The Finance Book Club

The Art of Currency Trading by Brent Donnelly

You know what? After looking at the table of contents of this book I’m convinced the most interesting material (if any) is at the end of the book so I’m going to summarize this book in REVERSE and begin at the last chapter and work my way to the start, Benjamin Buttons-style, because it’s my thread and I can do what I want.



Brent Donnelly is a senior FX trader at HSBC NY. He has been a market maker, trader, and senior manager at some of the top banks in foreign exchange.

The rest of his CV reads a lot like a resumé so if you’re looking for a guy who looks trustworthy and ties a perfect tie, Brent’s your man. By the way, are more traders than usual named Brent? Is it a coincidence that Ricky Gervais’ character of the boss in the British Office was named Brent?

Oh wait a tick - he’s also a creative! He’s written a cartoon that was on Canadian TV, it says, but I never saw it. He wants to win the Man Booker prize which means he’s secretly writing a novel and I bet, I just bet, he does some of it at work! Watch out HSBC!!

Brent Donnelly’s 25 Rules of FX trading

1. Don’t blow up
2. Adapt or die (this is a business rule, cheater!)
3. Do the work
4. You can always find a ‘tech level’ to justify a bad trade
5. A big level is not justification for a big trade
6. No FOMO
7. When in doubt get out
8. It doesn’t have to make sense
9. Don’t fade the central banks
10. Making money is hard and keeping it harder
11. Successful traders make more money on up days than they lose on down days
12. Anything can happen
13. Keep a trading journal
14. There is a time and place to go big
15. Good traders vary bet size
16. “It always looks bid at the highs. It always looks heavy at the lows.”
17. You control the process, not the outcome
18. Each trade is a drop; the market is an ocean
19. Know your edge
20. Know your horizon
21. Have a plan
22. Tight/aggressive wins
23. Be flexible
24. Don’t let random low conviction trades kill you
25. Have fun, otherwise what’s the point?

Seems solid enough if not entirely original

Chapter 16 - Conclusion
If you just tuned in I’m going backwards through this book.

 

1. Brent Donnelly (BD from now on) had a boss who told him in 10 years there would be no human traders (just losing ones)
2. Major trading desks that used to employ 20-30 people now have 3-4.
3. In the 1990s you spent all day busy like a broker executing client trades, trying to survive
4. Now human traders handle the big tickets and think how to stay ahead of the market
5. Retail traders can access research that was once only available to interbank and buy-side traders
6. Quant and research jobs are mainstream not niche now
7. HFT and electronic market making make room for mathletes
8. Everything changes - momentum rules til it doesn’t, ranges become trends, correlation cleans up or gets rinsed
9. Those with skill, discipline and a plan will win
10. Those without will lose
11. Good luck, be nimble

This seems like it would have been a good introduction. Weird!

Chapter 15 - The Voice of Experience

1. This chapter is a collection of random thoughts, tips and advice
2. Take what ‘resonates’ and ignore the rest
3. Don’t let random trades bleed you
   1. If you believe in the trades you have on, great. Otherwise get out.
   2. Resist the human tendency to favour novelty, and to adjust positions.
   3. Let your trades breathe.

4. How to avoid overtrading
   1. Be extremely disciplined. Failing that (use a robot)
   2. Set a trade quota
   3. Trade only at specific times
      1. “it often makes sense to put new trades on or take trades off at 7AM NY and then leave everything until at least 11:00AM NY. This allows your trades a full NY/LDN overlap session to play out and avoids the need for instant gratification and constant fine-tuning.”

   4. These are clear rule-based solutions.
   5. Write down your rules and follow them.
   6. Sticking to your rules allows you to research, concentrate, read, undistracted by flickering
   7. BD couldn’t control his overtrading so he made a compromise and allows himself to ‘dabble’ with single unit positions while his reasoned positioning is much larger
   8. This helps him get a feel for the market (Livermorian)
   9. Design rules and processes that fit with your personality

5. Trading Slumps
   1. They feel bad, man!
   2. You never see them coming
      1. After losing money eight days in a row you wonder if you’ll ever win again

   3. Probabilities
      1. 55% win rate means you average 2-3 five day losing streaks per year and probably one six day losing streak
      2. This will make you feel like a moron but you’re not. (you’re just a trader. )
      3. On their own slumps aren’t dangerous but they can mess with you and cause bad decision-making
      4. Self-awareness is the key
         1. Slow down
         2. Breathe
         3. Take a day off
         4. BD doesn’t take days off but reduces position size
         5. Unless things are really bad then he’ll take a couple of days off for a research project

   4. Vacations are a necessary part of a successful process
      1. Go on one once per year

   5. Experience will tell you when slumps are over
   6. A different slump is one triggered by external factors - health, marriage, etc.
   7. Square up
      1. Cut all existing positions so that any residual frustration related to losing views can dissipate (I dunno man)
      2. Trade smaller
      3. Talk about the slump - some firms have psychologists but you have friends, maybe, you lucky dog
      4. Read and do research
      5. Get perspective
         1. You are a 1/7.6B people on a spinning rock, in an infinite universe.
         2. This is the safest time in human history to be alive (or it was)
         3. Focus on health, sunshine
         4. Markets always get better
         5. Stay resilient and optimistic

