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Let’s reframe the question: can You be a top pro athlete while having a 9 to 5 job?

 

Automated trading is the hardest discipline

Automated trading is by far the hardest way to trade. If You think of the markets as driving a Formula 1, then automated trading is being in the cockpit without a steering wheel, brakes or accelerator, only adult size diapers.

Think about it logically:

  1. You compete against people who stare at the screen all day long. They can intervene anytime. Your algo will not.
  2. You need to have considered all contingencies. Things will go wrong. Rather than adding complexity, special cases and all kinds of savant fragility, You need to reach the essence of simplicity. It took Picasso 30 years to draw a face in three lines
  3. False positives: eyeballing charts in hindsight is one thing, getting the algo to distinguish false from true positives is another
  4. Time heals everything, after the fact. People who have not thought their system through usually default to longer timeframes. In hindsight, it does work. In practice, everyone is an investor until they lose 20%

Trading is a business

If You treat it as a hobby, remember that You compete against people who treat it as a business. Only a small elite survives. So, as a part-time trader, how do You expect to beat those who have devoted their lives to the craft?

This post originally comes from a question asked on Quora

How many people saw the financial crisis coming and profited from it?

2007 Christmas party at a dear Friend’s apartment in Azabu, Tokyo. He was the head of MacQuarie securities in Tokyo. Champagne was flowing and i was passably drunk. There was a bunch of Lehman, Morgan Stanley, Citi and other dudes, all smart articulate people.

They were talking about the current uncertainty saying it was an opportunity to buy on dips. I rolled in saying this would be the first time sh!t was about to flow uphill. All those delinquent loans would not end well. The two things that people buy on credit are homes and cars. If home loans turn delinquent, then the rest would follow, contagion. I happened to be tracking Japanese car manufacturers US car sales and watched them plummeting. They laughed at me and concluded that i was a drunken lunatic. Point taken…

1 year down the road, December 2008 same party, half the people. The Lehman dudes were gone or at Nomura. One of the guys ran up to me. I was about to duck and hit the floor as if chased by the police: “no

-“No i don’t do drugs anymore, no i did not do your wife, no i didn’t steal anything, you got the wrong guy” routine. He shook my hand and said:

-“You are the only one who saw it coming and had the courage to speak up. Whatever You say i do. What should i do now?”

-“Really?”, i said. “I don’t remember. I might have been seriously drunk”

-“You were a little more than tipsy, but you were funny and more importantly you were right”, he said

I had correctly predicted the crash, and was too drunk to even remember it. Sounds about right:

-“Hmm, Plausible”, i answered. “Alright, so buy when monetary authorities roll out the big guns”,  i said.

-“OK, but Buy what then?”

-“Come on, do i really look like i know? Seriously? Monetary authorities are panicking. They are about to roll out the mother of all monetary bazookas. So, it does not matter what you buy, everything will rally”

-“Yeah, right. You are drunk again” and he walked away

He did not buy and I should have followed my own advice. I gave back a lot of performance in the 2009 rally. I insisted on shorting cyclical stuff when i should have shorted defensives. I was stubborn. I stopped trying to make predictions shortly thereafter.

Now, the implicit question is probably: are we in the same situation now? I don’t know and frankly, it really does not matter. I looked at my forecasting accuracy stats and concluded i should not be in the forecasting business anymore. Not encouraging for the rest of the industry considering i foresaw the crash and the ensuing recovery.

These are the main lessons:

Don’ts:

  1. predict the next crash: you will sell too early. It is as useful as forecasting when you are going to get sick. Only hypochondriacs check themselves in hospitals before they get sick. Don’t listen to those market hypochondriacs telling you the mother of all bear markets is around the corner.
  2. Focus on why: what matters more? Why you got cancer or how to cure it?
  3. Duration and depth: when it happened, sell-side “quants” rolled out average duration tables. On average bear markets last for xx months. If You are sick, what would you think of a doctor who would say You will have 39,8 C fever and you will heal in 3 weeks 2 days, 17 hours?

Dos:

  1. Recognise when it is there: build a system that tells you now it is time to sell and go short. To identify the top, use my floor ceiling method. It works objectively after the fact. Laurent Bernut’s answer to What is the most precise way to draw support and resistance lines for forex trading?
  2. Recognise when it is gone: Everyone got terminally beared up at the end of the bear market. They all, me included, missed the rally. Those who said they bought in March 2009 are like descendants of the Mayflower: deluded liars. To identify the bottom, use my floor ceiling method. It works objectively after the fact
  3. Have a bear market plan: bear markets are notoriously stressful. Not the brightest idea to devise an emergency exit plan when the building is on fire

Is short selling bad for your psyche?

Is short selling bad for your psyche? by Laurent Bernut

Answer by Laurent Bernut:

“Lo que no mata engorda”, what does not kill you makes you fat. Bob Baerker, a respected short-seller, sums it well.

You are probably alluding to the good and evil battle between the righteous short seller who perceives wrong, the arrogant and corrupt management who falsify their financial statements and price that stubbornly goes up until the final collapse.

Fairness will kill You

Fairness is one of the very few built-in traits in humans. Numerous studies have been conducted on fairness in toddlers. It appears that our sense of fairness predates our language. Even children who turned out to exhibit clinical psychopathic tendencies, dysfunctional amygdala, react to fairness.

So, as short sellers, every now and then, we are tempted to right the wrongs. We engage in a duel with companies and the multitude who buy into the frenzy. One sane mind against a raging mob is still an unfair fight.

A simple advice is to wait until the mob has changed side and starts liquidating its position. You will be vindicated.

Short selling: the spinal tap of investing

Stress volume always at 11

In spinal tap, they can turn the volume at 11. On the short side, stress volume is always at 11, even when it works in your favor. In that sense, short selling is corrosive for your psyche until You learn to manage stress.

It takes time to get there but here are a few techniques that will help You:

  1. Plan your exits: the short side is a bumpy ride. I used to maintain between 40 to 60 shorts at all time. That’s a lot of bumps. It all changed when i set up hard exit rules. Having hard rules for exit is a tenfold reduction in stress. All my Long Only colleagues were glued to the newsfeed to guess what to do next. Meanwhile, as nothing flared up, i was left watching spiritually awakening and highly educational content on Youtube
    1. partial exit: take risk off the table as a short squeeze starts. No-one knows how far price will retrace and gains evaporate, so reduce size
    2. stop loss: never enter a short w/o a stop loss. Never override stop loss. No exception
    3. reversal: there are quite a few false positives. Sometimes, shorts turn into Longs before they trigger a stop loss. Do not ignore what the market is telling you. Market is right, or it can afford to stay wrong, you can’t
  2. Quantify your risk: risk is not a story in the US, China or wherever. Risk is a budget: how much you can afford to lose and keep trading. Accept you could lose that much because:
    1. This is called pre-mortem. It actually releases endorphine and facilitate recovery. The quicker you can put a bad trade behind you, the quicker you can focus on the next one
    2. More often than not, you will lose. Quantification helps you get better at money management
  3. Practice mindfulness: every other spiritual guru talks about mindfulness. In its simplest form, it is the ability to observe what is happening without being sucked into the emotional roller coaster
  4. Welcome to the dark side: the short side will test the darkest corners of your psyche. It will go and elicit fears so deep you did not know you had them. Great, fear dissolves when exposed. I used to journal fears and work through them using Byron Katie’s The Work. Van Tharp recycled this in his fantastic “trading beyond the matrix”. Fear elicitation is a great tool to help you work through your subconscious phobias.

