HIA – Future Bruce Robinson May

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“The Future Ain’t What It
Used To Be”
May 11, 2012
Copyright © 2012
Bruce Robinson
[email protected]
Overview
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Yogi Berra – great American
philosopher, baseball manager and
player
Two famous quotes that are
attributed to him 
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“The future ain’t what it used to be”
“It’s tough to make predictions,
especially about the future”
What we want to look at is how
the markets and investing have
changed over the last decade, and
what the future might hold
Background and disclaimer
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Spent 25+ years in hi-tech management, then 10 as a trading
system consultant
Have been an quant-oriented investor for 25+ years
Lessons learned
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This presentation will be from the perspective of –
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“Economic (excess) profits” of ALL businesses are eventually claimed by
competition
Too many “entities” believe their own hype
Its hard to identify the real problem when you are consumed fighting the
effects
An individual investor
A consultant to independent advisors and money managers ranging from
15 million to 3 billion
Objective –
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Stimulate thought about trends and issues
Offer some examples of what works and what doesn’t today
Topics
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Background – the 1990’s
What changed things
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Availability of computing power to individuals
Lower trading cost
More fund restrictions
New investments and derivatives
Internet and high speed networks
Democratization of information
Bubbles - web companies, real estate, social networking
Results related to investing and trading
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Increased flow of funds and speed of flow
Volatility
Price noise
Decreasing Alpha (return above relative risk to market)
Increasing use of Beta (relative risk to market)
Topics
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Truisms
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Follow the money to find the driving force
Systems will always be “gamed”
Additional areas to be discussed
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Trend trading
Money managers and independent advisors
High frequency trading
Opportunities for individual investors
Intra-day trading
System development and exploration
The Good Old Days
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One way to measure trend is with persistency
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This is the probability of an up day being followed
by another up day, or a down day followed by
another down day
For small-cap’s, it changed in 2001
At certain times since then, markets have been
anti-persistent, and mean reversion strategies
have worked well
Unfortunately, mean reversion strategies are
shorter term trades best executed at the close
Computing and Analysis Capability
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Both computing power and analysis sophistication have steadily
increased
Machine learning algorithms can now “discover” trading systems
Any system can now be optimized and analyzed in minute statistical
detail
We can measure sensitivity to parameter changes
Walk forward premise
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Walk forward methodology can be used to test optimizations in an
out-of sample period that is walked forward in time to see what would
have actually happened
This would be analogous to looking every month at what route from
the Woodlands to south Houston was the fastest with the fewest
accidents over the last two years and taking it for the next month
BUT the future may not mirror the past
Number crunching and visualization
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"Not everything that counts can be counted, and not
everything that can be counted counts."
 Albert Einstein
Measurement depends on when and how you measure
Almost all indicators have significant time variation
For these reasons, use the following charts with caution –
 Heat maps
 Correlation tables
In bear markets, correlations of many instruments goes up
Try to visualize the relationship as time-varying – patterns will
emerge
Mutual funds
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In the 1990’s and early 2000’s, managed funds generated
significant Alpha
September 2003 – Eliot Spitzer filed against Canary Partners and
Bank of America for late trading violations
Later charges were made against major fund groups that they
allowed market timing in violation of documented policies
Market timing became reviled quickly
Fund companies then clamped down on trades in and out of
their funds, but many refused to publish firm policies
Brokerages with fund “supermarkets” became the policing
agents
Alpha also decreased as funds grew quickly and became more
like the market
Advisors
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Registered investment advisors can perform various functions
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Selection of investments
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Timing of the market
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Goal is to meet client targets for return and risk
Many fail to achieve one or all of these goals
As for bottom line performance –
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Goal is to avoid bear markets
Position size
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Goal is to out-perform applicable index
Must overcome their fee (1.5% – 2.0%)
Management expenses of funds (1.25% - 1.5%), ETF’s (0.75%), etc.