   8. Tips for a happy life
      1. Think about the long game and your career
      2. Financial freedom is only a small part of happiness (spoken like someone with lots of money)

   9. Get some Perspective
      1. Didn’t we just do this?
      2. P&L is not life or death
      3. Some traders are afraid to admit they made a great trade or to feel happy because they don’t want to jinx it (for me it’s more about recognizing triumph and failure are both impostors - excellence is something that becomes mundane eventually)
      4. Don’t celebrate until you have taken the profit
      5. Make lower highs and higher lows emotionally (yes)
      6. Have a risk management system you trust

6. Don’t constantly check the market
   1. Exercise
   2. Spend time with family

7. Turn off your phone at night
   1. You make poor trading decisions when you are tired

8. Read Nonfinancial books
   1. BD alternates between math/finance books but that’s not much of a tangent

9. Eat properly and exercise
   1. BD admits he sounds like our mom
   2. Bank traders eat fatty restaurant food because the analyst makes a bulk order and orders for everyone - don’t be lazy, get your own lunch

10. Have Fun
    1. To succeed you have to love trading
    2. Trading is the second best job next to pro sports

BD recommends the following books:
Coates, John. The Hour Between Dog and Wolf: Risk Taking, Gut
Feelings and the Biology of Boom and Bust.
Douglas, Mark. The Disciplined Trader: Developing Winning Attitudes.
Douglas, Mark. Trading in the Zone: Master the Market with Confidence,
Discipline and a Winning Attitude.
Gardner, Dan. Risk: The Science of Politics and Fear.
Krakauer, Jon. Into the Wild.
Pirsig, Robert. Zen and the Art of Motorcycle Maintenance: An
Inquiry into Values.
Thoreau, Henry David. Walden.
Which ones should we add to the stack?

Chapter 14 - Common Weaknesses in Trading

1. Poor Risk Management
2. Bad Discipline
3. Negative Risk/Reward
4. Trading for the wrong reasons
   1. Gambling
   2. Entertainment
   3. Addiction
   4. BD cites the cautionary tale of Jesse Livermore that we’ve reviewed a few times
   5. To feel smarter than others
   6. FOMO (fear of missing out)
      1. The worst cases of FOMO happen in traders who are locked into one view for a long term
      2. Don’t get married to one view of the market
      3. If you miss a move there will be countless others

5. To lose money
   1. BD admits this is a crazy one
   2. Some people subconsciously don’t believe they deserve the money they have made
   3. People raised by hard working parents might feel guilty about the minimal exertion it takes to make large sums trading (and ironically the less you exert, the more you can make)
   4. Too tired or burnt out to care

6. Waiting for the Perfect Trade
   1. Risk-averse traders get paralyzed

7. Invincibility & Overconfidence
   1. Operate near the middle of the emotional spectrum
   2. Think about ‘tilt’ - there are both loser’s and winner’s variety
   3. For BD the winner’s tilt is a bigger problem
   4. BD has a spreadsheet that warns him when he’s risking too much

8. Woulda, Coulda, Shoulda Syndrome
   1. Rookies spend too much time thinking about the past
   2. When a trade’s over it’s done, move on (Rambo)

9. Directional Bias
   1. Bad traders stick with one view for too long
   2. ‘Too long’ is dependent on trading horizon
   3. Trade currencies from both sides

10. If you see yourself in some of these write down ways you can improve in those areas
    1. I would say discipline is a constant problem for me which is why I prefer algo trading
    2. My risk management can use some work, but also I feel that’s one area that’s never going to be strong enough. You have to work with what you have.

11. BD recommends Roy Baumeister - Willpower: Rediscovering the Greatest Human Strength. Can you get willpower from reading a book?

Chapter 13 - Characteristics of a Successful Trader
Remember I’m going backwards through this book so this is the start of Part 4, which we will have finished at the end of this chapter. Time travel is confusing!

1. Balances risky behaviour and discipline
   1. Some people are too risk averse
   2. Others are too wild
   3. These imbalances can be fixed with a ‘solid process’

2. Independent thinking
   1. Don’t follow the crowd
   2. Don’t be a reflexive contrarian
   3. Think for yourself
   4. ‘‘The most contrarian thing of all is not to oppose the crowd but to think for yourself.’’ – Peter Thiel, Zero to One
   5. Trade your own view, never someone else’s
   6. Successful traders do their own work and reach their own conclusions

3. Know your edge
   1. If you don’t know who the sucker is at the table it’s probably you
   2. Trading is a negative sum game because of transaction costs

4. Trade one time horizon
   1. BD trades last 3 hours to 7 days and the majority are in 1-3 day bucket
   2. The tighter you define your time horizon, the better
   3. Markets are fractal but mixing time horizons is a recipe for disaster (true)
   4. Poorly timed short-term trades become longer-term investments
   5. Forget about trading gold, oil and S&P because a jack of all markets = master of none (hmmm)

