2 ND EDITION

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Day Trading with Price Action
Volume IV: Positive Expectancy
Galen Woods
Trading Setups Review
Copyright © 2014-2016. Galen Woods.
PDF eBook Edition
Cover Design by Beverley S.

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Copyright © 2014-2016 by Galen Woods (Singapore Business
Registration No. 53269377M). All rights reserved.
First Edition, 1 September 2014.
Second Edition, 5 April 2016.
Published by Galen Woods (Singapore Business Registration No.
53269377M).
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Registered Trademark of NinjaTrader™, LLC. All rights reserved.
No part of this publication may be reproduced or transmitted in
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Disclaimer
The information provided within the Day Trading with Price
Action Course and any supporting documents, software,
websites, and emails is only for the purposes of information and
education. We don't know you so any information we provide
does not take into account your individual circumstances, and
should NOT be considered advice. Before investing or trading on
the basis of this material, both the author and publisher
encourage you to first seek professional advice with regard to
whether or not it is appropriate to your own particular financial
circumstances, needs and objectives.
The author and publisher believe the information provided is

correct. However we are not liable for any loss, claims, or
damage incurred by any person, due to any errors or omissions,
or as a consequence of the use or reliance on any information
contained within the Day Trading with Price Action Course and
any supporting documents, software, websites, and emails.
Reference to any market, trading time frame, analysis style or
trading technique is for the purpose of information and
education only. They are not to be considered a
recommendation as being appropriate to your circumstances or
needs.
All charting platforms and chart layouts (including time frames,
indicators and parameters) used within this course are being
used to demonstrate and explain a trading concept, for the
purposes of information and education only. These charting
platforms and chart layouts are in no way recommended as
being suitable for your trading purposes.
Charts, setups and trade examples shown throughout this
product have been chosen in order to provide the best possible
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demonstration of concept, for information and education
purposes. They were not necessarily traded live by the author.
U.S. Government Required Disclaimer: Commodity Futures
Trading and Options trading has large potential rewards, but
also large potential risk. You must be aware of the risks and be
willing to accept them in order to invest in the futures and
options markets. Don't trade with money you can't afford to

lose. This is neither a solicitation nor an offer to Buy/Sell futures
or options. No representation is being made that any account
will or is likely to achieve profits or losses similar to those
discussed on this web site. The past performance of any trading
system or methodology is not necessarily indicative of future
results.
CFTC RULE 4.41 - HYPOTHETICAL OR SIMULATED
PERFORMANCE RESULTS HAVE CERTAIN LIMITATIONS. UNLIKE
AN ACTUAL PERFORMANCE RECORD, SIMULATED RESULTS DO
NOT REPRESENT ACTUAL TRADING. ALSO, SINCE THE TRADES
HAVE NOT BEEN EXECUTED, THE RESULTS MAY HAVE UNDEROR-OVER COMPENSATED FOR THE IMPACT, IF ANY, OF
CERTAIN MARKET FACTORS, SUCH AS LACK OF LIQUIDITY.
SIMULATED TRADING PROGRAMS IN GENERAL ARE ALSO
SUBJECT TO THE FACT THAT THEY ARE DESIGNED WITH THE
BENEFIT OF HINDSIGHT. NO REPRESENTATION IS BEING MADE
THAT ANY ACCOUNT WILL OR IS LIKELY TO ACHIEVE PROFIT
OR LOSSES SIMILAR TO THOSE SHOWN.

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Contents
Chapter 1 - Introduction to Positive Expectancy ...................... 1
1.1 - Definition of Expectancy ............................................ 2
1.2 - Definition of Winning Probability ................................. 3
1.3 - Probability versus Reward-to-Risk............................... 4
1.4 - Beyond Price Action Analysis .................................... 16
1.5 - Conclusion ............................................................. 19

