After important changes to the trading system optimization methodology, I am revisiting EUR/USD on the day scale. The USD/CAD and USD/CHF reports indicated that our range of trade entry parameter might not include the optimum, consequently the range is extended. As a result, much better performance figures are seen. But caution is needed when comparing even the "minimum-bias" results with those of earlier reports, since the parameter ranges are now different.
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Optimizing the trading system parameters: EUR/USD revisited
June 5 2009, 7:02pm | Comments »
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Optimizing the forex trading system parameters: USD/CHF
After some important changes to the trading system optimization methodology, I continue with USD/CHF on the day scale -- this currency pair has not been analyzed in this context before.
May 29 2009, 7:59pm | Comments »
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Optimizing the forex trading system parameters: USD/CAD
After some important changes to the trading system optimization methodology, I continue with USD/CAD on the day scale -- this currency pair has not been analyzed in this context before.
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May 27 2009, 6:31pm | Comments »
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The optimization framework is being upgraded.
Our forex trading system optimization procedure is currently undergoing a change. This change is brought about by the recognition of the fact that a simple arithmetic average of monthly returns, a statistic used so far, is biased upwards and thus provides a falsely optimistic estimator of return. The popular Sharpe ratio statistic, if it incorporates such an estimator, is to be avoided or redefined. Here are some outlines of the upgraded approach.
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May 26 2009, 12:41pm | Comments »
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Possible figures of merit related to return on investment: arithmetic and geometric mean
When evaluating the performance of a trading system, I calculate the first moment (an arithmetic mean of the series of returns) as well as the second one (a variance of the series). Originally my "Sharpe-like" ratio, used to adjust the return for the risk, was a ratio of the first moment to the square root of the second. The series of returns would be composed of annualized returns calculated every month.
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May 18 2009, 7:31pm | Comments »
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Optimizing the forex trading system parameters: AUD/USD
This is the fifth report in the series of the buy-side forex trading system optimization reports for the individual currency pairs, traded on the day scale, which began with AUD/JPY. In the algorithm, the forecast signal whose nature will not be disclosed is fed into the money management framework driven by three adjustable parameters. The set of 13398 parameter combinations represents the totality of possible trading styles under study. The goal is to optimize the trading style by finding, on the basis of the simulated trading performance, such values of parameters as to maximize the return while minimizing risk. The insights obtained in the process may be of general interest, since the problem is common to all traders, robots and humans alike.
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May 14 2009, 5:12pm | Comments »
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Optimizing the forex trading system parameters: GBP/USD
This is the fourth report in the series of forex trading system optimization reports for the individual currency pairs, traded on the day scale, which began with AUD/JPY. In the algorithm, the forecast signal whose nature will not be disclosed is fed into the money management framework driven by three adjustable parameters. The parameters form a multi-dimensional space populated by figures of merit, as obtained by Monte Carlo simulation of independent trading histories. The set of 13398 parameter combinations represents the totality of possible trading styles under study. The goal is to optimize the trading style by finding the best values of parameters on the basis of the simulated trading performance. The insights obtained in the process may be of general interest, since the problem of money management is common to all traders, robots and humans alike.
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May 12 2009, 5:27pm | Comments »
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Optimizing the forex trading system parameters: USD/JPY
I continue with the series of forex trading system optimization reports for the individual currency pairs, traded on the day scale, which began with AUD/JPY. In the algorithm, the forecast signal whose nature will not be disclosed is fed into the money management framework driven by three adjustable parameters. In the current test setting, the parameters form a multi-dimensional space populated by figures of merit, as obtained by Monte Carlo simulation of independent trading histories. The set of parameter combinations constitutes the totality of possible trading strategies under study. The goal is to optimize the trading strategy by finding the best values of parameters on the basis of the simulated trading data.
