Mark, I'm kinda late boarding this thread... But it's really nice to have you back on ET. I'm posting again just because you're here!!! "Your secret admirer" and "Self proclaiming padwan" (FYI. I asked you for advice intraday trading using tick data for the ES market a while back... also... I asked you about moving to Chicago from LA, a long time ago... and you gave me valuable advice and some contacts... That's who I am...)
kool.. hope all is well with you, i still love chi town. yea like a big fat whale i surface for air once in a great while. mb
back to predicting - i would say that the law of motion theory lends more potential than anything to easily predict future price movement. it is simple and effective as a primer to finding a confidence level to build upon. mb
Yes. I wouldn't use the term "predicting" but all systems are based on the "assumption" that the specific tendency the system exposes sustains... And... Risk management deals with the impact of when the "assumption" changes. They're both Math. Considering MATH being used in all levels of "trading", it may be the only viable tool for a System trader, next to Computer Science (algos) if it's not considered as MATH.
I do...Use math... do the trend if above /Below 5 days sma all these should do well for next 20 to 34 days dell is a buy these days Stock Trend APOL Buy BBBY Sell BEAS Sell CELG Sell CHKP Sell CHRW Sell DELL Buy FAST Sell FLEX Buy GILD Sell GRMN Buy IACI Buy JOYG Sell LBTYA Buy MCHP Sell MNST Buy PTEN Sell QCOM Sell ROST Sell RYAAY Buy SIRI Buy TLAB Buy UAUA Buy VMED Buy WFMI Buy XLNX Sell XMSR Buy XRAY Buy
Interesting, but how did you come up with these hard-and-fast numbers: 5 20 34 ? Why not 10, 30, 50 for instance ? And this smoothing technique:"sma" Why not EMA, JMA, TRIX, DEMA ? Also, would these change things over time as the market volatility changed ? You make this sound so simple.
just used Max(High(t)/Close(t-1),Close(t-1)/Low(t)) Daily data with those nubers into an array The average-1= a number >0 since change/ day as in the above... % change/day then days/change = inverse so u take the 1/(average-1) as your estimated half cycle the more the volitility the smaller the cycle
days in here are trade days so calender days = 365/250* trade days the cycles are on that column I did not want to fill the page those coef and stdev of coef used to do trades using the close of any day offset it to your advantage by either dividing or mutliplying Say u want to buy apol take apol close and divide by that coef 1.036041879 that is the estimated next low if u add 2*stdev to that average that will get the 5th percentile of the lower prices of the prices Coef(5th Percentile)=1.036041879+2*0.036125915 gl Stock Trend High Low Close Cycle Days AVG Coef STD Coef APOL Buy 48.81 43.54 46.81 28 1.036041879 0.036125915 BBBY Sell 33.28 29.89 32.01 36 1.028254202 0.016544792 BEAS Sell 19.27 19.16 19.2 45 1.022272561 0.030850537 CELG Sell 65.85 62.23 63.56 37 1.027721474 0.022208292 CHKP Sell 24.58 22.01 23.92 40 1.025584911 0.013882118 CHRW Sell 63.09 56.33 62.33 39 1.025943552 0.014948183 DELL Buy 19.99 18.50 19.05 39 1.025645238 0.015977614 FAST Sell 51.07 47.64 48.83 37 1.027675023 0.017606017
you are correct to assert that the markets are not random, but the basis of your argument is flawed: random numbers are not proved to be random only when they fit in a normal distribution, otherwise they wouldn't be random.