Chapter 2 - Stop-Loss ........................................................ 21
2.1 - Initial Stop-loss ...................................................... 23
2.1.1 - A Method for Losing Small .................................. 25
2.2 - Trailing Stop-losses ................................................ 27
2.2.1 - Price Action Setups ........................................... 29
2.2.2 - Support and Resistance ..................................... 31
2.2.3 - Market Volatility ................................................ 33
2.3 - The Wrong Way to Place Stop-losses ......................... 37
2.4 - Consistency of Stop-losses....................................... 41
2.5 - Conclusion ............................................................. 42
Chapter 3 - Targets ........................................................... 43
3.1 - The Importance of Profit Targets in Day Trading ......... 44
3.1.1 - Trailing Stop-loss .............................................. 44
3.1.2 - Profit Target ..................................................... 44
3.2 - Finding Targets ...................................................... 49
3.2.1 - Support and Resistance ..................................... 49
3.2.2 - Price Thrust Projection ....................................... 53
3.2.3 - Price Channels .................................................. 59
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3.2.4 - Volatility Projection ........................................... 67
3.3 - Exiting with a Reversal Signal .................................. 70
3.3.1 - Anti-climax Pattern ........................................... 71
3.3.2 - Merged Congestion Zone.................................... 74
3.3.3 - Additional Notes................................................ 79
3.4 - Targeting Examples ................................................ 81
3.4.1 - FDAX 10-Minute Example ................................... 82

3.4.2 - ES 10-Minute Example ....................................... 85
3.4.3 - 6J 10-Minute Example ....................................... 89
3.4.4 - CL 3-Minute Example ......................................... 92
3.5 - The Wrong Way to Place Targets .............................. 98
3.6 - Conclusion ............................................................. 99
Chapter 4 - The Meaning of Likely ..................................... 101
4.1 - How to Assess the Probability of Winning ................. 103
4.2 - Conclusion ........................................................... 106
Chapter 5 - Achieving Positive Expectancy.......................... 108
5.1 - The Split Second .................................................. 110
5.1.1 - R2R Indicator ................................................. 113
5.2 - Complete Trading Examples ................................... 117
5.2.1 - CL 4-Minute Example (14 April 2014) ................ 119
5.2.2 - CL 4-Minute Example (1 May 2014) ................... 126
5.2.3 - CL 4-Minute Example (5 May 2014) ................... 133
5.2.4 - CL 4-Minute Example (12 May 2014) ................. 146
5.2.5 - CL 4-Minute Example (15 May 2014) ................. 156
5.2.6 - FDAX 3-Minute Example (8 August 2014) ........... 164
5.2.7 - FDAX 3-Minute Example (31 July 2014) ............. 171
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5.2.8 - FDAX 1-Minute Example (20th November 2015) .. 180
5.3 - Managing Trades for Positive Expectancy ................. 190
5.4 - Conclusion ........................................................... 194
Chapter 6 – The Analytical Cycle ....................................... 196
6.1 - Establish Rules and Guidelines ............................... 199
6.2 - Record Ongoing Analysis ....................................... 202

6.2.1 - Thought Process for Basic Analysis .................... 203
6.2.2 - Written Analysis as a Tool ................................ 205
6.2.3 - Tools for Recording ......................................... 212
6.3 - Classify Trades ..................................................... 214
6.4 - Review Trading Records ........................................ 219
6.4.1 - The Holy Grail................................................. 220
6.4.2 - Measuring Expectancy ..................................... 224
6.4.3 - Computing Drawdown (for Position Sizing) ......... 232
6.4.4 - Improving Expectancy ..................................... 239
6.5 - Refine Trading Rules and Guidelines........................ 253
6.6 - Conclusion ........................................................... 254
Chapter 7 - A Risk-Based Approach to Trading .................... 255
7.1 - Identifying Risks ................................................... 256
7.2 - Risk Management Card .......................................... 260
7.3 - Financial Risk ....................................................... 263
7.3.1 - Trading Capital ............................................... 263
7.3.2 - Living Expenses .............................................. 265
7.3.3 - Currency Risk ................................................. 267
7.4 - Operational Risk ................................................... 269
7.4.1 - Trading Computer ........................................... 271
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7.4.2 - Electricity ....................................................... 273
7.4.3 - Internet Connection ........................................ 274
7.4.4 - Broker ........................................................... 276
7.4.5 - Trading Platform ............................................. 280
7.4.6 - Execution Process ........................................... 281

7.4.7 - Trading Environment ....................................... 283
7.4.8 - Minimise Risk by Keeping It Simple ................... 284
7.5 - Psychological Risk ................................................. 285
7.5.1 - Psychological Foundation ................................. 289
7.5.2 - Practical Strategy ............................................ 292
7.5.3 - The Final Determinant ..................................... 303
7.6 - Integration of Risks .............................................. 303
7.7 - Conclusion ........................................................... 305
Chapter 8 - End of the Beginning ...................................... 307

