Alpha and Strategy MEDIUM

7/28/2019 Alpha and Strategy MEDIUM

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S t e v e n M o r a l e s : P r i v a t e a n d C o n f i d e n t i a

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A Focus on Alpha & Strategy

The following pages contain 4 things:

1) Alpha generators

2) Excerpts from strategy presentations made to clients over the last few

years that are based on personal (in-house) proprietary research

3) Dashboards

4) Optimization tools




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1) The Alpha generators:

These are visual basic work environments that allow for uploading any dataseries, such as a macroeconomic data, and using simple transformations,search for and rank the best drivers for a given asset. These relationshipscan be simple ways to produce forecasts.

Simple examples: one could set up an experiment to find the most relevantmacroeconomic data for predicting the price of the S&P 500 6 monthsforward or the price of Oil 6m forward. Any asset can be analyzed. Anyquestion can be considered.

Key takeaways: 100’s of drivers may be considered at once. Lesser known butvalid relationships between fundamental data and markets can be found,helping to find some structure in otherwise “incoherent” market behavior,100s of forecasts can be made at once, i.e. automated for consideration,discussion, visual representation of ideas, clear, repeatable methodology,




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1) The Alpha generators: Macroeconomics vs Assets:

The research process ranks drivers in terms of relevance to create or

“show” interesting relationships. Once those relationships have been

chosen by the portfolio manager a series of forecasts can be created

for each asset.




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Example: Forecasting the S&P 500, ranking indicators,

multiple forecasts and probability distribution






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S t e v e n M o r a l e s : P r

i v a t e a n d C o n f i d e n t i a l










1) The Alpha generators: Company fundamentals for forecasting forward

stock returns

A core group of company metrics, such as earnings growth, sales

growth, ROE, dividend growth can be used to adjust valuation and

then forecast share price returns.

The model chooses between multiple multifactor models based on

simplicity and reliability.

Key takeaways: large caps stock returns are many times dictated by

simple metrics, however, each company (Cisco vs Intel) may besensitive to different factors and to different degrees. Automating this

process of determining direction and magnitude for expected returns

across an equity universe is extremely important and easy.





Forecasting share prices using P/L metrics and valuation

Example: Apple Computer

The red line is the model prediction of

Apples 6m forward return.

Here it is observed that a slowing of share

price returns was coherent with the rate of

the change of the basic fundamentals of the

business even back in early 2012.







Fundamentally driven return expectations can be produced in mass, for comparison

and discussion






1) The Alpha generators: Optimal return portfolios and management

“Clients should expect to receive asset returns adequately

compensated for risk.”

Eliminating or tactically hedging portfolios and assets during periods of

“bad future risk” reduces volatility and is a valid profit hoarding

strategy. These models identify key volatility levels for assets: stocks,

bonds, etfs, commodities, currencies, asset pairs, etc.

Key takeaways: these models are not asset selectors but asset

managers, the tactical hedging frequency is medium 12x per 5 years,the exponential cumulative wealth effects of reducing exposure during

periods of bad volatility are impressive. The tactical hedging signals

can be generated for an entire universe of assets. Monte Carlo stress

testing suggests that this strategy is a good one, but definitely not “the

holy grail”





Tactical Hedging: clear and simple “profit hoarding” methodology for

stocks, bonds, etfs, commodities, currencies and pair trades.

“Optimal return” models for any asset…







2) Strategy excerpts: 2009 – 2013

The macroeconomic alpha generators – or financial markets

relationship analyzer has been a great source of idea generation and

generalized clarity in a many times confusing market place for

investing and discussion.

However, the key to a coherent strategy have not always required

original or complicated explanations. The December 2012 message

to clients was all about,

“Fed liquidity support of asset prices could be counted on given the still high levels of structural unemployment in the United States, keeping GDP

below potential and variations of the Taylor suggested -400 bp of easing

was probably in order.”






