Corporate Credit Spread Signals

In this note I describe some of the ways we at ActiveAllocator bring an active approach to investing in corporate credit.


Credit Spread Signals    

Valuation Relative to a Fitted Curve       

Bid Book            

Event Risk Indicator      

Liquidity Signal 

Equity Signals and Covenants    

Testing Equity Signals Without Bond Covenants

EDF and Rating Agency Measures of Credit Risk 

Flags to Identify At-risk Credits  

General Point   

ActiveAllocator Business Overview 2020, is seeking to enter into an equity swap, revenue sharing or a partnering arrangement with an established financial services company. We now have the world’s first portal that seamlessly integrates traditional, illiquid and alternative investments within portfolios. We help investors analyze existing allocations, discover inefficiencies and create bespoke portfolios in minutes. If you see complementary synergies and understand the Fintech space well, have decision steering authority, do email me in confidence at or call me on +1 312 498 1903, NY.
I explain our business in this short video.


Our Latest Regional Equity Valuation Model Captures Coronacrisis Recovery Differences

regional model 1

#ActiveAllocator develops state of art algorithms to capture different rates of coronacrisis recovery within countries and international equity markets. Here is the general design idea. We naturally also include multiple other proprietary dynamic factor drivers specific to coronavirus trackers, which are not shown here.

The objective is to rank the attractiveness of regional equity markets over a 12-month time frame

  • The ranks are based on a composite score
  • The composite score is a weighted average of individual ranks for various factors:
  • Valuation factors include Forward PE, PEG, Price to Book and Yield Gap
  • For each valuation factor we
    • Generate for each region a z-score (current level – 15 year historical average / standard deviation over that 15 year period) .
    • Rank the regions based on their z-scores, in other words based on how far the current valuation is from the historical norm (for most factors a low score ranks highest, but for Yield Gap a larger number ranks highest)
    • Momentum factors include earnings revision breadth and earnings revisions depth. Larger, positive numbers rank highest
    • Use different factors and different weights for developed markets and emerging markets

Recommended Changes in Strategic Asset Allocation Demonstrate Potential to Add Substantial Value

#ActiveAllocator Research Case Study – We successfully demonstrated to the world’s perhaps most sophisticated Government Investment Fund that our proposed changes to their strategic portfolio could increase annual returns by over 60 bps, while holding risk constant. That’s a non-trivial returns enhancement when you are speaking about hundreds of billions of dollars. Never underestimate the power of Strategic Asset Allocation done correctly. Here is a snapshot of one such portfolio sleeve by way of illustration (NDA prohibits us from disclosing specifics).

3- SAA case study

ActiveAllocator Research Drives Locating and Generating Alpha

2- incremental alpha

#ActiveAllocator Research – I was in essence recently asked “Why does ActiveAllocator create public goods by publishing its proprietary research?”. I guess an answer is we are in the business of creating incremental alpha for our clients, and holding on to ideas in a fast moving world is seldom optimal. Here is a visual on how we recently helped a very large public fund – where strategic asset allocation was a small part of our engagement.

Case Study:

Client has an objective to:

– increase returns by 100bps

– lower volatility

– Sharpe ratio of 0.5

Client has made substantial changes to its strategic asset allocation

These changes have the potential to add a great deal of value, although in and of themselves, they will not necessarily meet the above objectives

– Based on ActiveAllocator’s proprietary models, “index-like” returns in each asset  category will achieve approximately 60% of the return objective

To fully meet its objectives, Client will need to

– enhance performance through long-run value-added activities (“offense”)

– minimize ‘slippage’ in the portfolio during the transition period (“defense”)

While accomplishing these objectives will involve connecting a myriad set of puzzle pieces, Client should focus intensively on what may be the most important implementation areas

– enhancing internal alpha generation capabilities

– implementing an alternative investment strategy which maximizes value

– effective portfolio management

Carl Icahn Case Study – Mylan Laboratories


#ActiveAllocator Research – Companies are likely to become vulnerable to activist investors during the coronacrisis period. To explain transaction mechanics, activist hedge fund motives and criteria, we analyzed 15 Icahn transactions over the years. We present these in succinct case studies each day on our research blog.

