Live/Paper Trade the In

Great job,
If the algo had extensive trading/rebalancing intraday, a full automated solution on the cloud would be very necessary.

If there are only a few rebalancing daily/weekly, a local PC would be good enough.

Eighter on local or remote server, we
1. get data
2. generate signal
3. execute

So let's narrow down: We are discussing an algo based on EOD(End of Day) data.

We need a script that can:
1. get data: Yahoo has good EOD data
2. run algo to generate signal: once a day after market close
3. execute: send a limit order to the broker after market close and the broker would execute the orders the next day.

So, we do it once a day after the market close.

Just wondering - is the forum going to stay alive after Nov-14?

has someone used the portfoliovisualizer?

I'm a bit shocked about the Q shutdown. Now I can't post notebooks any more...

You can retrieve Yahoo data with pandas_datareader which can be installed using

pip install pandas_datareader

A history request might look like this:

import pandas_datareader as web

start_date='2014-01-01'  
end_date='2015-01-01'  
hist = web.DataReader('SPY', 'yahoo', start_date, end_date)

You can also pass a list of symbol to get prices for all of them at once. The end_date is optional, if you leave it out you get prices up to the most recent.

Another library I know of is yfinance, also installable with pip.
And brokers with an API usually also offer price data.

So where will we go now? What platforms do you know?
I'm already on QuantConnect but haven't been very active there.

@Aleksei
I think with community platform they mean the whole website, so the forum will be gone too.
What a shame, this forum is full of gemstones...

Deleted User

Does anyone have a good alternative for backtesting strategies? I loved the ease of use of Q.

@Charlie
I guess QuantConnect could be an alternative. But there are many differences, one of them being that you can only run one backtest at a time with a free account. And of course it takes a bit of research, time and work to get your Quantopian strategies working with QC code. But I think this will be the case with any alternative.

If any one knows other platforms please post them.

Hello everybody, I created a slack for discussion this strategy:
here is the link: https://join.slack.com/t/quantopian-workspace/shared_invite/zt-imkqihmt-IkFhFhc6tEAGrc4mQjlgUA

Another way to backtest trading Ideas would be Quantiacs.

Pros:

You can install their toolbox locally (I think you don't even need to sign up for that).
There's a competition going on right now where you can win an allocation

Cons:

It is meant for trading futures, so the universe is limited to 70 something futures + around 500 stocks
They used to have a forum some time ago where I could find answers to a lot of my questions but that's gone now

Can anyone please explain this piece of the code that @Vladimir kindly shared with us?

    if exit: BULL = 0; OUT_DAY = COUNT;  
    elif (COUNT >= OUT_DAY + WAIT_DAYS): BULL = 1  
    COUNT += 1

I am a bad coder, trying to re-run his strategy in Excel, but it's clearly not working as intended without this piece.

This is the entire code if anyone is interested:

# Price relative ratios (intersection) with wait days  
import numpy as np  
# -----------------------------------------------------------------------------------------------  
STOCKS = symbols('QQQ'); BONDS = symbols('TLT','IEF'); LEV = 1.00; wt = {};  
A = symbol('SLV'); B = symbol('GLD'); C = symbol('XLI'); D = symbol('XLU');  
MKT = symbol('QQQ'); VOLA = 126; LB = 1.00; BULL = 1; COUNT = 0; OUT_DAY = 0; RET_INITIAL = 80;  
# -----------------------------------------------------------------------------------------------  
def initialize(context):  
    schedule_function(daily_check, date_rules.every_day(), time_rules.market_open(minutes = 140))  
    schedule_function(record_vars, date_rules.every_day(), time_rules.market_close())  
def daily_check(context,data):  
    global BULL, COUNT, OUT_DAY  
    vola = data.history(MKT, 'price',  VOLA + 1, '1d').pct_change().std() * np.sqrt(252)  
    WAIT_DAYS = int(vola * RET_INITIAL)  
    RET = int((1.0 - vola) * RET_INITIAL)  
    P = data.history([A,B,C,D], 'price',  RET + 2, '1d').iloc[:-1].dropna()  
    ratio_ab = (P[A].iloc[-1] / P[A].iloc[0]) / (P[B].iloc[-1] / P[B].iloc[0])  
    ratio_cd = (P[C].iloc[-1] / P[C].iloc[0]) / (P[D].iloc[-1] / P[D].iloc[0])  
    exit = ratio_ab < LB and ratio_cd < LB  
    if exit: BULL = 0; OUT_DAY = COUNT;  
    elif (COUNT >= OUT_DAY + WAIT_DAYS): BULL = 1  
    COUNT += 1  
    wt_stk = LEV if BULL else 0;  
    wt_bnd = 0 if BULL else LEV;  
    for sec in STOCKS: wt[sec] = wt_stk / len(STOCKS);  
    for sec in BONDS: wt[sec] = wt_bnd / len(BONDS)         

    for sec, weight in wt.items():  
        order_target_percent(sec, weight)  
    record( wt_bnd = wt_bnd, wt_stk = wt_stk )  

def record_vars(context, data):  
    record(leverage = context.account.leverage)