5. Controls Emotion / Acts Robotically / Self-Aware
   1. Emotion kills
   2. Euphoria and disappointment lead to suboptimal decision making
   3. Be self-aware -know when you are on tilt
   4. Euphoria and depression can often signal a turning point in the market

6. Implement a consistent daily routine
   1. Good traders are totally prepared before they start
   2. They have a process and a plan
   3. BD has a daily sheet that he completes each morning
      1. Gauges his emotions
      2. Puts numerical ‘brackets’ around his day with a profit target and a stop loss number which helps enforce discipline
      3. Thoughts are noisy and abstract
      4. Written statements are concrete and focused
      5. Every trader should have at least a brief written plan for each day (daily exercise)

7. Happy to be Flat
   1. Good short-term traders get flat
   2. There are not always good trading opportunities
   3. Have patience and willpower to wait for good opportunities, that’s part of your job
   4. BD admits he isn’t good at this (is it even possible to be good at this if the market is mostly random?)

8. Tight/Aggressive
   1. An approach coined by poker players
   2. You don’t want to be involved in many pots
   3. But when you do be as aggressive as possible
   4. Wait for good cards and then go for it
   5. Never go ‘all in’ literally though

9. Self-understanding and metacognition
   1. Good traders are self-aware and understand the importance of thinking about thinking (metacognition)
   2. You should hear your own thoughts more clearly than you did in the past
   3. Identify your biases and info processing strengths
   4. Assesses ‘state of mind’ on ongoing basis
   5. When BD feels euphoric he reduces risk

10. Loves Trading
    1. Success demands love!
    2. BD has been into trading since he was a teenager
    3. If you are trading just for the money you can’t win as you miss out on a career that should have been your true passion

11. Learns and Adapts
    1. Good traders keep learning (why I’m here)
    2. Growth mindset
    3. Market microstructure has changed dramatically with the rise of algos
    4. As trading became automated in the 2000s there were two groups
       1. One group complained about the rise of the algos
       2. They were ‘messing things up’ and changing the game in unfair ways
       3. The other group analyzed the new market structure and adapted
       4. They changed their style to fit the new regime
       5. Guess which group lost their jobs (I guess it was the complainers!!)

12. Gut vs Head
    1. When you run a trade two systems are running in parallel
       1. Head - logic and analysis
       2. Gut - past experience and intuition
       3. Strongest views come from head/gut being in sync

    2. In situations where you’ve done the head-work but your gut is not on board
       1. Ask why
       2. Your subconscious may be warning you about a pattern you’ve seen
       3. Good trading takes courage
       4. You won’t always be able to ‘unpack’ your gut feelings but you need to try

    3. All Gut No Head
       1. The opposite situation is your gut tells you something will happen
       2. But you have no logical foundation for the idea
       3. You do analysis to confirm the gut feeling (it seems like you will always be able to find some confirmatory evidence, so what’s the point?)
       4. Confirmation bias will result
       5. Ask for someone to play devil’s advocate
       6. Analyze alternative hypotheses
       7. As you gain experience you will be able to trust your gut more
       8. However the best trades happen when both are in alignment
       9. BD recommends Daniel Kahneman’s ‘Thinking Fast and Slow’
       10. He also recommends a CIA article whose link is now 404. I think it’s this though: https://www.cia.gov/static/9a5f1162f...e-Analysis.pdf

And that brings us to the start (and therefore the conclusion) of part 4.

Part 4 - Understand Yourself
Chapter 12 - Understand Position Sizing
This is now the end of part 3 as we’re moving backward through the book.

Position Size as a Percentage of Capital
BD has an interesting take on sizing positions.

1. There are 4 factors that determine position size
   1. How much free capital do you have?
   2. How confident are you on this trade?
      
      Attached Image

      
   3. How volatile is the pair?
   4. Where is your stop?

2. Over years he has come up with ‘a very simple but effective approach’
   1. BD rates it by conviction as 3, 4 or 5 stars then allocates free capital in proportion to confidence
      1. 3 Star: 1%
      2. 4 Star: 3%
      3. 5 Star: 6%

   2. Adjusted free capital is how much you can afford to lose from now until the end of the year where ‘adjusted’ means the initial free capital adjusted for year-to-date P&L
      1. If adjusted free capital is $8M and a five star trade comes along
         1. Risk $480k (8Mx0.06)
         2. The bar for a five star trade is very high and these trades are rare, maybe 10 in a year

      2. Risk amounts are always calculated based on adjusted free capital
         1. If BD could afford to lose $8M on Jan. 1 but is up $4M in the year he how has $12M in adjusted free capital
         2. If a 5-star trade comes along he will risk up to $720,000 ($12Mx0.06)

      3. Some will say 6% on a single trade is too much
         1. BD disagrees! (go for the jugular - Soros)
         2. When you see a five-star setup you need to be ‘very aggressive’
         3. You can only do this when your capital position is strong

      4. Because of leverage you are no risking 6% of total capital - just ‘free capital’ (free margin)

   3. If you have $100M capital with a 9% dd limit
      1. You can only afford to lose $9M, not $100M
      2. You would be risking 6% of $9M which is $540k - less than 1% of your total $100M capital under management

