INET is an ECN (Merger Island and Instinet) = a market place like GLOBEX for futures but on the NASDAQ there're multiple market places. They all want to attract traders (so most of the volume is traded through their ECN).This is done by giving you rebates for adding liquidity and charging you for taking away liquidity. If you take away liquidity (ex. buy on the ask, sell on the bid) then you pay a fee of (INET) $3,- / 1000 shares traded If you add liquidity (ex. buy on the bid, sell on the ask) then you get a rebate of (INET) $2,- / 1000 shares traded The difference ($1,-) is of course for the ECN (INET) This has nothing to do with commissions etc. To keep a statistical advantage you have to make sure that your commissions and SEC fees are covered by the rebates you get. Hope this helps
I don't like to compare my trading or methods to anyone elses (especially a casino), I see no useful purpose in it. However, the ability to sit out of the game and wait for favorable conditions is always helpful. I can sit out when I want and enter when I want. To me that constitutes a fairly decent edge.
The casino has an easily computable defined mathematical edge on almost every play, and it plays millions of times a day. The speculator has a hard to compute undefined fuzzy edge on a very small minorities of plays. The speculator is analogous to the card-counter at blackjack, or a professional poker player gaming with high-rollers. He must conserve capital, pick his spots, and play very well in order to avoid loss and rack up winnings.
Harry, your method of calculating "edge" does injustice to the gaming industry. The house edge for European and American roulette is 2.70% (1/37) and 5.26% (1/19) respectively.
Good point about rebates, H2O. Some gaming establishments give selected clientele a rebate (certain percentage) of their losses. When used judiciously, this can make a session in a negative expectation game (like roulette) have a positive expectation.
Sorry my numbers have been checked with a statistical book in fact since I am not specialist of casino game . As for probability definition of edge, there is no edge if the house has 50% chance and the player 50% chance also. So the edge is the difference relative to 50%. The calculation here is no more or less that just flipping a coin that is biased. If the coin is not biased p=q=50%, if it is biased the edge = p - q (positive expectancy of gain ... meaning nearly assured for the casino at long term or against a great population of players at the same moment). In fact the modern term is "submartingale" see http://www.elitetrader.com/vb/showthread.php?s=&postid=401943&highlight=SUBMARTINGALE#post401943 If you use an other definition of edge then explain.
Hmm I suspect that the divergence is that you didn't take into account that I was talking about betting NOT on a NUMBER but on BLACK Or RED. This is the case where the edge of the casino is nearly above 50% which is the interesting case. For those not at ease with prob, a probability is just the number of favorable cases on the total number of cases. If you bet on RED (the same if on BLACK) the number of favorable cases is the number of RED numbers so 18. The total number of cases is of course 37 then the prob is 18/37.
Indeed Gambling was at the very origin of Probability : A Short History of Probability From Calculus, Volume II by Tom M. Apostol (2nd edition, John Wiley & Sons, 1969 ): "A gambler's dispute in 1654 led to the creation of a mathematical theory of probability by two famous French mathematicians, Blaise Pascal and Pierre de Fermat. Antoine Gombaud, Chevalier de Méré, a French nobleman with an interest in gaming and gambling questions, called Pascal's attention to an apparent contradiction concerning a popular dice game. The game consisted in throwing a pair of dice 24 times; the problem was to decide whether or not to bet even money on the occurrence of at least one "double six" during the 24 throws. A seemingly well-established gambling rule led de Méré to believe that betting on a double six in 24 throws would be profitable, but his own calculations indicated just the opposite. This problem and others posed by de Méré led to an exchange of letters between Pascal and Fermat in which the fundamental principles of probability theory were formulated for the first time. Although a few special problems on games of chance had been solved by some Italian mathematicians in the 15th and 16th centuries, no general theory was developed before this famous correspondence. The Dutch scientist Christian Huygens, a teacher of Leibniz, learned of this correspondence and shortly thereafter (in 1657) published the first book on probability; entitled De Ratiociniis in Ludo Aleae, it was a treatise on problems associated with gambling. Because of the inherent appeal of games of chance, probability theory soon became popular, and the subject developed rapidly during the 18th century. The major contributors during this period were Jakob Bernoulli (1654-1705) and Abraham de Moivre (1667-1754). In 1812 Pierre de Laplace (1749-1827) introduced a host of new ideas and mathematical techniques in his book, Théorie Analytique des Probabilités. Before Laplace, probability theory was solely concerned with developing a mathematical analysis of games of chance. Laplace applied probabilistic ideas to many scientific and practical problems. The theory of errors, actuarial mathematics, and statistical mechanics are examples of some of the important applications of probability theory developed in the l9th century. Like so many other branches of mathematics, the development of probability theory has been stimulated by the variety of its applications. Conversely, each advance in the theory has enlarged the scope of its influence. Mathematical statistics is one important branch of applied probability; other applications occur in such widely different fields as genetics, psychology, economics, and engineering. Many workers have contributed to the theory since Laplace's time; among the most important are Chebyshev, Markov, von Mises, and Kolmogorov. One of the difficulties in developing a mathematical theory of probability has been to arrive at a definition of probability that is precise enough for use in mathematics, yet comprehensive enough to be applicable to a wide range of phenomena. The search for a widely acceptable definition took nearly three centuries and was marked by much controversy. The matter was finally resolved in the 20th century by treating probability theory on an axiomatic basis. In 1933 a monograph by a Russian mathematician A. Kolmogorov outlined an axiomatic approach that forms the basis for the modern theory. (Kolmogorov's monograph is available in English translation as Foundations of Probability Theory, Chelsea, New York, 1950.) Since then the ideas have been refined somewhat and probability theory is now part of a more general discipline known as measure theory."
Why Chevalier de Méré would be been ruined by his bet do you know ? Remember the definition of prob: p = Number of favorable cases / Total Number of cases or p=1-q=1 - (Number of unfavorable cases / total number of cases) because sometimes it's more easier to estimate the number of unfavorable cases. The number of total cases N if you throw one dice of six faces one time is 6^1. If it is 24 times N=6^24. The number of total cases if you throw two dices of six faces twice time is 6^2. If it is 24 times N=(6^2)^24=(36)^24 I let you finish: calculate the number of unfavorable cases . Be lucky you have a pocket calculator whereas at the time of Chevalier de Méré they have to do it by hand so that error of calculation was not rare .
Confusing edge with drop. You can cut the house edge on blackjack to around 1% with proper strategy and good house rules (edge goes to the player if you count cards). But the drop at blackjack tables is much higher due to bad play and no money management. The variance in the swings works against the players because few walk with their winnings and they keep playing until they lose it all. I assume good traders do the opposite and leverage their edge through position sizing.