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Discrepancies in prices from Yahoo finances and price from Q
Kean Lin Sin
posted Jun 23, 2015

Hi,

I am very new to programming. This is my 1st time of doing. So, looking assistance from others to solve the discrepancies.

Checking the functionality of my code and realised that prices extracted from my code are not coherent with prices from Yahoo Finance. Pls input.

Below is my code:
def initialize(context):
set_universe(universe.DollarVolumeUniverse(floor_percentile=99.9,ceiling_percentile=100.0))
context.notional_limit=100000

def handle_data(context, data):
for stock in data:
log.info(str(stock)) # this will print out all the securities in the universe
context.cl_price_history = history (bar_count=2, frequency='1d',field='close_price')
print(context.cl_price_history)

Prices from Q:
Security(39840 [TSLA])
2014-03-31 20:00:00+00:00 208.4201
2014-04-01 13:31:00+00:00 210.3400

Prices from Yahoo Finance
Date Open High Low Close Volume Adj Close*
Apr 1, 2014 209.02 218.16 208.58 216.97 7,371,400 216.97
Mar 31, 2014 216.50 216.75 206.39 208.45 8,380,000 208.45

Thank you.

2 responses
Robert Putnam
Jun 23, 2015

Hi Kean,

I believe that when you're in the minute backtest mode, history(bar_count=2, frequency='1d', field='close_price') would give you non-adjusted close prices for the current minute and the previous day. So:

Date Time Quantopian Time Yahoo
3/31 market close 208.42 market close 208.45
4/1 9:31 EDT 210.34 market open 209.02

There is a small difference in close price on 3/31. I don't know if the Q number for 4/1 is right, but it's a little apples v. oranges (9:31 v. market open).

My two cents...

Robert

Alisa Deychman
Jun 23, 2015

Hi Kean,

Check out our FAQ about the differences in data:

Quantopian uses the last traded price as the close price for the security. Depending on the data source, others may use end-of-day (EOD) prices. For example, Yahoo is an EOD datasource. Yahoo and other EOD data providers get their price and volume data from the official exchange record. Quantopian's data is generated by the actual trades, regardless of what exchange the trade was made on. The EOD sources rarely exactly match data derived from intraday data. For instance, the official close for a NYSE stock is the last trade of the day for the stock on NYSE. But if the stock also trades on Chicago, Pacific or another regional exchange, the last trade on one of those exchanges could be our close.

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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 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.