   4. Some traders use a trade-by trade risk allocation
   5. Some use a monthly system
   6. BD overlaps between the two
   7. These numbers are starting points, not absolutes
      1. Sometimes BD has risked 7% or even %10 on a trade when he was in a strong P&L position and had strong conviction
      2. This is clearly risky and you cannot be wrong many times at 10%

   8. As BD makes money his per-month and per-trade risk allocations increase; and as he loses, they decrease (Penfold)
      1. This ensures he won’t blow up. If a 5 star trade comes along when he is near his monthly stop loss, too bad

3. BD trades looser when he’s up and tighter when he’s down.
4. You want to be a call option - limited downside but unlimited upside
5. There is a time and place to go big
   1. BD says hogs don’t get slaughtered
   2. It comes down partly to preference - some traders make money with risking only 2%
   3. Being a pig means betting heavily when you are already in profit
   4. It doesn’t mean risking your job or firm on a single idea or theme
   5. Managing risk of ruin is more important than missing a big opportunity
   6. BD does not see many successful traders who just ‘chip away’ all the time
   7. Increasing risk when doing well and decreasing when struggling is ‘easy to automate with a spreadsheet’ but alas BD isn’t disclosing details

6. Save money for big opportunities
7. Different currencies have different volatility profiles
   1. Size your position according to the current pair’s volatility
   2. BD measures volatility by %age over a daily range

8. BD links to a volatility calculator which is cool; I haven’t seen it before
   1. https://www.investing.com/tools/forex-volatility-calculator

And I was wrong - he does tell us what constitutes a five star trade!

1. When multiple indicators from different branches of market analysis all point the same way you have a five star trade
2. There is no such thing as a perfect trade though
3. Stay realistic

1. Fundamentals
   1. Recent info suggests a change in fundamentals that is not fully reflected in the price

2. Cross-market signals
   1. Correlated variables are suggesting the currency pair is away from fair value
   2. More variables signalling the same thing, the better

3. Positioning
   1. Sentiment support the idea or at least doesn’t hurt it

4. Technicals
   1. Multiple levels and patterns support the idea
   2. One or two of the seven deadly setups are in play
   3. If TA doesn’t support the trade, be patient - great trades can be ruined by terrible entries

5. Gut feel
   1. Do you feel lucky, punk?
      
      Attached Image

      
   2. Well, do ya?
   3. Have a weird feeling? If you don’t feel right about a trade you will ‘trade weak’.
      1. You’ll stop out at the first sign of trouble, you weak-handed gutless punk!
      2. You’ll be nervous about random news
      3. Listen to your gut but only as ⅕ of the factors

6. Some traders would include ‘catalyst’
   1. News or upcoming event that might push the currency
   2. BD finds them overrated
   3. Currencies move when they want to and sometimes there is a catalyst and sometimes there isn’t

1. The percentages mentioned are only for one trade
   1. If you’re entering multiple trades you need to think about correlation between your overall P&L risk if all the trades go wrong
   2. BD prefers to have no more than 8% of his free capital at risk at any time
   3. 3-5% is more reasonable most of the time

2. Keep your method as simple as possible
   1. If your method is simple, risk management is simple
   2. BD rarely has more than 3-4 trades on at once, and often just one

3. If you’re a short-term trader
   1. Don’t bother thinking about risk on an individual trade basis
   2. Simply allocate 1-6% of your capital to each day depending on opportunity you see
   3. For traders who do 20-100 trades in a day
   4. Don’t forget the monthly allocation though

4. A second way for short-term trades to determine risk
   1. Different, safer, simpler for day traders
   2. Take opening free capital in the morning and multiply by 0.02
      1. Don’t lose more than this in a given day
      2. Each day you reset

   3. No monthly limits
   4. So every day you risk 2% of your free capital

5. OR risk 1% of free capital per day

“Start with row 1 (21-Apr). A is the date. B is your free capital. C is Column B times 1%. D is where you record the main theme of the day just to make it easier to remember what happened if you are curious later on. E is overnight P&L. F and G are the high and low intraday. H is the closing P&L. I and J are month to- date and year-to-date P&L. Then in the second row (24-Apr) you simply take your starting capital (500,000) and add your YTD P&L (4,400) for a new starting capital of $504,400. So you can see as the month goes on and you make money, your risk appetite increases in linear fashion. If your capital doubles, your trade size doubles.”

1. It is critical to stick to the daily or per-trade limit
2. There were two instances where the trader broke her limit twice (red cells)
   1. Either bad discipline or gap risk
   2. Highlight your own breaches the same way

Trading

The Kelly Criterion

1. Cannot be applied directly to trading
2. “The Kelly strategy will outperform every other bet size strategy in the long run, so it has become an important part of probability theory that applies to both gambling and trading.”
3. We’ve already talked about it a fair bit so I’ll skip the history and reviews
4. “If you have a good idea of your probability of winning (either on a specific trade or on a given day) and you know your average gain compared to your average loss, you can plug it into this formula:
5. % of Capital to Risk=Win% − ((1 −Win%)∕(AverageWin∕AverageLoss))”
6. Example
   1. First trading day of the year
   2. $4M starting capital
   3. 50% win rate
   4. Average winning trade is $370,000
   5. Average losing trade is $300,000 (averages obtained from 3 years of historical trading data)
   6. These figures are approximately what someone generating $10M/year at a commercial bank would expect
   7. Plugging in the numbers:
      1. % of Capital to Risk = 0.50 − ((1 − 0.50)∕(370,000∕300,000))
      2. = 9.4%

