US Earnings Season vs. US Fiscal Deadlock

US corporate reporting opens today (Alcoa) and in Friday JPMorgan is due to report. Would the earnings season gain the focus of investors? Source: Deutsche Bank; assuming 40% recovery rate

The relation between finance and physics

“The true logic of this world is in the calculus of probabilities” – James Clerk Maxwell First I should make the disclaimer that I am graduated in finance and my interest in physics is due to a book I’ve read last summer on quantum physics (“Absolutely Small : How Quantum Theory Explains Our Everyday World” by Michael D. Fayer– strongly recommend it, by the way). Recently I’ve had the chance to listen a lecture by Prof. Jim Al-Khalili (by the way he has a book translated in Bulgarian - Paradox: The Nine Greatest Enigmas in Science) and also have found the Feynman Lectures on Physics (still missing Volume 2, however), which are greatly inspirational! The idea to look for a link between finance and a pure science as physics lies in the characteristics that both share – the probabilistic nature. Probability is the way to deal with uncertainty no matter where – in nature or in finance. In a way, successful investing is a probabilistic activity. It is the probability that makes both finance and physics very exciting but it seems to me in finance people tend to neglect this probabilistic nature. One of the common concepts is the Brownian motion. In finance we have the geometric Brownian motion model for price changes developed by Samuelson who rediscovered the work of the French mathematician Bachelier. When simulating stock prices we use two major components: drift (expected return) which is the deterministic component and volatility, which is the random shock component. In physics, as Feynman writes that the most precise description of nature must be in terms of probabilities. For instance, the probability plays an important role in the specification of a position of a particle in describing the structure of atoms. Hence, the way of looking at atom is as a nucleus surrounded by electron cloud (which is essentially probability cloud) – this is the atomic orbital model.

Rescaled Range (R/S) of returns of Bulgarian Stock Exchange index SOFIX and Bucharest Stock Exchange index BET

Rescaled Range analysis of the Bulgarian stock exchange index SOFIX and Bucharest stock exchange index BET for the period November 2010-August 2013 (daily observations) reveals that SOFIX return shows characteristics of long memory, while BET return is closer to random walk. Long memory feature contradicts efficient market hypothesis. When return series show long memory characteristics, it means the returns are not independent over time, ie past returns can help predict future returns, thereby violating the market efficiency hypothesis. Briefly, Rescaled Range calculates Hurst exponent (H exponent), which has the following values: H<0.5 is mean reverting characteristics of the return series, while H=0.5 is random walk and H>0.5 is long memory (persistence area). We can however divide the interval 0.0 to 1.0 into thirds, ie from 0-0.33 is the mean-reverting area, 0.34-0.67 is the random walk area and 0.68-1.0 is the persistence area. In the case of SOFIX Hurst exponent is 0.73 and for the same period the Hurst exponent of BET is 0.58. It should however be noted that during the different time frames, the indexes characteristics change - SOFIX return was random walk at some point of time and BET return was persistent. There are of course other indicators of long memory (as GPH, KPSS for instance); additionally the time period considered is short. The idea is just to show some insight. The analysis follows Jason Voss publication on S&P 500 in Enterprising Investor blog in Feb 2013.