{"id":53481,"date":"2020-07-23T09:45:00","date_gmt":"2020-07-23T13:45:00","guid":{"rendered":"https:\/\/ibkrcampus.com\/?p=53481"},"modified":"2023-02-13T15:17:36","modified_gmt":"2023-02-13T20:17:36","slug":"time-weighted-average-price-twap-in-financial-markets","status":"publish","type":"post","link":"https:\/\/www.interactivebrokers.com\/campus\/ibkr-quant-news\/time-weighted-average-price-twap-in-financial-markets\/","title":{"rendered":"Time-Weighted Average Price (TWAP) in Financial Markets"},"content":{"rendered":"\n<p><strong>What is TWAP?<\/strong><\/p>\n\n\n\n<p>Time-weighted Average Price (TWAP) is a well-known trading algorithm which is based on the weighted average price and is defined by time criterion. TWAP is calculated for executing large trade orders. With the TWAP value, the trader can disperse a large order into a few small orders valued at the TWAP price since it is the most beneficial value.<\/p>\n\n\n\n<p>This is basically done to not let a huge order suddenly increase the value of a particular financial asset in the financial market.<\/p>\n\n\n\n<p>Let us now see an example of TWAP.<\/p>\n\n\n\n<p><strong>Example of TWAP<\/strong><\/p>\n\n\n\n<p>Let us assume that someone wants to make a strategy to buy 10,000 shares of an asset. In the process of making the strategy, one can choose from two possible strategies. One, a trader can issue orders to purchase 500 shares every 15 minutes for 5 hours.<\/p>\n\n\n\n<p>Two, the trader can implement a strategy in which the order is issued to purchase 1,000 shares every 15 minutes for 2.5 hours.<\/p>\n\n\n\n<p>But, with a strategy going on in the financial market, it is simpler to track the trading pattern by other traders and make a guess about the next strategy until and unless its orders are modified by adjusting the parameters. Further, this modification implies that the orders\u2019 size can be randomized or the time between each order can be delayed.<\/p>\n\n\n\n<p>Now, let us find out how the TWAP value can be calculated for a longer duration.<\/p>\n\n\n\n<p><strong>How is TWAP calculated?<\/strong><\/p>\n\n\n\n<p>In the case of Time-weighted Average Price, TWAP is calculated by averaging the entire day\u2019s price bar, i.e., open, high, low, and close prices of the day. Then, on the basis of time decided to execute an order, every day\u2019s averaged price is taken for calculating the average of the entire duration\u2019s prices. This is known as the TWAP.<\/p>\n\n\n\n<p>TWAP strategy is the best execution strategy for spreading out the trades over a specific time period and reduce the impact of trade on the market.<\/p>\n\n\n\n<p>Like every trade, the TWAP also performs when all the conditions are met before which the price is calculated from the entry of the order and goes through the close of the market.<\/p>\n\n\n\n<p>The calculation of TWAP goes as follows:<\/p>\n\n\n\n<p><strong>Average of each day\u2019s price<\/strong>&nbsp;=<\/p>\n\n\n\n<p>(Open + High + Low + Close)\/4<\/p>\n\n\n\n<p><strong>Average of 28 days<\/strong>&nbsp;=<\/p>\n\n\n\n<p>(Average of first day\u2019s price + Average of second day\u2019s price +&#8230;&#8230;..+ Average of twenty-eighth day\u2019s price)\/28<\/p>\n\n\n\n<p>In the excel sheet, you can calculate the average of each day. You can take the historical data from&nbsp;<a href=\"https:\/\/www.nasdaq.com\/\" target=\"_blank\" rel=\"noreferrer noopener\">NASDAQ<\/a>&nbsp;by simply typing the symbol of the stock you want the data of. Here, we have taken the data of Apple Inc. on which the calculation of the average of each day in the excel sheet is done in the following way:<\/p>\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" data-src=\"https:\/\/d1rwhvwstyk9gu.cloudfront.net\/2020\/07\/TWAP-1-1.png\" alt=\"\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" class=\"lazyload\" \/><\/figure>\n\n\n\n<p>Above, the calculation was done using the formula =AVERAGE(B2:E2) as shown in the cell. We had taken two months\u2019 data from Apple Inc.