Acaban de publicar en FundsSociety nuestra visión sobre los retornos del mercado bursátil chino durante la próxima década. Puede consultarse aquí. En resumen, creemos que los índices chinos estarán en el mismo nivel de aquí a diez años (en el mejor de los casos, asumiendo múltiplos de valoración constantes), ya que el proceso de reequilibrio no sólo implica mover recursos de la inversión al consumo, sino también de los beneficios a los salarios.
Dado que la participación de los beneficios en el PIB tiene que caer a la mitad si se quiere completar el proceso de reequilibrio, y teniendo en cuenta que en el mejor de los casos el PIB en términos nominales crece al 7% en la próxima década, los beneficios en términos absolutos quedarían igual que hoy. Una aplicación muy elegante de la ecuación de beneficios Levy-Kalecki.
[Publicado originalmente en FundsPeople]
Desde que Alcoa diese el pistoletazo de salida a la presentación de los resultados empresariales de las empresas estadounidenses, los analistas económicos llevamos un par de semanas siguiendo con atención los números que al final presentará el conjunto de las empresas del S&P500. En un escenario como el actual de elevada incertidumbre a nivel macroeconómico en todo el mundo, la presentación de los beneficios de los integrantes del S&P500 representa un indicador valioso de dónde estamos y nos da una razonable idea de lo que podemos esperar en los próximos trimestres.
A riesgo de simplificar, para el presente artículo se tendrá en cuenta que hay dos maneras para pensar sobre los beneficios a nivel agregado: bottom-up y top-down.
La visión bottom-up es bien conocida y requiere de poca elaboración. Se suman una a una las estimaciones de consenso de cada una de las 500 empresas del S&P500 con el fin de obtener el número agregado de todo el índice. La principal ventaja del método es que compila las predicciones de analistas especializados en una industria o en un grupo de empresas, lo que hace que las predicciones sean más informadas que las de alguien que no tenga dicho conocimiento granular. Las principales desventajas del método son dos, que es intensivo en información (para llegar a la cifra agregada de beneficios se necesitan las estimaciones de los beneficios de las 500 empresas del S&P500, una tarea nada desdeñable) y, por otra parte, dicho método puede conducir inadvertidamente a falacias de composición no deseadas: si uno hubiese agregado las exuberantemente racionales estimaciones de consenso de finales de los 90, uno hubiese descubierto que tales estimaciones daban números superiores (o similares) a la cifra de beneficios global presentada en las cuentas nacionales. Dado que era de esperar que el resto de la economía estadounidense, una vez excluidas las empresas del S&P500, generase algún beneficio en aquellos años, las estimaciones bottom-up de aquel entonces, aunque aparentemente consistentes a nivel individual, a nivel global daban lugar a resultados ridículos. Continue reading
Chinese policy makers were gathered at the National People’s Congress (NPC) a couple of weeks ago to discuss the economics goals for the next few years. Given the recent turmoil in Chinese financial markets, it was an important meeting for international analysts.
Several issues were addressed at the NPC, but the most important one was the strict commitment of the Communist Party to keep sustainable (and moderately high) growth rates. For this year they have abandoned fixed targets and they have opted for some flexibility in their goals (e.g. 6.5% – 7%). ‘More active’ fiscal policies, through higher current and investment expenditures and tax cuts, were also put forward in order to achieve deficits around 3% of GDP – which is in stark contrast with the government position of the last years. But as we will see in a while, these goals (6-7% nominal GDP growth plus 3% of fiscal deficits) do not meet People’s Bank of China projections for government debt, unless other ‘extraordinary’ government operations (bailouts of banks and local governments in particular) are brought into the picture. Finally, the Communist Party has also suggested higher levels of inflation (around 3%) than in recent Chinese history.
[Here, in The Beauty Contest, we plan not to write only about finance and macroeconomics, but about other topics too. We are lucky to start this endeavour having José de Arcos with us, who will write today about the significance of Einstein’s gravitational waves. José de Arcos holds a Ph.D. in Physics from the Illinois Institute of Technology and he is currently working as a Postdoctoral Research Fellow at the Harvard Medical School. He also participated in the Daya Bay reactor neutrino experiment in Shenzhen, China]
I recently had the great honor of attending a lecture by Dr. Rainer Weiss where he introduced the achievements of the Laser Interferometer Gravitational-Wave Observatory (LIGO) experiment  in an easy going and approachable tone. He has inspired me to spread the word and share with you one of the most remarkable accomplishments in human history in my own way.
