Author:Olga M. LonderISBN:250Genre:ComputersFile Size:36.25 MBFormat:PDF, ePub, MobiDownload:735Read:1077This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book.
Classic Menu for Office + serial Tab + office. Option Login torrent microsoft office 2013 pirate bay.Search for and download any torrent from the pirate bay using search query office for mac. Microsoft Office 2016 for Mac v15.34.0 VL. Office 365 for Mac.microsoft office 2003 torrents pirate bay.Let me start with this, yes, we can.
Average rating: 3.5 (from 83 votes)By Dave Foxall Building the Business Case for On-boarding SoftwareWith the war for talent in full swing, and turnover for some industries at an all-time high, organizations are increasingly turning to to tighten up their procedures for new hires—and for good reason. Wynhurst Group research suggests that more than a fifth of employee turnover occurs within 45 days of taking up a new position. The same report shows that a properly structured on-boarding program can make a clear difference in that turnover rate for organizations; boosting retention for those companies leveraging on-boarding technology close to 60% higher than their less-focused competitors.
No stabiliser or filter ringCanon has some superb full-frame ultra-wide-angle zoom lenses, but until recently the only option shorter than 16mm was the EF 8-15mm f/4 – but that's a fisheye lens. The extra 5mm advantage of the 11-24mm lens may not sound very much, but even very small changes in focal length have a huge impact with ultra-wide-angle optics – every millimetre delivers a visibly wider angle of view.Although it may have a short focal length, the EF 11-24mm f/4L USM is a pretty substantial lens, with a bulbous front element shielded by a built-in petal-style lens hood. A lens cap pushes over the hood to protect the precious glass in transport – and you will want to protect it because the optical performance is excellent.2. Tamron 15-30mm f/2.8 DI VC USD for Canon. Not the widest angle of viewThis Tamron lens doesn't go quite as wide as the Canon 11-24mm, but it's still wider than most. Tamron has developed a line of 'fast' zoom lenses that have a constant, wide f/2.8 aperture, complete with optical image stabilisation or VC (Vibration Compensation), and this 15-30mm takes the lineup into super-wide-angle territory, continuing the themes of impressive build quality, weather-sealed design, ring-type ultrasonic autofocus and image stabilisation.It's a big lens, but it feels well balanced on Canon full frame bodies from the 6D to the 1D X and handling is excellent.
R/RagnarokMobile: Ragnarok M: Eternal Love is a free-to-play fantasy RPG based off the news The pre-registration for the European server has started!
2016-17 marks the 50th anniversary of the beginning of the GreatProletarian Cultural Revolution in China. AFE is offering are-examination in two strands: one strand will consider the politicaland social ramifications of the movement through independent reading of China Under Mao: A Revolution Derailed,by Andrew Walder, with 4 webinars with the author. The second strand,will read literary and autobiographical accounts of life under Mao infour different periods, from 1949-1980, divided among four book groupofferings. Teachers are free to participate in all just one or all 5 ofthe reading groups offered in both strands.The Dragon's Villageis the autobiography of a young, wealthy urban teenager who stays behind in Shanghai, after her family leaves for Hong Kong with the arrival of the Communist forces in 1949, and volunteers to help with the revolution in a rural village. An account of the land reform period of the early 1950s. The author, Yuan-Tsung Chen, is a Chinese writer living in Taiwan.
Potpisnici apela – Centar za obrazovne politike, Udruženje studenata sa hendikepom, Centar za interaktivnu pedagogiju, Privredna akademija, Savez učitelja Srbije, Forum beogradskih gimnazija, Sindikat obrazovanja Beograda i Nacionalni savet za naučni i tehnički razvoj, ukazuju na to da resori obrazovanja i nauke ne bi trebalo da budu.
Daruvarske Toplice, Daruvar: See 27 traveler reviews, 52 candid photos, and great deals for Daruvarske Toplice, ranked #1 of 2 hotels in Daruvar and rated 4 of.
