ActiveAllocator Shelves Growth Plans to Preserve Status Quo

  • This week we have had to take the very difficult decision to put our growth plans on hold, while preserving what we have already painstakingly created. While nothing fundamental has changed in our business thesis, we have, like many other early stage firms, not been entirely immune to the effects of the coronacrisis.  Given the very high costs of ongoing data, technology infrastructure and talent needed to operate what we have built, we no longer have the funding and investment wherewithal to scale and invest in growth. We have had to part with some colleagues, while preserving the absolute minimum core team to sustain and resurrect when opportunity accords in the future.

  • Building and evolving a digital asset allocation platform with technology-enabled customized advice capabilities over four years has been a Herculean task. Our end to end system now includes an investments accounts aggregator, a securities to asset class mapper, a capital markets comparator, a preferences personalizer, a multi-asset optimizer and a trade executor. Over the years we have enhanced our technology infrastructure through proprietary methodology and data-sets to search, recognize, classify and instantly map more than four million traded and non-traded financial instruments to 50 asset sub-classes and optimize their allocation within portfolios. We now have simultaneous optimization capabilities across skills, market exposure, downside risk and illiquidity, scalable across +200,000 portfolios concurrently. We have also added specific country/ market asset allocation models, including customized adaptation for certain emerging markets. Over the years we have surpassed business development targets with around one billion dollars in total portfolio value analyzed, reallocated and monitored across affluent and ultra-high net worth investors. We have also increased market coverage as part of our global expansion. Our efforts have been met with industry & client recognition, over a dozen endorsements, and have been supported by a thoughtful and prestigious advisory board.

  • Our efforts in the months ahead will be directed to preserving the world’s first portal that seamlessly integrates traditional, illiquid and alternative investments within portfolios. When we come out of this crisis we will continue to help investors analyze existing allocations, discover inefficiencies and create bespoke portfolios in minutes. In the days ahead we will continue to leverage our Wall Street experience and academic pedigree to provide unrivaled thought leadership to financial advisors, wealth managers, institutions and individual investors.

  • We thank our departing employees who have brought invaluable complementary asset and wealth management, investment banking and software development skills to our firm. We are grateful for their incredible hard work over the years and for their positive impact. We are also grateful to our product partners, complementary vendors who have enhanced our capabilities, clients, members of our board, supporters and so many others – for we have all created ActiveAllocator together.

 

Sameer Jain and Brian Jones

Cofounders of ActiveAllocator.com

 

 

 

 

 

 

 

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

Anatomy of Ecuador Sovereign Debt Exchange Transaction

Download PDF:

Ecuador – 2000 Sovereign Debt Exchange Transaction Anatomy

 

Wall Street Journal, July 18, 2020 “ Funds Clash Over Deal on Ecuador “

To swap $18 billion bonds into new that pay lower interest with delayed maturity. Restructuring debt proposals create creditor – including Ashmore Group, BlackRock, T. Rowe Price, Contrarian Capital – differences in how different bonds are to be treated. New transactions being asked to linked to ESG goals.

  • Ecuador seeking to restructure debt during coronacrisis, and lower oil prices given new liquidity and debt sustainability challenges
  • Oil dependent economy heavily reliant on external credit where external interest payments are 10% of current external receipts
  • For history of Ecuador Debt Restructuring we recommend: Feibelman, A. (2017). Ecuador’s 2008–2009 Debt Restructuring. In J. Bohoslavsky & K. Raffer (Eds.), Sovereign Debt Crises: What Have We Learned? (pp. 48-64). Cambridge: Cambridge University Press. doi:10.1017/9781108227001.004
  • We examine here the  anatomy of  Ecuador Debt Exchange Transactions — 2000 , the first instance of default in Brady Bonds

Asia Real Estate, Especially China, has Come a Long Way Since 2008

The Wall Street Journal today Friday, July 17, 2020  has an article “The $52 Trillion Bubble : China Grapples With Epic Property Boom”

Asian Real Estate markets have come a long long way over the last decade plus. I remember tracking them way back in 2008 when they were beginning to take off just around the time of the global financial crisis.

Here is my research note of 2008 for download :

Asia Real Estate – CAI_Journal_Summer2008

Strategic Asset Allocation Improvement and Superior Implementation

#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.  We further demonstrated concrete steps to enhance their portfolio by approximately 40 bps as described here. Here is a snapshot of one such portfolio sleeve by way of illustration (NDA prohibits us from disclosing specifics).

