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Tick Data price is a floating number, not a decimal number?

Hi this is my first-time looking into Tick data. I reviewed price, exchange, quantity, tradeorquote, suspicious etc in Log(). Everything seems correct except the price is a floating number. Should the price of SPY in the unit of $0.01?

An example piece of my SPY tick data is:
datetime price exchange quantity tradeorquote
2015-06-01 09:30:03 210.844245808 P 100 Trade
2015-06-01 09:30:03 210.844245808 P 200 Trade
2015-06-01 09:30:03 210.844245808 P 100 Trade
2015-06-01 09:30:03 210.844245808 P 100 Trade
2015-06-01 09:30:04 210.844245808 P 100 Trade
2015-06-01 09:30:04 210.844245808 P 100 Trade
2015-06-01 09:30:04 210.844245808 P 100 Trade
2015-06-01 09:30:04 210.844245808 P 400 Trade
2015-06-01 09:30:04 210.834294692 P 100 Trade
2015-06-01 09:30:04 210.834294692 P 300 Trade
2015-06-01 09:30:04 210.834294692 P 100 Trade
2015-06-01 09:30:04 210.834294692 P 100 Trade
2015-06-01 09:30:04 210.834294692 P 100 Trade
2015-06-01 09:30:04 210.834294692 P 58 Trade
2015-06-01 09:30:04 210.834294692 P 142 Trade
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Hi SSWW, please reframe from printing out data as is against the terms of use for QuantConnect. Data providers are very sensitive about it as its very valuable data which we make available as long as people follow their rules :)

The data is adjusted, so the price includes splits and dividends in the price. If you want raw ticks you can use SetDataNormalizationMode(DataNormalizationMode mode) - check out the QC University algorithm "How Do I Use Total Returns Price Normalization?"
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The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.


I was looking into the Tick DataFilter, filtering out outliers in Tick data, such as suspicious, trade in other exchanges. Not intended to print out a large amount of data.

Thanks Jared. SetDataNormalizationMode(DataNormalizationMode.Raw) solved my problem.
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@ssww I am also running into outliers in the tick data. Did you solve that problem? I suspect that setting the data normalization to raw doesn't solve the tick outlier problem that I'm seeing.
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Hey JP B, Tick data is unfiltered, raw data which comes from the exchanges. As such it includes sale codes which are "suspicious" and untradable. We automatically filter these out for second, minute, hour and daily bars. If you'd like to apply the same filters to your algorithm you need to setup a Data Filter which filters what gets into LEAN.

Check out the QC University Algorithm -- How Do I Filter Bad Data/Ticks?
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The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.


@JaredBroad Thank you for your answer.

Looking at this QC University Algorithm I see that the filtering simply removes most exchanges. What is the standard procedure for filtering the tick data? Only keep the exchanges on which it is traded?

For example, $AAPL is traded on NASDAQ so do I only include NASDAQ? Would that remove all said outliers?
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JP B, we filter out ticks based on the following conditions for equities when aggregating the ticks into second/minute bars
suspicious = true
sale condition = "W"
exchange = { "W", "u", "U", "D" }
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The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.


@MichaelH is that tick filter condition OR's or ANDs

(suspicious = true) OR (saleCondition = "W") OR (exchange in ["W", "u", "U", "D"])

Thanks

 

 

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@Mike_pp -- OR, if any of those conditions are met the tick is filtered out.

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The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.


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The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.


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