We've been listening to the discussions about the difficulties around the ability to retrieve and perform calculations on windows of data.I’d like to give a special thank you to Grant, Peter, Aidan, and everyone else for their diligence in making the current APIs work for them and their thoughts on how to make it more useful.We’ve been working on replacements to batch transform and the simple transforms (mavg, vwap, etc.) that are both easier to use and more efficient on the back end. We want to make it easier to access the data that occurred before the current bar. We want the new versions to be easy in daily and minutely backtesting, and we particularly want to them to make minute mode easier to manipulate.Here is a link, to the draft of the new idea that is part specification, part documentation, and part cookbook for a new API for accessing history. In this thread, we would love to hear your thoughts and discuss withyou about the proposal. What does it get right? Where can it get better?Thanks in advance for your help in making the algo writing, backtesting, and trading better. 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 Quantopian.
In addition, the material offers no opinion with respect to the suitability of any security or specific investment. No information contained herein should be regarded as a suggestion to engage in or refrain from any investment-related course of action as none of Quantopian nor any of its affiliates is undertaking to provide investment advice, act as an adviser to any plan or entity subject to the Employee Retirement Income Security Act of 1974, as amended, individual retirement account or individual retirement annuity, or give advice in a fiduciary capacity with respect to the materials presented herein. If you are an individual retirement or other investor, contact your financial advisor or other fiduciary unrelated to Quantopian about whether any given investment idea, strategy, product or service described herein may be appropriate for your circumstances.
All investments involve risk, including loss of principal. Quantopian 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. Eddie,It appears that you'll be addressing the 'warm-up' issue with backtesting:Daily History and Back Test StartUnlike batch transforms, daily history is available on the first day of the backtest, data availability permitting.Unlike batch transforms, the data history does not require the algorithm to run for the number of days the window before returning a value.The data is backfilled so that calculations can be done more immediately.Will this also apply to minute-level backtesting (since you only refer to 'daily history')?Grant.
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 Quantopian. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. No information contained herein should be regarded as a suggestion to engage in or refrain from any investment-related course of action as none of Quantopian nor any of its affiliates is undertaking to provide investment advice, act as an adviser to any plan or entity subject to the Employee Retirement Income Security Act of 1974, as amended, individual retirement account or individual retirement annuity, or give advice in a fiduciary capacity with respect to the materials presented herein. If you are an individual retirement or other investor, contact your financial advisor or other fiduciary unrelated to Quantopian about whether any given investment idea, strategy, product or service described herein may be appropriate for your circumstances. All investments involve risk, including loss of principal. Quantopian 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.
Thanks Eddie,Regarding your forward filling, it seems that the way you are structure the data could be different, which would avoid the problem of empty bars for Security A relative to Security B. As an option (or an example using pandas functionality) wouldn't it be possible to provide the data as independent pandas time series? This would be more consistent with the idea that the backtester is 'event-driven' with each security having its own stream of events. By forward filling, you are creating events where there were none historically.I'm not sure if you made it clear in your document, but as I understand, the filling is only done for the multiple security case. If the dataframe only contains one security, there is no way to know if bars are missing, correct? Or are you keeping track of wall clock time, to determine if minutes are skipped (or days, in the case of daily trading)?Also, what is the remedy if the first bar is empty?
The filling will fail, right? Should there be a warning?Grant. It makes sense to settle on pandas dataframes for time series data. '5m' for five minutes of data seems a bit strange, anyone who's used any other data platform may wonder, 'but how much five-minute bar data is there?'
Ie - that notation is usually used for periodicity, not for backfill.Also re forward filling, are you forward filling a nil tick to produce a degenerate bar with 0 volume? Or are you actually forward filling whatever the last bar was, causing any code that has exponential decay, volume accumulation or really any calculation at all to change.? My first thought was the same as Simon's. It might be better for data.history.minutes('15m', 'price')to be data.history.minutes(15, '1m', 'price')which also makes data.history.minutes(26, '15m', 'price')possible in the future.I don't agree with Grant on the 'independent' time series. I think a DataFrame of one SID or of many SIDs should have all missing timestamps inserted.I see Simon's point on forward filling and I would suggest the default is to fill with NaNs, To answer Grant a missing first bar can be filled from the day before so maybe the earliest backtest start date becomes instead of.It all looks very promising.P. That's interesting. I also thought to implement myself a kind of history object for a Python backtesterMy idea was to use a kind of rolling DataFrame (like a circular buffer) to store OHLCV price and volume for differents timeframe.I have some difficulties to understand how to access to price history of a given sidI also don't understand what happens (in term of memory usage) for a given strategy which use several sidpricesa = data.history.minutes('15m', 'price')Does it means that you are building a 15 minutes OHLCV internal dataframe for each sid?What is the length of this DataFrame (does size inflates?
