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Difference between Filled and Partially Filled

The document says:

"The OrderTicket Status property can be used to determine if the order is filled. The OrderStatus enum has the values Submitted, PartiallyFilled, Filled, Cancelled or Invalid."

 

From what I understand, the PartiallyFilled status only happens when the order is not set to All or None. Now my questions:

1- where do we set detail attribues of a buy order such as AllOrNone or Till End Of Day or Good Until Cancelled, etc.?

2- If Partially Filled happens, will the order stop there? or continues to try to fill the whole order?

3- If it continues to fill it, can we cancel the rest of the order?

 

Thanks a lot!

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1. Lean only supports the most common order types, with no variations. Jared commented recently on why this is: 

https://www.quantconnect.com/forum/discussion/2098/custom-order-types-to-brokerage/p1

2. Partially filled is an intermediate state. The order will only stay there if it cannot fill further (e.g. a limit order might have the limit price set too low or high, preventing it from ever filling completely). Basically, brokerage reports "order has now filled another X units of order total Y", and order will remain in partially filled state as long as sum(X) != Y.

3. Sure, you can cancel a partially filled order. Remember the volume filled at the time of cancellation at the market will not be "undone" though.

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Thanks Petter. Se let me make sure that I understand it correctly.

 

1. I place an order for 100 shares

2. 70 shared get filled -> my status is Partially Filled now

3. If I don't cancel the remaining 30 shares, the engine is going to keep trying until when? time based? until EOD? or until cancelled?

4. If I cancel the original (100 shares) order, the only thing that gets cancelled is the remaining 30 shares and I still have my 70 shares in hand.

 

Is that correct?

 

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3. I actually don't know how long an order will last assuming it's not filling and you don't cancel it - I haven't had to find out since I don't leave orders overnight. One can probably dig in the Lean source code to find out, but would be nice if QC staff can answer if they happen to read thread.

4. Here's what can happen to confuse matters w.r.t. latency:

  • You see you have filled 70 shares.
  • You cancel order.
  • Before cancellation arrives at market, another 20 shares fill of order.
  • Cancellation is confirmed (I *think* it will be reported in OnOrderEvent, but not 100% sure) and you will see you have 90 shares in total.

Unrelated: Look up the concept of "round lots" (increments of 100 units). If you place an order for 100 units on US equity exchanges, it won't be partially filled (though this is maybe not an assumption you wish to make in code). Either way, you will want to keep order quantities in increments of 100 if they're latency critical.

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Thanks Petter.

I was going through LEAN's code and I found that Order actually has an attibute called OrderDuration. Currently is has only GTC and Custom but the docs don't say what Custom means. Anyway I would try to not even think about customizing it and considering Jared's quote that you sent earlier, I'm not sure if it's even used anywhere. So, with this I think we can pretty much assume that all the orders are GTCs in LEAN.

 

 

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On the other note, I was finally able to implement a near-reality workflow model that supports a Limit Order for buys, Cancel for buy orders that are not good any more, and Market Order for sells. I chose this because when I get a sell signal, I don't want to take any risk of waiting for a Limit Sell to happen. So I just sell it for whatever market offers.

Anyway, I tested a sample algo with two models: A. buy at the market value and B. buy with a limit order, By comparing the downloaded trades side by side I can see that backtesting in LEAN is very optimistic at high frequencies such as Second. This is true even for very liquid assets. Basically LEAN just fills the order at the close price or better put, the last price.

The thing is that the close price even at the Second resolution belongs to the past and if I want to buy something at that price, there may or may not be someone out there that offers that ask price.

Of course using Limit Orders could go both ways. I could end up getting a better deal or not anything at all. The problem is that, when I tested the algorithm with those two models, model B turned a profitable results (of the model A) into loss! In the begining I was excited as I thought enabling Limit Order would make the results better for me because either I would only buy at the price that is accepted for the algo. But I guess this surprising outcome is very much related to the level of optimism that comes with the default immediate-fill-at-close-price of LEAN that is, you always get the best offers!

This is a little disappointing and I'm not sure what my next options are at this point especially with the fact that QC doesn't provide historical trade data so you can't even code based on the bid/ask data.

