Capital Context (CAPCON) was formed to offer individual investors a decision-making toolkit previously only available to sophisticated Wall Street and hedge fund investors. Simple-to-understand (and utilize) content is created thanks to a unique blend of unparalleled credit market data, cutting-edge model development, and real-world trading & research experience. Envisioned by two of the credit derivative market’s best known and most successful analyst/strategists, CAPCON provides unique color and insight across the bond and stock markets. Investors benefit from exceptional analysis of daily market movements, unique intraday insights, strategic & tactical asset allocation decision support, and simple buy & sell signals across the capital structure.

Additionally, a powerful and intuitive scenario analysis tool, built on the framework used by the CAPCON team, enables investors to identify macro and micro opportunities based on their own assumptions. As credit derivatives become more regulated and transparent, understanding the growing interdependence between the credit market and other asset classes requires new tools, new ideas, and new frameworks – CAPCON provides this in a simple-to-use package tailored for the individual investor class.

We make money via our premium subscription service and ad hoc consulting. We are not compensated by any companies we cover with our research.

In the future, we plan on adding asset management to our list of services. Currently, we do not manage investments for any parties other than the principals of the firm.

Please read our Disclaimer for more information about our service.

No. We currently offer our services to self-directed investors. All content and forecasts on the site should be validated with additional research.

Please read our Disclaimer for more information about our service.

No. We do not derive any revenue from companies we cover. We are not paid to promote companies. Our models are designed to take signals from the credit market and apply them to the equity market.

Please read our Disclaimer for more information about our service.

In much the same way that a company’s valuation varies due to business condition uncertainty and its cost of capital, so the broad market can be modeled based on its capital structure. Through years of ‘capital structure arbitrage’ experience in the credit derivative markets, Capital Context has created the ‘SPY Arb’ model which identifies a tradable relationship between the stock market (SPY) and its value implied from interest rates (TLT), credit risk (HYG), and volatility (VXX). Our framework enables an active trader to take relatively low-risk balanced trades to take advantage of mis-alignments between the various broad measures of risk in the capital markets via extremely liquid ETFs.

The world has become an increasingly inter-connected place to trade. Whether due to central bank liquidity or the shortening of business cycles, asset-classes tend to behave in highly correlated ways most of the time. The CONTEXT framework attempts to distill the world’s ‘risk’ asset-classes (interest-rates and curves, credit risk, FX carry, commodities, and precious metals) into a single-measure that can be judged against the US equity market in order to comprehend potential mis-pricings (or technical flows and liquidity impacts). Institutional and algorithmic clients tend to use CONTEXT as a confirmation tool for positioning against (or with) a trend. CONTEXT provides a 24-hour-a-day real-time indicator of the world’s risk appetite and whether US equities are over- or under-pricing that risk.

At Capital Context, we look at how the credit and equity markets interact with each other to judge fair prices. At the core of our individual company forecasts is a credit-equity model. This model helps us estimate a company’s fair stock price given how its credit trades. In other words, a company’s credit implies its stock price (and vice versa).

For equity investors, it is useful to keep an eye on the credit markets. Capital Context’s credit-implied equity models are one way to achieve this goal.

The credit-implied equity price only uses the empirical relationship between a company’s credit and equity to forecast fair value. Our C-RANK forecast uses other market and accounting factors to make its forecast.

Additionally, the credit-implied equity price is a short-term forecast intended to be traded daily whereas the C-RANK is useful to investors with a weekly/monthly trading timeframe.

Our credit-implied equity forecasts are based on a pure alpha model. The holding period for members of our long-short portfolio is measured in days rather than weeks or months. If you have a strong view of how the overall market will perform, you should hedge individual positions accordingly.

C-RANKS are grades assigned to companies we cover.  We use the familiar system of A’s, B’s, C’s, D’s and F’s.  Companies given A’s and B’s are expected to outperform their peers while C’s and D’s are expected to underperform.

At the heart of our quantitative model, we compare a company’s stock value to its credit risk.  We combine that with our expectations for the company based on other market and fundamental data.  This yields both an expected stock (equity) value and a credit risk level.

An equity C-RANK is a grade indicating our forecast for a company’s stock performance relative to the rest of the market.  A’s and B’s indicate we expect the company to outperform the market whereas D’s and F’s forecast underperformance.

A credit C-RANK is a grade indicating our forecast for a company’s credit risk (bond) performance relative to the rest of the market.  A’s and B’s indicate we expect the company to outperform the market whereas D’s and F’s forecast underperformance.

We forecast equity and credit performance on a 1-month time horizon.  Depending on a company’s current market capitalization and credit risk and the size of the forecast improvement (or deterioration), the expected move in equity (stock) will generally be different than the relative move in credit risk.  Different forecast moves often result in different C-RANKS.

Often the clearest investment opportunities are found when the C-RANKS differ.  For example, if a company has an A equity C-RANK  and a C credit C-RANK, then the best way to take a bullish position is to buy the company’s stock and leave its bonds alone.

If the outlook is set to Bearish or Extremely Bearish, then it is common for the expected equity forecast to be negative.  Still, relative to the broader market, the company is expected to outperform.  That is, it is expected to drop less, on a risk-adjusted basis, than the overall market.

The 1-Month Equity Forecast is our model’s expectation for what a company’s stock price will be in one month.  We generate the forecast in three steps.  First, we model a company’s stock behavior compared to changes in credit risk.  Next, calculate an expected rank for the company’s performance (both equity and credit) over the next month.  Finally, we combine this expected rank with a macro outlook (stock market up/down/neutral) to formulate an expected stock price for the company.

The Credit-Implied Equity Price is the price we would expect a company’s stock to be valued at to be “fair” compared to its credit risk.  At the heart of our quantitative model, we compare a company’s stock market behavior to changes in credit risk.  At any given time, the stock and credit markets will be slightly out of sync with each other (“away from fair value”).  Our credit-equity model calculates the expected change to both a company’s stock as well as its credit risk that would bring the equity and credit markets back in line with each other. It also forms the basis for our Long-Short Portfolio.

We define Outlook as one’s expectation for overall stock market performance over the next three months.  We adjust our C-RANKS and expected company performance based on this macro outlook.

How companies’ stock and bonds perform relative to their peers will differ based on how the broader market performs.  To create our expectations for a macro outlooks, we search for the smallest changes to the current distribution of credit risk that would result in the expected stock market performance.  Those are big words that boil down to the fact that we adjust our broader credit risk model.  Once we find the most likely settings that result in a match for our equity outlook, we then generate equity and credit C-RANKS for the outlook.