<\/p>\n\n\n\n<p>For calculating the average of each row, you simply need to copy and paste the formula for every row in the cell under TWAP.<\/p>\n\n\n\n<p>Further, for averaging the entire period\u2019s average, you simply put the formula =AVERAGE(G2:G23) as shown below:<\/p>\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" data-src=\"https:\/\/d1rwhvwstyk9gu.cloudfront.net\/2020\/07\/TWAP-2.png\" alt=\"\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" class=\"lazyload\" \/><\/figure>\n\n\n\n<p>The average comes out to be $328.15 taken out under the heading Av_row.<\/p>\n\n\n\n<p>After calculating TWAP, your order price will be considered undervalued when it is below TWAP and overvalued when it is above TWAP.<\/p>\n\n\n\n<p>In Python also, we can calculate TWAP. First of all, we will fetch the data of the stock we wish to calculate TWAP of.<\/p>\n\n\n\n<p><p style=\"background-color:#fcfcdb;font-size:11px\" class=\"has-background\">\n# Install package<br>\n!pip install yfinance<br><br>\n\n# Import libraries<br>\nimport yfinance as yf<br>\nimport pandas as pd<br><br>\n\n# Import price data for Apple<br>\ndata = yf.download(&#8216;AAPL&#8217;, start=&#8221;2020-05-18&#8243;, end=&#8221;2020-06-18&#8243;)<br><br>\n\n# Calculate adjustment factor<br>\nadjustment_factor = data[&#8216;Adj Close&#8217;] \/ data[&#8216;Close&#8217;]<br><br>\n\n# Calculate adjusted open price<br>\ndata[&#8216;Adj Open&#8217;] = adjustment_factor * data[&#8216;Open&#8217;]<br><br>\n\n# Calculate adjusted high price<br>\ndata[&#8216;Adj High&#8217;] = adjustment_factor * data[&#8216;High&#8217;]<br><br>\n\n# Calculate adjusted low price<br>\ndata[&#8216;Adj Low&#8217;] = adjustment_factor * data[&#8216;Low&#8217;]<br><br>\n\n# Delete Volume column<br>\ndel data[&#8216;Close&#8217;]<br>\ndel data[&#8216;Volume&#8217;]<br>\ndel data[&#8216;Open&#8217;]<br>\ndel data[&#8216;High&#8217;]<br>\ndel data[&#8216;Low&#8217;]<br>\ndata\n<\/p><\/p>\n\n\n\n<p>Output:<\/p>\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" data-src=\"https:\/\/lh3.googleusercontent.com\/bcsUEajB0L8DMKyOAPRL37isMd-ZF6D_XRwzMtmNAyO1vxd91ALqB2cZBpZ1oxSMS4tdgt1w6bHSIErw5HZ6rEYVARfZ1ja1oYETxYxCETUjhUgD5ybIMbV-8kxB_EV7iT59bKa7\" alt=\"\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" class=\"lazyload\" \/><\/figure>\n\n\n\n<p>Above we have got the entire data from 2020-05-18 to 2020-06-18 as we did above in the excel sheet.<\/p>\n\n\n\n<p><em>Stay tuned for the next installment in this series &#8211; the author will find each row\u2019s average under the column \u201cav_row\u201d since, in TWAP calculation, the first step is to find out the average of OHLC of each trading day.<\/em><\/p>\n\n\n\n<p>Visit QuantInsti website to download additional Python code: <a href=\"https:\/\/www.quantinsti.com\/\">https:\/\/www.quantinsti.com\/<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Learn what Time-weighted Average Price (TWAP) is and how it is calculated for executing large trade orders with this feature from QuantInsti. <\/p>\n","protected":false},"author":368,"featured_media":53482,"comment_status":"closed","ping_status":"open","sticky":true,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[339,343,349,338,350,341,344],"tags":[851,4922,1226,1225,1224,595,494,8081,8082],"contributors-categories":[13654],"class_list":{"0":"post-53481","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-data-science","8":"category-programing-languages","9":"category-python-development","10":"category-ibkr-quant-news","11":"category-quant-asia-pacific","12":"category-quant-development","13":"category-quant-regions","14":"tag-algo-trading","15":"tag-econometrics","16":"tag-financial-engineering","17":"tag-numpy","18":"tag-pandas","19":"tag-python","20":"tag-quant","21":"tag-time-weighted-average-price","22":"tag-twap","23":"contributors-categories-quantinsti"},"pp_statuses_selecting_workflow":false,"pp_workflow_action":"current","pp_status_selection":"publish","acf":[],"yoast_head":"<!-- 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