The only remaining hope is that, in real market there is still a good chance that most of the orders that are submitted at the close price are filled one or two seconds later. But even that maybe an optimistic assumption.

By any chance do you have any stats on what percentage of the orders get cancelled in a liquid asset such as SPY?

Thanks again.

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I am glad you have figured out everything!
The only question remaining is about Duration.Custom. It is custom because we can use DurationValue to define the limit time for being executed. Also, we need to create a custom brokerage model to deal with this value. 
Here is how it is used in OandaBrokerageModel

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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.


Alex,

I berifly looked at the code and I think I understand it a little better now. Not sure if I know enough to make my own custom implmenetation of it though. But I will send more questions when I'm there.

Can you also answer this question? I will put it in Gherkin format to make it easier:

Scenario:

Given - I am using Second resolution

Given - at 10:00:00 the close price of ABC is $30.00

Given - at 10:00:01 the close price of ABC is $30:02

Given - I am in an OnData loop at the time of 10:00:00

When - I submit a buy market order using ImmediateFill

 

Questions:

1- Do I get a fill in the same OnData loop? does it get filled in the next OnData loop? or it happens asynchronously beteen these two loops?

2- Do I get a fill at $30.00 or $30.02?

 

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Since we are working with the default fill model (ImmediateFillModel), you order is filled in the current loop interaction, thus the fill price is $30.00. 

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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.


Thanks Alex. In one of last conversations you said:

https://www.quantconnect.com/forum/discussion/2086/high-volume-orders-in-backtests/p1/comment-6360


"In backtesting mode, the default fill model is ImmediateFillModel that does not take volume into account.
If you want to add a check, ideally, you should create o custom fill model:

// Set the fill models in initialize:
Securities["IBM"].FillModel = new PartialFillModel();

// Custom fill model implementation stub
public class PartialFillModel : ImmediateFillModel {
public override OrderEvent MarketFill(Security asset, MarketOrder order) {
//Override order event handler and return partial order fills,
}
}

 

Is it possible to put a delay on the custom fill model and fill it on the next bar (in this case, the next second)?

Looking at the LEAN codes, MarketOrder has CreateTime but inside MarketFill I don't know how to get the current time to check it against.

BTW, another thing that I found is: MarketOrderDelayedTradeClose. Can you explain this as well?

Sorry for so many questions. I hope these conversations will be used for the next prople with similar problems :)

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I'm using delayed fill models in some of my backtesting (usually with on/off parameter to see effect). I would share them if I wasn't afraid they're buggy though. E.g. with ImmediateFillModel I have a Sharpe 7 algo, with a 1 s delay I get nearly -0.1% slippage (huge) and algo appears worthless. BUT in IB paper testing I get closer slippage to what I would expect of -0.01% for that symbol and my algo is making money (still in progress forward test, will be followed by minimal position real money test).

Point being, this stuff is very complicated. The lack of bid/ask data means fills at next trade will be very off if there's a longer delay, AND timestamps rounded to nearest second incurring up to 2 s of error (source timestamp 1 s off, fill timestamp 1 s off). My delayed fill models seem off anyway. There's no substitute for testing at the brokerage here.

As far as I know there's some volume aware fill model being worked on in Lean. Not sure if it incorporates delay.

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What would be the fundamental difference between a delayed fill model and a slippage model?
Say, instead of using a delayed fill model, we could use a slippage model with a fixed 0.1% slippage. Then we could make sensibility tests on that fixed value to find out how bad slippage can be.

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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.


Alex,

I did a similar (but primitive) model in my recent test. I changed the order type from Market to Limit and added 0.1% to the current price. The result was not too bad but I found many cases that in a second the price jumped more than that 0.1%. So I then increased it and increased it until it was a 5%. Given that I was using elevated ETFs I still had cases where the price jumped more than 5% in just a single second and I received a cancel signal! The more interesting thing was that even after adding 5% to the close price, the profit of this test was still behind the original test that got filled immediately at the current close/market price.

So the delay really could be different from slippage unless I don't understand the concept of slippage correctly - which is very much possible :)

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You tell me Alex, I am not the expert, haha. I've assumed that I can derive more accurate slippage via filling with some latency, but it seems overly pessimistic as I noted above. Maybe I should just be content with measuring real slippage and use that with ImmediateFillModel?

