TA5 Behavioural Indicators

8/12/2019 TA5 Behavioural Indicators

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Technical Analysis 5:

Behavioural Indicators

Professor Roy Batchelor

Cass Business School, London

ESCP-EAP, Paris

CESifo, Munich


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Roy Batchelor 2012Behavioural Indicators 2

Session Weekday Weekend Topic

1 Tuesday

8/5/2012

12:00-15:00

LG001

Saturday

2/6/2012

15:00-18:00

G001

What technical analysts do

- Methodology of Technical Analysis

- Evaluating directional forecasts

2 Monday

14/5/201209:00-12:00

LG001

Sunday

3/6/201212:00-15:00

G001

Statistical Indicators

- Moving Averages and Oscillators- Evaluating trading rules

3 Tuesday

22/5/2012

12:00-15:00

LG001

Sunday

3/6/2012

15:00-18:00

G001

Pattern Recognition

- Support, Resistance, Reversal and Volume

Indicators

- Bootstrap evaluation of trading rules

Saturday

16/6/2012

11:00-14:00

1001

3 x 1 hour Metastock Classes

(attend in alphabetical order, 11=A-H,12= I-

R, 13= S-Z)

Wednesday

23/5/2012

15:00-18:00

1001

3 x 1 hour Metastock Classes

(attend in alphabetical order, 15= A-H,

16=I-R, 17=S-Z)

4 Tuesday

29/5/2012

12:00-15:00LG001

Saturday

16/6/2012

15:00-18:00

Wave Theory

- Dow, Elliott, Gann and Fibonacci

- Gamblers Ruin and the Kelly Rule.

5 Tuesday

12/6/2012

12:00-15:00

LG001

Sunday

17/6/2012

09:00-12:00

Behavioural Indicators

- Biases in Investment Decision-making

- Smart Money Indicators

6 Tuesday

19/6/2012

12:00-15:00

LG001

Sunday

17/6/2012

13:00-16:00

Chaos Theory, Neural Networks and Expert

Systems

- Heterogeneous agent models and chaos

- Combining technical indicators


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Plan of session

Class test

Behavioural Biases and Heuristics

Implication for Technical Analysis

Trader position indicators


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Class test

Exam conditions

No open books

No talking

No copying

No writing (until asked)

Use the clickers ..... Which we will now test


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Plan of session

Class test





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Rational economic man

Stable UtilityFunction:

consistent attitudes

to risk and return

Rational

Expectations

Hypothesis:

uses information andmakes decisions in a

statistically optimal

way


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Misconceptions about the REH

Fallacy 1. Academics think its literally true

Its just a benchmark (like the frictionless surface)

Fallacy 2. It means everything follows a random walk

Markets are made efficient by trading on forecasts, and thiswont happen unless traders are rewarded

Exchange rate fundamentals need not follow a random walk

(though fixed horizon forex futures prices will) Return depends on risk and risk is to some extent predictable

Bubbles are rational and so strong price trends can occur


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Some problems in the rational model

Predictions of EM Model:

No rewards to forecasting

Single agreed fundamentals-based forecasting model

No speculative trades, sinceall beliefs are identical.

Prices trackingfundamentals.

Observations:

Market can only be made efficient by effortsof forecasters (Grossman and Stiglitz)

Many different models and theories,

including TA and fundamentalists

A lot of trade, with trading volumeuncorrelated with fundamentals

Excess volatility (Shiller), and FX rates,stock prices persistently away fromfundamentals


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Behavioural finance man

UnstablePreferences:

inconsistent attitudes

to risk and return

Bounded Rationality:

biases in processing

information

heuristics (rules of

thumb) used to make

decisions


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Risk and utility mental experiment

Suppose investors can put 100m in either

a safe 1-year bond which definitely pays 5%

A stock market investment which might pay +20% or -20%

Risk-averse investor A will buy the bond

Risk-loving investor B might buy the stock market investment

How will they feel at the end of the year?


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Investor A

Rational model:

get happiness = utility of 105m = U(105), a fixed number

no incentive to change behaviour next year

Behavioural model:

happiness depends on what happens in the stock market

if investment fell, U(105) is very high (Schadenfreude)

if risky investment rose, U(105) is not so high (Regret)

investor experiencing regretmay take more risk next year


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Investor B

Rational model: get happiness = U(80) or U(120)

fall in utility from -20% is bigger than rise from +20%

Behavioural model(s):

Prospect Theory:

if market falls, takes more risk to recoup losses

if market rises, takes less risk to preserve gains House Money theory:

if market rises, investor takes more risk since is now

playing with the house money


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Prospect Theory

Evidence favours Prospect Theory over House Money theory

Chicago Day Traders take more risks p.m. if they lost a.m.

