elect Joe Biden should interrogate whether this was sound policy. The process of assessing the usefulness of this warhead could present Biden with an opportunity to rebalance the US portfolio of nonstrategic nuclear weapons and, in turn, alter nuclear competition with Russia and China.

An Empirical Study on the Impact of Trade War on Both the US and Chinese Economies, Based on the Value-at-risk Approach

The trade war between the US and China has led to global instability, this makes studying this topic very important and sensitive. This study aims to show the impact of the trade war on both the United States and China, by studying both US and Chinese companies before and after the trade war.Although the trade war is still ongoing and has not ended, but it is long enough to judge its impact on the two countries. In this study, the value at risk was used as a tool to compare the size of the risks to both the US and Chinese portfolios before and after the trade war, the results showed that the VaR of the US and Chinese portfolio after the trade war was greater than the VaR before the trade war, This means that the two countries were affected by the trade war.However, the results also showed that this change in the VaR of the US portfolio was greater than the change in the VaR of the Chinese portfolio, this means that the US portfolio has been more affected by the trade war than its Chinese counterpart.

Momentum Returns, Uncertainty, and Energy Prices: Evidence from Major Equity Markets

This paper examines factors that affect the profitability of momentum returns for the US, the UK, Japan, and Germany, for the period 1998-2018. More specifically, the paper examines the impact of factors that have been largely neglected in the relevant literature, such as energy price changes and economic policy uncertainty, along with macroeconomic and risk factors on the profitability of professional momentum portfolios that are often used as benchmarks in the institutional investor industry. The results indicate that, since the financial crises in the US and the EU, energy prices and economic-policy uncertainty have become important return determinants, along with market-related uncertainty that seems to have a stable impact overtime, especially for the US and UK portfolios. For example, between 2007 and 2018, oil price variance accounts for 20.80% of US momentum return variance while natural gas price variance explains a further 10.57% of momentum return variance in the US.

The Power of Ranking: The Ease of Doing Business Indicator and Global Regulatory Behavior

AbstractWe argue that the World Bank has successfully marshaled the Ease of Doing Business (EDB) Index to amass considerable influence over business regulations worldwide. The Ease of Doing is a global performance indicator (GPI), and GPIs—especially those that rate and rank states against one another—are intended to package information to influence the views of an audience important to the target, such as foreign investors or voters, thus generating pressures that induce a change in the target's behavior. The World Bank has succeeded in shaping the global regulatory environment even though the bank has no explicit mandate over regulatory policy and despite questions about EDB accuracy and required policy tradeoffs. We show that the EDB has a dominating market share among business climate indicators. We then use media analyses and observational data to show that EDB has motivated state regulatory shifts. States respond to being publicly ranked and some restructure bureaucracies accordingly. Next we explore plausible influence channels for the EDB ranking and use an experiment involving US portfolio managers to build on existing economics research and examine whether the rankings influence investor sentiment within the experiment. Using a case study of India's multiyear interagency effort to rise in the EDB rankings, as well as its decision to create subnational EDB rankings, we bring the strands of the argument together by showing how politicians see the ranking as affecting domestic politics, altering investor sentiment, and engaging bureaucratic reputation. Overall, a wide variety of evidence converges to illustrate the pressures through which the World Bank has used state rankings to achieve its vision of regulatory reform.

How Do Foreign Firms Manage Their Exposure to United States Portfolio Flows?

From 1990 to 2013, US portfolio flows to foreign stocks and bonds nearly quadrupled. Across 44 countries, I show that non-US firms with stock returns that are more sensitive to these cross-border flows are more likely to sell stocks and bonds, but display lower investment and employment growth rates. Using large natural and industrial disasters, I document that after deadly disasters occur, firms that are more sensitive to US flows are less likely to tap capital markets and tend to cut their real behaviors at higher rates, as would be expected if capital flight could potentially spill over to the real economy.

Portfolio performance of linear SDF models: an out-of-sample assessment

We evaluate linear stochastic discount factor models using an ex-post portfolio metric: the realized out-of-sample Sharpe ratio of mean–variance portfolios backed by alternative linear factor models. Using a sample of monthly US portfolio returns spanning the period 1968–2016, we find evidence that multifactor linear models have better empirical properties than the CAPM, not only when the cross-section of expected returns is evaluated in-sample, but also when they are used to inform one-month ahead portfolio selection. When we compare portfolios associated to multifactor models with mean–variance decisions implied by the single-factor CAPM, we document statistically significant differences in Sharpe ratios of up to 10 percent. Linear multifactor models that provide the best in-sample fit also yield the highest realized Sharpe ratios.