Conclusion

Viktor Frankl, who happened to have survived Auschwitz and Birkenau, said between stimuli and response there is something called freedom. You have the choice of how you will respond. So, fear happens, losses mount. How you choose to deal with them is your path to emotional freedom

Is short selling bad for your psyche?

#Quora: How does one address the issue of regime shift in algorithmic trading?

How does one address the issue of regime shift in algorithmic trading? by Laurent Bernut

Answer by Laurent Bernut:change-of-season

Fascinating topic that has kept me awake for years. It is a thorny issue. As the patent clerk Einstein used to say: answer are not at the same level as questions. Answer is not at the signal (entry/exit) level. These are position sizing and order management issues.

Definition of regime change

Everybody has a savant definition, so i might as well come up with a simple practical metaphor. imagine You drive at 150 km/h on the highway and then all of sudden, this 4 lanes turns into a country road. If You do not react quick, you will go tree-hugging.

There are three market types: bull, bear and more importantly sideways. Each type can be subdivided into quiet or choppy. So, we have six sextants. Regime change is when market moves from one box to another.

It can be either a new volatility regime, or a move from bear to sideways, sideways to bull or vice versa. Markets rarely move from bull to bear. There is some battle between good and evil.

Why it matters?

Many strategies are designed to do well in a particular environment. They make a lot of money that they end up giving back when regime changes. Examples:

  1. Short Gamma OTM: sell OTM options and collect premium. Pick pennies in front of a steam roller. 2008–2009, August 2015, CHF depeg, Brexit etc. 1 day those options will go in the money and game over
  2. Dual momentum: trade the shorter time frame but determine regime on longer time frame. When market hits a sideways period, market participants get clobbered on false breakouts like poor cute little baby seals
  3. Mean reversion: works wonders in sideways markets until it does not. An extreme version of that is Short Gamma
  4. Value to growth and vice versa: that is probably the most lagging one. By the time, my value colleagues had thrown the towel and loaded up on growthy stocks, market usually gave signs of fatigue…
  5. Fundamentals pairs trading: relationships are stable until market rotation. For instance, speculative stocks rally hard in the early stage of a bull market, while quality trails. Example: Oct-Dec 2012, Mazda went up +400% while Toyota rallied +30%

The vast majority of market participants are trend followers, whether it is news flow, earning momentum, technical analysis. Trending bulls they do great, trending bears, they can survive. Sideways is where they lose their shirts on false positives.

The issue often boils down to how to enter a sideways regime without losing your shirt

The value of backtests

I agree that backtests will help you identify when your strategy does not work. This is actually the real value of backtest. This is when you modify the strategy and adapt the position sizing to weather unsavoury regimes. Then trade this version, not the ideal fair weather strategy.

Reason is simple: everybody’s got a plan until they get punched in the teeth. So don’t lower your guard, ever.

Asset allocation across multi-strats

Some market participants like to develop specific strategies for specific markets: sideways volatile, awesome for pairs trading, great for options strangle/straddle short. Breakouts are good for trending markets etc.

How do You switch from one to the next ? Fixed asset allocation is as clunky, as primitive and as MPT as it gets. There is something far more elegant and simple:

  1. Calculate trading edge for each sub-strategy: long Trend Following, pairs etc
  2. pro-rate trading edge for each strategy
  3. Allocate by pro-rata
  4. Allocate a residual minimum even to the negative trading edge strategies

This is a simple way to put money where it works best

Regime change for single strategy

When not to trade

Van Tharp believes that there is no strategy that can do well or at least to weather all market conditions. I believe there is more nuance. Is the objective to make money across all market regimes? For example, sideways quiet are preludes to explosive movements. In order to make any money, you need to trade big and if you are on the wrong side when things kick off, game over

We trade a single unified (mean reversion within trend following) strategy. What follows is our journey through solving the regime change issue. We found that the three best ways to manage regime changes are

  1. Stop Loss:
  2. position sizing:
  3. order management:

Stop Loss

Regime changes are usually accompanied with rise in volatility. Volatility is not risk, volatility is uncertainty #de-friendSharpeRatio

We used to have a complex stop loss rule. Now we have a uniform elegant stop loss. It just lags current position. It is fashionably late, hence its name: French Stop Loss.

The idea there is to give enough breathing room to the markets to absorb changes without giving back too much profit.

Our solution is to consider stop loss as a fail safe and allow the market to switch direction bull to bear and vice versa within the confine of a stop loss.

The result is we end up switching from one regime to the next more fluidly. We have reduced the number of stop losses by 2/3, which in turn has materially increased our expectancy.

Stop losses are costly. They are the maximum you can lose out of any position.So, unless you have a kick ass win rate or extremely long right tail, you want to reduce their frequency and allow the market to transition.

Position sizing

The first thing You need to understand is that You cannot predict/anticipate a regime forecast. You will find out after the facts. This has some immediate consequences on position sizing: always cap your portfolio risk

Many position sizing algorithms use equity in layers or staircase. We base our calculation of peak equity. So, drawdowns however small have an immediate impact on position sizing. This slams the break much faster than any other method i know.

The other side of the equation is risk per trade wich oscillates between min and max risk. When regime becomes favourable again, it accelerates rapidly.

The whole premise is early response to change in regime through position sizing

Another feature is trend maturity. Betting the same -1% at the beginning and at the end of a trend is asking for a serious kick in the money maker. Trends are born, grow, mature, get old and eventually die one day, just like believers in Efficient Market Theory. So, risk less as you pyramid.

Order management and hibernation

Along with the position sizing comes a vastly underrated feature in most order management: trade rejection.

Secondly, we use a position size threshold. When markets get too volatile and we experience some drawdown, stop losses dilate. As a result, position sizes get smaller. When sizes are too small, trades get rejected.

Order management is vastly under-utilised in most systems i have seen. It is often binary, all-in/all-out, or one way scale in or scale out.