Hedge Funds lock in above-average first-half-year returns

Prospect theory explains some trader/ investor behaviour: e.g thedisposition effect -

tendency to hang on to losers

(due to increased risk-taking after losses) tendency to sell winners too soon

(due to decreased risk-taking after gains)


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Behavioural finance man

UnstablePreferences:

inconsistent attitudes

to risk and return

Bounded

Rationality:

biases in processing

information

heuristics (rules of

thumb) used to make

decisions


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Poor intuitive statistical reasoning

Representativeness heuristic

Cannot replicate Bayes Theorem from verbal information


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Anecdotes v. Numbers

Narrative: Tom W. is of high intelligence although lacking in

true creativity. He has a need for order and clarity, in which

every detail finds its appropriate place. His writing is rather dull

and mechanical, enlivened by somewhat corny puns. He seems

to feel little sympathy for other people. Self-centred, he

nonetheless has a deep moral sense.

Group A. This description has been drawn randomly from a

folder containing CVs of 30 Engineers and 70 Lawyers.

Group B. This description has been drawn randomly from afolder containing CVs of 70 Engineers and 30 Lawyers.

What is the probability that Tom W. is an engineer?


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Are you persuaded?

FX markets have two states random walk (95% of the time)

and trending (5% of the time)

A trading system claims the following success rates:

If the market is trending the system will (correctly) identify

this 99% of the time

If the market is not trending the system will (incorrectly) say

that it is trending with only 5% probability

Suppose the system says the market is trending. How likely is

this to be true?


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Law of Truly Large Numbers

In 1986 Evelyn Adams became the first person ever to win more

than one million dollars twice in any state lottery.

After consultation with a professor of statistics at Rutgers

University, lottery officials concluded that the odds of one

person winning the top lottery prize twice in a lifetime were 1 in

about 17.3 trillion..." ("Odds-Defying Jersey Woman Hits

Lottery Jackpot 2d Time," The New York Times, Feb. 14, 1986).

What do you think?


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Anchoring and Availability

Anchoring heuristic: people tend to grab any available numberwhen making a forecast in an uncertain environment

Leads to:

Conservatism in forecast revisions

Stock-picking rather than diversification


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Support, Resistance and Anchoring

Support and resistanceoften found at obvious

anchors such as:

Recent highs and lows Big round numbers

Round numbers may also

reflect option exercise andretail order flow.


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Conservatism in earnings forecast revisions


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How to lie with statistics .


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but actually


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Overconfidence: The F-test

Academic studies show that about 80%

of you think you are above average with

respect to being witty, driving a car,

doing your job, living for a long time.

Overconfidence is highest when there is: a lot of (not necessarily helpful)

information

little relevant feedback (do

subscriptions and bonuses count?)

Leads to

Failure to learn from errors

Illusion of Control


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Confidence boosting behaviours

Performance attribution:

If Ive made money, it shows I have skill

If Ive lost money, well thats just bad luck

Hindsight bias. I knew it all along

Self-rated probabilities of an event (e.g. sub-prime collapse)much higher after the event has occurred than before

People often deny earlier opinions, rewrite history(Greenspan wrong not to burst asset price bubbles earlier)


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Illusion of Control: Overexplaining

Bloomberg Commentary onMonday 15 Dec 2003:

13.01 US Treasuries Rise. Husseincapture may not curb terrorism.

13.31 US Treasuries fall. Hussein

capture boosts allure of riskyassets.


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Plan of session

Class test





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Implications for Technical Analysis

Irrationality puts patterns in prices

Irrationality also makes you see patterns that arent there


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Price patterns after Good News

Path if news is soft

(statements, forecasts,

plans, ..)

Over-reaction due

to overconfidence in

new situations

Path if news is hard:(economic data)


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Price patterns after Bad News

Path if bad news is hard

initial underreaction due to

reluctance to realise losses

Path if news is soft


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The traders and the mouse

Fenton OCreevy, M., N. Nicholson, E. Soane and P.

Willman,Journal of Occupational andOrganisational Psychology 2003

Traders told to control a dot on the screen using

keystrokes, so as to keep the dot in top right segment.

Most reported success as experiment progressed, even

though movements in the dot were random.

