FAQs

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On this page, we will find links and worked examples that can be replicated to answer the most frequently asked questions.

• What are the different types of curves in Xplain?

  In the Curves section, we will learn how to build a curve. First, we will need to set the anchor date for the sandbox environment to 30^th November 2022.

  We recommend to refer to the Permissible Values section to get a full description of all inputs for each process.

  There are four types of curves in Xplain:

  • IR_INDEX curves (e.g. USD SOFR) ⁽¹⁾
  • INFLATION_INDEX curves (e.g. GBP RPI) ⁽²⁾
  • XCCY curves (e.g. GBP/USD) ⁽³⁾
  • INDEX_BASIS curves (e.g. AUD 3M) ⁽⁴⁾

  ⁽¹⁾ IR_INDEX curves are single currency curves built with FIX vs. float nodes (e.g. FixedOvernightSwap) or float vs. float nodes (e.g. OvernightOvernightSwap)
  ⁽²⁾ INFLATION_INDEX curves are single currency curves built with FIX vs. float nodes (e.g. FixedInflationSwap)
  ⁽³⁾ XCCY curves can be defined as hybrid curves with a mix of FxSwap, XCCYIborIborSwap, XCCYIborOvernightSwap, or XCCYOvernightOvernightSwap as applicable
  ⁽⁴⁾ INDEX_BASIS are single currency curves built with float vs. float nodes (e.g. OvernightOvernightSwap) - this type of curve will be deprecated in the future

  Permissible values for curve names and associated nodes per currency can be found here.

• What are the companies/entities/portfolios used for in Xplain?

  In Xplain, a company tree will be defined by a company and its entities (and each entity’s portfolios). This can be used for instance to represent a client account and its funds, or a bank’s business unit and its trading desks.

  At the company level, you can define company’s default valuation settings and preferred valuation data providers. These can also be overridden at entity level.

  In the Portfolios section, we will learn how to create a company tree and a portfolio of trades, with default settings for valuation and exception management, prior to performing the valuation process. First, we will need to set the anchor date for the sandbox environment to 30^th November 2022.

  We recommend to refer to the Permissible Values section to get a full description of all inputs for each process.

  The three steps required to define a company tree are as follows:

  1. Create a company
  2. Add entities
  3. Upload documentation, if any

  Once the company tree has been defined, you can create a portfolio of trades and define default settings for valuation and valuation data.

• What are Market Data and Valuation Data?

  There are two types of data used in Xplain:

  • market data
  • valuation data

  Market data are stored in a market data group and correspond to the (daily) market values associated for instance to a curve node (e.g. 10Y USD SOFR swap) or to a volatility point (e.g. 5Y into 10Y ATM swaption volatility for USD SOFR).

  Valuation data are stored in a valuation data group and correspond to (daily) trade valuations sourced from third-party providers.

  In the Data section, we will learn how to input data in Xplain. First, we will need to set the anchor date for the sandbox environment to 30^th November 2022.

  We recommend to refer to the Permissible Values section to get a full description of all inputs for each process.

• How do we set up Xplain to be able to calibrate curves?

  In the Curves section, we will learn about calibration settings and how to calibrate a curve. First, we will need to set the anchor date for the sandbox environment to 30^th November 2022.

  We recommend to refer to the Permissible Values section to get a full description of all inputs for each process.

  The steps required to build then calibrate a curve group are as follows:

  1. Create (or edit) a curve group
  2. Define a curve configuration that will link a curve group to a market data group and to preferred data providers on an instrument type basis
  3. Calibrate the curve group, after selecting market data sources, discount ccy and stripping type (see here)
  4. Export curve calibration results, if need be
• How do we set up Xplain to perform valuations?

  In the Valuations section, we will learn how to run PV calculations and compare calculation results. First, we will need to set the anchor date for the sandbox environment to 30^th November 2022.

  We recommend to refer to the Permissible Values section to get a full description of all inputs for each process.

  Once we have defined a curve configuration, a market data environment, a portfolio and the relevant valuation settings, the PV calculation interface can be accessed i) at the portfolio level under Portfolios/Portfolio List by clicking on PV Calculations or ii) under Valuations/Run Valuation.