In our system, taking profit off the table is a not a function of chart, technical analysis but driven by risk management. Until price goes a certain distance, exits are not triggered. If exits are not triggered, entries cannot be triggered either. Since volatility goes up and position sizes get smaller, the system drops into hibernation.

We have factual evidence that hibernation during an unfavourable regime is a powerful mechanism to weather regime change. It involves a lot more sophistication than muting indicators, slope flattening etc. It encompasses position sizing, order management, stop loss and to a lesser degree signals.

Conclusion

Multi-strat asset allocation based on pro-rated trading edge is the easy way to go.

Single strat across multiple market regimes means acceleration/deceleration but also hibernation. This is not an easy problem. There is one thought that kept me going through the frustration of figuring this out: “Building a system is like watch making. Time will always be off until the final cog fits in”

How does one address the issue of regime shift in algorithmic trading?

#Quora: How can Renaissance Technologies make so much money from financial markets by hiring scientists/mathematicians with no domain knowledge o…

How can Renaissance Technologies make so much money from financial markets by hiring scientists/m… by Laurent Bernut

Answer by Laurent Bernut:

I have never worked at Renaissance, so please take my answer with a grain of salt, but here is a first hand story that could shed some light.

Red OctoberOn June 22nd in NYC, my colleague, who is also ex-US Department of Defense consultant and myself, met with one of the foremost US experts on sonar detection (good luck finding him on Facebook, LinkedIn). He is a physicist with multiple PHDs, geeky funny. His expertise is signal processing. He is the real “Hunt for Red October”.

It was one of the most refreshing experiences ever. He explained his world. I explained mine. Cotes de Provence Rose, beer and wild berry Zinfandel helping, we tumbled down the rabbit hole talking even about epistemology, the philosophy behind math.

His world, signal processing, bears uncanny resemblances with ours. We explored Bayesian probabilistic determinism, which models (Gauss, Poisson etc) to apply to distributions, the cost of false positives (think trading edge), arbitrage between time and action with sparse data (confirmation). We spoke the same language. We were talking real problems: how do distinguish signal from the noise ? How fast ? What is the cost of being wrong ? What is the cost of being right ? Which statistical law applies to randomness ?

We entered a massive time distortion. We started around 2 pm and a couple of bottles down the road, but then after what seemed like 5 minutes, we were hungry. It was 10 pm. We could have gone on forever (*)

Compare this with glorified journalists, otherwise referred to as fundamental analysts.

  • “This is fairly valued”… life is unfair darling, so do you really think markets are fair ?
  • “On a sum of the parts valuation”… Frank N. Stein zombie valuation
  • “Fundamentals are strong”… Make fundamentals great again…
  • “Long term story is still intact”… Some HF reality TV celeb says that about Valeant by the way…
  • “On a DCF basis, our target price is +10% above current market valuation” … stop tinkering the terminal value to rationalise your subjective views
  • “i think there is 80% chance that” … bad arithmetic meets emotional roller coaster
  • “top quality management” … was also said about Enron, Bear Sterns, Kodak, GM, Chrysler, Valeant

Too much B/S bingo, too much theory,

Bottom line: “In theory, theory and practice are the same. In practice, they are not”. Yogi Berra, Yankee philosopher

Physicists approach the markets as a statistical problem. This is practical.

MBAs have too much untested theories in their head. It is costly and time consuming to unlearn all that junk.

 

(*) There is no way i could ever afford someone of that caliber; he charges something the size of Liberia’s national deficit per hour. But, he wants to send his granddaughter to Mars and he thinks our algo could be the right fuel, so we invited him to have fun with us. Maybe good guys do not always finish last…

How can Renaissance Technologies make so much money from financial markets by hiring scientists/mathematicians with no domain knowledge o…

@Quora: What is the point of hedging a portfolio instead of closing losing positions?

My answer to What is the point of hedging a portfolio instead of closing losing positions?

Answer by Laurent Bernut:

It seems like You are experiencing pain right now. This is clouding your judgment. So, let&s do a step-by-step approach’ 1. Emotional relief, 2. Boundaries, 3. Recovery 4. New rules

1. Emotional and Financial capitals: forgiveness and dissociation

You can recover from financial losses over time, as long as You recover from emotional losses. So, We need to get out of your emotional pain first.

The power of forgiveness

Village PeopleForgive yourself for losing money. Make peace with yourself. You made a bad a decision. It is alright.  In Jungian archetypes, this is called re-parenting the orphan. You soothe yourself as if You were soothing your child who got hurt. This is no new age fell good stuff: i am a professional short seller, not a cat lady.

There is solid academic research that links forgiveness and learning ability. Bottom line, if You beat yourself up, You create trauma and are statistically more prone to relapse. The Village People masculine approach  to taking losses like a man  may result in storing memories in the hippocampus (trauma, pain), rather than the pre-frontal cortex learning centre.

Dissociation

No problem can be solved at the level it was created“, Albert Einstein, patent clerk

This is a cool jedi trick. Put yourself in the shoes of someone You respect for her investing/trading skills. Really feel being that person. How would she react ? Would she be calm, composed ? Would she have slow or fast breathing ? Try to emulate this person both physically and mentally.

While You do that, exhale twice as long as You inhale, and widen your vision from tunnel to peripheral, look up a bit.

When You have impersonated this person, ask yourself how would this person solve the problem ? Take a pen a paper and write it down. Do not commit to memory. The chemical reconstruct we call memories are highly fickle and inaccurate.

This is a powerful exercise that frees up some mental bandwidth. Stress triggers the fight flight syndrome. This hijacks the prefrontal cortex and hijacks the thinking brain. This exercise frees up mental bandwidth. Practice often and You will be the iceman on the trading desk

2. Set boundaries

Mad Max

“Hope is a mistake”

Hope is a mistake“, Mad Max, Aussie philosopher

If You ask this question, it is probably because You thought this “soft patch” would go away and You would be back on happy street in no time. You ignored the signals and You got caught in a storm with a t-shirt, didn’t You ?

Stock repair strategies as we use in options world never really do the job properly and they cost a lost of mental capital. Bad idea. Same applies to your situation.

You were probably optimistic and failed to think about stop loss. You probably don’t believe in them and may buy into the “buy and hope” fairy tale. Well, the best car in the world would not even sell 1 unit if it did not have good brakes.

At this stage, You will have to decide a NUMBER of the loss You can afford to sustain. Not maximum pain, just how much can You afford to lose so that You can recover within 6 months ? Repeat the exercise and stretch the time horizon, 1 year, 2 years 3 years, 5 years etc. Stop when You come to the same number at various intervals. Focus on the recovery period.

This neat jedi trick invokes the “future self” and reframing: it focuses on recovery as opposed to pain.

