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How does HiddenLevers model bonds, ETFs and mutual funds?

Since bond prices have a precise mathematical relationship with interest rates, HiddenLevers uses standard bond analytics to project the change in a bond's prices based on changes in interest rates. HiddenLevers calculates the duration and convexity of an individual bond using standard inputs; coupon, frequency, maturity date, and bond price. This data is first used to calculate yield to maturity, which is then used to calculate both duration and convexity (the first and second derivatives of bond price with respect to interest rates).

Bond funds' interest rate sensitivity is modeled using an approach identical to that used for individual bonds. Rather than calculate bond duration and convexity, however, the fund's modified duration and convexity are sourced from market data sources. Since bond funds do not typically publish their complete holdings more often than once per quarter, using the fund's total modified duration and convexity provides a sound estimate with the data available.

Fixed income securities pricing can be impacted by broader economic forces beyond interest rates. Since bond mutual funds and ETFs do trade daily, their relationship to economic levers can be directly analyzed using HiddenLevers regression engine. Many individual fixed income instruments don't trade frequently enough to enable direct correlation analysis, however. Instead, Hiddenlevers models the impact of other economic levers on bonds using a proxy-based approach. A bond's economic sensitivity can be modeled using a listed symbol or using a general industry mapping as its proxy.

A HiddenLevers user can provide a ticker symbol to be used as a proxy for measuring a fixed-income security's relationship to the broader economy. In the case of publicly-listed companies, this approach is ideal, as the debt can be modeled as a combination of standard interest-rate sensitivity and company-specific economic sensitivity.

Industry-based proxies work very similarly to symbol-based proxies. A user can choose to use an industry category like Coal or Railroads as a proxy instead of a particular symbol. In this case, the economic impacts used represent averages across the companies within a particular industry. As with symbol-based proxies, the issuer's credit rating is used to scale the sensitivity of the bonds relative to relationships found between the industry's equities and the economy.