Macroeconomic announcements and stock returns in US portfolios formed on operating profitability and investment

The authors explore the reaction of US stock portfolio returns to macroeconomic announcements spanning the period from April 1998 to May 2017. Using daily returns of 25 portfolios formed on operating profitability and investment, the authors investigate the extent to which potential asymmetries permeate the stock portfolios following macroeconomic announcements. The three methodological approaches utilized in this study suggest that the ISM non-manufacturing index, employees on non-farm payrolls, retail sales, personal consumption expenditure and initial jobless claims have a significant impact on portfolio returns. Also, portfolios consisting of companies with higher operating profitability and investment level are found to be less responsive to announcements. As the particular area has received little currency over the years, this contribution is of great significance, because it provides insights into the reaction of returns in value-weighted portfolios to announcements on certain macro-indicators. At the same time, the study informs portfolio managers of the implications of macroeconomic news, which drive economic expectations and can reverberate through the expected returns in US stock portfolios.

Learning to Average Predictively Over Good and Bad: Comment on: Using Stacking to Average Bayesian Predictive Distributions

We suggest to extend the stacking procedure for a combination of predictive densities, proposed by Yao et al in the journal Bayesian Analysis to a setting where dynamic learning occurs about features of predictive densities of possibly misspecified models. This improves the averaging process of good and bad model forecasts. We summarise how this learning is done in economics and finance using mixtures. We also show that our proposal can be extended to combining forecasts and policies. The technical tools necessary for the implementation refer to filtering methods from nonlinear time series and we show their connection with machine learning. We illustrate our suggestion using results from Basturk et al based on financial data about US portfolios from 1928 until 2015.

Portfolio Performance of Linear SDF Models: An Out-of-Sample Assessment

We evaluate linear stochastic discount factor models using an ex-post portfolio metric: the realized out-of-sample Sharpe ratio of mean-variance portfolios backed by alternative linear factor models. Using a sample of monthly US portfolio returns spanning the period 1968-2016, we find evidence that multifactor linear models have better empirical properties than the CAPM, not only when the cross-section of expected returns is evaluated in-sample, but also when they are used to inform one-month ahead portfolio selection. When we compare portfolios associated to multifactor models with mean-variance decisions implied by the single-factor CAPM, we document statistically significant differences in Sharpe ratios of up to 10 percent. Linear multifactor models that provide the best in-sample fit also yield the highest realized Sharpe ratios.

How Do Foreign Firms Manage Their Exposure to United States Portfolio Flows?

From 1990 to 2013, US portfolio flows to foreign stocks and bonds nearly quadrupled. Across 44 countries, I show that non-US firms with stock returns that are more sensitive to these cross-border flows are more likely to sell stocks and bonds, but display lower investment and employment growth rates. Using large natural disasters and industrial accidents to identify bad shocks across countries, I document that after disasters occur, firms that are more sensitive to US flows are less likely to tap capital markets and tend to cut their real behaviors at higher rates. Additionally, during natural disaster years, firms with higher sensitivity to US flows have significantly lower stock performance during the months in which US portfolio investors exit their country’s capital market, and not vice versa, as would be expected if capital flight could potentially spill over to the real economy.

Is Anyone Listening? Does US Foreign Assistance Target People's Top Priorities?

The United States government has made repeated declarations over the last decade to align its assistance programs behind developing countries’ priorities. By utilizing public attitude surveys for 42 African and Latin American countries, this paper examines how well the US has implemented this guiding principle. Building upon the Quality of Official Development Assistance Assessment (QuODA) approach, I identify what people cite most frequently as the ‘most pressing problems’ facing their nations and then measure the percentage of US assistance commitments that are directed towards addressing them. By focusing on public surveys over time, this analysis attempts to provide a more nuanced and targeted examination of whether US portfolios are addressing what people care the most about. As reference points, I compare US alignment trends with the two regional multilateral development banks (MDBs) – the African Development Bank and the Inter-American Development Bank. Overall, this analysis suggests that US assistance may be only modestly aligned with what people in Sub-Saharan Africa and Latin America cite as their nation’s most pressing problems. By comparison, the African Development Bank – which is majority-led by regional member nations – performs significantly better than the United States. Like the United States, however, the Inter-American Development Bank demonstrates a low relative level of support for people’s top concerns. The paper concludes with a number of policy questions, which should be considered if the US government plans to concertedly pursue closer alignment with local concerns and priorities. These include whether the US government should: (1) require regular citizen surveys to help formulate foreign assistance strategies and programmatic priorities; (2) recalibrate health assistance programs in Sub-Saharan Africa; (3) increase support for the African Development Bank; (4) expand under-utilized private sector-based development tools, such as the Overseas Private Investment Corporation; (5) increase its engagement in select Latin American countries to help combat crime and insecurity; (6) better leverage the Millennium Challenge Corporation, which is the only U.S. development institution with an explicit mandate to support country-based priorities; and (7) expand support for USAID’s under-resourced economic growth programs, such as the Development Credit Authority.

