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Historical LIBOR charts archive |
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Written by Mikhail Kopytine
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Friday, 24 October 2008 16:08 |
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There is quite a shortage of good historical LIBOR interest rates data charts with a selection of currencies and maturities on the net. ForexAutomaton.com has a new section for just that: find historical LIBOR charts sorted by currency, loan duration and year on our site. These are essentially graphical "dumps" of our SQL database, based on the official BBA LIBOR archive. Use the Filter feature of the list to find the data you need. |
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Last Updated ( Monday, 17 November 2008 15:37 )
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EUR/CHF and USD/CHF 2004-2008: "trivial" intermarket correlation |
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Written by Mikhail Kopytine
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Tuesday, 25 November 2008 18:03 |
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The intermarket correlation between Euro/ Swiss Franc and US Dollar/Swiss Franc has a narrow positive peak at the zero time lag whose internal structure can not be resolved on the hour time scale -- simply put, these currencies are positively with fast enough response to one another, and their combination offers no visible benefit for forecasting. |
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Last Updated ( Tuesday, 25 November 2008 18:08 )
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Minimizing the "benefit of hindsight" in trading system testing |
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Written by Mikhail Kopytine
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Monday, 27 October 2008 16:07 |
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Once you know something, such as the past history, pretending that you do not is very difficult. The ways a trader can delude him-/herself while backtesting a trading system vary in degree of subtlety. A crude one is to develop a set of trading rules by observing the past history of the market, and apply the algorithm on paper to the same past history. A more subtle one has to do with the choice of adjustable parameters. It is common to abstract the algorithm, and split it into the "artificial intelligence" (AI) core, capable of "learning", and adjustable parameters which may control the learning process, the application of its effects, or both. A developer would then prevent the AI from learning the future, and run a trading simulation program on historical data, having the AI algorithm fixed, for a range of parameter values and then pick the value that gives the best result. By not letting the AI learn the future, the developer reduces the level of self-delusion somewhat. The best simulated performance would still incorporate "the benefit of hindsight" albeit in a refined way -- through the choice of the adjustable parameters. While the AI did not learn from the future directly, its way of learning would incorporate the benefit of hindsight, and the results might contain a survivorship bias of sorts. The result? In case of a poor AI, the result will be a trading strategy with a hidden "peso problem". Below I demonstrate the quality of the Forex Automaton™ AI directly, by removing the selection step and thus the survivorship bias it brings in. I look simultaneously at the entire range of possible "ways of learning", refusing to reject any, even if there are a priori reasons to do so, no matter how convincing they might be. Nor do I reject any of the possible money management styles, for the same reasons.  Fig.1:Return vs risk for paper trading in real AUD/JPY and simulated reference random walk markets. Vertical axis: annualized return, calculated as an average of independent monthly statistics, 1=100% per annum. Horizontal axis: standard deviation (RMS) of such annualized return from the same monthly statistics, same unit. Each point represents an instance of a trading system, a simulated trader; points differ by trading strategy which is subject to optimization. Black points: trading 4 fantasy markets with volatility of AUD/JPY, random by construction (no predictability or patterns). Red points: real AUD/JPY. Not all outcomes are included: in some cases, the trading did not last even a month therefore no RMS could be calculated -- there would be no other month of trading performance to compare with. In such cases the system is programmed to record a zero RMS, and such outcomes did not make it into the figure. The only other requirement is that of excluding the mean annualized returns above 5 (500%) and RMS above 20 -- happy as I am to include higher returns, they would make the picture difficult to analyze visually. |
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Last Updated ( Monday, 24 November 2008 17:57 )
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DKK LIBOR technical predictability overview |
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Written by Mikhail Kopytine
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Monday, 01 December 2008 14:30 |
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Among the other LIBOR rates, the Danish Krone LIBOR is remarkable for its positive autocorrelations, peculiar and very strongly pronounced short-range pattern of the overnight interest rate, and the weakness of the correlation between different duration terms. Like the previous LIBOR predictability overviews, this document begins with historical LIBOR charts for the currency, continues with volatility analysis, and culminates with autocorrelations and correlations of logarithmic returns for various DKK LIBOR terms. As with many other currencies, the predictable patterns in DKK LIBOR evolve with loan duration term from short-range but strong and regular oscillation in the overnight through smooth waves in 3-month and into relative featurelessness of the 12-month LIBOR. Motivation for publishing this type of study on a forex trading system site has been outlined in the USD LIBOR analysis. Here I can only add that for a student of financial correlations, LIBOR is a nice real-life intuition-building tool, for the correlations are so strong you can learn to identidy features in the charts with features in the correlations visually. |
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Last Updated ( Monday, 01 December 2008 14:32 )
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