How DataFrame size can be set?)I also wonder how to access to 'latestprice' and 'latestvolume' for a given sid into handledataIs there a way to feed this object to have both access to bid price and ask price?(and also spread?)How to access to 'lastdatetime'? Perhaps you've thought of it, but I'd have a look at a couple cases:. What happens when you feed asynchronous data (e.g.
Datetime stamps that don't fall on the whole minute)?. You've talked about adding other types of securities/futures/etc. In general, it seems that you'll need to deal with 24/7/365 asynchronous data feeds, right?. I agree with Simon's sentiment above that you need to provide exact details on how the filling will be done. Also, if users want do do their own filling, you might provide details. Are you planning to provide guidance on how to generate a length N trailing window of OHLCV bars (e.g. 15 minute) on a rolling basis, updated every minute?
This would basically be a specialized moving (rolling) statistic like the ones described on.Grant. Peter,Perhaps I wasn't clear on my #4 above.
If you have a look at the moving (rolling) statistics available in pandas , they actually return a new pandas time series, with statistics applied over a rolling window. I think that the proposed new functionality would just return the data over the last N minutes.
For example, this would yield 15 minutes of price data: minuteprices = data.history.minutes('15m', 'price')I'm thinking of a rollingbar function, in analogy, for example, to the rollingmean function described on under 'Moving (rolling) statistics / moments.' Basically, there ought to be a way to generate OHLCV data on a rolling basis from the original minute-level data. Note that this is different from a trailing window of 15 OHLCV minute-level bars.Are you perhaps suggesting the same thing above with: data.history.minutes(26, '15m', 'price')Would this return a pandas time series, with 26 rows, each containing a 15-minute OHLCV re-sampled bar?The Quantopian folks provide some guidance in their under the 'Resampling' section, but it seems that the whole approach could be re-cast into the rollingbar statistic that I'm suggesting to yield the OHLCV data with one call.Grant. Hi all, First off – thank you for your questions and suggestions, your feedback is important to us and we definitely want to get this feature right! Let me speak to the two major themes you have all gravitated towards first. Then, I have several individual replies.
We will continue to update this thread throughout the week, as well as updating the documentation to reflect changes as they are made.(1) Filling in for missing data – you will have the following options to handle missing data points:'ffill=False', would have the same DatetimeIndex as if the stock were fully liquid (i.e. The minutes and days would be all of the market open minutes and days), with the empty minutes or days having a 'np.nan' for all of the OHLCV values.'
Ffill=True' - fill the pricing information forward with the last known value (with the exception of inserting a '0' for volume)In the case that there is no last known value the time series will be padded with leading nans, until a price for that stock occurs, after which the behavior will be defined by the options above.(2) Syntax for specifying frequency vs. Duration of historical data – there was much internal debate on the right syntax for a user to separately specify both the frequency and the duration (or window length) of the ‘history’ object – and it’s very possible we’re still not quite there – so suggestions on that front are very welcome.Our goal is not to recreate or supersede pandas elegant resampling functionality – but rather to give you the ability to define upfront how much data your algo will need – and let you code from there. The simplest thing to do would be to always dump the highest frequency data we allow (minutely) and only ask you how far back you want to look (15 minutes, 2 days etc.). The problem we saw there was that many users have algos that operate on a much longer timeframe and across a large universe of securities, and saddling those folks with minutely data to constantly be discarding seemed onerous.
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 Quantopian. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. No information contained herein should be regarded as a suggestion to engage in or refrain from any investment-related course of action as none of Quantopian nor any of its affiliates is undertaking to provide investment advice, act as an adviser to any plan or entity subject to the Employee Retirement Income Security Act of 1974, as amended, individual retirement account or individual retirement annuity, or give advice in a fiduciary capacity with respect to the materials presented herein. If you are an individual retirement or other investor, contact your financial advisor or other fiduciary unrelated to Quantopian about whether any given investment idea, strategy, product or service described herein may be appropriate for your circumstances. All investments involve risk, including loss of principal.
