jperl

No darth, you are incorrect. The one std dev is for whatever the distribution is when you make the trade. It has nothing to do with the normal distribution. Again you still seem to be hung up on the idea that std deviations are defined in terms of the normal distribution only. You are partially correct here. Years of experience do make a difference in how well you trade. The best analogy is playing a musical instrument. I can teach you all the techniques for playing, but it takes years of practice to develop your own style and to be good at it. My point of the market statistics threads was to teach you a technique for analyzing the data and how you might use it. But it will still take you years of experience to use it successfully and to develop your own style

No. I would never fade the 1st SD (that is trade toward the VWAP). You are trading against the trend. Always dangerous at the 1st SD.

Two points: Don't trade at the VWAP if VWAP is close to the PVP. Skew is usually small at that point, so market doesn't know which way it wants to go. Fading the second SD is ok, provided price has already passed through it and is coming back toward the VWAP. For example, if price is rising toward +SD2, wait for it to pass through it and then comes back down through it a second time before fading it. You may miss a few good trades this way, but at least you won't be caught in a continued range expansion to the upside.

It's possible to do this in Ensign, but it is not a standard study. You would have to write your own ESPL code to do it. Your other choice is to ask Howard Arrington (Ensign software developer) to offer this as a study.

Most of the videos were recorded during live sessions although in some cases, I had to go back and edit them for pedogogical and time constraints. A few were playbacks that I did in order to demonstrate some particular principle.

The answer to your question is yes. In normal times (which this is not), starting the VWAP before regular trading hours usually wouldn't make much difference. Remember the VWAP is volume weighted, so including price data prior to the open would have little effect. However these are not normal times and there has been considerable volume pre-open in some markets. Under those circumstances starting the VWAP early could be helpful as you have pointed out.

Yes of course. If you scalp you could start the VWAP anytime you want to have a quicky. This works well in non trending markets.

No Ramora, I don't start a new VWAP every hour. You lose two important pieces of information by doing so: a) The present trend, determined by price relative to the VWAP and b)the day's volatility as measured by the standard deviation. The present trend determines my bias and thus whether I will favor longs or shorts. The SD tells me how much I should expect to pull out of the market when I trade. I don't want to lose either of those two pieces of info by restarting the VWAP computation.

Head2k has given us a "simple" explanations of what is going on at the VWAP. I have heard these types of explanations before. Whether they will help you as a trader is another matter. Or perhaps they now will make you more comfortable in thinking about VWAP and the associated SD as you have described them, as "decision points for market forces" what I call hold up prices or dynamic HUP as described in thread XI of the Market Statistics threads. Once you draw the HUP lines in for the trading day, you have a powerful tool for understanding and dealing with the price action.

You have this correct Pepperdog. A newbie trader would just have to sit and watch, while the market moves against the skew. After you feel comfortable trading in the skew direction, you can become a more advanced trader and trade against the skew as well. This is discussed in some detail in the later threads on Market Statistics. The skew then no longer becomes a relevant factor in your trading. However be careful here. You need to know that you are doing this and what it implies. Trading with the skew is the teaching mode. Trading against the skew is where the real action lies. You can't do the latter unless you're comfortable with the former.

and The problem with using Fibonacci levels as with most other technical analysis is that there is a builit in time dependence of unknown structure. Using your example of downtrend, if two traders, one using a 1 minute chart to trade from, the other using a 3 min chart to trade from were to determine fibonacci levels starting at the same high point, they would not agree as to where to place the end of the range for computing the levels. As a consequence they would not agree as to where the retracement levels would occur. Now compare that to the same two traders using market statistics starting at the same time. They would both agree what the VWAP is and the value of the standard deviation, even though they were using different chart times to trade from. This has been discussed in great detail by others. See the thread [thread=2859]Playing with the dynamic VWAPS open research[/thread] Hurst analysis is a way to analyze a time series data for fractal components. This has been discussed in some detail by Mandelbrot. I have only taken a cursory look at this so I can't really comment about how useful it might be. From what I understand there is considerable disagreement as to how to compute the Hurst exponent. Whether there is a holy grail or not isn't important. More important is learning how to trade.

I don't know. There is considerable research going on in this field associated with unstable time series evolution. Examples would be fractal analysis and other non-linear dynamic analysis (chaos theory and complexity theory). I'm in the process of looking at these in some detail, but haven't reached any conclusions yet in so far as there use for traders.

Based on the history of all financial markets, they are all unstable. This includes normal distributions which don't remain that way for very long. This does not mean however that you as a trader should not use the evolving statistics as a framework for deciding both trade direction and trade management. On the contrary, without the statistical information you are depriving yourself of what the market's price action might be like. For example, if I enter a trade, how much should I expect the market to move. The answer is simple if you are following the market statistics. It's one standard deviation.

The deviation is from a symmetric distribution which can have any shape. You seem to have a fixation that averages only have statistical significance if the distribution is gaussian. Nothing could be further from the truth. You can always define an average for a finite sampling of data. The question that you should be asking is, is the average stable or does it change if you take a different sampling of data? Yes, and that's why you want to use statistical data. There are too many variables to ever possibly know anything deterministic about a single trading event. If you want to argue that the price data is not the proper variable to use in the statistical analysis, then you are a believer in the existence of hidden variables. Until you define what those variables are however, you don't have a valid argument against using statistical analysis.