   8. 9.4% x $4M means the trader should risk $378k on their first trade of the year

7. Recall that that Kelly Crit is formulated for situations where you know the EXACT odds like flipping a coin
8. So it’s very aggressive. For this and other reasons it’s better suited to gambling than trading, says BD
9. Consider ½ Kelly or ¼ Kelly
10. BD started out with the KC for risk allocations with 3,4,5 star trades
    1. He uses less than full Kelly even for 5 star trades
    2. “because there is too much uncertainty in the probabilities and you can survive much longer if you err on the small side rather than the big side.”

11. Once you have a risk percentage you can live with, set up a spreadsheet and update your risk allowance

Determine Position Size
Is that not what we’ve been doing?

1. Imagine you are a junior FX trader at a bank
   1. Max DD is $1M
   2. You determine your daily SL should be $20k (0.02x1M)
   3. You treat each day as a separate bet

2. First question is - do you want to risk your whole day on one idea?
   1. Max of 2-3 good opportunities per day and often only one
   2. Opportunities vary with volatility, there are more when it’s higher
   3. Check VIX
   4. In this case VIX is low so we risk all $20k on this trade

3. Choose entry point and stop loss first
   1. Suppose long EURUSD at 1.2670
   2. Ideal SL is calculated at 1.2622
   3. The loss if the position is stopped out is approximately
      1. 1.2670 - 1.2622 + 2 pips of slippage = 50 pips
      2. How many Euros can we buy so that 50 pip SL = $20K
      3. 20,000/0.0050 = 4,000,000
      4. Therefore we can run a position of 4M Euros and know if we get stopped out we will lose approx. $20k

   4. Simple to set this up in a spreadsheet

4. The formula is: POSITION SIZE = ($ AT RISK) / (LOSS PER UNIT IF STOP TRIGGERS).
5. There is no other way to choose your position size, says BD!
6. Your position size should always be determined by the location of your stop, not the other way around.

Have you noticed how brilliant this chapter is? But it gets better. At the risk of being a big ol’ plagiarist I’m copying this whole section verbatim because it’s that good. Hey, maybe BD should write a book about a trader?

Here’s a good example of how incorrect position sizing can hurt you. Picture a trader who doesn’t like to lose more than $100,000 in a day. Every seasoned trader knows the scenario seen in Figure 12.2.

Not only is this a good example of position sizing done correctly, it's a great contrast between how a good trader thinks and acts, versus a bad trader. I see myself in both characters. It’s important to be more like trader 2.

Errors in Position Sizing
Traders of all experience levels make 3 common errors in position sizing

1. Positions are too big
   1. Young and aggressive traders run positions that are too big for their P&L tolerance

This chart shows how position size increases account volatility. Only a bank could ride out 50M fluctuations (from -200k to +50k) whereas a home-based retail trader could be wiped out by even 3M. Now you see some of the scale of what you’re up against. Your little maroon line looks like a calm lake on a breezeless day, whereas the bank trader can withstand a storm with perfect waves.

1. Size the position to survive the volatility without blowing up when you are wrong
2. You will be wrong a lot
3. Positions are too small
   1. Won’t blow you up but won’t cover your expenses when you are wrong
   2. This is mainly a problem for bank traders more than retail or hedge fund traders

   
   

4. Static positions
   1. It’s a mistake to always trade the same position size (though it’s often taught by broker training)
   2. Different currencies move different amounts on average
   3. It doesn’t make sense to trade a 1.2% average daily move currency and a 0.6% daily move currency with the same volume
   4. Volatility adjusting sizes positions according to volatility and the expected R:R of each trade.
   5. It also relates to your conviction

Stop Losses

1. Without a stop loss you don’t know your downside for a given day or month or on any trade
2. This introduces risk of ruin - always the number one risk to avoid

Where to put your stop loss

1. Use TA to determine the optimal stop loss and then add 20% of a day’s range as extra room
   1. Ideally there is a convergence of tops, bottoms, trendlines and other levels
   2. Then add padding to the stop to give it some room
   3. BD believes in ‘round number bias’ and so he never leaves his orders at round numbers
   4. Second derivative thinking
      1. You don’t want to put your stops where everyone is putting their stops
      2. So if you see a very obvious place to put a stop, add some extra room
      3. This is the most useful application of TA says BD - the positioning of stops

2. Second criterion is average daily range
   1. BD wants to set his stop loss at least one day’s range away from his entry point (though not always)
   2. There is too much noise in the market to use tight stops
   3. Opportunities where you can risk 10 or 20 pips are rare unless you are trading a level break or a news event
   4. There is a relationship between your stop and your time horizon
      1. Short term
         1. “you could use a standard formula of CURRENT PRICE + (1.2 X AVERAGE DAY RANGE) and that would be reasonable”

      2. Medium term
         1. CURRENT PRICE + (AVERAGE DAY RANGE X 2.5)

3. Trailing Stop losses
   1. Move your stop up as spot moves in your favour
   2. Use a 100 hour MA or another suited to your timeframe
   3. Or just move it up according to a pre-existing plan

Could not be more true.