Patrick: With "slippage" as I've been using it in this context, I mean difference in "intended" fill price (in my case, latest trade price at time of order) and actual fill price of market order.

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Petter, my algo is making good trades right now when I test it with paper QC and I would really love to test it with paper IB. But the problem is that I should keep at least $30K in that account. I remember you mentioned earlier that you have never taken your algo to live trading. I think in one point we should just say, f** it, I'm going to do it in real world and if it's really burning the cash, I will pull the plug.

Having said that, I added a safe guard to my code to make sure that if I make more than 5% loss in a day, it will stop trading. The problem with thsese safeguards is that they can also go against you as they stop when it's really time to hold and wait for the bounce.

Any ideas how to make it safer with live trading?

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When I see the results of the back tests, it's too good to be true. I believe if something is too good to be true, then it's definitely too good to be true. That's why I'm looking so hard to see what is the flaw here? why I am making so much profit? LOL

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True, I've reached the point where I have to test the algo in real trading. Better backtesting would save time though because running algos at IB is a bottleneck; they have only one live data feed per account by default (IB using it for simulated fills), etc. And, when algo keeps crashing due to external circumstances (as it's currently doing for me) the test is unreliable nontheless because you keep restarting it with warmup state which may be different from live state.

Stoplosses tend to work against you, really badly. That said, I would look at Maximum Draw Down for a period you define as the current market regime, and multiply that by some factor. Then, if your algo reached a greater draw down than that, you declare the market regime has changed and take it down. It's going to happen some time, the problem is once it does you're on a guaranteed loss from the peak similar to your tolerance level. Hopefully, your algo has increased your capital correspondingly before then...

In addition to that, intraday limits can be sensible for some algos. Same problem with stoplosses there, but they can be backtested easier since you should/can probably look at some points in history where they triggered without stopping algo longer than that day (or however long period). Nonetheless, it can be really difficult to not have stoplosses drain on your algo's performance.

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Ah, I didn't know they have only one data feed. I definitely need more than that. But you can add data feeds to your account, right? or the paper IB test applies that limitation even if you have the data feed added to your account?

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My understanding is live and paper account share real time data feed, so if you're running real money algo it blocks paper account algo from using it. But you can get one more sub-account live-paper pair with another live feed if you pay for said feed. Not sure if you can get more than one additional sub-account like this. IB has weird limitations like this. Disclaimer: It was a while ago I looked at this, please do look into it yourself.

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Petter Hansson, your assumption is totally valid. However, since you said it was complicated, buggy and overly pessimistic, I was wondering whether a simpler approach shouldn't be revisited.
It is great that both of you and other members (I am thinking of JayJayD) are making some research and talking about it here. By the way, if you could share some code, we would appreciate it.

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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.


Thanks Alex. It will be hard for me to share the main code but if I find enough time I will make a simplified and cleaned version of it to share.

BTW, I implemented a manual delay system last night and did some testing. Basically what it does is, it kicks off a buy (or sell) counter but doesn't place the order until the next n OnData cycles. A little primitive but better that trying to get the custom filler to work with so little knowledge that I have about LEAN.

Are you ready for the results?

Here they are:

1- with 0 sec delay: 158.2% gain

2- with 1 sec delay: 68.8% gain

3- with 2 sec delay: 27.5% gain

 

Conclusion: if you are using an algo like mine that deals with high resolution data and is trading at high frequency, ImmediateFill could be your enemy as it's too optimistic to rely on! fortunately in this case it's not losing money but it's way less than having a fast fill.

Now researching on how to make the orders fill faster, so far what I have found are these:

- Broker! the most important factor

- Network latency

- Make the orders in Round Lots

If you guys have something else to share, I would really appreciate it.

 

PS: @Petter, would it be possible for you to send me an email? it's patrick.estariane and it's on gmail. Thanks!

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Hmmm 

this article is one of the most interesting ones. I am always intersted in what people are playing with. There is so much stuff out there. I am backtesting Volatility-Strategies mostly but trying to get a Trendfollowing-Strategy on minute bars profitable. It seems you too... :)

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Michael,

A couple of years ago I put at least 50 different strategies into test but only using daily data. Eventually I came to this conclusion that technical trading is not reliable. You could increase profit by adjusint things but at the end news, events, and sentiments are much much more important than Stochastic, EMA, trend, etc.