Write that number down and commit now to liquidating everything if your losses reach that point. No negotiation, no investment committee, just out

The way to make it more acceptable is to tell yourself being right means following a process, being profitable is an outcome, not a process thought.

3. Recovery: two certainties in life: death and short squeezes

“There are unknown unknowns”, Great War Criminal

There is no way to tell how long a bear market will last. Forget about the talking heads, They did not see the bear coming, so they probably won’t see it go either

One rule of thumb about hedging: it gets expensive during sell off, so be patient. Wait for a squeeze to hedge. They come once a month. Politicians feel compelled to flap their mouth at regular intervals during bear markets… So, don’t worry, someone is coming.

When short squeeze comes do this:

  1. Reduce your exposure: reduce size of positions that stress You the most. Reduce until You can sleep if You are not mathematically inclined. You have to do it, it is part of hedging
  2. The smart way to reduce risk is to sell call against your holdings: You collect premium and reduce exposure
  3. Do not trade VIX options to hedge: this is for losers, amateurs and TV talking heads
  4. Long put spread: skew changes marginally during squeezes. So, this is time to put on put spreads. Put spreads are volatility structures that will make money if the markets fall between a ceiling and a floor. Risk is capped and so is profit potential. It is not very risky
  5. Don’t waste time looking for the golden fleece of safe asset class that does well in bear markets: The only asset class that fits this profile is cash.
  6. Avoid short selling yourself, delegate: short selling requires a level of skills that takes time and practice to mature. You should delegate this to a professional short selling manager.
  7. Be careful with selling index futures: Shorting S&P futures while being Long small caps it not a hedge. You are implicitly Long small caps and short large caps. Large caps fare better in bear markets, small caps get crushed. So, this feeling of being hedged is illusory at best

4. New rules

The best time to repair the rof is when the sun is shining“, JFK, Great XXth mystery

Hedging is like swimming lessons, It is a bad idea to think about taking swimming lessons when You are drowning.

The market is a joint venture between Murphy and Marcelus Wallace. Murphy makes sure that if something goes wrong it will. Then, Marcellus gets medieval on your a@#.

Bottom line: be prepared. Decide your hedging strategy before you put on a trade.

The best advice about position sizing I can ever give is: size your position not thinking how much you could make, but expecting them to fail and how much You can afford to lose.

What is better in the end, earning a little less than You could, or losing a lot more than You should ?

Good luck, and practice the first two mental exercises. May the force be with You


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What is the point of hedging a portfolio instead of closing losing positions?

@Quora: How do i improve the sharpe ratio of my trading strategy?

My answer to How do i improve the sharpe ratio of my trading strategy?

Answer by Laurent Bernut:

Reverse engineering Sharpe ratio is the trademark of some very large shops, with a large pension fund clientele… Like diet, it is simple in theory but not easy in practice.

How to boost Your Sharpe

The basic idea is to generate consistent returns however puny and then magnify them through leverage. Here is how it is done step by step:

  1. Collapse volatility: only one way to do it, collapse net exposure (Long -Short market value) to a band +/-10%. That is tantamount to market neutral. Few strategies can achieve this.
    1. The most common way is pairs-trading. This has built-in market neutrality, but some unpleasant side effects such underwhelming returns and left tail risk
    2. Another way to achieve low net exposure is to run series not on absolute but prices relative to the benchmark. The long book outperforms while the short book underperforms. It then becomes a matter of controlling net exposure. This reduces the correlation risk
  2. Generate low volatility consistent returns: returns can be nanoscopic, it does not matter, as long as they are positive. Consistency matters more than quantity because the denominator is a function of volatility of returns , i-e consistency
  3. Leverage up: if your net exposure is +/-10% and your returns are consistently positive, then You happen to have a low 54d10607d7130_-_pufferfish-bdb80n-deapparent risk profile. So, your prime broker will be willing to extend your leverage. Now, if you clock +0.20% at 200% gross exposure and your PB accepts to lend 4 times, you could wake up with consistent +0.80% per month. times 12 and before You know You will be on the cover of magazines

Limitations:

  1. Very important: Read this Sharpe ratio: the right mathematical answer to the wrong question by Laurent Bernut on Posts
  2. Pairs trading has a nasty side-effect that few people are aware of. It is essentially a mean reverting strategy. It works very well until it blows-up. It does not need to blow up “a la LTCM”. It takes a loss of 3-4% in one month and a full year to recover
  3. Most market participants do not understand Sharpe ratio. They assimilate volatility and risk. Volatility is an expression of uncertainty. Risky strategies are not necessarily volatile, they have open ended risk like short Gamma strategies

Conclusion

Sharpe ratio is part of the Modern portfolio theory package. This dates back to one of the major crimes against humanity of the otherwise barbaric XXth century: the year the US army drafted Elvis. Doctors prescribed pregnant  to smoke cigarettes to calm anxiety back then… Maybe it is time we upgraded our repertoire

How do i improve the sharpe ratio of my trading strategy?

Better System Trader: Questions from the audience

These are questions from the audience on the Better System Trader podcast with Andrew Swanscott. I am honored and humbled by the interest of listeners. We did not have time to cover all questions, so here are some written answers. If You have questions, please feel free to ask

Trading Psychology

From: Jim

The mind plays tricks on us, even with a successful system, as a system trader, what methods to use for the mental part of the system trading?  So meditation, journaling but how to implement them in one overall plan?

EXCELLENT QUESTION: Part 2 of the book will focus on this

  1. You cannot trust your mind. Michael Gazzanikas 1964 split brain theory. Self-deception: (Daniel Goleman) is a built-in feature. It happens automatically and covers its own tracks and designed to deceive us.
  2. Accountability: simple exercise to test validity of prediction and convince us we are unable to predict.
  3. Reframe from outcome to process: develop a system, account for signals generation and be honest about signal execution
  4. Daily market journal: write what You think markets, thoughts, things that happen, small comments, ideas, formulas. Do the James Altucher method: keep a moleskin with You at all times. Deliberate practice: activates the Default Modal Network (Olivia Fox Cabane)
  5. Write about the thoughts that cross your mind:
    1. dreams and aspirations when making money, why You keep doing that, why You like it. How does it manifest in the body
    2. fears, pains, detail, reflexes (ex: read the press, look for expert opinions): be specific and commit to writing or dictating. Very important
  6. Walk through your fears: meditate and manifest your fears. Seneca was history’s first investment banker. He also happened to be the founder of stoicism school of philosophy. He advocated one day a month of living frugally as a form of inoculation.

Another post on the topic:

From: @trader1970

So far as a Trader what is the biggest fear that you have not been able to overcome?  How do you manage this situation?

