Trump Made $70,000 by Praising Foreign Leaders and Bashing the Fed on Twitter
Last week, GovTrades launched a new dashboard tracking President Donald Trump’s investments in publicly traded stocks and privately held businesses. This post, focusing on Trump’s publicly traded investments, is the first in a series investigating the relationship between Trump’s financial holdings and his behavior in office.
We find that Trump avoids investing in individual stocks, and instead holds broad-market funds with returns that are closely correlated with the S&P 500 index. With this knowledge, we dig into how Trump may impact overall market returns in ways not necessarily aligned with the national interest. Specifically, we combine data from GovTrades with recent academic research on how Trump’s Twitter presence shapes market returns to quantify the impact of each tweet on the president’s financial wealth. Our results suggest that Trump earns up to $70,000 for tweets praising foreign leaders, relating to trade policy, and criticizing the Federal Reserve. While concerning, these results do not necessarily imply conflicts of interest with respect to Trump’s publicly traded portfolio, since Trump makes money when the stock market broadly performs well. Future research will investigate Trump’s privately held assets, which are much less transparent and constitute a much larger fraction of the president’s total wealth.
Basic facts about President Trump’s publicly traded investments
Trump hired JPMorgan Chase & Co to manage three trusts that hold publicly traded investments, meaning he does not have direct input over investment choices. Like the general public, however, he knows what holdings the funds contain, and therefore may take into account how his policy decisions as President impact his personal fortune.
First, none of Trump’s investments are in individual stocks or bonds. Instead, he holds mutual funds, exchange-traded funds, and other securities that invest in many assets.
Second, 89% of Trump’s portfolio is invested in equity funds, compared with only 11% invested in comparatively safer bond funds. On face, such a high equity allocation seems like poor financial planning for a 74-year-old. Indeed, most retirement funds reduce their equity exposure to around 30% for people who are Trump’s age [1], and even more aggressive economic models put optimal equity exposure around 60% [2]. However, this allocation may make sense for Trump in particular. First, he holds much of his fortune in cash accounts — over $50 million dollars, according to our analysis of his private holdings. Second, Trump’s immense wealth means he can afford a more aggressive investment strategy — even in poor market conditions, he would remain wealthy in absolute terms. Without existential downside risk, it makes sense to pick a portfolio with higher potential upside. Finally, much of Trump’s wealth is likely invested on behalf of his children, who have a much longer investment horizons and hence would prefer the higher long-run expected returns that equities offer.
Third, Trump’s largest investment is in a fund that tracks the S&P 500 index, which constitutes almost 25% of his portfolio. For context, the next largest investment — a JPMorgan-managed mutual fund that invests in large global companies such as Microsoft, Apple, and Nestle — constitutes only 6% of his portfolio.
As a consequence of these facts, Trump’s portfolio returns are closely tied to S&P 500 returns. Figure 1 plots the daily percentage return of Trump’s portfolio on the horizontal axis against the daily percentage return of the S&P 500 on the vertical axis. The blue line shows the relationship between the two, with a slope of 0.6. This implies that a 10% increase in the S&P 500 produces a 6% increase in Trump’s portfolio. In fact, variation in the S&P 500 explains 97% of the variation in Trump’s daily returns.
The fact that Trump’s wealth moves in almost perfect lock step with the overall stock market puts a new perspective on his obsession with market performance. Of course, a booming market could improve Trump’s approval ratings, possibly boosting his re-election odds. However, this analysis reveals another reason for Trump to keep financial markets happy -- it’s important for his bottom line.
The impacts of Trump’s tweets on market performance
Given the broad-market composition of Trump’s publicly traded portfolio, any conflicts of interest are less likely to arise through preference for particular companies or sectors. Instead, we should look for incidents in which Trump’s individual actions impact market returns in ways that are not necessarily in the public interest.
Recent research suggests that Trump’s Twitter feed represents an important way that the president can directly manipulate market returns. In a working paper issued by the National Bureau of Economic Research in January 2020, economists Francesco Bianchi (Duke), Thilo Kind (London Business School), and Howard Kung (London Business School) use high-frequency data on transactions immediately before and after Trump’s tweets to measure impacts on financial markets [3]. The authors study two types of tweets: (i) tweets expressing sentiments about foreign leaders or trade and tariff policy; and (ii) tweets criticizing Federal Reserve policy and Fed chair Jerome Powell.