4-SAA Case Study continued

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

Argentina Sovereign Debt Case Study – Bonds Rise On New Debt Deal

The Wall Street Journal, July 8, 2020  reports” Argentina Bonds Rise On New Debt Deal ” : Average recoveries around $53.50, swaps existing bonds to newer lower interest paying, delayed maturity..

Earlier on May 23,  2020 The Wall Street Journal reported  ” Argentina Defaults on Sovereign Debt Amid Coronavirus Crisis – The country is struggling with economic contraction, runaway inflation and a hard-currency squeeze”

Argentina defaulted on sovereign debt for the ninth time in its history, as Latin America’s third-biggest economy grapples with a new cycle of economic contraction, runaway inflation and a hard-currency squeeze exacerbated by the coronavirus pandemic. The cash-strapped country officially entered into default on Friday after failing to make a $500 million interest payment on foreign debt. The…

We examine here the  anatomy of historical instances of Argentina Debt Exchange Transactions — February and June 2001

–Argentina Reverse Dutch Auction exchange – February 2001 when the Republic successfully exchanged over $8.0 billion of international and domestic securities

–Argentina “Mega Debt Exchange”—June 2001 when the Republic successfully executed a $29.5 billion debt exchange of 46 eligible international and domestic debt securities

Download PDF:

Argentina -Sovereign Debt Exchange Transactions 2001 Anatomy

 

 

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

Bringing an Investing Mindset to Active Funds Due Diligence

In seeking risk transparency without seeking position level specifics of a hedge fund we need to know, at minimum, a few things usually captured in a risk report. Risk reports are a useful starting point, but they are of course a static snapshot and do not tell us the entire story. For each hedge fund we can develop a better story using the understated approach and reasons for the approach:

  • Position level information: Provides a static picture of where the fund stands. These measures are most relevant for short term shocks where the actual position held matters much more than a manager’s behavior or trading strategy to define performance. These are especially useful during volatile markets as well as periods of market stress.

For medium term horizons this needs to be coupled with a fund’s trading strategy.

  • Trading strategy information: This helps us understand how (magnitude and direction) the previous static position will change over time when external market factors change i.e. trading strategy should explain sensitivity of the fund to market rises and falls.

In addition, we need to be clear about a fund’s exposure, leverage and counter party risk depending on the specifics of the hedge fund. Exposure is generic risk proxy and specifics are important.

  • Exposure as sensitivity to ‘what’ i.e. to which few important factors?

Is it net exposure? : i.e. the sum of – Short positions and + Long positions; but we should use this measure for tightly correlated positions with similar volatility for this gives a sense of sensitivity to market factors i.e. how much we stand to lose or win when a market factor moves.

Is it gross exposure: Sum of absolute positions; we should use this measure for loosely or uncorrelated positions with dissimilar volatility such as for example global equities.

  • If the hedge fund trading strategy employs futures and derivatives it helps us to see a future’s contract as a +Long position in the underlying with -Short position in cash/funding and variation margin. The “exposure” to a future’s contract is equivalent position in the underlying funding position. Therefore, we must separate the funding position from the future’s position in a risk report. Likewise, for derivatives, we can see it as a case of ‘futures’ i.e. a +Long position in underlying with -Short position in cash/funding but with the underlying changing dynamically.

 

  • Long Short: If +Longed and -Shorted assets are correlated (as often happens in relative value trades) we should look at net exposure as measure of leverage. If less correlated, we should look at gross exposure.

The key point here is to answer the question exposure to ‘what?’ for there is usually no one single exposure measure to characterize a position’s risk. For the same position we may be interested in different exposures and we may meaningfully aggregate the same sensitivities only

  • Leverage which is the ratio of fund assets to equity contributed where leverage may be explicit from borrowing or embedded from derivatives. Leverage provides us with a simple relative indication of risk to answer how large will losses or gains be to an un-leveraged portfolio. It is important to bear in mind that higher leverage does not automatically imply greater risk. It is a relative measure for a twice leveraged portfolio is twice as risky as an un-levered portfolio provided the two portfolios invest in exactly same underlying assets.