In the past, no such long time ago in the timescale of the universe, the first human species looked up toward the stars for first time, wondering, as we do today, what secrets were hidden in those twinkling lights. The first astronomers deduced that there was some kind of pattern in the never-ending dance of stars, a periodicity that taught them when was optimal to harvest their crops, and as a result the first civilizations flourished. The same lights showed the way to all travelers, sailors and wanderers who pushed our own frontiers a bit further at a time, until we mapped the whole world. But even then, we kept looking up to the infinity of the darkness, still wondering what secrets were hidden in those sparkling dots. One of the first experimental physicists, Tycho Brahe, kept track of the position of the planets for decades, providing Johannes Kepler with enough data to recognize a mathematical pattern: the planets moved in an elliptical fashion. And along came Newton, who, in a staggering demonstration of intelligence, was able to unravel the laws of gravitation. The work of three men changed the history of all humanity in a remarkable way.
Celestial navigation was one of the first practical applications of astronomy
[This post was co-written with Rafael Wildauer, Ph.D. Candidate at Kingston University, who is doing research on the links between income and wealth distribution, credit, growth and financial stability]
We are pleased to present our first report on the US economy using a model we have developed together over the last year. We will only provide here a brief summary with the main conclusions; interested readers can read the whole report for free here. Senator Sander’s economic program (and the discussion that has erupted in the last few weeks) has provided us with a nice example of why having a simple but holistic model of the US economy can help a lot in discussing economic policy issues and in dispelling ‘half-way’ economic reasoning. Because a copy-paste strategy from the report would be boring for the readers of the blog, we have decided to add a brief analysis of the Mr. Sander’s economic program as an example of the usefulness of the model advocated here. We think it is worth discussing what has been left out by Gerald Friedman as well as by his critics – notably Christina and David Romer. If you already read the original report, then you can skip the first section and go directly to the section dealing with Mr. Sanders’ economic program.
The Kingston Financial Balances model (KFBM)
First, a few words about the model. The Kingston Financial Balances Model (KFBM) is a stock-flow-consistent (SFC) model that tracks the evolution of the main variables of the US economy. A SFC model is, in a nutshell, a framework that ensures that all real and financial flows of an economy accumulate into stocks over time. For many people (e.g. engineers, physicists and accountants), we are sure this definition will not be very innovative. But in economic modelling, it is. Most of the economic modelling is carried out without any concern for the accounting consistency of real world economies. At the most basic level, such models simply estimate ‘sophisticated’ econometric equations for the GDP components (i.e. consumption, investment, etc.), and then they sum them up to come up with a (usually short-term) forecast for GDP, but without mentioning the implications of these expenditures for the financial positions of the different sectors of the economy. At a more advanced level, exemplified for instance by the Dynamic Stochastic General Equilibrium (DSGE) models, the sophistication falls on a rational description of the agents of the economy, but again, with little concern for the accounting consistency of the framework. In other words, economists have been in general very busy to come up with more sophisticated models, but accounting consistency is not among the top priorities.
The governor of the People’s Bank of China (PBoC), Zhou Xiaochuan, had some days ago an interesting interview with the financial magazine Caixin. You can find the English transcript here. The initial part of the interview is really worth reading (and not so much the last part, which deals with criptocurrencies and other topics that are not “core issues” for the PBoC at the moment). Right at the beginning Zhou talks about the prospects of an additional (or not) depreciation of the renmimbi and how China has moved from a dollar-peg regime to a basket-currency regime (although such baskets are still very loosely defined). And by the way, he is not very concerned about international reserves going down (around 100USD billion in January), because he thinks this process is mainly driven by Chinese firms trying to reduce their foreign currency denominated liabilities, a process that (obviously) will not be endless. As he says:
As such, it is necessary to distinguish capital outflows from capital flight. It is normal for export-oriented enterprises to choose their foreign exchange conversion strategies and adjust their liability structures after weighing benefits and costs. Such adjustment will not be endless. Such behaviors do influence capital flows and foreign exchange reserves, but they do not necessarily constitute capital flight.
But the most interesting part of the interview is when he talks about investment expenditures. Although he does not address explicitly in these paragraphs the rebalancing process (how to reduce current investment levels and increase at the same time consumption without any disruption), it is clear that some conclusions for the rebalancing issue can be drawn from the following statement [emphasis added]:
February is always a very sad month for the Spanish financial industry, and this February has not been an exception. Pablo Fernández, professor at the IESE Business School, and collaborators have published the latest version of their annual paper on the returns of pension funds in Spain. The paper of this year, ‘Return of Pension Funds in Spain. 2000-2015’, studies the track-record over the last fifteen years of the 322 Spanish pension funds that have been in existence at least for fifteen years. You can find the paper here. The main takeaway? The performance of the pension fund industry in Spain has been simply terrible. Well, it has been even worse than that. As the authors succinctly explain in the abstract (unfortunately the paper is only in Spanish):
During the last 15 year period (2000-2015), the average return of the pension funds in Spain (1.58%) was lower than the return of government bonds (5.40%). Only 1 fund (out of 322) had a higher return than the 15-year government bonds. Nevertheless, on December 31, 2015, 7.8 million investors had 67.6 billion euros invested in pension funds.