2) Strategy excerpts: 2009 – 2013

Even so, one of the more interesting strategy pieces I wrote and

spoke about near the end of the 2009 crisis was based on a new

model I had made for forecasting core inflation. Intuition, curiosity and

research showed that potentially the future shape of “everything” was

based, directly or inversely, the shape of future inflation”. The topic atthe time was “deflation” and forecasts showed it was improbable,

already, but that stocks prices might flatten as a consequence.

Next 18 months core Inflation

forecast





Strategy excerpts: 2009 –

2013






2013






Strategy excerpts: 2009 – 2013



S t e v e n M o r a l e s : P r i v a t e a n d C o n f i d e n t i a l

“Against all Odds” the U.S.Economy is recovering mildly

but consistently in the face of aglobal slowdown and importantfinancial systemic risk fromEurope

• Stable to impoving companyearnings, normalized creditconditions, cash returns toshareholders (buybacks anddividends) a better housing

market, a “comitted” FederalFederal Reserve (QE3 / GDPTargeting), and a positve windfrom the Election year allsupport a stable riskenvironment and mild (1H) togood (2H) stock market returns

US Macroeconomics

M a c r o

I n v e s t m e n t s

InvestmentPolicy

Sectors and

Stocks

Until evidence of further monetaryand politicalsupport:UnderweightFinancials,Commodities

Overweight:Stable Growth

“Against All Odds” - Mild Recovery and Election

Year Supports “Mild to Good” Returns and Lower

Risk in 2012

Inspite of stable

earnings and risk,sector and stockselection 1H 2012should stillrecognize thefollowing risks:

1) the globalslowdown, 2)

financial systemrisk and 3) thepossibility of onlyrange boundmarkets 1H. S&Pp.obj: 1359


2013




I) Mild Growth &

Corporate Action

II) Systemic Risk

from Europe

IV) Presidential

CycleIII) Policy Action

(Fed)

Growth

Business activity, GDP,

leading indicators,

lending conditions,housing PLUS

corporate cash returns

Policy Action:

Fed recognizes the

need to improve

economic conditions

further (QE3, GDP

targeting)

Systemic Risk:

Financial Risk indicators

are showing alarm bells,

even as macoeconmic

contiions improve, thanks

to the crisis in Europe

Presidential Cycle:

A better and well

supported economy could

help Obama return to the

White House. Worst case,

less grid lock in

Washington.

II) Systemic Risk

from Europe



Risk in 2012


2013




Confidence (+)

Housing (+)

Inflation Expectations

(+)

Personal Income (+)

Expenditures (-)

Savings (+)

Credit

Supply (Lending) (+)

Demand (-)

Unemployment

(+)

GDP and Components

(+)

Leading Indicators

(Conf Board)

(+)

Business Conditions

(ISM, Philly Fed)

(+)

NBER Business Cycle

(+)

Macro Matrix – showing improvements accross the board



Risk in 2012






2013





2013







S t e v e n M o r a l e s : P r i v a t e a n d C o n f i d e n t i

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2013

Consumer confidence vs S&P 500



Risk in 2012




Circle - puzzle

ISM New Orders is inversely correlated to Pharma (-0.82)



Risk in 2012


2013




Circle - puzzle


2013



Risk in 2012




Circle - puzzle

Expect Stocks to Beat Bonds by 10%



Risk in 2012


2013




Circle - puzzle

Expect Stocks to Beat Bonds by 10%



Risk in 2012


2013





3) Investment Dashboards

Dashboards are useful for visualizing strategy and showing even a large

array of forecasts




Investment Dashboards




Monitoring global indices

Investment Dashboards





4) Optimization Tools

Research into developing interesting metrics measuring the smoothness

of returns when comparing trading strategies was useful for the much

simpler task of portfolio min var optimization.




Portfolio Optimization

Targeting beta, ir ratio, “smoothest return”, alpha slope etc, sector weight

ranges or any other desirable metric

Optimization Tools

Documents

Alpha and Strategy MEDIUM