Understand Risk/Reward

1. Your SL and TP levels should have a relationship governed by risk/reward
2. It is true that a trader that continually risks more than 2x what he earns will not be profitable in the long run
3. However it is incorrect to insist on a fixed risk/reward ratio
4. It’s acceptable to risk 100 pips to gain 100 if you believe the probability of earning the pips is greater than the probability of losing them (yes! Is this the first book writer who has stated this obvious truth?)
5. This boils down to expected value and you should Google it and do some research if you don’t know it, says BD
6. Don’t mechanically shy away from a trade just because its R:R is less than 3:1
7. “If you look at only the stop loss to take profit ratio, you are taking a one-dimensional view of a two-dimensional problem. Risk/reward is calculated not just from the relationship between the stop and the take profit but also from the estimated probability of each event.”
8. It is difficult to calculate probabilities using EV
9. Your trading journal and observations can help with data about your system
10. Trading deals with subjective, not objective probabilities (ehhh, which maybe means it deals with random stochastic probabilities?)

Rules for stop losses

1. Write them down in your journal
2. Record the level and treat it with importance
3. When you are losing you are subject to all kinds of irrational pressures
4. Don’t let the irrational mind overrule the rational one that wrote down the level
5. Don’t keep changing your stop loss level as new info comes to light
6. “DO NOT MOVE YOUR STOP LOSS LEVEL”
7. Automate the process if possible (ro-bots!)
8. Good reasons to move a stop loss
   1. Upcoming event risk
   2. Trailing to lock in profits (debatable)
   3. Risk management trigger reached

9. Bad reasons
   1. Everything else

BD makes a very interesting observation about SLs from a market-maker perspective
“Slippage on stop losses can be a source of great frustration for both market makers and speculators. This is because stop losses tend to be a no-win situation on both sides. The trader leaving the stop is unhappy by definition when the order is executed because he is getting taken out of his position. On the other side of the coin, market makers usually struggle to execute stops without losing money because stops are always on the weak side of the market and tend to come in clusters. This is known as ‘‘negative gamma,’’ which means market makers become short on the way up and long on the way down when they have stop loss orders. Nobody likes negative Gamma.

You will often see situations where a customer trader is stopped out on the buy side (and not happy with his fill) while on the sell side, the market maker has done his best for the customer and still lost money himself! Everybody loses. Keep this in mind when you leave stop loss orders and when grading your fills afterward.”

Take profits

1. Err on the side of caution
2. Don’t move them just like SLs
3. Bad reasons to move a TP
   1. ‘‘Whoa! This thing is ripping! No point taking profit yet!’’
   2. ‘‘Whew, I’m back to flat. I’ll just get out here and forget about this stupid trade.’’
   3. ‘‘I’m deep in the money here but my take profit is still another 25 pips away and we’re stalling. If it turns against me now, I’ll never forgive myself!’’

Process vs. Outcome

1. You may heard this before - the idea is simply that a process can be good even when the outcome is bad
2. If the process is good, trust it
3. The market is indifferent to you (is it though)
4. Luck is a crucial short-term factor in trading.
5. Be stoic.
6. The importance of luck drops toward zero in the long run.
7. "God doesn’t care about your trades. God will not push the market in your favor no matter how hard you pray.”

“Your biggest enemy in the market is not the central banks or other traders or hedge funds or bad luck. It’s you. All the rules in the world will not mean a thing if you do not follow them.”
BD recommends Annie Duke’s ‘Thinking in Bets’. This guy’s clearly a fellow reader!

A large and enlightening chapter from someone who clearly has some real experience. This book is exceeding my expectations as when I looked at the table of contents it seemed to be simply repeating what we find in a lot of trading books for beginners. However it could also be due to my reverse-reading, as most authors hide their best stuff at the end. Can BD keep up the pace or rather, did he keep up the pace?

Next: Understanding Free Capital

Chapter 11 - Understand Free Capital

BD begins by telling us about different ways that banks, hedge funds and individuals define ‘capital’.
However it all comes down to:

1. How much money can you afford to lose?
2. That’s your ‘free capital’
3. This section must be understood before moving on says BD
4. If you have $150k in your trading account
5. And 10x leverage
6. Is your free capital $1,500,000?
7. No. It’s $150k (but it should be much less)
8. If you are a hedge fund trader and you have $100M to manage
9. Is that your free capital?
10. No. You have a clause in your contract that forbids you from losing more than 10%.
11. So in that case your free capital is $10M
12. If you lose more than this you’ll have to find a real job and you won’t be a trader anymore. So this is more than just a matter of semantics.

Seems straightforward enough so far.