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May 1 2009, 3:11pm | Comments »
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CHF/JPY and EUR/AUD leading indicator history, 2002-2009
In the screening we conducted last summer using the data set from 2002 to early 2008, CHF/JPY was identified as a leading indicator for EUR/AUD. This time-evolution study confirms that the signal was real, as the fairly robust relationship persisted till the middle of 2007. Around the middle of 2007, CHF/JPY and EUR/AUD changed from being positively correlated to being negatively correlated. About the same time, CHF/JPY stopped being a leading indicator for EUR/AUD. Curiously, it's hard to interpret this as a result of changes in the interest rates: dramatic changes in that area did happen, but much later, not until the Fall of 2008.
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April 28 2009, 1:55pm | Comments »
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Optimizing the forex trading system parameters: EUR/USD
I continue with the series of forex trading system optimization reports for the individual currency pairs, traded on the day scale, which began with AUD/JPY. In the algorithm, the forecast signal whose nature will not be disclosed is fed into money management framework driven by three adjustable parameters. In the current test setting, the adjustable parameters form a multidimensional space populated by figures of merit, as obtained by Monte Carlo simulation of independent trading histories. The interpretation of the data set leads to a quantitative discussion of relative merits of various trading styles. Two features of the data set make this material unique: first, the data incorporate the real inefficiencies of the real market, as opposed to more academic simulations with martingales. Second, the money management styles are being tested in a setting where the forecasting part is entrusted to the generally successful "artificial intelligence" component.
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April 24 2009, 5:28pm | Comments »
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AUD/JPY and GBP/USD leading indicator history, 2002-2009
AUD/JPY and GBP/USD form a weakly correlated pair, often but not always correlated positively, which many traders would regard to be one of the last suspects when it comes to predictive forex correlations. Nonetheless, in the screening we conducted last summer using the data set from 2002 to early 2008, AUD/JPY was found to form a leading indicator for GBP/USD. The feature was found by studying the time-integrated correlation of logarithmic returns in the two time series. As usual in such cases, a detailed time-evolution study is necessary to tell whether this effect is merely a result of a single high-impact event or a recurrent feature. I extend the period of observation up to April 2009, split it into three time windows of varying volatility, and analyze the time stability of the leading indicator effect.
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April 20 2009, 7:41pm | Comments »
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Optimizing the forex trading system parameters: AUD/JPY
This is the first Forex Automaton™ report on the optimization of the automated forex trading system performance. The general introduction to the trading system optimization (back-testing) and a brief description of parameters have been posted before. As before, the nature of the forecasting engine and the meaning of the related parameters are intentionally left beyond the scope of the discussion. You will see however that even though money management alone can not turn bad trades into winning trades, the converse is possible. The combined experience of 13,398 simulated trading histories testifies that a trader can systematically lose money and effectively take extra risk mainly due to the incorrect (too tight) stop-loss placement, despite having the quality of insight equal to that of the winner. It is demonstrated that significant improvement in performance can be achieved by parameter adjustments, guided by an analysis of the simulated trading histories, and an example of reasoning behind such a process is given.
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April 17 2009, 4:08pm | Comments »
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AUD/JPY and EUR/CHF leading indicator history, 2002-2009
This is a follow-up report on the predictive feature discovered in the correlation analysis of AUD/JPY and EUR/CHF. The feature was found by studying the time-integrated correlation of logarithmic returns in the two time series. A detailed time-evolution study is necessary to tell whether this effect is merely a result of a single high-impact event or a recurrent feature. The effect in question was found not to exist in the Asia-Pacific trading, therefore in this report I cover the trading hours from 4am to 8pm New York time, which excludes Asia. I extend the period of observation up to April 2009 and analyze the time stability of the leading indicator provided by AUD/JPY for EUR/CHF.
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April 15 2009, 3:34pm | Comments »
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Setting up an algo trading system test bench. Description of parameters.
Our general approach to the problem of forex trading system back-testing has been outlined before. This post gives a more detailed picture of the parameters subject to the optimization -- a useful reference point for the optimization reports that may follow. The only caveat is: since the nature of the forecasting algorithm will not be disclosed, discussion of the nature of the parameter(s) related to it will be similarly avoided. Therefore, the scope of the optimization problem is reduced, essentially, to the problem of money and risk management in the presence of a more or less successful forecasting engine. It need not be quite the same as the problem of money and risk management in the hypothetical efficient market.