  • My father had a hemiplegia (brain stroke) when i was 7. He never regained motor skills and speech ability. We fell into severe poverty. As a result, I have a deep seated fear of becoming handicapped and not being able to feed my family anymore. Personal and vulnerable. Markets related fears I can deal with, I am a short seller, this is a versatile skill
  • How does it manifest itself in trading:
    1. Diversify sources of revenue: we have a real estate business that generates enough to cover our primary needs. That provides peace of mind. My family is safe from harm
    2. Frugal lifestyle
    3. Systematically take less risk: when making sizing arbitrage ask yourself, would You be satisfied with earning a little less than You could or losing a lot more than You should ?

 

Position sizing

From: Bass

Tell us more about risk management, Volatility based Stops and position sizing.

  • It really depends on your customers: Investors are like teenage girls: Teenage girls say they want a nice guy and they fall for bad boys. Investors say they want returns but they react to drawdowns:
    1. Magnitude: never lose than what investors are willing to tolerate
    2. Frequency: never be the last person investors think about before going to sleep
    3. Period of recovery: never test the patience of investors
  • Risk is not a story, risk is a hard number: it manifests itself in individual trade risk per trade (RPT), in aggregates exposures. Example: Long small caps / short futures is synthetically residually Long large caps as the index is primarily composed of large caps
  • Volatility stops: swings +/- 3 ATR. Volatility is as welcome as Kanye West at an award ceremony. Bad news, volatility is like Monsieur Kardashian bad manners: it is here to stay. Your job is to ride it and the way to do so is position sizing. For example, biotech and internet stocks are more volatile than department stores for example. So, size them accordingly.
  • used in position sizing. Rank trades by size (bigger first) so as to go for better volatility signature

 

From: Derek

Hi Laurent,

I have been following your website ASC for quite some time and also your answers on quora. I have something related to an answer you had to a quora question In investments, does more risk really equal more return, in the long haul? Your answer immediately clicked with me and it logically made sense to me. Laurent – you may want to quickly summarize what the answer was before we move on to the next part of the question. I’ll ask you what the answer was.

 Would you please elaborate on your convex position sizing method for a risk per trade and draw down module. This was discussed as an answer on Quora. I understand that as you make money you will allocate a larger risk budget using a convex surface with a max risk budget of -0.30. But i do not understand the reverse side of this, the draw down part.  As we get more draw down we should decrease our risk budget again using a convex surface. It starts at 100 and bottoms out at around 35. I do not understand how that part works.

 Also how did you come up with this method? Can you give a practical example of when you used this both for drawdown and additional risk scenarios?

Thank you very much

Derek

Here is a complete article on the topic. Thank You very much for asking

  1. Long Side: people add risk. Short side; frequent squeezes, start from manageable risk then reduce
  2. Metaphor of accelerator and brakes. Optimum fuel consumption happens when You do not solicit brakes. It clicked while listening to Larry Williams interview on the famous Better System Trader after bringing my daughter to the Hoikuen (crèche in Japanese)
  3. Market Value (MV) = AUM * Risk Per Trade (RPT)
  4. Most position sizing formulas will use one side RPT usually to calculate risk. In my case, this is convex so as we make money take more risk. This is accelerator. You want this to be responsive and nervous so to re-accelerate quickly after drawdown
  5. Meanwhile, when strategy stops working, You need to trade minimum risk. The problem with conventional formulas is that brakes are spongy and re-acceleration slow. You can get whipsawed. Which then erodes emotional capital, which leads to downward spiral. (Feedback loop between emotional and financial capital). By allocating a convex surface, AUM drops dramatically very quickly but then re-accelerates as there are signs of life
  6. Practical example: ETF. At the moment squeeze so drawdown, then surface immediately reacts and I naturally trade smaller. Residual open risk in my latest short entry was -0.12%, down from min risk at -0.25%

Trading Edge

From: Marcia

During your interview in episode 32 you talked about the “Edge” formula, which is, I think, ” (%wins X Average Win) – (%Losses X Average Loss) “? Would you talk more about that and what number you are looking for, or, what insights the number gives YOU?  thank you

Thank You very much. I am writing a book on short selling. Part 1 is about how to build a statistical trading edge. Part 2 is about building a mental trading edge. Part 3 is about constructing a portfolio with a positive trading edge. On the Long side, the market does the heavy lifting. On the short side, the market does not cooperate, so building a trading edge is critical

  • I am looking for positive number. I have never looked for a specific number, thank You for the suggestion
  • Use as asset allocation tool:
    • Plot trading edge by side and strategy
    • Pro-rate trading edge
    • Allocate resources (trading AUM or surface) based on trading edge, with floor and ceiling
  • This is useful for multistrats portfolios where You would systematically allocate resources to the best performing strategy

Shorting strategies

From: Adonis

What are the 3 most successful triggers he uses in going short? Does he use daily or weekly charts?

There were originally several variations on two strategies (mean reversion and trend following). Over time i have managed to merge them into one.

  1. Define trend: lower highs, lower highs
  2. Wait for roll-over: maximum information: volatility, swing high
  3. Enter on next bar

Exits:

  1. stop loss: full
  2. trend reversal (logical time exit): entry qualified on the other side happens within stop loss
  3. partial exit: risk reduction, take profit objective is to break even

Now, the delicate part is not in the signal module. Trading suspension for example is not a signal issue but a position size one. If sizes are too small, then trades are rejected. For example, sometimes currency pairs flip-flops between bull and bear. So, we count entries and add penalty for each full exit. This reduces risk per trade. If the overall equity is ain a drawdown, then position sizes get smaller. If they are too small, they are automatically rejected. This allows us to trade more pairs as some of them stop trading.

 

From: Graham

How do you simulate borrowing costs when testing a shorting strategy?

Everything at General Collateral (GC) +0,15% added to slippage. The question is probably related to hard to source issues or crowded shorts.

Do not short issues with borrow >5%, except on the Long side: squeeze box. Do not squeeze people: it is bad karma

 

From: Nikhil

1)  Majority of ideas for a short strategies seem to fail rigorous testing on larger time frames so one should focus on more active time frames [5min to 2H based data] instead of passive time frames [Daily to Monthly based data]  ?

Assumption: Nikhil may trade breakdowns, because this is a classic symptom or rebound higher than entry which leads to false positives.

Solution is not in better entry signal, but in partial exit and better money management, Trading system has 3 components: exit/entry, money management and mental.

 

2) Can you highlight a basic idea on a short strategies variable for further research for those struggling with constructing a short only strategy ?

JNK Short

Sure, check post on JNK attached. It is a scale-out/scale-in system.

There are 2 certainties in life: death and short squeeze. Use squeezes to your advantage

3) What opportunities do you see in the financial industry going forward for new generation of entrepreneurs (non trading/investing related) coming up ?