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Chapter 1 - Introduction to Positive
Expectancy
The expectancy of a trading setup refers to the expected
outcome of taking that setup many times over a long period of
time. The sole aim of every trader is to take setups with positive
expectancy in order to accumulate profits. Otherwise, your
trading capital will be depleted in a matter of time.
Having a positive expectancy is also referred to as having a
trading edge. Conceptually, it is akin to a casino’s edge. Over a
large number of bets, the casino expects to make a profit at the
gamblers’ expense.
As profit-driven traders, positive expectancy is everything.
The difference between us and the casinos is that their edge is
rooted rock solid in statistics. They have rigged the games in
their favour, and they know it. They can even prove it. As for

us, we are trying to rig the game, not quite knowing if we have
succeeded. It is a much tougher play for traders.
So, if you can get over the legal issues and possibly moral
qualms, I suggest that you open a casino rather than day trade
futures.
When it comes to trading, there are numerous topics covering
strategies, indicators, setups, entries, exits, risk management,
psychology, software, hardware, and many others. Ultimately,
these pieces should fit together to help you take trading setups
that exhibit positive expectancy.
Positive expectancy is the single most important concept in
trading. Hence, it is essential that every trader has a thorough
understanding of it and see how the different parts of a strategy

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Chapter 1 - Introduction to Positive Expectancy

come together to highlight opportunities with positive
expectancy. While the concept of having a trading edge is
covered in many trading books, most of them do not give it the
attention it deserves.
The earlier volumes taught you how to analyse market bias and
trading setups. However, they did not show you how to trade,
because nobody can trade without understanding the concept of
positive expectancy.
To learn how to trade, read on.

In this first chapter, we will break down the concept of
expectancy into concrete aspects that we can examine and
improve with respect to each trading opportunity. The ultimate
purpose is, of course, positive expectancy for each trade we
take.

1.1 - Definition of Expectancy
To this end, we cannot be content with the one-line basic
definition mentioned above. Expectancy is more than a fluffy
trading concept. It is a statistical concept. To achieve positive
expectancy, we have to understand it statistically.
If you did not enjoy your mathematics classes, do not fear.
There are only three ingredients.




Probability of winning a trade = W
Reward of a trade = R
Risk of a trade = L

Expectancy = ( W x R ) – [ ( 1 – W ) x L ]

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Chapter 1 - Introduction to Positive Expectancy


Both intuition and mathematics tell us that to maximise
expectancy, we need to:




Maximise the probability of winning a trade (W)
Maximise the reward of a trade (R)
Minimise the risk of a trade (L)

It seems like there are three distinct steps to finding great
trading opportunities.
1. Find a high probability trade.
2. Place our target far away to maximise profit.
3. Place our stop-loss near to minimise risk.
That sounds simple.
Unfortunately, the above recipe is wrong. The greater
misfortune is perhaps the large number of traders with this
erroneous understanding.
To uncover the correct approach, you need to understand the
true meaning of winning a trade and the inter-relationships
between the winnings odds, our target, and our stop-loss.

1.2 - Definition of Winning Probability
Many traders discuss the probability of winning a trade as
though it is independent of its potential reward and risk.
That understanding cannot be any further from the truth and is
a very dangerous idea. Any discussion of the probability of a
winning trade is flawed if it does not incorporate its potential
reward and risk. It is important to comprehend why.

The first step is to understand what it means when we say we
win a trade. It means that the trade results in profits.
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Chapter 1 - Introduction to Positive Expectancy

Let’s assume that each time we enter the market, we place a
target limit order and a stop-loss order, and we do not adjust
them.
It follows that for a trade to be profitable, the market must hit
our target before hitting our stop-loss. If our stop-loss level is
hit first, then our trade results in losses and not profits.
Hence, the probability of winning a trade is the probability of the
market hitting our target price before hitting our stop-loss point.
This is why the probability of winning a trade is not independent
of its target and stop-loss. Thus, we must integrate them into a
single thought process. As mentioned, a useful way to formulate
the winning probability of a trade is the “probability that the
market will hit our target before hitting our stop-loss”.

PROBABILITY OF WINNING
Probability that the market will hit our
target before hitting our stop-loss

This definition offers great insight. It shows clearly that the
probability of winning a trade is dependent on how well we set
our target and stop-loss.