  Prior to valuing a portfolio, we need to:

  1. Set the valuation parameters
  2. Apply curve shifts, if any
• What do the outputs mean in the calculation results?

  At the calculation results level, the various outputs are:

  1. Trades PV, T0 cashflows and greeks on a trade basis
  2. Portfolio metrics (cashflows and bucketed greeks)
  3. Graphs of calibrated curves used in the valuation process
  4. Message log of events that were recorded during the valuation process

  In the Valuations section, we will learn how to run PV calculations. First, we will need to set the anchor date for the sandbox environment to 30^th November 2022.

  We recommend to refer to the Permissible Values section to get a full description of all inputs for each process.

• What is Data Cleansing?

  If you have to periodically cleanse and validate data within a specific time window, and keep an audit trail of your validation process, you can use Xplain’s anomaly detection module for market data or for valuation data.

  You can also use our trade onboarding module, which is based on a similar methodology.

  The process is started via a dashboard, where progress can then be monitored dynamically.

  This is described in further details in the Introduction to the Data Cleansing Menu section.

  Prior to learning how to start a data cleansing dashboard, you will need to set up the generic prerequisites:

  • define applicable break tests (including applicable measure, scaling, threshold and data scope) which will be applied to identify potential outliers
  • define the resolution and approval teams that will be responsible for i) resolving potential breaks and ii) approving the proposed resolutions, as part of the two-stage data cleansing workflow
  • upload the ‘raw’ data that will be subject to the anomaly detection process

  First, you will need to set the anchor date for the sandbox environment to 30^th November 2022.

  We recommend to refer to the Permissible Values section to get a full description of all inputs for each process.

  Specific prerequisites for market data and valuation data are as follows:

  For market data, you will need to define:

  • the portfolio(s)
  • the associated curve configuration(s)
  • the relevant market data environment
  • the company/entity’s default valuation settings, which will set out the link between the market data group, the portfolios and the curve configuration

  For valuation data, you will need to define:

  • the portfolio(s)
  • the relevant valuation data group(s)
  • the company/entity’s default valuation data provider settings, which will set out the link between the pricing slot, the valuation data group(s) and the portfolios
• What is required to start a market data dashboard?

  Market data cleansing can be performed ahead of valuation in Xplain, to ensure that the market data used in Xplain is of high quality. Xplain’s valuations will be based on the cleansed market data and can subsequently be used in the valuation data XM workflow, where Xplain is one of the valuation data providers.

  In the Market Data Cleansing section, you will learn how to perform an anomaly detection workflow on market data. First, you will need to set the anchor date for the sandbox environment to 30^th November 2022.

  We recommend to refer to the Permissible Values section to get a full description of all inputs for each process.

  For market data cleansing, you will need to define:

  • the portfolio(s)
  • the associated curve configuration(s)
  • the relevant market data environment
  • the company/entity’s default valuation settings, which will set out the link between the market data group, the portfolios and the curve configuration

  To start a market data XM workflow:

  • create a market data dashboard
  • specify the market data group that holds the ‘raw’ data to be validated
  • specify the curve date

  The steps in Xplain’s market data anomaly detection workflow are described here.

• What is required to start a valuation data dashboard?

  Valuation data cleansing can be performed on a standalone basis, based upon third-party data only.

  If Xplain is one of the valuation data providers, we will also perform trade valuations as part of the XM workflow, based on company/entity’s default valuation settings and (cleansed) market data.

  In the Valuation Data Cleansing section, you will learn how to perform an anomaly detection workflow on valuation data. First, you will need to set the anchor date for the sandbox environment to 30^th November 2022.

  We recommend to refer to the Permissible Values section to get a full description of all inputs for each process.

  For valuation data cleansing, you will need to define:

  • the portfolio(s)
  • the relevant valuation data group(s)
  • the company/entity’s default valuation data provider settings, which will set out the link between the pricing slot, the valuation data group(s) and the portfolios

  To start a valuation data XM workflow:

  • create valuation data dashboard
  • specify the pricing slot(s) (with further portfolio granularity options allowed) corresponding to the ‘raw’ data to be validated
  • specify the valuation date

  The steps in Xplain’s valuation data anomaly detection workflow are described here.

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Related Docs

• Coming Soon
• Introduction to Xplain's Sandbox
• Predefined Items / Settings in Xplain's Sandbox
• Prerequisites to Explore Xplain's Sandbox