At the moment, everyone wants to be in the HF game. I entered the HF game in 2003 when it was still in infancy: a bunch of cowboys blowing stuff up in their kitchen. HF is bound for yet another healthy correction.

I believe the future to be threefold:

  1. Algorithmic assets allocation: fire your financial advisor. If You don’t know why, he probably does. Machines do a better job and they don’t get kickbacks…
  2. Separately managed accounts (SMA): open a brokerage account and let algo do the heavy lifting. Funds running costs are prohibitive. Besides, there is a proliferation of single brain cells parasites called compliance. They are the TSA (US airports officers) of finance: utterly useless at catching problems but extremely annoying
  3. Active management “soft patch”: SPIVA.com. The overwhelming majority of funds underperform the index and they are more expensive than ETFs. There is a gambler’s fallacy going on: ETFs have outperformed active managers so far, but the latter will be better equipped to navigate volatility and downturns. That is gambler’s fallacy: if managers failed to outperform during easy times, why would they even succeed during hard times ?

As for non-investment profession, I honestly don’t know

 

From: Ola

I am using market filters to keep me out of bear markets for my long only strategies for stocks, and I’m cashed up for periods of time. I find this a bit boring. What type of indicators or price action should I look for to create a short strategy to complement the long strategies? I’m looking for something simple and robust to be used on the daily time frame.

Best regards,

Ola

Check JNK trade attached. 1 Define trend, 2, enter on counter-trend move 3 exit partially as rebound comes

 

General trading

From: Bengt

Hello, it is often said that short trading is very difficult to make money off: Do you agree with this? If so, do you think it is a matter of the odds not being on your side or is it too much to handle mentally?

EXCELLENT QUESTION: “This is space, the environment does not cooperate… You solve one problem after another, and if You solve enough problems, You get to come home”, The Martian.

Andrew, Allow me to explain why people fail on the short side: they think from a Long perspective. This is deep shit that no-one has ever explained in statistical and psychological terms. Fascinating theme, I am writing the book on the topic and how to build a sustainable short selling practice

Example: 4 stocks: A,B Long C,D short, all start at 100

Start: Long exposure 200%, Short exposure: 200%, Gross exposure: 400% , Net exposure 0%,

A goes up by 10%, B drops by 5%. C drops by 10% and D goes up by 5%

End: Long exposure 205%, Short exposure: 195%, Gross exposure: 400% , Net exposure +10%,

Bottom line:

  1. On the long side, the market does the heavy lifting for You. There is a bigger bet on something good
  2. On the short side, the market does not cooperate: there is a bigger bet of something that does not work
  3. Net exposure is +10%. The main reason why people fail is that they want to short a throw away the key when they should be working more on the short than the long book. Just to stand still they should keep running: this is a Sherlock Versus the Red Queen effect

 

On the other end of the spectrum: is there an outer limit, odds-wise, for profitable long term trading, or is an 800-day breakout tougher to handle mentally than a 2 day breakout?

Best regards: Bengt

The problem is false positives: You will have many more false positives because of poor trend formation with shorter periodicity. You will deal with being systematically late. A more robust statistical approach is to deal with exits so as to move the needle from “near win” (false positive) to “near miss” (partial win)

 

From: Rob

Please ask for the following:

1) What works better in the forex market – momentum or mean reversion?

Mean reversion works until trend following works. It is a question of periodicity and tolerance for stop loss.

My strategy is a combination of both.

Post about two types of strategies:

2) If you had to start over from the beginning with the knowledge you have now where would you focus on and what would you throw away?

  1. Psychology: clarity about beliefs. 90% of trading is mental, the other half is good math
  2. Trading edge is not a marketing gimmick: it is a number
    1. Money management: example of convexity
    2. Exits: stop loss is the 2nd most important variable

3) You have said in the past to focus on exits and not entries – but how exactly do you do this? Is it a matter of thinking about when you will exit if you are right or wrong?

Never think about right or wrong, it is the wrong mental association that will lead to death. Think about profitable. I am writing something on the psychology of stop loss. This article is potentially the most or second most important post I have ever written.

The best analogy is diet. Diets don’t work. We are all getting fatter and there has never been as much information on diet. Diets fix the wrong thing. The problem is not what we eat. The problem is how we think about we eat. Same goes with stop loss and exit.

This is not a mathematical problem. This is a psychological issue about the meaning we ascribe to closing positions. If we associate stop loss with being wrong, the ego will revolt.

IAU option trade anecdote funny and excellent example to talk about emotional capital and Zibbibo viognier white wine blend from Etna

4) What do you think about fixed fractional position sizing

it is a good basis of any position sizing algorithm. Now, it is a bit simplistic for 2 reasons:

  1. Uniform risk taking through the cycle: think of it as a car. Sometimes it is good to accelerate, sometimes You need to decelerate. Win rate changes through the cycle and so should risk
  2. Dissociation: Long and short sides rarely work well at the same time. Since they have different win rate, they should have different risk numbers

Dissociation by side of the book, strategy using trading edge or win rate. Please check my post on convex position sizing

5) Please talk more about stops. you said in the past your stops have a large impact on your P&L – but how do you calculate your stops. What are the considerations when using a mean reversion vs momentum strategy and type of market forex vs futures.

Sure, happy to explain the equation

Now, for mean reversion strategies, the equation includes another variable: frequency. Let me give You a simple example. If you clock +0.5% per month and then have -6% month, it will take roughly a year to make that back if everything else works. So, a simple idea is to empirically come up with a patience factor. Example: never allow losses to be greater than 4 months of average profit. The difficulty though is correlation. Accidents travel in group.

Another important point on mean reversion, never trade open risk strategies. Example: short naked gamma. I was having dinner with some options portfolio managers friends. Short OTM gamma is still marketed to unsuspecting investors. Those are scams: they show consistent returns until they blow up

From: John D

I trade a long term trend following (trade every 1-3 months) system on stocks indices currencies and commodities. What type of exits would you use on this type of system?

Trailing ATR stop? Time stop? Both?

John D, You are right on all of them

Three stops:

I have developed something called box concept. Once in a trade, there are three possible scenarios:

  1. It does not work and needs to be stopped out. That is a floor or ceiling depending on whether You are Long or Short
  2. It works well and warrants some de-risking: take money off the table and leave a portion for the long right tail
  3. It goes nowhere: this immobilizes resources and needs to be dealt with

The concept is that whatever happens, it will trip one of the mines and will be dealt with. This is how it is done in practice

  1. Isometric staircase stop loss: swing +/– allowance for volatility. Markets do not go up in straight lines. They go up or down, retrace and resume their course. This method allows markets to breathe
  2. Partial trailing stop loss: take some money off the table so as to reduce risk, but leave a residual for the big trend. After taking some money off the table, it makes sense to re-enter and a add a little bit more risk.GBPJPY
  3. Time stop: buying power and trading frequency. Some stocks do not move enough to warrant either a stop loss or a risk reduction. These are the harder ones to spot. The solution is to timestamp them.