Quantopian 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. 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 Quantopian. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. No information contained herein should be regarded as a suggestion to engage in or refrain from any investment-related course of action as none of Quantopian nor any of its affiliates is undertaking to provide investment advice, act as an adviser to any plan or entity subject to the Employee Retirement Income Security Act of 1974, as amended, individual retirement account or individual retirement annuity, or give advice in a fiduciary capacity with respect to the materials presented herein.
If you are an individual retirement or other investor, contact your financial advisor or other fiduciary unrelated to Quantopian about whether any given investment idea, strategy, product or service described herein may be appropriate for your circumstances. All investments involve risk, including loss of principal. Quantopian 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. 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 Quantopian. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. No information contained herein should be regarded as a suggestion to engage in or refrain from any investment-related course of action as none of Quantopian nor any of its affiliates is undertaking to provide investment advice, act as an adviser to any plan or entity subject to the Employee Retirement Income Security Act of 1974, as amended, individual retirement account or individual retirement annuity, or give advice in a fiduciary capacity with respect to the materials presented herein.
If you are an individual retirement or other investor, contact your financial advisor or other fiduciary unrelated to Quantopian about whether any given investment idea, strategy, product or service described herein may be appropriate for your circumstances. All investments involve risk, including loss of principal. Quantopian 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. Simon - definitely agree it's not perfection, but we did bat around a number of alternatives which all had problems.
How would you expect it to look?Would you prefer something like:data.history(frequency='minutes', duration='60', value='price')where frequency can be 'minutes' or 'days', duration can be any integer, and value can be price, volume, etc?or do you want to ask for any arbitrary 'bar size' upfront like this:data.history(barsize='15m', count=30, value='price')And my only issue with option #2 is that it feels like we're rolling a lot of duplicative resampling functionality inside the API, where it might be more flexible to leave it up to the user to do this in pandas. But I might be throwing the baby out with the bathwater on that concern - would love your thoughts.Jess. 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 Quantopian.
In addition, the material offers no opinion with respect to the suitability of any security or specific investment. No information contained herein should be regarded as a suggestion to engage in or refrain from any investment-related course of action as none of Quantopian nor any of its affiliates is undertaking to provide investment advice, act as an adviser to any plan or entity subject to the Employee Retirement Income Security Act of 1974, as amended, individual retirement account or individual retirement annuity, or give advice in a fiduciary capacity with respect to the materials presented herein.
If you are an individual retirement or other investor, contact your financial advisor or other fiduciary unrelated to Quantopian about whether any given investment idea, strategy, product or service described herein may be appropriate for your circumstances. All investments involve risk, including loss of principal. Quantopian 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. Well, I guess the answer to that question depends on, 'Who are your users?'
:)Another question I would pose, rhetorically, is, 'Who really wants daily data in a minutely backtest/live trading anyway?' That is to say, if I have a daily strategy, ought I expect implicitly that it be evaluated exactly once a day?If I were a TA man, coding a 50day 200day moving average crossover, would I ever want that inequality tested every minute?If the answers to those questions are 'nobody', 'yes' and 'no', then your API requirements are simplified:data.history(length=60, frequency='1m')Just a thought.EDIT - the above isn't 'simplified', my mistake.
What I meant was, that the the bar frequency would drive the simulation or vice versa, so that it would be implicit. 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 Quantopian. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. No information contained herein should be regarded as a suggestion to engage in or refrain from any investment-related course of action as none of Quantopian nor any of its affiliates is undertaking to provide investment advice, act as an adviser to any plan or entity subject to the Employee Retirement Income Security Act of 1974, as amended, individual retirement account or individual retirement annuity, or give advice in a fiduciary capacity with respect to the materials presented herein. If you are an individual retirement or other investor, contact your financial advisor or other fiduciary unrelated to Quantopian about whether any given investment idea, strategy, product or service described herein may be appropriate for your circumstances. All investments involve risk, including loss of principal.
