US Dollar (USD) LIBOR rates: technical predictability overview

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Written by Forex Automaton   
Wednesday, 01 October 2008 10:42
Article Index
US Dollar (USD) LIBOR rates: technical predictability overview
LIBOR volatilities
LIBOR autocorrelations
LIBOR cross-correlations
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This article begins a series of analysis reports investigating a degree of predictability in the LIBOR rates, a popular capital cost indicator. The analysis is based on historical LIBOR interest rate data released by the British Bankers Association. I continue with the same technique proved useful in the predictability analysis of forex exchange rates, as our interest in the interest rates in general is in part provoked by the results of the latter analysis, namely:

  • sometimes, one forex exchage rate can "show the way" to a number of others, or in other words, foretell (in a probabilistic or statistical sense) their movement.
  • when that happens, it is usually the exchange rate with a large interest rate differential showing the way to the ones with lower interest rate differentials.

Autocorrelations in s/n-o/n USD LIBOR 2002-2008

Fig.1: LIBOR heartbeat: autocorrelation in logarithmic returns of historical USD LIBOR rates, s/n-o/n duration, shown against the backdrop of statistical noise (red). The noise is obtained from martingale simulations based on the recorded LIBOR volatility for the period under study (2002-2008). The noise is presented as mean plus-minus 1 RMS, where RMS characterizes the distribution of the correlation value obtained for each particular bin by analyzing 20 independent simulated pairs of uncorrelated time series. The LIBOR shows strong regular structure with a period of 10 business days (two weeks). Time lag is measured in days. The familiar jump-the-gun pattern (strong negative signal around zero time lag) seen sometimes in forex, is also visible here. This is the level of predictability one can only dream of in forex exchange rates, yet it is the interest rates that drive forex. Is LIBOR always that predictable?

Obviously, when exploring these "loopholes" or market inefficiencies for wealth generation, an algorithmic trader or a forex trading system (an automated decision making algorithm such as the one being built here on Forex Automaton™ site) must be mindful of the picture of LIBOR rates and its evolution, albeit in a somewhat different context than a long-term money manager. Being able to predict events, even in a weak statistical sense, is even better than merely following. Besides being useful via their implications for forex forecasting, LIBORs form an underlying indicator for derivatives of their own. LIBOR futures contracts and options on such contracts are traded on the CME. How does the predictability of LIBORs compare with that of currencies? Which one, LIBOR or forex, is more attractive to trade? Answering these questions, or providing a technical analysis framework to approach the answers, while leaving the fundamentals and event-driven trends aside, this series of articles about correlation features in LIBORs will serve as a useful compliment to our set of forex correlation analysis notes. I start this new series of articles with the all-important US Dollar LIBOR.

Executive Summary

The time series of US Dollar LIBORs is highly volatile; on the day scale, the distribution of "returns" (daily increments) is not only not lognormal but for some maturities not even power law. The main correlation pattern is positive correlation, between different terms as well as inside individual time series (autocorrelation). The heart-beat pattern of short-range LIBOR is replaced by longer-range waves and finally disappears in 12-month term data.

LIBOR charts

BBA tracks LIBORs for various loan durations (maturities). I focus on spot-next/overnight (s/n-o/n), 1 week, 1 month, 3 month, and 1 year maturities.

History of s/n-o/n USD LIBOR 2002-2008 History of 1 week USD LIBOR 2002-2008 History of 3-month USD LIBOR 2002-2008 History of 12-month USD LIBOR 2002-2008

Fig.2: Historical USD LIBOR rates charts, top to bottom: s/n-o/n, 1-week, 1-month, 3-month and 12-month. Time axis is labeled in MM-YY format.

Comparing the histories of different LIBOR maturities in different panels of Fig.2, you see their regular and sharp pattern becoming progressively less sharp as the maturity increases, with the shortest, s/n-o/n LIBOR, having the sharpest structure. The origin of the negative spikes surrounding the zero time-lag peak is quite clearly visible: the history of LIBOR is full of false alarm events when the rate suddenly changes its course (typically, jumps up) only to correct itself completely the next day. The money markets jump the gun trying to anticipate the course of events almost regularly, to the extent this nervousness must represent a regular and significant arbitrage opportunity, if the market instruments tied to the LIBOR rates have the same features.



Last Updated ( Monday, 04 January 2010 12:29 )