Sorry for the delay in getting back to this. What I sense here, is a need for a better understanding of market probabilities and how that helps your trading style. The market statistics threads will help you in this regard, which is why I wrote them. They are NOT a methodology(although I do present some methods along with them). It isn't necessary for you to read all the threads. In fact if you just read the first few and look at the videos you will have a good working knowledge of market statistics. I think once you have a feel for the concept of standard deviation, you will understand my statements above about why you should not trade bars whose range is larger than 1 standard deviation

What I personally do, is look at the the SD from the end of yesterday and see if there is a position trade that I could enter for today. If there isn't then I will start a computation of the data just for today and wait until the SD gets large enough compared to the bar range before initiating a trade for today. Again this has all been discussed in the Trading with Market Statistics Threads I gave you a quantitative definition of volatility. It is a measure of the deviation of the data from the mean. If I enter a trade at the mean, I expect the market to move 1 standard deviation. How it gets there is not of any concern. It could move there smoothly or jiggle its way there. If you wash out all the jiggles(which are just standard deviations of the data on a shorter time scale which I presume is what you mean by noise) then you miss the opportunity to define a good entry and a good exit point.

The average I am referring to is that of all trade data over the time frame which you are looking at. So, for example, if you are a day trader and your chart data starts at 9;30 this morning, you would average all the data from 9:30 till the present. For a complete discussion of averages, standard deviations, see the [thread=1962]Trading with Market Statistics[/thread] Threads and No if you start every average computation at the same starting time. Yes if you start the computation at different starting times. For example, if you compute the average of the trade data starting at 9:30, it will look the same on every chart you use, 1 min, 2 min 3min etc. That's the beauty of this type of statistic. It's time frame independent. If however you start the computation including yesterdays data along with today's, then the average will have a different value. No. If you filter out the noise you essentially filter out any trade. Noise is where the action is. In the words of Nihabaashi "To fear volatility is to fear profits". Again a complete discussion of this is in the Trading with Market Statistics threads.

This would be correct only if the number of trades at each price were identical, which is usually not the case. To determine the median, you have to order all the trades from low to high, add up the total number, then find the price where the half way point is located. Example: 1,2,2,2,2,2,3,4,5. There are nine trades between 1 and 5. Half way point is 2, not 3.

There actually is a much simpler analytic approach in determining what time frame you should use for trading. The idea is based on the premise that most traders are actually trading market noise: the volatility of the market as it oscillates up and down during the day. The time frame to chose then is one in which the range of each bar is much less than the market volatility. Once you know the market volatility, it's a simple matter to choose a time frame. So quantitatively, what's the market volatility? The market volatility is one standard deviation of the price data with respect to the average price. So for example if the standard deviation is 20 ticks, choose a time frame in which the range of each bar is much less than 20 ticks. If you are using a time frame for which the range of the bars is more than 20 ticks then you are using too long a time frame.

Good observation Karish. The second computation may be simpler to do for those who can't use the exact definition of the moment.

If you scaled in at VWAP and there was no retrace back toward break even, it suggests the market is strongly moving against you. You might want to condsider a reversal trade provided you are still within your risk tolerance for the day. I understand your dilemma. I introduced the approximate skew because it was easy to visualize, and required no further computation on the part of the trader. However since Head did the complete computation of the third moment, I took a closer look and it seems like that may be a better alternative.

Sorry Head, but this is incorrect. A skewed distribution MAY return to a SYMMETRIC distribution, which is not the normal one. Notice my emphasis on MAY and SYMMETRIC. Using the exact definition of skew which you presented, a skew of zero does not imply anything about the distribution being normal, only symmetric. Example would be a double peaked distribution which is far from normal. There are many others. Moreover, there are many days when the skew never returns to zero. I learned something new from you HEAD when you presented a way of looking at the skew using the exact definition of the third moment. There is more there than I think you realize, certainly more than I originally realized using the approximate definition. One of the most difficult problems traders have commented on to me using market statisitics is how to decide which direction the market will go once it touches a standard deviation point. Knowledge of skew action can help in this regard. Perhaps I will start a new thread on this if I can find the time. I agree with this. I hope I haven't mislead anyone into thinking that what I presented is a "system" for trading. It is rather a way of looking at the data from which you have to develop your own trading style. I presented some simple ways that you might use market statistics to trade, but in the final analysis every trader must develop his/her own style.

Darth, I'm glad that you were motivated to learn something about statistics. It's a difficult subject. I know you can drive something through, I don't think a truck. But perhaps you would like to tell us what you learned in the past year that gives you this feeling. It's tough to comment on so much in one discombobulated sentence. But you are forgiven considering you posted it at 3 am in the morning. But here is my take on it. THERE IS NOTHING THAT I PRESENTED THAT ASSUMES A NORMAL DISTRIBUTION. One does look at a finite sample population and that sample population has a mean, a standard deviation, a skew and a kurtosis. Those are the first four moments for the distribution. This implies nothing about the distribution being Gaussian(ie normal). Every finite distribution has these properties. These moments can and do change with additional data added to the population. I think I have shown this numerous times in the videos. How you might use this information depends on your trading style. I presented some simple ways as example, but there are many others. The question you might raise is: Is this statistics the best way to view the data or are there other ways. At the moment this is the best I know. There are other alternatives such as fractal analysis a la Mandelbrot or perhaps some kind of Bayesian analysis. That is perfectly correct. But I couldn't understand price action without knowing what the volatility looks like, how the skew is changing and where the mean is at the moment. I won't comment on this since it requires a whole new thread for discussion. The debate between the frequentists and the bayesians has been around for ever. Your comment doesn't add anything to the debate.

This is essentially correct Blowfish. Your success as a trader depends more on how you manage a trade then on what methods you use to enter a trade. Darths comments however are too extreme. I will comment below

The problem with that AgeKay, is the VWAP is volume weighted. The front month contract has little or no volume going back 6 months. Consequently the VWAP will be essentially flat and then show a sharp spike in the front month data as the volume picks up.