Quantopian 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. 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 Quantopian. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. No information contained herein should be regarded as a suggestion to engage in or refrain from any investment-related course of action as none of Quantopian nor any of its affiliates is undertaking to provide investment advice, act as an adviser to any plan or entity subject to the Employee Retirement Income Security Act of 1974, as amended, individual retirement account or individual retirement annuity, or give advice in a fiduciary capacity with respect to the materials presented herein. If you are an individual retirement or other investor, contact your financial advisor or other fiduciary unrelated to Quantopian about whether any given investment idea, strategy, product or service described herein may be appropriate for your circumstances.
All investments involve risk, including loss of principal. Quantopian 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.
If you are going to provide 5 minute bars in a simulation, they should be a bar for the entire previous five minutes, not the fifth minute bar with the previous four ignored, that was my point there.More generally, I think you should consider whether the flexibility to request data of different frequencies than that in which the algorithm is being evaluated is worthwhile. If not, then you can just fix a strategy as 'Daily' or 'Minutely', feed it daily or minute bars once per period and forget about the frequency argument entirely, with the only parameter being how far back the data has to go.
Hello all,Some feedback (perhaps re-iterating some comments above):. The fields/flags and their syntax should be consistent across Quantopian and pandas. Would it be possible to just keep things simple, and provide data.history(length=N), and then provide examples of how to apply pandas? N would correspond to the number of market tics when the security could have traded (N days or N minutes, depending on the base frequency of the backtest). The trailing window of data would be available at the start of the backtest (rather than after a 'warm-up' period, as presently required). By the way, I'm not sure that this would be any different than the current batch transform with refreshperiod = 0, so I've been wondering (aside from eliminating the warm-up issue), why you are adding the history functionality. It is still kinda murky what happens when Quantopian includes markets other than U.S.
Equities (e.g. It seems that the data structure won't work since the datetime stamps won't align (e.g.
Asian, European, and U.S. Markets all have different open/close times). It seems that the database should have another flag, besides the OHLCV data, to indicate whether the market was open for a given security, right?Grant. Hello W4C,I cannot speak for Quantopian but I assume the first paragraph of their Business Plan specifies an event model based on 1-minute data (from which is derived daily data) implemented in, and leveraging, Python/pandas.From this I believe data alignment follows as this is the nature of Data Frames and Data Panels.
Should Forex data ever be available - other than via 'fetch' - I have no doubt that this will be aggregated into 1 minute OHLCV bars. Additionally, I doubt that Bid/Ask prices will ever be offered within the Quantopian data.P. Spread is an important problem in a Forex strategy (or when trading CFD). I don't understand why Quantopian could ignore this.When trading CFD, you can buy/sell contracts (underlying is shares) during night (market closed) and so spread is different (higher) than daily spread (market open).Moreover 1 minute OHLCV bars is not enough if you want to trade realtime. (at least for some scalping strategies) you need to feed your strategy using tick data.Some Forex tick data are available here but you can probably find other tick data elsewhere for backtestingAbout live trading.
You can get data not only 'fetching' them but also using broker API such as Interactive Brokers (or probably some others)here is a sample(from ). Hello W4C,I'm not disagreeing with you. I'm just relaying an impression I get from'@Peter - good question - but totally unrelated to the historical data timeframes question I was trying to answer here:)Quantopian's backtesting and live trading are all built around minute-level pricing data and that is the fastest access that Quantopian-IB link will give you to the market. For the equity markets this is pretty standard for any type of trading that falls outside of market making or what is often referred to as high frequency trading' or HFT.
As you described, you are exposed to intra-minute price risk.' Hello Peter,sorry for being so rude.if Zipline can't provide what I'm looking for (tick data storing) and also different rolling buffers to store OHLCV data for different timeframes. I suggest adding a 'Technical Implementation' section to.
It is not clear how data.history will work 'under the hood.' At the start of a backtest, I gather that you will somehow find all references to sids, and then start accumulating the data for all of them, prior to the start of the backtest. What happens if the list of sids changes during the backtest? Or what if the user wants to delay the accumulation? Also, there must be a memory limitation? You might want to provide guidance on how to manage it, in the limit of a large number of sids and a large window size. If I understand it correctly, I can use either data.history.minutes('3d', 'price').resample('1D') or data.history.days('3d', 'price')to get a daily price series, where the last day uses the most recent partial values.
