binary options

BEWARE: Scrooge-like Binary Option Payouts

Binary Options PayoutsThe binary option payouts offered by some binary providers are so Scrooge-like as to be considered daylight robbery or even extortion. Yet these two nouns are inappropriate because clients that accept these low payouts are apparently doing so at their own volition. Why would a client accept such low payouts? One answer, unlikely as it may be, is that these traders are aware that their win/lose ratio is sufficiently high to wear these payouts. Unfortunately though, the obvious answer to that question is ignorance!

Trader’s Win/Lose Ratio

This note hopes to clarify for traders the importance of assessing their own level of trading skills in order to make a better, educated decision as to whether to open a binary options account with a particular broker, or to look elsewhere for a broker that is offering a reasonable payout.

The focus is on the staple offering of binary options providers, the Over and Under.

Over & Under

The Over and Under are quite simply the least complex, easiest to use financial instrument to be offered in the world of financial trading.

Over: At any time one can speculate that the underlying asset price, e.g. gold, will be higher than the current price at some fixed time in the future. That time in the future is when the trade ends and in options parlance is referred to as the option’s expiry.

For example: if the gold ‘Over’ is due to expire in one hour and the current price of gold is $1,100 then the Over is a very simple ‘Yes’/’No’ proposition: “is the price of gold going to be higher than $1,100 in one hour’s time?”. If the answer to this is ‘Yes’ then the customer buys the Over and if correct, i.e. the price is higher than $1,100 in one hour’s time a $100 investment could payout anything between 65% and 90%.

Under: The opposite to the Over. If the answer to the above example was ‘No’, the customer believes gold will be lower than $1,100 then an Under is purchased instead.

Yet there is a further decision to be made that is all too often not considered and this involves a concept known as Expected Return.

binary option payoutsHeads or Tails

Consider the game of Heads or Tails where two contestants (Player1 and Player2) toss a coin for, say, a $1 stake. Assuming some physical quirk in the coin does not exist, e.g. it can’t balance on its edge, or a subtle form of cheating is eliminated, then the coin has a 50% chance of being a head and a 50% chance of being a tail. The expected return (ER) is:

Player1 ER     =     ((1-Prob. of Winning) – (Prob. of Winning x Payout)) x Stake

and the expected return of Player 2 is:

Player2 ER     =    ((Prob. Of Winning x Payout) – (1-Prob.of Winning)) x Stake

With a normal coin the probability of either player winning is 50%. The probability of either player losing is therefore 50% also.

The payout would be 100% since the winner that calls right gets their own dollar back plus a dollar from the loser.

Therefore, assuming Player 2 bets $1:

Player1’s Expected Return    =     ((1 – 50%) – (50% x 100%)) x $1

                                               =                $0

which, of course, is the same for Player2.

Tossing a coin is devoid of skill therefore the probability of winning or losing will remain at 50%. The only variable is the payout so unless Player1 can persuade Player2 to accept a percentage below 100%, while remaining at 100% themselves, then this game is futile; they can toss the coin one million times but the likelihood is that neither will have gained very much financially.

binary option payoutsRed or Black

Now compare the above with the game of roulette where Player2 is now speculating on Black or Red. The house (previously Player1) is still offering 100% payout but Player2’s expected return is now negative. This is because there is a white zero slot for the roulette ball to drop into and that 0 loses for Player2. Red and black have eighteen slots each, with the additional 0 slot, meaning that there are a total of thirty-seven outcomes. When Player2 puts money on either red or black they now have only an 18/37 chance of winning, i.e. their probability of winning has now decreased to 48.64864864%. Player2’s expected return has now turned negative:

Player2 ER     =       ((48.64865% x 100%) – (1 – 48.64865%)) x Stake

=0.4864865 – 0.5135135


Yet again, there is no skill in playing red or black at roulette so these odds of winning and losing will forever remain at these levels.

Efficient Market Theory                      

If financial markets were what is known as ‘efficient’ then trading would be a crap shoot and there would be a 50% chance of calling the market right or wrong. But for efficient markets to exist then all information about an asset must be known by absolutely everyone in the world, and furthermore everybody in the world would have the wherewithal to actually act on that information. In effect Efficient Market Theory states that all asset prices fully reflect all information available in the marketplace. Information can mean all data about a listed company, all data about trade balances, currency reserves, stockpiled gold etc.. It can also mean what technical analysis price charts are depicting. In effect, any piece of information that might possibly impact on an asset price is known to all.

This is clearly not the case as time lags in information travelling can mean that prices are not in equilibrium and are subject to price moves which may appear illogical to the uninformed.

Investors of the ilk of Warren Buffet only look at long-term investments while day traders look at time scales of a day or less. At the ultra short end of the time scales there are High Frequency Trading programmes that are in and out of the market in seconds. None of these forms of trading are pot luck, they all rely on investment/trading skills in one form or another.