1.3 - Probability versus Reward-to-Risk
The next step is to find out exactly how our targets and stoplosses are related to our winning probability.
For clarity, let’s start with a completely random market. A
random market implies that, assuming there is no slippage and
commissions, the long run outcome of any trading strategy is
breakeven.
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Chapter 1 - Introduction to Positive Expectancy

Let us establish a long position in this hypothetical market. We
place a sell limit order above our entry price as our target and
concurrently place a sell stop order below our entry price as a
stop-loss. Our target and stop-loss are equidistant from our
entry price.
For illustrative purpose, let’s assume that both the target and
stop-loss are 10 ticks away from our entry price as shown in
Figure 1-1.

Target (50%)
10 ticks
Entry price
10 ticks
Stop-loss (50%)

Figure 1-1 Equidistant target and stop-loss


Since the market is random, the probability that it will move up
10 ticks is the same as the probability of moving down 10 ticks.
Basically, the probability of either scenario is 50%. This means
that over the long run and over many such trades, 50% of the
trades will make us 10 ticks each, and 50% of the trades will
incur 10 ticks of losses each. Since the profit per winning trade
is the same as the loss per losing trade, we will end up in a
breakeven position. (Assuming that that there are no slippages
and commissions.)

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Chapter 1 - Introduction to Positive Expectancy

Now, let’s consider a trade with a 20-tick target and 10-tick
stop-loss. What are the odds of this trade being profitable? Is it
still 50%?
If it is, according to our expectancy formula, we expect to make
5 ticks per trade (0.5 x 20 – 0.5 x 10). When we say we expect
to make 5 ticks a trade, we mean that our average profit per
trade over a large number of trades is 5 ticks.
Wow, fantastic. Simply by using a larger target, we have
managed to squeeze some money out of a random market.
Is that possible?
Absolutely not. It is impossible to make money from trading a
random market over the long run.

By placing our target further from our entry price, a random
market will no longer churn out winning trades and losing trades
with equal probability.
Instead, the market will have a lower probability of hitting our
target first and a higher probability of hitting our stop-loss first.
This is because the distance between our target and our entry
price is larger than the distance between the stop-loss and our
entry price.
The 50-50 probability applies only when the target and the stoploss are at the same distance away from our entry price (i.e.
when our reward-to-risk ratio is 1). When we push our target
further to 20 ticks away and maintain our stop-loss at 10 ticks
away, our reward-to-risk ratio increases to 2.
Thus, the probability of the market hitting our target order
before hitting our stop-loss order decreases to approximately

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Chapter 1 - Introduction to Positive Expectancy

33.3%. The probability of the market hitting our stop-loss
before reaching our target increases to roughly 66.6%.
Figure 1-2 illustrates this change in probability.

Target (33.3%)

20 ticks


Entry price
10 ticks
Stop-loss (66.6%)

Figure 1-2 Lower winning probability for higher reward-to-risk ratio

How do we know this? How did we get the probabilities of
33.3% and 66.6%?
Recall that the market we are talking about here is random and
the outcome of any trading strategy over the long run is
breakeven.
Simply put, it indicates an expectancy of zero. By plugging the
value of zero into the expectancy formula, we can work out the
relationship between the probability of winning a trade, and the
target and stop-loss of a trade, in a random market.

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Chapter 1 - Introduction to Positive Expectancy

Expectancy = 0 (Random market)




W – Winning probability
R – Reward

L - Risk

(W x R) – [(1 - W) x L] = 0
W x R = L x (1 - W)
R / L = (1 – W) / W
We plotted a graph of Winning Probability (W) against Rewardto-Risk (R/L) using this equation in Figure 1-3. It reveals an
important relationship. In a random market, the probability of
winning decreases as our reward-to-risk ratio increases.