Kyle Oates

Just a thought, if QuantConnect has the slightest chance of rising to the top maybe one of the contributors or OP of In_Out can get something started on QC soon so you capture the main thread for it, even if its a wip share as porting issues are worked out. Since In_Out became quite a popular algo the move of it to somewhere else will give the Q community a good indication where to go next.

I'm in the middle of playing around with a port on QC now but personally Id rather see the owner or one of the other main contributors be OP for on it QC. I'll help with porting and DM the owner or any of the main contributors my progress if you want it (send me a DM on Q).

My fear is that with things like QuantConnect or Quanticas we become too much dependant on external infrastructure which can be shut down any day. I was hoping there are some tools that allow to leverage broker's infrastructure for algo trading. I know people are running backtests and trade algos using Interactive Brokers' not exactly sure how they get there though.

Lee YOyo

Please migrate to QuantConnect. It is very reliable and many are live trading on it for years!!

Lee YOyo

Quantconnect is the best option. Please do this amaizing strategy on it. QC also has a very vibrant community forum. Plus their staff is actively helping people.

What about IBridgePy.com - did anyone try?

I use the IbridgePy since months. The problem is tutorial is quite simple. And it seems not so easy to do the backtesting. If you need more you have to pay.

I see this in the post of closing community:

Erol Aspromatis 2 hours ago
Very sad to see this happen. Guess I'm lucky as I've already transitioned to my own server and data using Zipline and Pyfolio for backtesting. If anyone needs help, feel free to reach out to me. I've also recently created a few videos on my YouTube channel on how to set up and run Zipline and Pyfolio locally if it helps anyone:
https://www.youtube.com/c/ErolAspromatis

This sounds interessting for backtesting.

https://www.quantopian.com/live-portfolios

Has someone seen this?

@ Thomas Chang, understood, thank you!

Any chance someone could help with the code above please? The strategy seems too good to be true, so I am recalculating it in Excel to manually check. So far I am getting results inferior to Quantopian test, but I don't understand the piece of code highlighted. I am willing to share the results, but want to finalize the test first.

Done: https://www.quantconnect.com/forum/discussion/9592/in-and-out-strategy-migration/p1

Hello everybody, I created a slack for discussion this strategy:
here is the link: https://join.slack.com/t/quantopian-workspace/shared_invite/zt-imkqihmt-IkFhFhc6tEAGrc4mQjlgUA

Norman Chong

Backtrader is also another platform I've used before. It purely offline so it doesn't require a subscription to use.

John Harmon

Since Quantopian is based on Zipline, I tried out Norgate Data for my backtesting futures and stocks. It works well (only on a daily timeframe though) and easy to port any price-based filters across. Has some nice features for historical index constituent universes/delisted stocks and futures rolls.

Alexander Rehf

Hi,

just a quick idea: i started to implement this strategy with a python script and yahoo finance. as this strategy trades on a monthly basis, i dont think, that there is a need to automate the trading. i plan to implement a telegram bot, which sends notifications.

Alex

Elsid Aliaj

For what it’s worth I’ve traded $200K live through QC and IB. It’s well worth the $20/mo which includes a machine to run your algo on... it’s basically the price of a VPS.

Even getting something to run locally you’ll need a dedicated machine to rune your code on.

I don’t think there is anything that can be beat at its current price point. I was honestly still surprised people were still on Quantopian after they shut down live paper trading.

A lot of the guys from here moved over to QC. I actually suggested the “In and out” strategy over there in a thread.

I’ll make a new thread there and people can hop over if they’ll like.

Elsid Aliaj

Quantconnect support will even help in migrating the strategy fully over, what else can you ask for?

Elsid Aliaj

You have to be logged into Quantconnect to see the thread for some reason FYI.

I get 404 error.

I like Quantopian like platform such as zipline.

have you guys tried backtrader?

Slack group link for discussing the algo: https://join.slack.com/t/quantopian-workspace/shared_invite/zt-imkqihmt-IkFhFhc6tEAGrc4mQjlgUA