Set Goals

1. Risk management requires a clear set of goals
2. You need targets
   1. For returns
   2. For volatility

3. Targets + free capital = the amount of risk you can take for any day/month/year OR the amount you can lose before you have a problem
4. The targets will vary based on your job
   1. Budget or revenue target if you work at a bank
   2. Absolute return target in % or basis points, volatility target and Sharpe ratio if you work at a hedge fund
   3. Monthly USD P&L goal or % return if you are a retail trader

5. BD has a year goal but manages his risk and P&L on a monthly basis
6. He has tried daily and yearly chunking but daily limits fail to recognize that opportunities vary dramatically per day
7. Weekly or monthly makes the most sense for short-term traders
8. BD resets his P&L target and risk each month
   1. The target is not static it is determined by his year-to-date P&L
   2. As the P&L goes up his risk increases and as it goes down his risk decreases

9. Another way to do it is trade-by-trade
10. BD’s formula for monthly targets and stop loss:
    1. Suppose $10M is the annual goal
    2. Max dd limit (peak to trough) is $5M
    3. This is a standard setup at a bank or if you manage $100M of hedge fund capital
    4. Free capital is $5M ($10M-$5M max dd = $5M free cap)
    5. So January SL will be 10% of $5M or $500k
    6. January P&L target will 2x his stop loss so $1M

11. This goal is adjusted depending on how the year goes
12. Resetting monthly allows you to shed emotions related to the prior month and gives a fresh outlook
13. Suppose BD makes $2M in January
    1. Free capital for the remaining 11 months is now $7M ($5M + $2M)
    2. BD can now risk $700k in February
    3. P&L target for February is $1.4M (2x700,000)
    4. Risk increases when he is winning and decreases when he is losing

14. Therefore the formula is:
    1. Free capital X 10% = January stop loss
    2. Stop loss × 2 = Take profit objective
    3. In each subsequent month:
       1. (Free capital at start of month) X 10% = Stop loss for the month
       2. Note (Free capital at start of month) = (Free capital at start of year + YTD P&L)
       3. Stop loss X 2 = Take profit objective

15. If BD hits his monthly SL he stops trading for the month and waits for the new month rollover. This allows a mental reset and forces him to take his foot off the gas when things are going poorly
16. If he reaches his target he also slows down so as to protect his successful gains for the month
17. Most traders don’t have a money-making problem, they have a money-keeping problem
18. Some model funds make allowance for reversion in returns so if the model is over-earning it will pullback in anticipation
19. BD addresses the fact that a monthly chunking creates an arbitrary break in the risk since the risk traded on the 31st of the month won’t be continuous with that traded on the 1st of the next month
    1. Yes, it’s true
    2. The benefits, psychological and process-related outweigh the negatives
    3. Also, opportunities tend to cluster near the start and end of the month for most traders (really??) “given the distribution of economic data and central bank meetings.” (that seems like the kind of thing that would reveal itself in price data)

Track and analyze your P&L

1. Simpler is better

Daily P&L

1. Spreadsheet
2. Enter open, high low and closing P&L for each trading day
3. Open is the overnight P&L. if you weren’t holding any positions the amount is zero.
4. High and low allow you to track volatility of P&L
5. Close is the total end of day P&L
6. Add columns for each product you trade
7. BD doesn’t track per currency but separates options, commodities, interest rates
8. His core interest is G10 spot fx
9. Every six months
   1. Ask how does the high compare to the low?
   2. Upside volatility should be higher than downside volatility
   3. If there are many days where you are down but then recover to flat that might mean you are being too aggressive in the morning and need to wait for better opportunities later in the day
   4. Or conversely, if it’s the opposite pattern, you might be too loose after being up for the day
   5. Markets tend to mean revert intraday
      1. So the pattern you’ll see is there is a level where the HIGH tends to peak before reversing and closing lower in the day

      
      

   6. The other reason for a profit peak is that average daily volatility has a rough limit which when combined with your position size limits your profit for any day
   7. So in BD’s case if he is trading an avg position size of $100M and intraday moves max out around 1% your peak will be around $1M.
   8. So you can use this knowledge to reduce risk as you reach your intraday high-water mark.

   
   

Create a chart of your daily and YTD data

1. The daily bars (gray) show the trader only wins about ½ the time but the average wins are bigger than the average losses. This is how you achieve a strong performance while having essentially random wins.
2. The dabbling trades show up as consolidation while the big bursts in profit are from high-conviction ideas with big positions. A few bursts of ‘in the zone’ trading account for most of the year’s profit. Some traders are more and some less consistent than this. Make hay while the sun shines.
3. The flat lines are from when the trader was on vacation. A healthy practice.