Figure 1-3 Decreasing probability with increasing reward-to-risk ratio

This graph illustrates the definite breakeven outcome in a
random market without trading costs like commissions and

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Chapter 1 - Introduction to Positive Expectancy

slippage. The expectancy of every trade is zero and falls on this
line.
The relationship depicted in Figure 1-3 is intuitive. Achieving the
target is necessary for winning a trade. The further the target,
the harder it is for the market to achieve it. Hence, the further
we place our target, the higher the reward, and the lower the
probability of winning the trade. Conversely, if our target is
near, our probability of winning increases.
Another necessary condition for our trade to succeed is that the

market must not hit our stop-loss before hitting our target.
Thus, tighter stops lower our winning probability because the
market has a higher chance of hitting them. Wider stops are
less likely to be hit by the market. Hence, the further we place
our stop-loss, the larger the risk, and the higher our winning
probability.
When we combine these two lines of thought, we conclude that
the higher the reward-to-risk ratio, the lower the winning
probability. This inevitable trade-off between the winning
probability and the reward-to-risk ratio is an essential trading
concept.
This random market marks our theoretical start point. Now, let’s
move on to considering the same relationship in real markets.
Does the relationship described above hold true for the real
financial markets that we intend to trade?
The efficient market hypothesis is relevant for this discussion. I
am not going to expound on the full-fledged theory, and will just
present a short explanation before we move on.
Basically, the hypothesis states that markets are efficient at
absorbing price-sensitive information. The more efficient they
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Chapter 1 - Introduction to Positive Expectancy

are in doing so, the harder it is for anyone to make money from
the market.
The underlying explanation is very logical. If there is a trading

strategy that works, everyone will jump in and trade with that
strategy. In doing so, the trading edge of that strategy is
eroded.
For instance, let’s consider the January effect1 which is the
tendency for stock prices to rise in January each year. This is
purportedly due to income tax reasons. The trading strategy to
take advantage of the January effect is to buy stocks near the
end of the year and sell them in January after the stock prices
has risen.
However, if everyone employs the same strategy, then they
would all buy near the end of the year. By doing so, they push
up the prices. As a result, the difference between their cost
basis and the eventual (supposedly higher) price in January
narrows. Their potential profit diminishes. If the market is
perfectly efficient, this impact will be so pronounced that
January effect simply ceases to exist.
In a perfectly efficient market, all information is reflected in its
price and movements cannot be anticipated. Thus, all
movements are random. In that case, the relationship in Figure
1-3 would hold.
Everyone who is trying to make money from the market
believes that financial markets are not entirely efficient. They
believe that inefficiencies of varying degrees exist in the market.
Some detractors of the efficient market hypothesis go as far as
to say that the hypothesis is wholly wrong and completely
useless.
First documented by Sidney B. Wachtel in his 1942 paper “Certain Observations on
Seasonal Movements in Stock Prices”.
1


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Chapter 1 - Introduction to Positive Expectancy

I do not agree with this extreme view. The efficient market
hypothesis does make sense. Its underpinnings are logical and
rational. Hence, I believe that it is difficult to make money from
trading the market and profitable opportunities are fleeting. The
generally high failure rates of traders and the underperformance
of most fund managers prove this point.
At the same time, to believe that markets are completely
efficient is naïve.
Thus, a realistic view is that it is possible, although challenging,
to make money from predicting market movements.
The relationship in Figure 1-3 holds true in financial markets
most of the time. However, at times, the market exhibits a kink
in the relationship that offers positive expectancy. Those kinks
represent the trading opportunities we are looking for.
Figure 1-4 illustrates where these positive expectancy
opportunities lie.

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Chapter 1 - Introduction to Positive Expectancy


Positive Expectancy

Negative Expectancy

Figure 1-4 Positive expectancy region on the right of the curve

Recall that the curve represents zero expectancy. Note that
traders do not start on the line of zero expectancy. Due to
trading costs like commissions and slippage, all traders start in
the negative expectancy region.
Our job as traders is to focus on getting on the right side of the
line where we find trading setups with positive expectancy.
These setups can be the result of a higher probability or higher
reward-to-risk ratio or both.
A reward-to-risk ratio of 1 paired with a winning probability of
0.5 (50%) produces zero expectancy. If there is a chance to
enter the market with a reward-to-risk ratio of 1.5 and
probability of 0.5, do we take it? Yes, because it has a better
reward-to-risk ratio than a zero expectancy trade. It carries
positive expectancy.
Great, we know where we want to be - on the right side. But
how do we get there?