So I can trade at for example an hour prior to close, and examine the daily charts (just as I would with stockcharts.com). And I can at the same time look at minute data or other data to fine tune entries and exits. Sounds perfect.
It's also a bit more transparent than batch transform.Rich. Hello Eddie (and Richard),I'm kinda unclear, as well. It seems that to apply the pandas resampling to obtain daily bars in a minutely backtest, it would be (as Thomas W. Shows above for different timeframes, data.history.minutes('60m', 'price').resample('15m', how='ohlc')): data.history.minutes('5d', 'price').resample('D', how='ohlc')Would this return, every minute, the prior 4 days of daily OHLCV data (i.e. A pandas timeseries with 4 rows)? And at the closing minute, would it return 5 days of daily OHLCV data (since at closing, the current day's OHLCV would be available?Or would it return 4 full days of OHLCV and a partial day of OHLCV (up to the current minute) (i.e.
A pandas timeseries with 5 rows, with the 5th row changing every minute).?Grant. 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 Quantopian.
In addition, the material offers no opinion with respect to the suitability of any security or specific investment. No information contained herein should be regarded as a suggestion to engage in or refrain from any investment-related course of action as none of Quantopian nor any of its affiliates is undertaking to provide investment advice, act as an adviser to any plan or entity subject to the Employee Retirement Income Security Act of 1974, as amended, individual retirement account or individual retirement annuity, or give advice in a fiduciary capacity with respect to the materials presented herein. If you are an individual retirement or other investor, contact your financial advisor or other fiduciary unrelated to Quantopian about whether any given investment idea, strategy, product or service described herein may be appropriate for your circumstances. All investments involve risk, including loss of principal. Quantopian 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. Hello Eddie,Could you elaborate on:Frequency of one day and above (i.e., '1d', '2d', '1W','1M', etc.) have a limit of being within the date range of the backtest. If the simulation date range was from 2011-01-01 to 2011-12-31, the limit for barcount at a frequency of '1D' would be 252, the limit for a frequency of '2D' would be 176, for '1M' would be 12, etc.If the backtest dates were 2011-01-01 to 2011-06-30 what would be returned by: data.history(barcount=200, frequency='1d', field='price')i.e. 200 bars or approx. (I'm guessing '176' above is a typo. Not bad arithmetic!) I'm thinking in terms of a 200-day MA in a six month backtest.Are multiple history requests allowed?
If so is the 2000 data point limit for all or for each?P. Simon:With the current spec, yes, four history requests would have to be made.But, we had discussed it while working on the spec, and while adding the ability to return multiple at once is out of scope for the first release of the new API, it's something that we may enable in the future via an additional parameter.Peter:Starting with the first handledata call of the backtests, i.e. At bar 0, the history will return with the 199 preceding business days in 2010 and the first business day in 2011.Multiple history requests are allowed, a goal is to enable multi-factor algorithms.Some of the limits will be tuned and re-calibrated during development, but currently it's envisioned that the 2000 cap only applies to minute, and for daily pricing data, all available bars within the universe.
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 Quantopian. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. No information contained herein should be regarded as a suggestion to engage in or refrain from any investment-related course of action as none of Quantopian nor any of its affiliates is undertaking to provide investment advice, act as an adviser to any plan or entity subject to the Employee Retirement Income Security Act of 1974, as amended, individual retirement account or individual retirement annuity, or give advice in a fiduciary capacity with respect to the materials presented herein. If you are an individual retirement or other investor, contact your financial advisor or other fiduciary unrelated to Quantopian about whether any given investment idea, strategy, product or service described herein may be appropriate for your circumstances. All investments involve risk, including loss of principal. Quantopian 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.
Thanks Eddie,Regarding the 2000 minute bar limit ('In minute simulations, the number of data points in a history is limited to 2000.' ), this sorta rules out the multiple time frames some folks were looking for, since it is only 5 days.
I'd assumed you'd provide a much longer window (e.g. 30-90 days of minute data), that could then be re-sampled down to daily OHLCV bars (using pandas).Or perhaps one can actually obtain 2000 days, in minute mode, with: data.history(barcount=2000, frequency='1d', field='price')Presumably a 2000 bar minutely window will still be available with the batch transform?