Illusion of control:

inversely related to profit contribution andremuneration, analytical skills

directly related to people skills

Directly related to religiosity, superstition, belief

in ESP, (Blackmore and Troscianko, 1985, British

Journal of Psychology)


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Assessment of Technical Analysis

Characteristics of a good forecasting system:

Formal models better than unaided judgment

Models should give most weight to recent data

Accuracy improved by combining models (and judgement)

TA has many characteristics of a good forecasting method

Adaptability to structural change

Emphasis on confirmation

But subject to limitations highlighted by behavioural finance:

Emphasis on informal and judgmental methods meansanalysts very vulnerable to bias


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How not to be irrational

Keys to success are:

rigorous scientific testing of methods to control data mining

(beyond backtesting: e.g. bootstrap methods)

continuous objective feedback, with rewards for success and

failure linked to the forecast

Some forecasters are known to be unbiased: e.g.

Weather forecasters

Betting Odds setters/ Information Markets

Market professionals


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Plan of session

Class test





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Smart Money Indicators

In a market with heterogeneous agents, rational expectations

formation is almost impossible, since it requires knowing other

agents beliefs

Some TA indicators try to infer beliefs of other well-informed

traders: e.g.

NYSE Members Short positions Commitment of Traders Reports

Call-Put Ratio and VIX Index

Investment Intelligence


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NYSE Members short positions

Member Trades: If specialists, floor traders and other membersof the New York Stock Exchange are shorting heavily themarket is usually ripe for a correction. On the other hand, if theyare doing relatively little shorting it is most likely that the market

has hit bottom.

The Members / Public Short Ratio is calculated by dividing thevolume of the weekly short sales made by stock exchangespecialists (members) and those made by the public

(nonmembers), by the volume of total short sales.


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NYSE member trades


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CFTC Commitments of Traders Report

The Commodity Futures Trading Commission provides

information every Friday about positions taken during the weekby Commercial Hedgers and Large Speculators. (Positions ofSmall Traders can then be calculated)

Commercial Hedgers hold a significant informational edge overother traders as far as fundamental supply-and-demand statisticsare concerned. Follow commercial hedgers to pick up on longterm trends.

Small traders are liable to be less well informed. So high ratio oflong to short positions taken by small traders would be a sellsignal.


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Commitment of Traders: $/Euro

Small traders buying,

informed traders selling


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Sell signals in Jan 09 and Apr 09

Selling profitable for

informed traders


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Large Speculators OI, Oil and Gold


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Indicators from options markets

Pu-Call Volume Ratio is calculated by dividing the weekly

volume of Put options by the weekly volume of Callt options.

Big Put volume appears at market bottoms and big Call

volume at tops.

VIX (CBOE Volatility Index) computes volatility of four OEX

contracts in two nearby months and is published daily by the

CBOE. Options selected for this index are one call and one put

just out of the money, and one call and one put just in the

money, for each of the two front months of the OEX (S&P 100).

Extremely high readings of VIX indicate bottoms and low

readings tops.


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Put-Call Ratio

Indicator used as oscillator

Buy when ratio has

been high but is falling

(high number of puts

means excessive

pessimism)

Sell when ratio has

been low but is rising

(high number of calls

means excessive

confidence)


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VIX: Leading or Lagging?


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Investors Intelligence index

Based on a survey of

140 investment

newsletters by

Investors

Intelligence

Trade on

turning points in

ratio

excessive bull or

bear counts (e.g.

sell if ratio > 2, buy

if > 0.6)
http://www.market-harmonics.com/free-charts/descriptions/investors_intelligenc_survey.htmhttp://www.google.co.uk/imgres?imgurl=http://proudatheists.files.wordpress.com/2009/07/pity-the-fool1.jpg&imgrefurl=http://proudatheists.wordpress.com/2009/07/07/religious-quotes-of-the-day-atheists-are-fools/&h=330&w=300&sz=26&tbnid=T4UZ6febKpaKYM:&tbnh=119&tbnw=108&prev=/images?q=fool+picture&usg=__fREh-eeC2qk07dC5nb-hVI_uQ0w=&ei=Fy_HS8eqLIqI0wTGwajTDA&sa=X&oi=image_result&resnum=1&ct=image&ved=0CAgQ9QEwAA


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In every market there is a fool

To make money, seek to trade against the fool

If you dont know who the fool is

then its probably you
http://www.google.co.uk/imgres?imgurl=http://proudatheists.files.wordpress.com/2009/07/pity-the-fool1.jpg&imgrefurl=http://proudatheists.wordpress.com/2009/07/07/religious-quotes-of-the-day-atheists-are-fools/&h=330&w=300&sz=26&tbnid=T4UZ6febKpaKYM:&tbnh=119&tbnw=108&prev=/images?q=fool+picture&usg=__fREh-eeC2qk07dC5nb-hVI_uQ0w=&ei=Fy_HS8eqLIqI0wTGwajTDA&sa=X&oi=image_result&resnum=1&ct=image&ved=0CAgQ9QEwAA

TA5 Behavioural Indicators

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