What the abstract does not say (but the paper does) is that with an average return of 1.58%, pension funds were not even able to beat inflation! More details: only 2 funds (out of 322) outperformed the Ibex 35 (the main Spanish stock market index), only 1 fund outperformed 15-year government bonds and 47 displayed in average negative performance. Although the paper gives us more interesting details (very small correlation between fund size and return, no correlation between number of beneficiaries and return, etc.), the crucial part is about returns and how pension fund performance compares against other benchmarks. In other words, pension fund performance has been simply embarrassing and it should make us to think why one should invest in one of these vehicles. And as it was reported by Félix López one year ago in this blog, the 2014 paper by Pablo Fernández and collaborators reached the same conclusion: pension fund performance has been consistently dismal.
This is a follow-up on my previous post, where I dealt with the latest Tetlock-Gardner’s book, Superforecasting: The Art and Science of Prediction. As I mentioned there, there are several valuable lessons to learn. Although the best way to hone our forecasting abilities is obviously getting some practice in prediction tournaments, it would be wrong to think that this is the only field where we will be able to apply our new knowledge. As long as we try to answer very specific questions with a reasonable time spam, we keep record of our initial forecasts and we commit to update our beliefs on a regular basis, then this routine qualifies as a useful exercise to improve our forecasting abilities. And it seems that investing in equities meets these requirements.
In particular, I realised on further reflection that there are many similarities between the way superforecasters make their predictions and the way value investors select their investments. So I was wondering whether superforecasters can give us some insights for value investors or not. And indeed they can. Although the comparison may seem a bit awkward at first, we should remember that the purpose of the book is how we can improve the way we make our forecasts, and in this regard value investors have to make forecasts as everyone else. Therefore, although the most succesful value investors already incorporate many of the procedures regularly used by superforecasters, it is worth attempting to make a systematic comparison in order to see what parts of the value investing approach can benefit from superforecasters’ abilities.
New year, new predictions. Or at least that’s what many economists are doing during these weeks. But it turns out this year that a couple of months ago was published the book Superforecasting: The Art & Science of Prediction by Philip Tetlock and Dan Gardner, and I wanted to start the year with the topic of predictions. So economic forecasters, beware.
One reason to read the book is because Kahneman says to do so in the book cover (well, that’s enough reason for me). If for you that’s not enough, then you may be thinking that the whole topic of forecasting the future is a bit fanciful and it should not deserve any serious attention – and even more in economics. After all, one could argue that we have the overwhelming daily evidence of so-called experts making their predictions and failing spectacularly most of the time. If they are experts and cannot get it right, who could? It seems then that since Cassandra’s time, Homer’s Iliad character, forecasting has been an elusive activity for the mankind.
Cassandra and the fall of Troy
Professor Michael Pettis has recently published another brilliant post on the Chinese rebalancing issue. We regularly follow Pettis’ views on the Chinese economy, which we consider valuable if one wants to understand the macro management dilemmas China will have to face. In his post, Pettis does not address how the rebalancing process should be ideally done (something which he has explained on several occasions), but rather how much time China has in order to accomplish it successfully. Pettis says that:
Credit growth in China is too high as are current debt levels, and the sooner Beijing gets credit growth under control, the better. This latter statement in itself is not controversial of course, but my simple debt model shows just how urgent it is for Beijing to get credit growth under control. It clearly does not have ten years or even seven years. It might have five years, but only if the markets – Chinese investors, businesses, and savers, both wealthy and middle class – are convinced that it is moving in the right direction.
In other words, the current high levels of debt can derail the rebalancing process if it is not done quick enough. In order to understand the link between debt levels and GDP, Pettis proposes a simple model that captures their dynamics over the long run (up to 2023). In his baseline scenario, Pettis assumes (following the trend of the last few years) that nominal debt initially grows twice as fast as nominal GDP (notice the use of nominal values), but gradually converging in a linear way to the growth rate of GDP by the end of 2023 – at that moment the economy reaches a steady-state position, and GDP and debt grow at the same pace. Depending on the GDP growth rate assumed, Pettis’ model projects debt-to-GDP ratios from 251% (with a 3% growth in GDP) to 274% (with a 6% growth) by the end of the period, too high in comparison to other economies. He then proposes alternative scenarios, but the result is the same: unless Beijing advances more radical measures to curb debt growth and improve the efficiency of the financial system, the growth in debt will derail the rebalancing process.