Category Archives: investment

3/2/21: Monetary Easing and Stock Market Valuation

There has been quite a puzzling development in recent years in the monetary policy universe. A decade plus of ultra low interest rates has been associated with rising, not falling, risk premium in investment markets. In other words, a dramatically lower cost of new and carried debt induced by lower interest rates - a driver for lower risk, is being offset by something else. What?

Laine, Olli-Matti paper "Monetary Policy and Stock Market Valuation" (September 18, 2020, Bank of Finland Research Discussion Paper No. 16/2020: tries to explain. 

To start with, some theory - especially for my students in the Investment and Financial Systems courses. Per author, "the value of a stock is the present value of its expected future dividends... Hence, the changes in stock prices must be explained by 

  • either changes in dividend expectations or 
  • changes in discount rates. 

The discount rate, or (approximately) expected rate of return, can be thought as a sum of a risk-free rate and a risk premium. Theoretically, monetary policy should have an effect on stock prices through the risk-free rates. In addition, monetary policy should affect dividend expectations, for example, through the output or debt interest payments of firms. The effect on the risk premium (not to mention the term structure of risk premia), however, is less clear."

Looking at Eurostoxx50 index components, Laine shows "...that the average expected premium has increased considerably since the global financial crisis. This change is explained by the change in long-horizon expected premia. ... monetary policy easing has had a positive impact on the expected average premium."

Specifically (emphasis added): "a negative shock to the shadow rate is estimated to increase average expected premium persistently. Instead, the results show that monetary policy easing temporarily decreases short-term expected [risk] premia. This means that expansionary monetary policy steepens the slope of the term structure of risk premia."

This is not exactly new, as Bernanke and Kuttner (2005) observed that "expansionary monetary policy generates an immediate rise in equity prices followed by a period of lower-than-normal excess returns. ...However, Bernanke and Kuttner (2005) do not study the effect on the long-run excess returns. My results show that effect on long-horizon expected premia has a different sign. This effect on long-horizon premia seems to more than offset the effect on short-horizon premia."

Interestingly, "Contractionary monetary policy increases the short-term premia temporarily, but decreases long-horizon premia persistently. The effect on average expected premium is negative. Thus, monetary policy tightening actually makes stocks expensive relative to the expected stream of dividends. The results provide no evidence that expansionary monetary policy causes stock market bubbles..."

Here is (annotated by me) a chart showing evolution of implied and actual risk premia:

From theory perspective, therefore, monetary policy "can affect equity prices through the dividend expectations, expected risk-free rates or expected premia":
  • "The effect of expansionary monetary policy on the dividend expectations is probably positive, because expansionary monetary policy can be expected to increase output and firms’ earnings.
  • "Expansionary policy probably lowers the risk-free rates, but it is also possible that the effect is totally different. Central bank’s rate cut can increase risk-free rates, if people think that the rate cut eventually increases inflation. 
  • "As for the expected premium, the sign of the effect is unclear. ... Gust and López-Salido (2014) show theoretically that expansionary monetary policy lowers the premium ... where asset and goods markets are segmented. When it comes to quantitative easing, ... investors who have sold their assets to the central bank rebalance their portfolios into riskier assets, which lowers their expected returns. ... Theoretically, it is also possible to argue that monetary policy easing actually increases the expected premium. If one assumes that there exists mispricing like Galí (2014) and Galí and Gambetti (2015), then the sign of the response is ambiguous. ... This means that monetary policy easing increases the expected premium implied by dividend discount model (see Galí and Gambetti, 2015, p. 250-252)."

So, onto the empirical results by Laine: 

  1. "Interest rates have declined considerably since the global financial crisis, yet the expected average stock market return has remained quite stable at around 9 percent. This implies that expected average stock market premium has increased remarkably. This rise is mainly explained by the premia over a discounting horizon of four years.
  2. "These results may seem unintuitive as the prices of stocks have risen, and ratios like price-to-earnings have been historically high. However, high price-to-earnings ratios do not necessarily mean that stocks are expensive, because the value of a stock is the present value of its expected future dividends.
  3. "When it comes to the role of monetary policy, the results show that monetary policy easing decreases short-horizon required premia, but increases longer-horizon premia
  4. "The effect on expected average premium is positive, i.e. expansionary monetary policy lowers the prices of stocks in relation to the expected dividend stream."

2/2/21: The Disaster of Investing via Smartphones?

Some stuff I've been reading that (sometimes) falls into current newsflow: 

Kalda, Ankit and Loos, Benjamin and Previtero, Alessandro and Hackethal, Andreas paper, titled "Smart(Phone) Investing? A within Investor-Time Analysis of New Technologies and Trading Behavior"from January 2021 (NBER Working Paper No. w28363, :

The authors tackle an interesting issue relating to the automated and low cost investing platforms (proliferating in this age of fintech). Per authors (emphasis is mine, throughout): "Technology has dramatically changed how retail investors trade, from placing orders using direct dial-up connections in the 1980s or Internet-based trading in the 1990s to the more recent rise of robo-advisers. With few exceptions, the introduction of these new technologies is generally associated with a decline in investor portfolio efficiency." In addition, "whether good or bad for investors, it is accepted that new technologies influence investor behavior". 