Data from GovTrades allows us to quantify how much money Trump makes from these tweets through their impact on his personal publicly traded financial holdings. We find that each tweet increases the value of his portfolio by up to $70,000.
Tweets about trade and tariff policy
Trump often uses Twitter to express his views on trade and tariff policy, or otherwise express sentiments about foreign leaders that markets may interpret as signaling his planned policy course. For instance, on December 3, 2018, at 8:54am, Trump tweeted the following about his meeting with Chinese Premier Xi Jinping:
The authors of the study collected all such tweets between Trump’s election and November 2019, and classified them as either expressing positive or negative sentiments about trade policy and foreign leaders. To measure the impact on the S&P 500, the study compared the change in index value from five seconds before each tweet to five minutes afterwards [4]. Focusing on this narrow window ensured that changes represent the impact of the tweets themselves, as opposed to other confounding factors that may influence market value.
The study suggests that Trump’s tweets expressing positive sentiments boost the S&P 500 by about 2.9% [5]. This translates to an increase of about 1.75% in Trump’s publicly traded portfolio, given the association between his returns and the S&P 500. According to our estimates of Trump’s portfolio value, this implies that each positive tweet about trade policy or foreign leaders earns about $70,000.
Trump tweets about trade policy and foreign leaders all the time. Why hasn’t the cumulative effect of these tweets pushed the S&P continually up? Although positive tweets push up market values, negative tweets — criticizing foreign leaders or arguing for more restrictive trade policy — push them down. Considering all of Trump’s tweets on trade and foreign leaders together, the authors find no net effect.
Does that mean that Trump is not profiting from these tweets? It’s hard to say for sure. But without the optimism reflected in Trump’s positive tweets, it is possible that markets would more fully reflect the negative economic impacts of his restrictive trade policies, and therefore earn lower returns. In this sense, the language that Trump chooses for his tweets may reflect an attempt to guard against the market losses potentially imposed by his economic policy agenda. In the process, Trump also saves a lot of money himself.
Tweets about the Federal Reserve
Trump’s tweets about trade policy may feel relatively innocuous. A more dovish stance by Trump on trade may facilitate economic growth, generally a plus for the country. The fact that he also personally profits from this growth isn’t necessarily a problem.
However, Trump has recently taken to attacking the Federal Reserve and chair Jerome Powell, with the goal of pressuring the Fed to keep interest rates low. For instance, on April 16, 2018, Trump tweeted the following:
Russia and China are playing the Currency Devaluation game as the U.S. keeps raising interest rates. Not acceptable!
— Donald J. Trump (@realDonaldTrump) April 16, 2018
The Federal Reserve sets targets for the Federal funds rate. This important economic indicator impacts interest rates throughout the economy, from rates on loans between banks to rates on consumer mortgage and auto loans. Lower rates increase stock market valuations both by stimulating economic activity and by increasing the risk premium for holding stocks. However, the consensus among economists is that the Federal Reserve ought to behave independently of political pressure when setting interest rates — otherwise, the US risks slipping into a high inflation environment akin to the 1970s and 1980s, when annual inflation peaked at 13%. If Trump’s tweets succeed in pressuring the Federal Reserve to lower interest rates — eroding its independence from the political branch — then he may achieve his goal of higher stock market valuations at the expense of broader economic health.
It is possible to infer real-time market expectations for future Federal Reserve policy using transaction prices for financial derivatives called Federal funds futures contracts. The value of these products changes based on the actual Federal funds rate in future months. Therefore, present transaction prices indicate how market participants expect the Federal funds rate to change in the future.
Using transaction prices for Federal funds futures contracts, the authors investigate whether Trump’s tweets bashing the Fed impact market expectations about future policy. As with Trump’s trade policy tweets, the authors measure impacts on expected Federal funds rates by comparing transactions immediately before and after each tweet.
The results suggest that the cumulative effect of Trump’s Fed tweets pushed down market expectations of the Federal funds rate by 0.1% [6]. This may seem small, but is quite significant in the context of Fed policy — the Fed typically contemplates changes of 0.25% at a time.
