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Data may be used in its natural time frame or may need to be processed into a different time frame. Depending on the time frame being traded and on the nature of the trading system, individual ticks, 5.minute bars, 20-minute bars, or daily, weekly, fortnightly (bimonthly), monthly, quarterly, or even yearly data may be necessary. A data source usually has a natural time frame. For example, when collecting intraday data, the natural time frame is the tick. The tick is an elastic time frame: Sometimes ticks come fast and furious, other times sporadically with long intervals between them. The day is the natural time frame for end-of-day pricing data. For other kinds of data, the natural time frame may be bimonthly, as is the case for the Commitment of Traders releases; or it may be quarterly, typical of company earnings reports. Although going from longer to shorter time frames is impossible (resolution that is not there cannot be created), conversions from shorter to longer can be readily achieved with appropriate processing. For example, it is quite easy to create a series consisting of l-minute bars from a series of ticks. The conversion is usually handled automatically by the simulation, testing, or charting software: by simple utility programs; or by special software provided by the data vendor. lf the data was pulled from the Internet by way of ftp (tile transfer protocol), or using a standard web browser, it may be necessary to write a small program or script to convert the downloaded data to the desired time frame, and then to save it in a format acceptable to other software packages. What time frame is the best It all depends on the trader. For those attracted to rapid feedback, plenty of action, tight stops, overnight security, and many small profits, a short, intraday time frame is an ideal choice. On an intraday time frame, many small trades can be taken during a typical day. The nttmeroous trades hasten the learning process. It will not take the day trader long to discover what works, and what does not, when trading on a short, intraday time frame. In addition, by closing out all positions at the end of the trading day, a day trader can completely sidestep overnight risk. Another desirable characteristic of a short time frame is that it often permits the use of tight stops, which can keep the losses small on losing trades. Finally, the statistically inclined will be enamored by the fact that representative data samples containing hundreds of thousands of data points, and thousands of trades, are readily obtained when working with a short time frame. Large data samples lessen the dangers of curve-fitting, lead to more stable statistics, and increase the likelihood that predictive models will perform in the future as they have in the past. On the downside, the day trader working with a short time frame needs a realtime data feed, historical tick data, fast hardware containing abundant memory, specialized software, and a substantial amount of time to commit to actually trading. The need for fast hardware with plenty of memory arises for two reasons: (1) System tests will involve incredibly large numbers of data points and trades; and (2) the real-time software that collects the data, runs the system, and draws the
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charts must keep up with a heavy flow of ticks without missing a beat. Both a database of historical tick data and software able to handle sizable data sets are necessary for system development and testing. A real-time feed is required for actual trading. Although fast hardware and mammoth memory can now be purchased at discount prices, adequate software does not come cheap. Historical tick data is likely to be costly, and a real-time data feed entails a substantial and recurring expense. In contrast, data costs and the commitment of time to trading are minimal for those operating on an end-of-day (or longer) time frame. Free data is available on the Internet to anyone willing to perform cleanup and formatting. Software costs are also likely to be lower than for the day trader. The end-of-day trader needs less time to actually trade: The system can be run after the markets close and trading orders are communicated to the broker before the markets open in the morning: perhaps a total of 15 minutes is spent on the whole process, leaving more time for system development and leisure activities. Another benefit of a longer time frame is the ability to easily diversify by simultaneously trading several markets. Because few markets offer the high levels of volatility and liquidity required for day trading, and because there is a limit on how many things a single individual can attend to at once, the day trader may only be able to diversify across systems. The end-of-day trader, on the other hand, has a much wider choice of markets to trade and can trade at a more relaxed pace, making diversification across markets more practical than for intraday counterparts. Diversification is a great way to reduce risk relative to reward. Longer time frame trading has another desirable feature: the ability to capture large profits from strong, sustained trends: these are the profits that can take a $50,000 account to over a million in less than a year. Finally, the system developer working with longer time frames will find more exogenous variables with potential predictive utility to explore. A longer time frame, however, is not all bliss. The trader must accept delayed feedback, tolerate wider stops, and be able to cope with overnight risk. Holding overnight positions may even result in high levels of anxiety, perhaps full-blown insomnia. Statistical issues can become significant for the system developer due to the smaller sample sizes involved when working with daily, weekly, or monthly data. One work-around for small sample size is to develop and test systems on complete portfolios, rather than on individual commodities. Which time frame is best It all depends on you, the trader! Profitable trading can be done on many time frames. The hope is that this discussion has clarfied some of the issues and trade-offs involved in choosing correctly.
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