The way to analyze leverage is to decompose positions to make implicit borrowing (from derivatives) explicit. One can for example replicate a forward contract by borrowing the present value of future fixed price X at X^e-rt + F(today) and buying the asset. The futures position contributes to leverage, but when matched with an equivalent cash position, may serve as an alternative to buying the underlying. When so coupled we cannot say that just because a fund uses futures or derivatives to gain exposure, we are increasing leverage. Therefore, we need to know the risky underlying asset position and the cash positions together. It is for this reason a risk report should separate the two.

  • Risk of total loss to fund equity capital; This is an important measure that every risk report should continuously monitor. i.e. at what loss will equity get wiped out.

 

  • Risk of a fund, including from its explicit loans and from its implicit derivatives or leverage producing positions, should be less than or equal to X times ( as mentioned in the fund documents usually) the risk of the fund’s unleveraged counterpart/risk benchmark. A fund’s performance benchmark may be used as risk benchmark as a rule of thumb.

 

  • Exposure to credit risk/counterparty. This is the cost to replace the contract or a set of positions if the counterparty defaults; it may be a loan equivalent amount measure. One can develop a forecast of distribution of future exposures in which case qualitative questions range around long term forecasts of underlying risk factors, accounting for collateral, netting, and credit risk mitigation techniques etc.

We should ask for a risk report with the above as basics so that we can have; (i) a consistent set of scenarios side by side; (ii) effect of scenarios as short term shocks based on position level information and; (iii)effect of scenarios over medium horizons based on factor models and a fund’s stated strategy.

It is important to be cognizant of some issues that surround active strategies.

  • Since hedge funds hold non-linear instruments they trade dynamically and produce non- linear payoffs. So, we can say that while funds are certainly exposed to markets, the exposure is non-linear. Using multi factor models here is akin to using mis-specified linear models and inevitably leads to erroneous conclusions. So how do we then capture non linearity through appropriate factor construction? The literature is replete with suggestions including; (i) perfect trend follower replicated through a look back straddle options;  (ii) momentum trades; (iii) use of factor regressions over rolling windows to see if a hedge fund has significantly altered its strategy or compare the regression results on either side of a market event. In interpreting such we need to examine both position level results and factor sensitivities.

We can use current price information and pricing model and not need historic data dependency for:

  • Sensitivity measures: The effect of a small movement in spreads on the present value of a position. this is typically at the security level and not at portfolio level.

 

  • Stress test or scenario analysis: Modeling ‘what happens if spreads widen by X with variants such as parallel spread stress test or historic volatility of spread moves.

 

  • Relative value investors: Buying a bond and simultaneously buying credit protection through CDS (i. if the basis between them is historically very wide and investor will profit if basis returns to normal typical. Or if basis is negative and investor receives difference between bond spread and cost of CDS protection without taking any credit risk.

 

For relative value fixed income hedge funds, we need to be aware of special issues around performance and risk forecasting.

  • Forecast the overall portfolio risk: an example is to isolate interest rate risk where hold credit spreads constant, while allowing the base interest rate curve to change. And similarly, to isolate credit risk, we should hold interest rate curve constant while allowing credit spreads to change.

 

  • When credit spreads are strongly correlated to the interest rate base curve, the distinction between interest rate risk and credit spread risk is not relevant. Therefore, it is important to decompose risk across factors that are independent of each other. Spreads on CDS often exhibit little correlation with base rates and are a good mechanism to decompose risk.

 

  • We may also decompose the risk and estimate the portion from spread movements in which case we need historical data that has statistical properties amenable to forecasting. So, we cannot use Yield Spread to treasury as the benchmark T Bill rate will be changed and this change should not reflect in change in creditworthiness of a corporate bond. Also, spread volatility tends to be greater for longer maturity bonds and it is better to create spread curves on each day and apply stats on data for a constant maturity point.

 

  • Series to be analyzed: Whether we use OAS (OAS added to the base curve gives us a discount curve for cashflows promised by a bond issuer) or CDS spreads the objective is the same i.e. to ascertain how much compensation an investor should receive for bearing credit risk. The two are not interchangeable as for a CDS , upon a credit event, the receiver gets par-amount irrespective of the prevailing interest rate; to make them strictly comparable we may need a fixed to floating IRS which cancels at the event of default . ((CDS and Bonds risk free value: discount all cash flows by base curve)) – (Default probability * loss given default at the same time points)); can give us a ‘bond implied CDS’.

