{ "fetched_at": "2026-10-19T08:19:03Z", "source_url": "https://www.kaggle.com/competitions/benchmark-bond-trade-price-challenge/data", "pages": [ { "name": "Description", "content": "

The Benchmark Bond Trade Price Challenge is a competition to predict the next price that a US corporate bond might trade at. Contestants are given information on the bond including current coupon, time to maturity and a reference price computed by\r\nBenchmark Solutions.  Details of the previous 10 trades are also provided.  

", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "Rules", "content": "\r\n\t\r\n

One account per participant

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You cannot sign up to Kaggle from multiple accounts and therefore you cannot submit from multiple accounts.

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No private sharing outside teams

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\r\n Privately sharing code or data outside of teams is not permitted.\r\n It's okay to share code if made available to all participants on the forums.\r\n

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Team Mergers

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\r\n Team mergers are allowed and can be performed by the team leader. In order to merge, the combined team must have a total submission count less than or equal to the maximum allowed as of the merge date. The maximum allowed is the number of submissions per day multiplied by the number of days the competition has been running.
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Team Limits

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There is no maximum team size.

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Submission Limits

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You may submit a maximum of 2 entries per day.

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You may select up to 5 final submissions for judging.

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Competition Timeline

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Start Date: 1/27/2012 1:40 AM UTC

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Merger Deadline: None

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Entry Deadline: None

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End Date: 4/30/2012 11:59 PM UTC

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  1. Winning participants are required to provide code, as well as a description of their algorithm in document form.\r\n
  2. All participants are encouraged to provide code and documentation of their methods.\r\n
  3. Participants may reconstruct full time series data out of the training examples and previous 10 trades.  The bond_id field and the ordering should help with this. The test data is mean to be distinct and no time series reconstruction should be possible.\r\n
  4. Benchmark Solutions retains the right to not award a prize if it is determined that a player has violated any of the competition rules.\r\n
  5. The challenge organizers should be notified if any article is written using results or data from the Benchmark Bond Trade Price Challenge.\r\n
  6. Papers may be written summarizing the results from the Benchmark Bond Trade Price Challenge. By submitting an entry into the challenge you agree that a discussion of the method may appear in these papers.\r\n
  7. Participants will not use the data for commercial purposes.
  8. Participants will not use the data for purposes unrelated to the competition.\r\n
  9. Participants will not use data other than that provided to estimate their model.\r\n
  10. If necessary, the competition host may modify the training and/or testing dataset to address any problems/issues that come up during the competition.\r\n
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Performance evaluation will be conducted using mean absolute error.  Each observation will be weighted as indicated by the weight column.  This weight is calculated as the square root of the time since the last observation, scaled so that the mean weight\r\n is 1.

", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "Background", "content": "

As far as price transparency is concerned, there has historically been a huge gap between the amount of reference information available to those trading equities versus those trading corporate bonds.  Stock exchanges report trades, bids and offers at all\r\n times.  Free access is available online with a 15 minute delay while traders who demand more information can pay for ultra efficient real time data and information about size of current bids and offers. By contrast, bond trades are required to be reported\r\n within 15 minutes and only those who pay for the TRACE feed can access this information.  No quotes are publicly available and the best way to get a quote is to solicit multiple brokers and wait for a reply.  Alternatively there are data companies that provide\r\n end of day prices, published after the market has closed and with no guarantee that the specific information sought will be included.  Accurate bond pricing is also hindered by lack of liquidity.  Only a fraction of TRACE eligible bonds trade on a given day,\r\n so the most recent trade price is often multiple days old.  Pricing bonds based on other more liquid bonds that have similar features is common, but again limited by the presence of such bonds.

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Benchmark Solutions is the first provider of realtime corporate bond prices. Every 10 seconds we provide accurate prices that incorporate interest rate data, trades or quotes of the bond in question, trades or quotes of other bonds or CDS of the issuer of\r\n the bond in question as well as other input sources.  Pricing bonds accurately requires an exacting knowledge of payment schedules, trading calenders and reference data for each bond.  This, as well as synthesizing all of the bonds and CDS quotes and trades\r\n of a given issuer into implied hazard and funding curves, is something that we feel is beyond the scope of this challenge.  Rather, we provide you with a reference price which is an intermediate result of our calculations and is labeled 'curve_based_price' \r\n in the dataset. Thus the competition focuses on trading dynamics and microstructure of individual bonds, rather than all bonds from a given issuer.  

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", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "SubmissionInstructions", "content": "

For each observation, a contestant should provide the expected trade price. In the data section, please see random_forest_sample_submission.csv for an example submission. You can also examine the\r\n provided R code (random_forest_benchmark.r) which generates this example submission.

", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "Prizes", "content": "

The competition will award prizes to the top three entries:

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  1. A cash prize of $10,000.
  2. A cash prize of $5,000.
  3. A cash prize of $2,500.
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Additionally, one or more of the leading teams may be invited to participate in the\r\nThird Stanford Conference on Quantitative Finance on 3/30/2012

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This one day symposium will focus on the changing nature of the OTC fixed income markets, currently the subject of intense scrutiny by regulators, academics and the private sector. Join a prestigious gathering of experts from both industry and academia\r\n for a forensic examination of the corporate bond and credit default swap markets, culminating in a panel discussion about the central role of quantitative finance and technology in their likely evolution.  Other key themes include the broader implications\r\n of increased information dissemination in the fixed income markets - a widely anticipated development in 2012, bolstered by strong regulatory impetus. This symposium is open to the public

", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "Help", "content": "

Please write any questions or comments on the user forum.

", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "data-description", "content": "

NOTE: The compressed files contain .csv versions of the training and test data.  The .mat files are provided for MATLAB users as a convenience.

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US corporate bond trade data is provided.  Each row includes trade details, some basic information about the traded bond, and information about the previous 10 trades.  Contestants are asked to predict trade price.

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Column details:

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We have posted code using R's random forest package to create a benchmark. To handle missing values in some columns, the R code creates indicator variables for missing/non-missing and replaces the missing values with a number.

", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "Custom", "content": "

Benchmark Solutions is a “next-generation” financial intelligence firm founded on a core principle: Accuracy Matters. We believe\r\n that transparent, credible, unbiased financial data is essential to making better investment decisions. Led by industry pioneers from the fields of finance, technology and mathematics, our team is relentless in its mission to create a science of accuracy for\r\n the multi-trillion dollar global capital marketplace. With over 70 employees in New York and backed by Warburg Pincus, Benchmark is creating an unrivaled platform to deliver investor-focused and trade-accurate solutions.

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This competition has been designed to be an introduction to some of the highly complex data assimilation problems we routinely face.  If you feel that you would like to learn more\r\n about either the transparency solutions we provide, or about a potential career with Benchmark please contact\r\nsales@benchmarksolutions.com or\r\ncareers@benchmarksolutions.com  

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