About timestamp:

 

Convex position sizing algorithm: something your brain can trade through euphoria and depression

Introduction

There are two position sizes: too little or too much. Too little when it is working and too much when it is not. Of course, our inner idiot compels us to take too little risk when we should be bold and vice versa when we should be prudent.

Position sizing is this critical juncture between financial and emotional capital. Deplete the former and it will take effort to rebuild. It is a complicated problem, but not a complex one. Break the latter and “Game Over”.

On the short side, position sizing is even more critical: failures get bigger and painful, while successes shrink away. Over the years, I have experimented with many position sizing algorithms. Many of them were brilliant, but I would always drift away and abandon each one of them after a while. Then, I realised I looked at the problem from the wrong angle. Convex position sizing is the story of my journey

If You have encountered “fear of pulling the trigger” or if You routinely take too much/too little risk at precisely the wrong time, then this position sizing algorithm might be for You.

 

Part 1: The correct mathematical answer may not be the right one

The first part of the journey was to find out why I consistently drifted from conventional algorithms.

  1. Short selling is not a stock picking contest, it is a position sizing exercise

On the short side, the market does not cooperate:

  1. Volatility is elevated: that rules out systems like equal weight.
  2. Concentrated bets is a bad idea, as their volatility drives the short book and consequently the entire book
  3. Short squeezes are frequent: expect all shorts to rally >10% over 5 trading days
  4. During bear phases, correlation goes to 1. Expect Longs and Shorts to go against You at once
  5. Unprofitable trades balloon rapidly. So, the natural tendency is to be conservative and take small risks.
  6. Unlike the long side, there are no 2-3 baggers. Winners shrink and contribute less. So, there is an opposite tendency to oversize positions.

Bottom line: the short side is less a stock picking contest than a position sizing exercise. Winners get smaller and loser get bigger. The difficulty is to size positions so that they contribute when successful, but do not torpedo performance when unsuccessful.

 

  1. Two types of algorithms and two types of people

There are two types of position sizing algorithms: aggressive or conservative. Risk seeking systems will have You bet beyond your comfort zone, and sometimes lose more than You should. System failure means cumulative losses have permanently damaged your ability to bounce back.

Conservative systems will have You bet small and earn less than You could. Failure means returns are not attractive enough, and/or period of recovery after a big loss is too long.

There are also two types of people when it comes to risk: risk seeking or risk adverse. Risk seeking people have higher tolerance for the volatility that comes with bold choices. If they go too far, they may no longer have the resources to bounce back.

Risk adverse people accept underwhelming returns in exchange for low volatility. Their downfall is they are sometimes conservative to the point of being risk seeking. Failure does not mean they aim too high and miss their target. Failure means they aim too low and succeed.

 

  1. Regime Change, transition and drift

Now, the world is not Manichean. There are times when it is wise to be conservative, settle for a risk adverse system, accept to earn a little less than You could.

There are also times when it pays off to be aggressive, ride a risk seeking system, but potentially lose a lot more than You should.

The problem is that most position sizing algorithms are good at either one or the other. They are not equipped to transition smoothly from equity growth to capital preservation. A core principle is that systems must be followed throughout a cycle in order to achieve predicted results.

 

  1. The correct mathematical answer may not be the right one

The problem with many position sizing algorithms is not to find the optimal size that will achieve desired geometric returns. The difficulty is keeping executing through euphoria and depression. Of course, optimal f is the correct position sizing algorithm. The problem is my inner idiot thinks he knows better.

For example, “fear of pulling the trigger” is simply the inner idiot (often referred to as amygdala) saying those bets are too big. This fear gets reinforced after every loss in the thalamus. It eventually gets to the point where the brain overrides the algorithm, but rationalises decisions. Self-deception is insidious, it covers its own tracks.

I did not abandon any of the position sizing all at once. I just gradually drifted away. I failed because my inner idiot constantly second guessed what the algorithms suggested. Discipline is futile. It’s like diet: everyone puts those kilos back on in the end.

I therefore realised that the only way to makes more sense to build a position sizing algorithm that the brain can embrace and then figure out the math.

 

Part 2: Convex position sizing

  1. Philosophy of the convex position sizing

Convex position sizing algorithm was conceived backward. Math is subservient to the brain. It may not be the optimal mathematical solution, but it is one my inner idiot will have no problem executing during triumph and disaster.

So, I started out with a list of demands

  1. Trade at optimum risk: (accelerator)
    1. Accelerate to maximum risk during run-ups, but
    2. Decelerate quickly as soon as there is a drawdown
  2. Absorb volatility: (brakes)
    1. allocate maximum equity, but
    2. reduce risk drastically during severe drawdowns
    3. Avoid whipsaws due to premature re-acceleration
  3. Reduce risk for each new re-entry: (trend maturity)
  4. Simple input variables (risk appetite)

The best analogy is fuel efficiency. Flooring the accelerator and then slamming the brakes is not a fuel efficient way to drive. These are aggressive systems like Kelly criterion, optimal f and Fixed Ratio Position Sizing (FRPS). Driving like Mrs Daisy is lovely, but not necessarily the most competitive style. These are systems like constant Fixed Fractional Position Sizing (FFPS), equal weight.

Convex position sizing algorithm runs at optimum acceleration. It will take on risk as equity curves rises and reduce as it comes down. It will slam the brakes to avert accidents and then re-accelerate smoothly. Risk Per Trade is the accelerator and Equity would be the brakes.

One of the strengths of the algorithm is smooth transition from risk seeking to risk adverse. The algorithm focuses on drawdowns. As soon as there is a drawdown, risk is reduced. Conventional position sizing algorithms focus on winning streaks and thresholds. They are therefore slow to react.

 

  1. Fixed Fractional Position Sizing revisited

Fixed Fractional Position Sizing algorithm basic formula is:

Market Value = Risk Per Trade / Distance to Stop Loss * Equity

Most formulas focus exclusively on Risk Per Trade (RPT). With the notable exception of Market’s Money, few of them consider Equity (capital allocation or surface). The idea became clear to use both sides, one for acceleration, the other for deceleration.

 

  1. Convex Risk Per Trade

In practice, this is what Risk per trade looks like:image (1)

Risk per trade oscillates between a minimum and maximum. Trends mature, so risk per trade is reduced for each re-entry. Convexity comes from the ratio of min/max risk. In this example, min risk is set at -0.25% and max risk at -1%. The bigger the ratio the steeper the acceleration.