How does this change in market expectations impact the value of Trump’s publicly traded portfolio? Prior research documents that an unanticipated 1% decrease in the Federal funds rate increases the value of the S&P 500 index by about 4.7% [7, 8]. Therefore, we estimate that in total, Trump’s Fed tweets earned the president about $11,000, or, given his 40 tweets pressuring the Fed to ease rates through November 2019, about $275 per tweet.
Investigating Trump’s private holdings
This analysis does not reveal a conflict of interest per se, but rather highlights how Trump can use his office to grow his fortune in ways that are not necessarily in the best interest of the country.
However, Trump’s publicly traded holdings amount to a small fraction of his total wealth. As our dashboard makes clear, the $4 million that Trump holds in publicly traded assets pales in comparison to his largest private holdings — for instance, Trump Tower in New York (40 Wall Street LLC) and the Trump International Hotel and Tower in Chicago (401 North Wabash Venture LLC) are valued at over $50 million each. Private holdings are much less transparent, as their valuations and revenues may not be publicly disclosed.
Therefore, if Trump were to use his office to grow his wealth, we believe he would focus on his privately held assets. The potential returns are much higher, and the risk of getting caught is lower. Our next post will investigate this possibility.
Footnotes
[1] Bodie, Zvi and Treussard, Jonathan, Making Investment Choices as Simple as Possible: An Analysis of Target Date Retirement Funds (January 21, 2007). Available at SSRN: https://ssrn.com/abstract=900005 or http://dx.doi.org/10.2139/ssrn.900005.
[2] These models assume that labor supply is flexible even later in life -- that is, they assume that individuals have the option to work again to hedge downside financial market risk. See Gomes, Francisco J, Laurence J. Kotlikoff, and Luis M. Viceira. "Optimal Life-Cycle Investing with Flexible Labor Supply: A Welfare Analysis of Life-Cycle Funds." American Economic Review: Papers & Proceedings 2008, 98:2, 297-303. Available at: https://pubs.aeaweb.org/doi/pdf/10.1257/aer.98.2.297.
[3] Bianchi, Francesco, Thilo Kind, and Howard Kung. “Threats to Central Bank Independence: High-frequency identification with Twitter.” NBER Working Paper. Available at: https://drive.google.com/file/d/1khrQPCwg-XrdzcwEqjdvXyHBYWVIOPu0/view
[4] Technically, the authors used tick-by-tick data on trades of the SPDR S&P 500 ETF, which tracks the S&P 500 index. Since multiple trades typically clear each second, the authors used the median trade within each one-second clearing period to measure changes.
[5] See Table 9, Panel B. Coefficients are reported in log points. The authors unfortunately do not report standard errors on their estimates that would allow us to generate confidence intervals for our own estimates. However, with a t-stat of 2.3, the estimated effect is statistically significant from 0 at the 5% level.
[6] See Table 2, Panel A. Coefficients are reported in basis points and report the average effect for each tweet. The cumulative effect is obtained by multiplying the average effect by the count of tweets in the sample (40).
[7] See Table 2, Column (b) in Bernanke, Ben S and Kenneth N. Kuttner. "What Explains the Stock Market's Reaction to Federal Reserve Policy?" The Journal of Finance, May 2005. Available at: https://onlinelibrary.wiley.com/doi/full/10.1111/j.1540-6261.2005.00760.x.
The outcome variable in this paper is not the S&P 500, but rather the CRSP Value-Weighted Index. The two indices are quite similar; in Footnote 4 of the paper, the authors indicate that the version of their results using the S&P 500 are nearly identical.
[8] The authors in Bianchi, Kind, and Kung (2020) do explicitly compute the impact of the Trump tweets on the S&P 500, but do not find statistically significant effects. However, I am skeptical of these results, as they lack the statistical power to detect the likely impact of individual tweets on the S&P 500 through the Fed funds channel. Specifically, given their sample size of 40 and an expected true effect on the S&P of -0.0025% * -4.67% = 0.012%, there is only about a 5% chance of detecting an effect that is statistically significant at the 5% level. Therefore, I use the estimates from the Bernanke and Kuttner (2005) paper.