 

  • A single risk measure or a single risk factor to describe all positions on a single issuer is almost never relevant. For example, if the mark to market value of negative basis trade moves against investor, a previously predictable ‘zero risk’ position would suddenly become risky. Therefore, it is important to separate the two distinct sources of risk – bond and CDS market spread where simplification to a single source of risk for relative value trades would be inappropriate.

 

  • Since volatility changes there is a limit to how much historic data we need to use; using more history will not improve forecasts.

 

  • Qualitative questions too can lead to better understanding of relative value / fixed income hedge funds: What type of pricing model do you use to arrive at the NAV? How do you mark your positions to market? Is it to a model? Have you stress tested the value of your portfolio against alternative methods for marking to market? What did you conclude? How long would it take to liquidate your portfolio and what will be the incremental effect on NAV? Why would you not? What is your data source for volatility? How do you deal with correlation assumptions during these stressful times? How do you build your volatility curve?  Give us a breakdown of your trades (at the position level) by major strategy types.

While VAR alone is a reasonable measure of market risk for some portfolios, the risks of many arbitrage type strategies are better represented by stress tests and scenario analysis. Stress tests should be chosen based on the nature of the portfolio, but might include:

  • Large market shocks
  • Changes in the level of volatility, the shape of the yield curve or the volatility curve, sector definitions, correlations
  • Changes in liquidity
  • Some variables, given a small move, cause a large move in price or risk valuation
  • Some variables important to a portfolio that have a high likelihood of change
  • Those variables or exposures that offset each other

Is 2020 Going to be More Profitable for VIX Shorts – Recovery Hope Fuel Bets on Lower Volatility?

The WSJ  Friday July 3, B11 article “Recovery Hope Fuel Bets on Lower Volatility” says that traders are projecting calmer markets as the VIX drops to a low 28. We analyzed variance swaps for the last 14 years and our take on payouts is presented here.

3- vol shorts

 

Development Banks Must Now Find a New Raison D’être

2- new raison d etre

Lets call a spade a spade. Development banks have done precious little to bring about meaningful development for their member states. Their members remain mired in poverty, their efforts have spurred little economic growth, and for the most part have done little to attract private capital or catalyze strides. These institutions have been parking places for bureaucrats, served as jobs programs for mediocre but well connected civil servants pursuing careers with cushy benefits, low expectations and job security with precious little accountability.

I did a back of envelop inventory of around 600 development banks worldwide. 40 are international, regional and sub-regional development banks and 560 national development banks.  To be relevant they need to do more than lend. They need to catalyze financial flows, beef up on new products, as well as mobilize newer resources.

And U.S. tax payer should stop funding such agencies.

 

Deals Resume in Sale of Risky Loan Funds

1- clo investors hit brakes

“Deals Resume in Sale of Risky Loan Funds” The WSJ, Tuesday June 30, 2020, B9.

CLO sales cross $34 billion YTD, $5 billion in June alone as investors re-enter the risky loans market. The Fed’s corporate debt buying program is catalyzing U.S. investor appetite seeking higher spreads ( AAA at LIBOR+1.65) , even as Japanese institutional investors curtail risk taking and have been pulling back.

In 2020 CLO investors need to be especially hands-on to understand the origination processes, servicers, borrowers and quality of underlying collateral. Quality and performance of the underlying collateral is worsening materially more than expected, suggesting that the underwriting process did not consider severity of coronacrisis induced slowdown. In many cases originators had created loans primarily for sale and retained little, if any, interest in ongoing performance. Investors also need to get more deeply involved in the information cycle where excessive reliance on lagging ratings doesn’t help. In the 2008 global financial crisis default and delinquency data was artificially low because of extend and pretend and refinancing. Reliance on historical performance data and statistical models and stress test is insufficient. Investors need to manage the risk that their models are becoming irrelevant to changing conditions in the underlying loans space.

Carl Icahn Case Study – Mylan Laboratories

Slide6

#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 activeallocator.com

Debt From American Companies Lures Asian, European Investors

Wall Street Journal, June 29, B1 article “Debt From American Companies Lures Asian, European Investors”.

U.S. corporate debt  now much riskier as default rates rise, but Asian and European investor demand is very high. Fed backstop expectations prompts switch from holding low yielding treasuries to higher yielding corporate debt.

1-corporate debt