In this unique study, the authors used data that comes "from two large German retail banks that have introduced trading applications for mobile devices. For over 15,000 bank clients that have used these mobile apps in the years 2010-2017, we can observe all holdings and transactions, and, more important, the specific platform used for each trade (e.g., personal computer vs. smartphone). [As the result of having such a granular data over time] we can conduct all our main tests comparing trades done by the same investor in the same month across different platforms."

The authors present four sets of results:

  1. "First, we study if the use of smartphones induces differences in the riskiness of trades. Comparing trades by the same investor in the same year-month, we find that the probability of purchasing risky assets increases in smartphone trades compared to non-smartphone ones
    • "smartphone trades involve assets with higher volatility and more positive skewness. [Thus], smartphones increase the probability of buying lottery-type stocks by 67% of the unconditional mean for smartphone users."
  2. "Second, we examine the effects of smartphones on the tendency to chase past returns. We find that smartphones increase the probability of buying assets in the top decile of the past performance distribution. Smartphones increase the probability of buying assets in the top 10 percent of past performance by 12.0 percentage points (or 70.6% of the unconditional mean)." In other words, smartphones trades involve severe and pervasive biases in investor decision making.
  3. "Third, we investigate if investors selectively use smartphone to execute their risky, lottery-type, and trend-chasing trades. In this scenario, investors could simply substitute their trades from one device to another, without any real consequences for their overall portfolio efficiency. ....We find that, following the launch of smartphone apps, investors are—if anything—more likely to purchase risky and lottery-type assets and to chase hot investments also on non-smartphone platforms. ...this evidence potentially suggests that investors are learning to become overall more biased after their initial use of smartphones to trade."
  4. "...smartphone effects are stronger during after-hours (i.e. following exchange closure). Institutional differences between trading on official exchanges and in after-hours markets do not drive this heterogeneity. Given that individuals are more likely to rely on the more intuitive system [System 1-type] later in the day (Kahneman,2011), stronger effects during after-hours are consistent with smartphones facilitating trades based more on [intuitive] system thinking."

As an interesting aside, it is worth noting that the above results have nothing to do with the demographic biases or the potential lack of trading experience by smartphone-using investors. As noted by the authors: "German investors that adopt smartphone trading are, on average, 45 years old with nine years of experience investing with the banks."

Another aside is that authors also tested if the adverse effects of smartphones-based trading can be attributed to the first / early usage of these devices. It turns out not: "The effects of smartphones are stable from the first quarter of usage up to quarter nine or afterwards. The effects on volatility and skewness of trades, and probability of purchasing past winners are also stable over time."

To conclude: "Collectively, our evidence suggests that investors make more intuitive (system 1-type) decisions while using smartphones. This tendency leads to increased risk-taking, gambling-like activity, and more trend chasing. Previous studies have linked these trading behaviors to lower portfolio efficiency and performance. Therefore, the convenience of smartphone trading might come at a cost for many retail investors."

Ouch! Then again, this is fitting well with what we are observing happening in the markets these days: amplified herding, trend chasing, lottery-like speculative swings in investment capital flows, recency effects of overbidding for previously outperforming stocks and so on. 

13/11/20: The economy has two chronic illnesses (and neither are Covid)

My column for The Currency this week covers two key long-term themes in the global economy that pre-date the pandemic and will remain in place well into 2025: the twin secular stagnations hypotheses and the changing nature of the productivity. The link to the article is here;


31/10/20: Gold Coins Market is Still Hedging Residual Covid Risk

Sales of the U.S. Mint gold coins have moderated off their pandemic highs, but remain elevated by historical standards, especially controlling for higher gold prices:

Since hitting a pandemic-period high of 216,500 oz in March 2020 (the highest sales volume since April 2013), the demand has moderated through June, topped 145,000 in July and 149,000 oz in August, and has been around 91,500 through the four weeks of October. This puts October sales above the last three years' average.

Average gold weight per coin sold remains relatively elevated and is co-trending with price per oz, most likely indicating lasting FOMO effect (herding by investors). The correlation is weaker than during prior episodes of major crises and recessions, suggesting that the pandemic-period demand is probably less influenced by the herding effects than in prior crises.

Annualized data through October also confirms precautionary, but not 'flight to safety' type of demand:

As the pandemic re-accelerates, it will be interesting to see how seasonality (uplift in end-of-year sales) plays out against the pandemic-related hedging positioning of investors.

4/10/20: Technological Deepening Is Coming for Our Jobs


In my recent article for The Currency (link here:, I argued that COVID19 will act as an accelerator of technological capital deepening in the modern economies, with a resulting faster displacement of workers (including highly skilled ones) by technology. 

McKinsey survey of the developing trends in businesses strategic responses to the pandemic confirms my hypothesis:

Per above, across all sectors, and (peer charts below) across specific sectors, businesses are planning to prioritize deployment of technology in addressing long-term change in response to the current pandemic. 

McKinsey state that "Fifty-five percent of leaders anticipate that at least half of their organization’s workforce will be fully or partially remote postcrisis. While the expectations vary widely by industry—from 69 percent predicting this level of remote work in technology, telecommunications, and media to 43 percent in advanced industries—even in the industries where manufacturing, patient care, and sales transactions often require people at offices, stores, plants, and other company facilities, a significant portion of the workforce may be partially or fully remote." Source: And "Our survey results show that executives are focused on three courses of action ... making good decisions more quickly, improving communication and collaboration, and making greater use of technology."