Monthly Archives:October 2013

How Much To Bet?

littl121 post on October 17th, 2013
Posted in Trading Tags: , , , , , ,

Any financial market opened to risk taking is a casino.

A friend asked me how much to risk on each Forex trade.  I reprised what Ed Seykota has advised : Risk no more than you can afford.  Risk enough so the win can be meaningful.  If you cannot achieve both – don’t trade. That about sums it up:  How much one can afford to lose?  How much one hopes to make?  How good is one’s edge ie.  can it help you achieve both mandates?  (Ed Seykota is incidentally a great trend trader who generally does not risk more than 5% in each trade.)

The Bottom Line

Chande, in my previous post, has demonstrated the prospect of ruin by risking beyond 2% of equity for various probability trade set ups and pay off ratios.  For example if your payoff ratio is 2:1, you need to win at least 35 to 40% of the time to possibly avoid risk of ruin comfortably.  (Note “possibly”.)  Chande underlined the probability of ruin for stop losses amounting to 1%, 2%, or 3% of equity etc,  calibrated against the trader’s edge (payoff ratio and probability of winning).

An Optimal Bet Size

Ed Seykota with Druz proceeded to show that each trading edge had an optimal betting percentage – beyond which the returns start to dwindle.  The optimal “bet size”  or “optimal heat” for a 50:50 toss of a coin with a 2:1 reward ratio is 25% of equity.  The theoretical return is approximately 12.5% after a 50%  gain and a 37% drawdown.

Evidently, how much to risk and how much to bet are different concepts.  A trader may risk 10% of his equity by entering a position that uses 50% of his equity.  How much to risk is a money management decision.  How much to bet is a strategy decision depending on how good the trader’s edge is.

How Much Do You Want To Bet In A Casino?

The forex market is like a casino.  Casinos as a rule only offer games that favor their owners.  This is known as the House edge.  Gamblers in casinos usually engage in negative expectancy games.  That means if they play long enough, they will eventually lose everything in accordance to probability theory.

Several years back, I was engaged to develop a financial feasibility study for a casino acquisition in Macau.  In my diligence, I had the opportunity to confer with an old Don of the establishment.   One gem he shared was that a casino did not need to cheat.  All its games had built in advantages and safety valves.  The two key principles were simple – have a “small” house edge (eg. the double zeroes in roulette) so that gamblers think they still have a good chance, and keep the gambler actively betting for an extended duration (think free rooms, free drinks, no clock). Over time, regardless how much the player had won, he would likely give the winnings back.  This is the negative expectancy game.  Many would get “cleaned” out.  If the player had walked into the casino with $100, the casino would not mind letting him rake in profits.  As long as the gambler continued with the casino’s games, he would most likely give everything back, and more importantly – the “play money” he originally brought with him.  The gambler’s initial profits if any, were merely the casino’s “working capital” – (now even more conveniently “stored” on digitized prepaid cards – think QE).  It is only by taking over the player’s original equity, that the casino gets richer.     The casino is further assisted by the gambler’s psychology.   How often does one walk into a casino with a  mental stop loss and hopes of large cash winnings?  The gambler had already been primed to at least lose a pre-determined amount and is further seduced by greed.  He would be lucky if he only lost what he originally  intended.  But the casino’s edge is only a small percentage, would it not take forever to clean out the gambler’s original equity?  Well, how fast that happens depends on how much the gambler bets …….. (think trade size and excessive leverage for the retail trader).

Forex – A Casino By Any Name   (By the way, Singapore’s third casino is also third largest in the world)

The spread between bids and offers, the private collaboration between market makers,  and the confidential intelligence that bank dealers have  (eg. major customers’ buy and sell orders), are tremendous “house” advantage – not privy to the ordinary retail trader.  Additionally, many traders wrestle against unscrupulous brokers with dealing desks (some hidden), and unethical practices of widening spreads inordinately to pick off stops, “slowing down quotes” according to the win-loss profile of the trader, and ill timed slippages.   Brokers also know where the traders put their stops.   Many offer excessive leverage, marketing promises that are difficult to keep, and deceitful half truths disguised as trading advice.   Like a casino punter, nothing a retail player does can modify the behavior of the Forex market.   The odds against the ordinary retail trader are simply incredulous.  As with all negative expectancy games, the trader will have a higher probability of losing his complete equity the longer he stays in the game.

Is This The End Game For The Retail Trader?

What does the retail trader have – his edge, his money management system, the ability to control when to play and how much to speculate each time (bet size).

How a trader bets should depend heavily (not wholly) on how good his edge is.  Assuming the trader already has his basics in place – money management, sound trading psychology – then his edge and game plan will tell him how much to bet in volatile situations and in highly favored scenarios.

Is there a formula for bet size?

There are many formulas for bet size (eg. Kelly criterion, Fixed Fractional, Unit Betting ), and many are relevant when used with complementing strategies.  Bet size depends on the trader’s edge and his ability to take the “heat” (ie. stomach for the risk undertaken).   There is no one universal formulation.

But there is definitely a correct bet size according to one’s edge.  At the very least the trader’s money management system shall be able to suggest a maximum bet size for his account’s acceptable level of risk.  (That said, will you trust a strategy with no money management system in place?)

However many traders do not know how much they should bet on each trade or how effective their current bet sizes are.  Obviously, many traders do not know their edge and strategy well.  They are looking for quick answers.  They will complain of not being able to determine stop loss points, exit points, and some will even give the excuse, ” gotta to let your profits run”.

Let us be clear, there are successful traders who do let profits run, and there are others happy with predetermined exits.  There are traders with lenient stops, tight stops and even no stops (there are tactics for this).    Indeed successful contradictions abound.

Different game plans, different edges – yes, but each trader that is consistently profitable knows his edge very well.  The trader will know whether to reduce or run up his bet size when the odds are favorable, or how to vary his bet size to reduce risks and yet achieve targets.   His strategy and edge will tell him when and how to enter or exit a trade.  His strategy will clearly tell him what to risk if stops are too near, too far or cannot be identified.  His strategy will tell him what conditions are favorable, and how to exit based on signals.    If a trader does not know his edge well, and has no discipline to organize his trading game, he will not be able to size his positions.  Unfortunately, over time he will likely lose whatever amount he has won, regardless his bet size.  (Reflect on how casinos work.)

PS.  If the trader’s edge or its execution is unreliable, and falls below the market’s house advantage, then it will ultimately be a negative expectancy game for him.

3 good articles to read on money management are:  http://www.littledada.com/tag/money-management/ ,    http://www.investopedia.com/articles/forex/06/fxmoneymgmt.asp , http://www.futuresmag.com/2011/12/31/simple-money-management-wins-over-time

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