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Chapter 1 - Introduction to Positive Expectancy


The key factor that causes opportunities to open up on the right
side of the zero expectancy line is the market bias. The market
bias denotes a higher tendency of the market to move in one
direction, either up or down. If the market has no bias, then it is
random. In that case, there is no money to be made. If the
market has a bias and we manage to decipher it, then there is
money to be made.
Thus, if we get the market bias right, we have managed to
squeeze through to the right side of the graph. This is why we
devoted the entire Volume II to the art of figuring out the
market bias.
This is also why the market bias is our foremost consideration
when we look at any market we intend to trade. If we are
unsure of the market bias, we are unsure if we are on the left or
right side of the graph in Figure 1-4. When we are unsure, we
should not trade.

“He will win who knows when to fight and when not to fight.”
Sun Tzu, The Art of War

However, even after we confirm the market bias, we cannot
enter the market until we are able pinpoint an exact entry with
a clear reward-to-risk ratio and an acceptable probability.
To define our reward-to-risk ratio, we need to find a reliable
trading setup aligned with the market bias. It will give us our
entry price and stop-loss level. The difference between them is
our risk.
Concurrently, we must figure out where to put our target by
examining the market support/resistance and by employing


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Chapter 1 - Introduction to Positive Expectancy

target projection techniques. The difference between our target
price and our entry price is our reward.
Then, we can finally put our reward and risk together to find out
our reward-to-risk ratio.
How about the probability of winning?
Recall that the probability of winning refers to the probability of
the market reaching our target before hitting our stop-loss. It
follows that the probability of winning depends on how well we
select our stop-loss and target.
We need a stop-loss that the market is likely to stay away from.
This means that we need to find a high quality trading setup.
Then, we need a target that the market is likely to move to,
which means that we need to find a magnetic target level that
draws the market towards it.
Accordingly, to maximise the winning probability, we need to
examine how we select our target and stop-loss, and if they are
reliable.
Summing up the above, we get the correct approach to finding
trading opportunities as shown in Table 1-1.

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Chapter 1 - Introduction to Positive Expectancy

No. Task

Purpose

1

Determine the market bias

Open up the possibility of
positive expectancy

2

Find a reliable stop-loss point

Define risk

3

Find a reliable target level

Define reward

4


Determine how likely it is for
the market to hit the target
before hitting the stop-loss

Define probability

Calculate expectancy

Evaluate if the trade
offers positive
expectancy

5

Table 1-1 Correct trading approach

We enter the market only if the setup offers positive
expectancy. Let’s take a look at our progress with respect to this
trading approach.
Assessing the market bias is the subject matter of Volume II.
Return to it if you are still unsure of the techniques for
uncovering the market bias.
Items 2 to 5 lay out the roadmap for the first part of this
volume.
In Chapter 2, you will learn that a high quality trading setup will
provide a reliable stop-loss. As we have already discussed the
attributes of a high quality setup in Volume III, we will devote
our time to learning about alternative stop-loss techniques and
their implications.
In Chapter 3, you will pick up techniques to identify reliable

targets. We will rely heavily on our earlier discussion on support
and resistance, in particular the different types of swing pivots
and the Congestion Zone. We will also talk about the importance
of using target limit orders in day trading.

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Chapter 1 - Introduction to Positive Expectancy

In Chapter 4, we will embrace the fuzziness of deriving the
probability of winning. We ask ourselves what is the likelihood
that the market will hit our target before hitting our stop-loss?
This is where we decipher the inner workings of our mind in an
attempt to arrive at a quantified probability of a successful
trade.
In Chapter 5, we will combine risk, reward, and probability using
the expectancy formula to decide if a trading opportunity is
worth taking. This chapter also contains comprehensive
examples to bring you through the entire trading process, from
evaluating the market bias to deriving the expectancy of a
trade. These important examples serve to reinforce everything
we have learned and show how they fit together to produce
profitable trading prospects.

1.4 - Beyond Price Action Analysis
The second part of this volume, from Chapter 6 onwards, moves
beyond price action analysis. Our trading approach creates our

trading edge. Beyond that, we need to focus on two things.
First, we work on improving our trading edge or expectancy. We
will deal with this in Chapter 6 in which we will focus on keeping
good records of our trades and learn how to analyse them to
improve our trading performance.
Next, we ensure that we are adequately prepared to exploit the
positive expectancy of our trading strategy. In Chapter 7, we
will discuss the three main risks that might affect our ability to
trade.
First, we must avoid financial risks, in particular the risk
of ruin. Every trading strategy suffers drawdowns, including
those with positive expectancy. For instance, you have a trading
strategy that would cause you to lose $1,000 before making

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