Also, you can derive your own optimal portfolio allocation to activist and other hedge fund strategies on

Carl Icahn Case Study – General Motors


ActiveAllocator Research – Companies are likely to become vulnerable to activist investors during the coronacrisis period. To explain transaction mechanics, activist hedge fund motives and criteria, we analyzed 15 Icahn transactions over the years. We present these in succinct case studies each day on our research blog.

Also, you can derive your own optimal portfolio allocation to activist and other hedge fund strategies on

Technology Driven Personalization in Financial Advice

ActiveAllocator’s core growth strategy capitalizes on several long-term industry trends that continue to be valid and even stronger in 2020. One being mass-customization. Technology driven mass customization is affecting many customer oriented industries, driving clients to expect highly personalized services uniquely tailored to their specifications. ActiveAllocator allows the “traditional” advisor to provide a modern digital advice experience. Recognizing that the “market of one” is the new norm, we go far beyond broad meaningless categories such as the wide spectrum of “very conservative” to “very aggressive” investors. Rather, our system is designed to drive the individualization of every aspect of asset allocation, down to the level of a single client.

Customers demand personalization without realizing they are demanding it, as they grow accustomed to companies anticipating their needs and offering what they’re looking for – sometimes before they even know what that is. Retailers and travel companies are using predictive tools and algorithms to exceed expectations, yet digital teams at financial firms have been slow to re-engineer websites and apps to enable highly personalized digital experiences. As consumers become more accustomed to personalized services – from online music selection, to customized exercise plans, to personal shopping, to travel – expectations will further rise. Within the financial advice sector, our approach rapidly exposes the fallacy of the “one size fits all” solution approach – such as those embodied in model portfolios and managed accounts.

Personalized service is going to be a key weapon in advisors’ battle, against competition from and disintermediation by, digital advice platforms. Once investors realize that the same managed accounts offered by advisors can be manufactured in minutes by robo-advisors at a fraction of fees, advisor fee compression is but inevitable. In an era when money can be managed effectively, efficiently and cheaply, ActiveAllocator helps advisors move up the value curve. Marrying our cutting edge fact-based, algorithm-driven predictive analytics with the advisor’s special understanding of the client’s unique circumstances drives superior outcomes. We believe that this powerful combination goes far beyond anything offered by emerging digital financial advice platforms, robo advice and digital investment managers.



Which Asset Class is Now Attractive For You? Which is Not?

The world has changed in 2020 and so should your investment portfolio. But has it?

Given what you/ your client already owns within a portfolio, should  one own more of a particular asset class? Or less? What is attractive and what is not?The most consequential, and often best decisions, are those that are made at the margin. However marginal decomposition, on a forward- not backward -looking basis within portfolios is easier said than done. While there is much written in the academic literature, one is often hard pressed to arrive at fact based decisions at the moment of making investing calls.

In the past such was often relegated to opinion, conjecture and gut feel. Not anymore. ActiveAllocator calculates it for you in 15-20 seconds.

ActiveAllocator Comparison to Addepar

ActiveAllocator is very inspired by Addepar, and the generous analogy investors now draw. At a closed door briefing I was told ‘one day you will exceed Addepar’. For a struggling FinTech CEO this, I thought was the highest compliment! I looked at similarities and differences between our companies

email me for pdf


ActiveAllocator Tech Improvement in 2019

ActiveAllocator is a MIT-Harvard-Technion-Yale -UCDavis alum founded WealthTech startup. We analyze and integrate traditional, illiquid and alternative investments to improve complex portfolios: This actual live screen capture here aggregates customers accounts across +15,000 banks, sources capital market inputs from +10 Wall Street firms, simultaneously analyzes +10 million asset allocations deployed across +4 million securities, within +50 granular asset sub-classes, personalizing target portfolio to +100,000 preferences, whilst executing seamlessly across +20 broker dealer systems. All done in under 2 minutes.