Federal Open Market Committee meetings (aka FED meetings) have a significant influence on the number of different assets (see for example our article related to drift in equities during FED meetings). The main channel which FED uses to influence the US economy is the level of short term interest rates. Therefore, it’s not a surprise that FED meetings have influence also on long-term interest rates. But just how big? Bigger than most people think. We are presenting one interesting research paper written by Sebastian Hillenbrand, which shows that the whole secular decline in equity yields and long-term interest rates since 1980 was realized entirely in a 3-day window around FOMC meetings. Now, that’s called the influence …

Author: Hillenbrand

Title: The Secular Decline in Long-Term Yields around FOMC Meetings

The U.S. (and world too) economy is currently entering a recession. Right now, everybody can see it, the only question is how deep it will be. But is it possible in a real-time predict if the economy will enter a recession? And will that information help us to better set % allocation of equities in our portfolio? Most of the macroeconomic data shows recession in macroeconomic reports with a significant lag. There are multiple different forecasting models which we tries to predict recession or at least estimate the probability that we are entering into one. We are presenting one interesting research paper written by Jonathan Hartley which shows that prediction markets (betting markets created for the purpose of trading the outcome of events) can be successfully used as a complementary tool in various economic forecasting tools. Prediction markets can be used to measure risk in U.S. equities, credit spreads, the U.S. Treasury yield curve, and U.S. dollar foreign exchange rates.

Author: Hartley

Title: Recession Prediction Markets and Macroeconomic Risk in Asset Prices

There are many calendar / seasonal anomalies by which we can enhance our strategies to gain more return. One of the least frequent but still very interesting anomalies is for sure the Pre-Election Drift in the stock market in the United States. This year is the election year, and public discussion is getting more heated. The current president of the United States and candidate for re-election, Donald Trump, is a peculiar figure who split the population of the United States into two parts, ones who hate him and those who love him. We can probably expect volatile market moves as we will move closer to this year’s presidential election. But this post will not be about politics but about trading. In this post, we will try to uncover a pattern in historical data that shows significant market moves a few days before elections…

Authors:Vojtko, Cisar

Title:Pre-Election Drift in the Stock Market

The end of the year is a good time for a short recapitulation. Apart from other things we do (which we will summarize in our next blog in a few days), we have published around 50 short blog posts / recherches of academic papers on this blog during the last year. We want to use this opportunity to summarize 10 of them, which were the most popular (based on Google Analytics tool). Maybe you will be able to find something you have not read yet …

We are continuing in our short series of articles about calendar / seasonal trading. The main focus of this paper is to show that the well-working calendar / seasonal anomalies can be refined. The aim is to find the right factors and find a way how to combine them in a search for profit from the practitioner’s point of view. Based on our previous research, calendar anomalies are profitable, but there is a possible way how to enhance their performance. This can be done by employing momentum strategies. By assigning a weight to assets from a diversified set according to their momentum value, it is possible to find a profitable asset during various global market conditions. Moreover, a trend factor is used to ensure that when market conditions are not favorable, the strategy will not trade. Such addition is a typical approach used for reducing maximal draw-downs. Finally, since this paper is written from the practitioner’s point of view, we are assuming some model transaction costs and examine the strategy in their presence.