Advisors also face some logistical challenges
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May be held to lower trading frequency requirements
As they become successful, size limits their ability to perform the three
functions
Size also limits their ability to service accounts individually
ETF’s
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Total varies depending on the database
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1200 is an approximate total
Fees are lower than mutual funds
Three classes of ETF”s
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New ETF’s being created
Existing ones being terminated
Index tracking
Pseudo-managed
Managed ETF’s
Trading volume is key to easy entry and exit
Intermediaries, such as Wallach-Beth, exist to facilitate trading of
larger blocks
But, it is still hard for advisors to trade ETF’s and distribute
shares to clients
High Frequency Trading
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This is a very polarizing topic
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HFT shops are either “predatory scum”
Or, they are a “boon” to liquidity and transparency
Critics – for example, www.themistrading.com
July 9 – the European Parliament votes on new regulatory
proposals to force orders to dwell for 500 milliseconds
It will be tough to “put the genie back in the bottle”
HFT shops are very secretive, but, consider that an example of
an algorithm is called the “Disruptor”
And, consider a somewhat imperfect analogy –
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Would you consider an auction where “shills” made bids, then were
allowed to withdraw them before the auctioneer recognized them
And, the “shills” received rebates from the auction house
High Frequency Trading Effects
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“Noise” has increased
But, has volatility really increased ?
Depends how you measure it
 Two standard ways –
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Average True Range
 Standard deviation of rates of change
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The following shows the S&P index as an
example
Individual Investor
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Advantages
Can make decisions and move money more quickly
than advisors
 Now have tools to trade throughout the day
 Have access to economic and company information
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Disadvantages
Very difficult to compete at the tick or multi-second
level
 Insider information will always exist
 Self-reliance is difficult to achieve
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What’s a conservative investor to do ?
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One might consider high-yield bond funds as a portion
of your portfolio
They are relatively easy to time with simple EMA rules
Fund managers have the opportunity to contribute
Alpha by recognizing companies that will survive and
flourish
To date, high-yield ETF’s are inferior to mutual funds –
IOW, the mutual fund managers are earning their fees
But, over time an investor will typically run afoul of
trading restrictions of a fund
Other good funds can be rotated to in order to
minimize timing violations
What’s a moderate 401K investor to do ?
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Many 401K plans allow monthly changes AND have a
decent variety of investment choices
As an example, here is a system for a company called
Sparta that has 18 funds that range from bonds to
equity to international funds
Simple metrics work as well or better than complex
calculations
On the last day of the month (this improves results!)
rank the funds on –
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3 month return
1 month return
Volatility (ATR, or alternately SD)
Hold the top 2 funds for the coming month
What’s an aggressive investor to do ?
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If one is able to time accurately, you may “buy” volatility (ex. leveraged funds)
Ability to short issues or utilize puts can increase returns – but
tight control is needed, particularly for mean-reversion trades
Stock selection is a way to exploit the account size and agility of
an individual investor
Some diversification in sectors is needed
Knowledge of the macro-economic landscape is helpful and can
be used in allocations, but it is very difficult to use it to time
investments – it is perhaps better used to guide allocations
Tools to scan a candidate stock list are very useful
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Cheese charts
Scanning charts with lines previously drawn for support, resistance, trend,
etc. and producing a tabular report
The following are just examples – not recommendations
Summary
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The future is here. It’s just not widely distributed yet. – William
Gibson – SciFi author
We are seeing pieces of the future, but not in the final form
Market characteristics have changed and will probably change
again
Mutual funds have become problematic
Advisors will feel increased pressure to show value
ETF’s are expanding and still evolving – managed ETF’s are
coming
High frequency trading may be restricted, but the computer
driven strategies will not go away
Individual investors have some advantages that can be exploited
Investors who evolve their approach with changes that occur will
be the most successful
What the Future May Hold
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Remembering what Yogi said 
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“It’s tough to make predictions, especially about the future”
With that in mind …
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Broad market returns will be generally lower
Global economic turmoil will create opportunity
It will become increasingly hard to time broad markets
Selection will play an increasing role for individual investors
Automated trading will increase among individual investors
Holding periods will become shorter
“Edges” will evolve, but will exist for shorter periods of time
Contact Bruce Robinson
[email protected]
281-576-8857
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