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April 10 2009, 12:19pm | Comments »
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Patterns of financial crisis: USD/CAD in 2007-2009.
With USD/CAD, I am continuing the series of reports focusing in the time evolution of the forex correlation shapes during the present financial crisis. Extending the time coverage up to the end of March, I see the need to make the picture a bit more complex with three, rather than two phases with considerably different volatility level, since the volatility is seen to abate at the end of January 2009. The bipolar correlation pattern, a major subject of this research, is seen to disappear during the peak of volatility, but reappear later.
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April 8 2009, 7:47pm | Comments »
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The First Annual Summary of Forex Automaton Research Progress, April 2009.
Forex Automaton was launched in April 2008 with the ambitious mission of leveraging the specific algorithmic know-how to create a trading signal service geared toward retail forex traders. From the very beginning a two-prong strategy was adopted: first, development of the trading system product whose usefulness relies on secrecy of the relevant know-how. Second, white-paper research focusing on statistical properties of the market time series, especially those aspects which are potentially interesting from the point of view of algorithmic trading, however counter-intuitive, technical and remote from the mainstream picture of forex trading they may be. As of now, it is mostly the second prong that's visible to the website visitor. This document summarizes the main findings to emerge so far from a year of studies, including some glimpses into the progress made on the black-box algorithmic trading system front.
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April 3 2009, 4:22pm | Comments »
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The First Annual Summary of Forex Automaton Research Progress, April 2009.
Forex Automaton was launched in April 2008 with the ambitious mission of leveraging the specific algorithmic know-how to create a trading signal service geared toward retail forex traders. From the very beginning a two-prong strategy was adopted: first, development of the trading system product whose usefulness relies on secrecy of the relevant know-how. Second, white-paper research focusing on statistical properties of the market time series, especially those aspects which are potentially interesting from the point of view of algorithmic trading, however counter-intuitive, technical and remote from the mainstream picture of forex trading they may be. As of now, it is mostly the second prong that's visible to the website visitor. This document summarizes the main findings to emerge so far from a year of studies, including some glimpses into the progress made on the black-box algorithmic trading system front.
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April 3 2009, 4:22pm | Comments »
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What information does a forex trading system need to communicate to the user?
As any computer program, a forex trading system has input and output. This post is about the output -- what should be in it? What are the guiding principles of this communication? Here are the basic principles as we see them now: Regularity. Communicate actions, not prophecies. Communicate actions as they happen. Program the computer, not the user. Be accountable for the past performance. No misrepresentation. Access control.
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March 2 2009, 2:46pm | Comments »
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What information does a forex trading system need to communicate to the user?
As any computer program, a forex trading system has input and output. This post is about the output -- what should be in it? What are the guiding principles of this communication? Here are the basic principles as we see them now: Regularity. Communicate actions, not prophecies. Communicate actions as they happen. Program the computer, not the user. Be accountable for the past performance. No misrepresentation. Access control.
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March 2 2009, 2:46pm | Comments »
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Swiss Franc (CHF) LIBOR: technical predictability overview
I've outlined the original motivation to study historical LIBOR data from predictability point of view in the USD LIBOR article. I continue with the logarithmic returns technique that proved useful in forex. Like the previous reports, this document begins with historical LIBOR charts for the Swiss Franc, continues with volatility analysis, and culminates with autocorrelations and correlations. You will see that predictable patterns in CHF LIBORs vary with duration term. Autocorrelations of short-term LIBORs show fast (about 4-day period) oscillation. For 3-month and 6-month terms, the main correlation pattern does not develop 70-day period waves on top of positive background, in contrast to USD and EUR LIBORs, but keeps oscillating between positive and negative autocorrelation values, with the oscillation period longer than that of the shorter terms. The autocorrelation of 12-month LIBOR remains similar to 6-month instead of becoming more uniformly positive as it does for JPY or more jittery as it does for USD, EUR and GBP.
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November 10 2008, 5:45pm | Comments »