What drives the US portfolio investments to the European Union countries?

This study identifies the major determinants of the US portfolio equity and debt investments in the European Union (EU) countries during 1997-2012. It examines whether the EU financial development has promoted the US portfolio investments. The results indicate that the higher stock market development accelerated by the European Monetary Union formation has boosted the portfolio equity flows. The stock market size has the larger positive effect on the equity flows than the stock market liquidity. The results also suggest that the higher bank development has decreased the portfolio investments. More bank credit flows have diminished the equity and debt flows. Finally, the results confirm that the financial crisis has not weakened the stock market development effect on the portfolio investments. The stock market liquidity has continued to be the main investment driver during the crisis period 2008-2012. The EU countries are still considered as the safe destinations for the US portfolio investments given their better macroeconomic fundamentals and institutions to better insulate themselves from crisis.

ROBUST ESTIMATION AND FORECASTING OF THE CAPITAL ASSET PRICING MODEL

In this paper, we develop a modified maximum likelihood (MML) estimator for the multiple linear regression model with underlying student t distribution. We obtain the closed form of the estimators, derive the asymptotic properties, and demonstrate that the MML estimator is more appropriate for estimating the parameters of the Capital Asset Pricing Model (CAPM) by comparing its performance with least squares estimators (LSE) on the monthly returns of US portfolios. The empirical results reveal that the MML estimators are more efficient than LSE in terms of the relative efficiency of one-step-ahead forecast mean square error in small samples.

Does cross-border syndication affect venture capital risk and return?

Venture capital (VC) cross-border syndication has increased significantly in recent years. This study examines the risk and returns of investments of US–European cross-border syndicates in US portfolio companies. We use a large sample of investments across four financing stages, and highlight several noteworthy differences between cross-border syndicates and previous US-only evidence. By comparison, US–European syndicates are larger than US-only syndicates, involve younger VCs, and focus more on later financing stages. Controlling for sample selection bias caused by the endogenous choices of exit route and exit timing, we examine the risk and returns of investments backed by cross-border syndicates. Consistent with evidence from US-only syndicates, alpha and beta decrease monotonically from the earliest (start-up) stage to the later stages of financing.

Does venture capital portfolio size matter?

PurposeThe purpose of this study is to investigate the effects of increased fund commitments on portfolio size and subsequent effects on portfolio success rates. This paper empirically analyzes the changes in average portfolio size over a 20‐year time period and how these changes affect the venture capitalists' ability to successfully exit their investments.Design/methodology/approachThe authors utilize venture capitalists' fund level data and conduct both univariate and multivariate analysis. The multivariate analysis is conducted using a two‐limit regression tobit model. This is justified since the authors' dependent variable is a ratio bounded by zero and one, hence the tobit specification is the most appropriate methodology.FindingsThe authors find that increasing the size of portfolios not only leads to a decrease in the number of successful investments but also significantly affects portfolio success rates. They also find evidence which suggests that some optimal portfolio size exists.Research limitations/implicationsThe sample was limited to independent private partnerships that raised funds specifically for investment in US portfolio companies and it represents all funds maintained in the SDC database with non‐missing data on fund size and other fund characteristics.Practical implicationsThere are three main practical implications derived from this study. First, venture capitalists overextend themselves by investing in too many portfolio firms. Second, some optimal portfolio size exists beyond which success rate of the venture capitalist's portfolio declines. Third, portfolio size is an important determinant of venture capital portfolio success rates.Originality/valueThe study presents new evidence that venture capitalists have a tendency to increase their portfolio size in years following growth in fund inflows, an idea that has not been investigated earlier. The authors also use data that is not adulterated by significant economic and financial conditions such as internet bubble burst of 2000 and financial crisis of 2007/2008.