How to calculate min and max risk per trade

  1. Max Risk per Trade: Risk Appetite / [AVG number of positions * (Long Term Loss Rate + 2 STDEV(Loss Rate)]
    1. Risk appetite: is not a mathematical number. It is the drawdown investors are willing to stomach before redeeming. Whatever You think that number is, divide it by 2. This is a clear case where You do not want to be right !!!
    2. Long Term Loss Rate: ideally, this is the win rate through the entire cycle. When there is not enough sample data, default to a conservative 2/3. That means 2 trades out 3 will fail. 51% Win rate is for fairy tales, and Prince charming is not coming
  2. Min Risk per Trade: this is the minimum RPT that would still allow trading during drawdowns
  3. Position count: Trends mature. Risk should therefore be reduced after each entry so as to avoid giving back profit on last entries

Risk appetite is one of the two input variable of the entire posSizer algo. Everything else is calculated.

 

  1. Drawdon module

image (4)This is the equity allocated to each trade. The objective of this component is to absorb small daily volatility. As a drawdown becomes severe, surface is exponentially reduced so as to collapse residual risk. Note the slope of the curve. Small recovery results in rapid increase of the surface.

Trading floor: this is the second input variable. This is a percentage of equity balance that will be allocated if drawdown exceeds tolerance. A good example here is Millennium partners. After a drawdown of 5%, equity is automatically reduced to 50% of initial capital.

When investors say they can stomach a 20% drawdown, what they mean is they will think about redeeming after a 10% drawdown. So, it is wise to cushion the blow with this drawdown module.

 

Part 3: Convex position sizing in action

This posSizer runs on auto-trade Metatrader MT4. We trade closer to 30 currency pairs, leveraged at 100:1 on 15 minutes periodicity. This is probably as aggressive as it can be.

It feels like being in a driverless Formula 1, without a steering wheel, pedals for accelerator and brakes. Yet, thanks to this algo, there is no need to stay glued to a screen all day. This posSizer provides priceless comfort when most needed. It will smoothly handle trouble: reduce risk, collapse it if necessary and then re-accelerate rapidly.

This is what it looks like in practice. Below is a hypothetical equity curve (GS stock price). The real equity curve does not have those big drawdowns, so it is harder to distinguish.image

Blue and pink lines are min and max market values per trade (MVPT). Green lines are market values for each position n1 to n4. Orange line is first entry without the drawdown module.

As equity curve rises, MVPT rises in unison. MVPT reacts rapidly to each drawdown but still remains closer to the upper bound until a more pronounced drawdown happens. Risk is reduced for each new tranche.

The drawdown module kicks in during severe drawdowns. This is the difference between the orange and green dotted line. MVPT goes down even further than minimum risk. There are times when even small positions seem too big. This ensures trades go through but at bare minimum risk. This reduces concentration, which in turn sets the stage for a rebound.

One of the problems of FFPS is premature re-acceleration after a drawdown. This leads to whipsaw in sideways markets. This is again a potential reason to drift from suggested positions. After a severe drawdown, the orange line rises faster, while the dotted line adjust re-acceleration to the speed of recovery. For example, the first drop below min risk was followed by a prompt recovery. The second one was more gradual.

 

Conclusion:

Under extreme stress, every degree of freedom, every bit left to interpretation has the potential for costly human error.

Position sizing often overlook the most important component in any trading system: our inner idiot. This algorithm reconciles math and affective neurosciences. It helps us “meet with Triumph and Disaster, and treat those two impostors just the same”, extract from Rudyard Kipling, “If”

Round 2: synchronous short selling signals across multiple asset classes

1. Trading journal

2. Tip of the day: Triage, kick out the free loaders and never trade laggards

1. Trading journal: Round 2, time to short again and don’t complain there aren’t enough short ideas

This is the big day, time to get back in the ring. Short squeeze came and went. Now, stocks are rolling over again. This is quite an unusual to do so though. Roll-over usually happen over the course of a week. This time, it’s different (just love to say that to confuse people).Roll over happens across asset classes on the same day. In fact, there were so many they had to be split in two files. It took more than an hour and almost half a bottle of Prosecco to process them. So, don’t complain there aren’t enough short selling ideas.

So, “is it the right time to dip our toes in the water ?” When everyone is buying, short selling seems like a bad idea. By the same token, when everyone around the world, across asset classes is selling, does it sound like a good idea to go out and buy ?

If You want details on any signal, send a mail or a comment and i will post it with comments.

All signals are ranked by size assuming a 0.10% risk per trade. I placed a whole bunch of orders. The priority algo was as follows:

  1. Free up some space and kick out free loaders: see Tip of the day
  2. Top-up of existing positions: SPY, EWL, EWH, EPP, PHO, VWO. Ignore EWA, IDV and TDIV already fully loaded or expensive borrow
  3. Enter qualified trend reversals: we have designed a neat trend reversal qualification test some time ago. This is as early and as safe as a trend reversal can be detected. So, anchor positions with minimum risk per trade very near the top
  4. Enter trending shorts by size and lot numbers: the bigger the size and the higher the number of lots the better. High lot number means easier partial exit

Tip of the day:

Triage:

  1. Make space, get rid of stale positions: multiple simultaneous positions means something happened in the markets. So, the first thing to do is to get rid of the positions that did not react. Those that do not react are likely to hurt when the market moves the other way. For example, during this sell-off, some positions held their ground. Two of them even went up. Fine, OUT now. Yeah but the thesis, the long term prospect, blah blah blah. Sure, when ready to cooperate, we will talk about it, but for now OUT. This frees out some resources to more promising ideas
  2. Weight ranking: position sizing algo is fixed fraction position sizing of equity at risk -0.10%. So, for the same risk budget, the bigger the position size, the lower the volatility. Yeah, but i like the thesis on bio stocks. Great, they are too volatile still, so wait until they are ready for a serious relationship

Free Loaders:

Managers often fail to meet their objectives not because of spectacular blow-ups, but because of the drag of poor performing stocks. So, relentlessly kick out stocks that do not react or perform poorly. Here is a simple powerful way to reframe the situation

If You owned a building, would You allow tenants to stay rent free ? No, You expect them to pay their rent. Apply the same discipline to stocks and performance will mechanically improve. Here is a simple elegant “how to” article

http://alphasecurecapital.com/the-game-of-two-halves-an-eleg…

Never trade laggards

Brokers and fund managers have this constant fear of missing the boat (fear of missing out or FOMO). So, they have come out with this brilliant idea to round up thematic stocks and identify laggards. The basic thought is “This is the next…”. IBM is not the next Apple, Squarespace is not the next Facebook. Laggards are just left overs

The best remedy is to think that the boat You just missed is not an ocean liner but a Vaporetto. There will be another one shortly. The market will give You another chance