That time I did not have access to high resolution data as it's really expensive. Now thanks to QC, I was finally able to test some of my best performer algorithms with Minute and Second and I must say TA works just fine when news, events, and sentiments can't impact them. Because an OPEC meeting or a FED meeting or an earning report can make the indicators goofy and out of the radar's screen but it will take many seconds/minutes before that happens and your algo has enough time to take a decision and get out of the market until it's back to normal.

By any chance have you tried your method with Second data?

 

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thanks for the honest words Patrick. Still people are trading a lot with RSI for 20 years and get profits and build very impressive strategies with that. Moving averages also work for a bigger time window. If you go on youtube and search EMA 20 you get 21800 results. But yes if someone can define his own rules for investing his own money thats the best thing that can happen. The things you decribe are the reason why i'm working on a intraday strategy. Mostly trying to find a trend to follow. 

I tried to reduce to seconds resolution and build minute bars for trying to predict where the bar will be in few seconds to buy/sell. But that never worked because of gaps every full minute. I have never thought of taking a lot of money to buy at a specific price and sell 0,8% later like the big guys do at spikes when the stock is falling for example. With IB i always thought it will never work because you get 200ms Bars from them at tick resolution. And you are working here at QC with data from a different provider. So with a different broker people are always ahead of you when you use IB. That was always my view on my small trading planet. :)

I would test with 1 - 2 seconds fill time as it gets very realistic with IB. With less the others are ahead of you but maybe not. I dont know your strategy. So maybe try the TickConsolidator to create Second Bars and then try to tune it somehow. Ticks would be maybe faster than seconds. But my opinion is that QC fillforward will homehow interfere with real life environment, So forget the paper trading and do instead of real orders writing to a log file when and at which price your algo would buy and sell in live trading. That would be the first test. 3MB or more of log reading. 

but i dont have that much experience in trading. thanks for answering once again

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Thanks Michael, these are good advices. And please don't take me wrong. I did not mean to say that TA doesn't work at all. By not being reliable what I meant was that news, etc. can change the results drastically. If an OPEC meeting happens when the US market is closed, the next morning your MA, Stoch, RSI etc. are going to give you completely wrong signals. As you said, in a long enough time, these noises will be rectified by clean signals but then let's not forget that the profit will be a lot less. Especially because as a wise trader said, a 50% loss takes a 100% profit to go back to zero! So loss is always more impactful than profit.

One more thing. A lot of times we tend to test strategies in a specific time span and adjust it to get a better result. However, when you take the same "optimized" strategy to a different environment, it can behave completely different. Personally I'm very cynical about strategies and try to apply the Murphy's laws wherever I can. So I test things in bullish, bearish, sideways, and mixed time periods to make sure the behavior is consistent. I also test them with extreme price jumps like when Netflix lost 40% in a couple of days or during the market crash in 2008-2009.

Anyway these are very good discussions. Please keep it coming :)

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I am typically skeptical of TA because there's a lot of algos automatically trying to discover patterns already and whenever a new is found is will be quickly arbitraged out. Humans can make it work by constantly adapting and filtering raw TA signals, for algos you need ML for that or other forms of parameter tuning, and even then it's not easy.  One needs a lot of luck to find a TA strategy posted online that is still working. ;)

Simply avoiding scheduled press releases since our algos can't compete in latency versus HFT seems like a very good idea. Where do you get your data for that Patrick?

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Because in one point I hit the wall and couldn't improve the indicators any more. Nothing could prevent the news (I have to also say that Elliott Waves are effective for tracking sentiments). Large trading entities have sophisticated systems to consistently follow the news and events and convert them into quantifiable measures and feed them to their automatic systems but obviously we don't have that. Therefore, the only remaining way is to make the trades short/fast enough to minimize the amount of noise (and increase the signal).

As you said, ML is much more effective than primitive indicators. From what I see in my test results, keeping the average trade time under a few minutes also can increase the performance a lot.

 

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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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