So at this point it begs the question: “How good at trading or calling the market right do I have to be to trade the Over and Under binary options?”. Well the answer to this depends on the binary option payouts being offered.

Expected Returns & Binary Option Payouts

Assuming that the trader has studied the number of trades they’ve made and counted the number when they’ve called the market correctly and incorrectly, then the trader might convince themselves that they get it right fifty-five times out of a hundred.

The trader would then have an expected return based on 85% binary option payouts of:

Trader’s Expected Return = ((55% x 85%) – (1 – 55%)) = 1.75%

The following table offers a range of binary option payouts against the trader’s view of their own competence as measured by their percentage of winners.

  1. The top axis is the client’s own perception of their probability of winning and ranges from 50% to 70%. If you believe that you can achieve in excess of a 70% win/lose ratio then stop wasting your time on this site. Get proof of your performance from your stock broker, FX account, whatever, and contact a hedge fund. They would love to have you on board!
  2. The Platform Payout are the binary option payouts offered by the binary operator and ranges from 60% to 90%.
  3. The body of the table presents the client’s Expected Return.
Trader's View of Probability of Winning
Platform Payout = 60%-20.00%-16.00%-12.00%-8.00%-4.00%0.00%4.00%
Platform Payout = 65%-17.50%-13.38%-9.25%-5.12%-1.00%3.13%7.25%
Platform Payout = 70%-15.00%-10.75%-6.50%-2.25%-2.00%6.25%10.5%
Platform Payout = 75%-12.50%-8.12%-3.75%0.63%5.00%9.38%13.75%
Platform Payout = 80%-10.00%-5.50%-1.00%3.50%8.00%12.50%17.00%
Platform Payout = 85%-7.50%-2.87%1.75%6.38%11.00%15.63%20.25%
Platform Payout = 90%-5.00%-0.25%4.50%9.25%14.00%18.75%23.50%


Some binary operators will offer a rebate. The rebate is usually in a percentage format and the provider will reimburse the client when losing to the tune of the rebate percentage of the client’s initial investment, e.g. the client invests $100, the binary operator has set a rebate level of 15%, the client loses. The operator will then reimburse the client’s account with $15 having already deducted $100 at the bet’s inception. TANSTAAFL!!! This magnanimous gesture comes with markedly lower payouts on offer to start with. Binary operators are not by nature philanthropic, and that’s being polite……….

The following three tables are based on Rebates running from 5% to 15% as described in the top left hand corner of each table.

Trader's View of Probability of Winning
Platform Payout = 60%-17.50%-13.63%-9.75%-5.87%-2.00%-1.88%5.75%
Platform Payout = 65%-15.00%-11.00%-7.00%-3.00%1.00%5.00%9.00%
Platform Payout = 70%-12.50%-8.37%-4.25%-0.12%4.00%8.13%12.25%
Platform Payout = 75%-10.00%-5.75%-1.50%2.75%7.00%11.25%15.50%
Platform Payout = 80%-7.50%-3.12%1.25%5.63%10.00%14.38%18.75%
Platform Payout = 85%-5.00%-0.50%4.00%8.50%13.00%17.50%22.00%
Platform Payout = 90%-2.50%2.13%6.75%11.38%16.00%20.63%25.25%
Trader's View of Probability of Winning
Platform Payout = 60%-15.00%-11.25%-7.50%-3.75%0.00%3.75%7.50%
Platform Payout = 65%-12.50%-8.62%-4.75%-0.87%3.00%6.88%10.75%
Platform Payout = 70%-10.00%-6.00%-2.00%2.00%6.00%10.00%14.00%
Platform Payout = 75%-7.50%-3.37%0.75%4.88%9.00%13.13%17.25%
Platform Payout = 80%-5.00%-0.75%3.50%7.75%12.00%16.25%20.50%
Platform Payout = 85%-2.50%1.88%6.25%10.63%15.00%19.38%23.75%
Platform Payout = 90%0.00%4.50%9.00%13.50%18.00%22.50%27.00%
Trader's View of Probability of Winning
Platform Payout = 60%-12.50%-8.88%-5.25%-1.62%2.00%5.63%9.25%
Platform Payout = 65%-10.00%-6.25%-2.50%-1.25%5.00%8.75%12.50%
Platform Payout = 70%-7.50%-3.62%0.25%4.13%8.00%11.88%15.75%
Platform Payout = 75%-5.00%-1.00%3.00%7.00%11.00%15.00%19.00%
Platform Payout = 80%-2.50%1.63%5.75%9.88%14.00%18.13%22.25%
Platform Payout = 85%0.00%4.25%8.50%12.75%17.00%21.25%25.50%
Platform Payout = 90%2.50%6.88%11.25%15.63%20.00%24.38%28.75%

The Moral of the Story

It is pretty important to be able to forecast whether the market’s going up or down: what is a good deal more important is to have an accurate handle on your trading win/lose ratio because that then determines whether your trading is viable in the first place.


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