Month-to-date P&L

1. Can you make money most months?
2. Are your good months much better than your bad months?
3. Daily performance is random and determined by luck
4. Monthly performance is skill

YTD P&L

1. The ultimate measure of your performance.
2. Most people cannot survive more than 2-3 bad years before going bust or losing their jobs
3. Be like a call option
   1. Bad years are flat or ‘down small’
   2. Good years are up or ‘up big’
   3. This is the payoff profile hedge fund managers are looking for

Win%

1. Number of days you make money divided by the number of days you trade
2. Most traders are in 45-60% win area
3. Bank traders with good ‘franchise books’ can hit as high as 80%
4. Those who ‘chip away’ and trade tactically will have high win rates
5. Those who go all in on big opportunities and stay flat most of the time will have smaller win %

Average Gain/Loss

1. Ultimate success is a combination of win% and avg gain/loss ratio
2. Generally traders with higher win% have shorter holding periods and smaller gain/loss
3. There is no correct ratio but you should know how they’re evolving
4. If gain/loss is falling month after month you’re probably cutting winners too early or riding losers too long
5. Big up days and small down days are the key to success in trading
6. After you have a decent amount of data about your own trading, analyze it to find improvements
   1. BD noticed he was not always sticking to his original plan and exiting before his TP was hit
   2. This is tricky as a reversal after being up 80% looks bad (and feels bad too)
   3. If you take profit too early consistently then you aren’t meeting your risk/reward
   4. By discovering and fixing his own leak he improved his gain/loss ratio

   
   

A system will be profitable if its win-rate is larger than the percentage of “(average loss) / (average loss + average gain)” …

Sharpe Ratio

1. Commonly used performance measure
2. Measures relationship between volatility and returns
3. The idea is if an investor can get the same return from two different investments it’s preferable to invest in the one with lower volatility
4. formula for Sharpe Ratio is: (Return - risk-free rate / Standard deviation)
5. Higher ratios are better
   1. Above 1.0 is good
   2. Above 2.0 is outstanding
   3. Some humans can sustain over 4.0 for some periods
   4. This measure isn’t the end-all be-all
   5. A strategy with a built-in flaw, like someone who sells S&P500 puts or VIX futures, will have a good Sharpe ratio (trend-biased as it is) but when volatility spikes they will blow up
   6. The Sharpe ratio can hide non-normal distribution of returns
   7. Market-making can distort the Sharpe and make it meaningless

Fat Tails and Risk of Ruin

1. Tail risk is not always captured by conventional risk analysis like a Sharpe ratio
2. It can lead to ruin
3. Avoiding ruin is the trader’s first concern. Live to fight another day.
4. The 2015 SNB CHF peg removal incident is cited as a type of tail risk
   1. The SNB members had continually messaged their commitment to the floor level of the peg
   2. Many traders simply assumed a default long position. Some traders (like BD) had reservations but thought the risk was remote
   3. Without warning the SNB removed the floor and the bottom fell out, ruining many traders, and some banks.
   4. Anything can happen
   5. Don’t blow up
   6. “Sure, there was profit to be made trading long EURCHF for several years, but the problem was that while the rewards were clear, the risks were not measurable. Many people expected that if 1.20 broke, they would be able to sell their EURCHF at 1.15 or maybe 1.12 as a worst case. Instead, the first trades were around 1.0100 and the pair quickly traded down to 0.8500 within minutes!”
   7. BD tells us to avoid anything with ‘discontinuous gap risk’ but you can never really know for sure. Reasons are always found in hindsight which is the only 20/20 vision.

BD notes that big tail risks seem to be increasing in recent years. This seems contrary to the general reduction of currency volatility. Though BD says it hasn’t changed you can see it’s in a downward trend at the moment.


So what has changed in FX since 2008?

1. Trading is becoming automated. Senior trader numbers have dropped.
2. Electronic trading is 60% of the market. Algo trading rose since 2000. Many market-making algos are price makers in slow markets and price takers in fast markets. This can create feedback loops and generate ‘negative convexity’. The algos may not react rationally when things get crazy.
3. Order slicing/hiding has left fewer resting orders away from top of book. Pre-2007, most orders left on ECNs showed full size and trader interest. Now, most orders are sliced into the tiniest possible increment or show nothing to the market and wait only to aggress others’ liquidity. Many trading algorithms sense aggression or velocity in the market and pull back or cancel at the moment that liquidity is needed most. All this means fewer truly firm orders in the market.
4. Central bank pegs, bands, caps, floors lead to stability at first but instability later. Stability breeds instability. When policymaker intervention stops they tend to equilibrium once intervention stops.
5. There are fewer strong hands on the buy side. Hedge funds doubled from 2003-2007. They operate with similar strategies and place similar stops. By chasing momentum and targeting volatility they add to fat tail risk.

Lesson: “in a world where many humans and algorithms are running similar strategies at higher and higher speeds, there are bound to be some accidents.”
Advice: “Get used to it.”

Rolling Drawdown

1. Along with Sortino ratio this provides a visual representation of your downside volatility over time
2. Contrast this with Sharpe which shows upside and downside volatility
3. Create a chart of your current P&L minus your YTD high P&L and this will show your rolling dd from peak

P&L by Time of Day

1. BD used to gather this info by updating a spreadsheet every 30 minutes!
2. Doing this automatically is obviously better
3. He noticed his P&L rose from 7:00AM and peaked around 11:00 AM and then gradually declined.
4. After London goes home, things die down
5. He did his best to reduce risk around 11:00AM
6. Use the afternoon for research, exercise, etc

1. Be thoughtful about the data you collect

Keeping a Trading Journal

1. Not just for noobs. Pros use it too
2. Write your plan - make it concrete instead of fuzzy
3. Auto-analysis can improve your game

Another chapter of pure gold.