Or will it be limited, too?Grant. 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 Quantopian. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. No information contained herein should be regarded as a suggestion to engage in or refrain from any investment-related course of action as none of Quantopian nor any of its affiliates is undertaking to provide investment advice, act as an adviser to any plan or entity subject to the Employee Retirement Income Security Act of 1974, as amended, individual retirement account or individual retirement annuity, or give advice in a fiduciary capacity with respect to the materials presented herein. If you are an individual retirement or other investor, contact your financial advisor or other fiduciary unrelated to Quantopian about whether any given investment idea, strategy, product or service described herein may be appropriate for your circumstances. All investments involve risk, including loss of principal. Quantopian 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. Hi Eddie,I'm a bit confused about the relationship between the data that will be available via history, and the stream of events that the backtester uses. It appears that the event stream is already forward-filled, prior to the backtest start (e.g. ), with no way to turn off the filling. Presumably, the history method won't be operating on the filled data, but rather the unmodified event stream, right?
But will handledata still be running on the forward-filled event stream (with non-zero volumes for non-events and lagging datetime stamps)? If so, I think that this could lead to confusion. For example, if I turn off the forward filling on the history method, then the data provided by history won't match the event stream data (assuming that you continue to forward fill the event stream data with no way to turn off the filling).Sorry, I'm having a trouble articulating the problem.perhaps you or someone else can clarify my point (or set me straight that there is no problem). I think it comes down to laying out how history, handledata, order, slippage, etc. Will manage the multi-sid case with some (or all) of the securities not trading every minute/day.Grant. 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 Quantopian.
In addition, the material offers no opinion with respect to the suitability of any security or specific investment. No information contained herein should be regarded as a suggestion to engage in or refrain from any investment-related course of action as none of Quantopian nor any of its affiliates is undertaking to provide investment advice, act as an adviser to any plan or entity subject to the Employee Retirement Income Security Act of 1974, as amended, individual retirement account or individual retirement annuity, or give advice in a fiduciary capacity with respect to the materials presented herein. If you are an individual retirement or other investor, contact your financial advisor or other fiduciary unrelated to Quantopian about whether any given investment idea, strategy, product or service described herein may be appropriate for your circumstances.
All investments involve risk, including loss of principal. Quantopian 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. Thanks Jess,One use case is to get the sid data into a numpy ndarray for analysis, in a specific order. Presently, if I understand correctly, the history API does not order the securities in the dataframe output (or the order is not obvious). One approach is to use a sort on the list of sids (e.g. By sid number), and then apply the same ordering to the dataframe (as I show in ).
It would be preferred to apply an arbitrary order to the dataframe. If I poke around in Pandas I can probably sort it out. If you or anyone there knows how, just let me know.Grant. Hi,I really think that Simon sentence was very clear 'If I were a TA man, coding a 50day 200day moving average crossover, would I ever want that inequality tested every minute?'
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 Quantopian.In addition, the material offers no opinion with respect to the suitability of any security or specific investment. No information contained herein should be regarded as a suggestion to engage in or refrain from any investment-related course of action as none of Quantopian nor any of its affiliates is undertaking to provide investment advice, act as an adviser to any plan or entity subject to the Employee Retirement Income Security Act of 1974, as amended, individual retirement account or individual retirement annuity, or give advice in a fiduciary capacity with respect to the materials presented herein. If you are an individual retirement or other investor, contact your financial advisor or other fiduciary unrelated to Quantopian about whether any given investment idea, strategy, product or service described herein may be appropriate for your circumstances. All investments involve risk, including loss of principal. Quantopian 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.
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 Quantopian.In addition, the material offers no opinion with respect to the suitability of any security or specific investment. No information contained herein should be regarded as a suggestion to engage in or refrain from any investment-related course of action as none of Quantopian nor any of its affiliates is undertaking to provide investment advice, act as an adviser to any plan or entity subject to the Employee Retirement Income Security Act of 1974, as amended, individual retirement account or individual retirement annuity, or give advice in a fiduciary capacity with respect to the materials presented herein. If you are an individual retirement or other investor, contact your financial advisor or other fiduciary unrelated to Quantopian about whether any given investment idea, strategy, product or service described herein may be appropriate for your circumstances. All investments involve risk, including loss of principal.
Quantopian 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.
|
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |