Saturday, January 30, 2010

Outlook for February 2010

  1. The Overbought level is 5478, the Oversold Level is 4297
  2. The Phantom Price Line is at 4888, BSAR is at 4628
  3. The Important Pivots would be, 5353,5306,5228,5182,5032,4982,4932,4882,4832,4782,4732,4582,4536,4458,4411
  4. The Nifty is buy on dips, keep SL @ 4628
  5. The PCR for Nifty Options for January: µ=1.12, s.d.=0.13 σ=1 band =1.25 to 0.99; closed on 0.92; we could expect some rampant Put writing now. Also Supports the short term Bullish view
  6. In last two three months we have seen historically quiet periods, but don't be mistaken
  7. All weekly indicators are near their lower sigma

the central limit theorem

In probability theory, the central limit theorem (CLT) states conditions under which the mean of a sufficiently large number of independent random variables, each with finite mean and variance, will be approximately normally distributed (Rice 1995). The central limit theorem also requires the random variables to be identically distributed, unless certain conditions are met. Since real-world quantities are often the balanced sum of many unobserved random events, this theorem provides a partial explanation for the prevalence of the normal probability distribution. The CLT also justifies the approximation of large-sample statistics to the normal distribution in controlled experiments.

In more general probability theory, a central limit theorem is any of a set of weak-convergence theories. They all express the fact that a sum of many independent random variables will tend to be distributed according to one of a small set of "attractor" (i.e. stable) distributions. For other generalizations for finite variance which do not require identical distribution, see Lindeberg's condition, Lyapunov's condition, Gnedenko and Kolmogorov states.

The central limit theorem states that given a distribution with a mean μ and variance σ², the sampling distribution of the mean approaches a normal distribution with a mean (μ) and a variance σ²/N as N, the sample size, increases. The amazing and counter-intuitive thing about the central limit theorem is that no matter what the shape of the original distribution, the sampling distribution of the mean approaches a normal distribution. Furthermore, for most distributions, a normal distribution is approached very quickly as N increases. Keep in mind that N is the sample size for each mean and not the number of samples. Remember in a sampling distribution the number of samples is assumed to be infinite. The sample size is the number of scores in each sample; it is the number of scores that goes into the computation of each mean.


Thursday, January 28, 2010

watch this drama

  1. DIIs are buying, and did I say buying yet?
  2. PCR is @ 0.98 (median=1.07) 5 EMA is @ 0.97 (median=1.07), 10 EMA 0.99 (median=1.09);
  3. Tomorrow they might take a breather from Rampant Call Writing!
  4. Keep Biased Stop And Reverse in front of your eyes while taking any decisions
  5. Will answer your questions during the weekend

Wednesday, January 27, 2010

So where are we?

  1. Nifty, after making a 52 week high of 5310.85 on 6th Jan 2010 made a low of 4833.05 today
  2. Nifty is in downtrend in Short Term Daily and Weekly charts.
  3. Indicators are in oversold zone, so a relief rally on Thursday or Friday can't be ruled out
  4. Remain Short if you want to but -> Do not go long unless Nifty goes above the daily BSAR level
  5. Conservative Swing traders could wait for Nifty to get above Weekly BSAR Levels, to initiate longs
  6. Please do not mail me your questions, post them here as comments

Monday, January 25, 2010

the normal probability curve

    The 68-95-99.7% Rule

    All normal density curves satisfy the following property which is often referred to as the Empirical Rule.

  1. 68%

    of the observations fall within 1 standard deviation of the mean, that is, between µ-σ and µ+σ .

  2. 95%

    of the observations fall within 2 standard deviations of the mean, that is, between µ-2σ and µ+2σ.

  3. 99.7%

    of the observations fall within 3 standard deviations of the mean, that is, between µ-3σ and µ+3σ .

  4. Thus, for a normal distribution, almost all values lie within 3 standard deviations (or any measure of volatility) of the mean.

    My observation has been that each segment within any given Normal Gaussian Distribution, consists of at least one Normal Gaussian Distribution, and in turn is a member of a large Normal Gaussian Distribution. Fractals? Or Billions!

Read this if you are crazy

Sunday, January 17, 2010

You said it

  1. I am in receipt of your questions in the e-mail, and comments on different blogs. Please allow me to answer all of them at this one place
  2. First VK ji, thanks for your comment, Nifty is in uptrend but overdue for correction. It seems government is planning some strict fiscal measures or something that might not be good for capital markets sentiments
  3. Gentleman with a Non English name, I couldn't understand what you were asking for.
  4. Nifty Trader ji, we have dark clouds all over, only waiting for lightning
  5. Dharmesh ji, I have decided not to discuss technical analysis anymore, it doesn't benefit me in anyway, while people who crucify their Prophets, (profits) and later worship them, find a way to make me angry.
  6. Rishi ji, I don't chase volatility, but let volatility chase my trade. There are three kinds of people that are trading in this market, viz, Punters, Swing Traders, Investors. Punters are those who fancy that they could handle the volatility. Swing traders try to determine the trading ranges and try to profit the shorter term trends within the larger term trends. Investors bet on the growth of the underlying of their investments, and hence are bullish no matter what. I am neither of the three, but try to determine opportunities as to where I could maximize my gains. So I am basically Opportunistic trader. Remember, when I had first suggested that we should trade Bank Nifty, you had expressed the situation mathematically, like so, 1 bank nifty = 2 big nifty? Doesn't this equation hold anymore?
  7. Alnesh Bhai, relax, people who come here wouldn't be loosers, Inshallah
  8. Bala Bhai, I am sorry for that, keep an eye on the table. I have included median values for all indicators so that you could benchmark respective indicators readings agains their median values
  9. SH Jain Sahib, anything that trades for a price has three stages, making higher highs and higher lows, fluctuating between an established high and low and sometimes touching, and sometimes violating a bit the previous highs and lows, like being in a rectangle price formation, and lastly higher highs and lower lows OR lower highs and higher lows, like triangles in the price formations. Any given trading strategy would only suit either of three conditions!!! So you need three strategies, one for each market situation. Basically to use as a starting point, Moving Average Lines are good for the first market state, which is also called trending market, Camarilla is good for the second state, which is also referred to as rangebound, and RSI indicator is good for markets that exhibit the triangular price formation. Triangular price formations are generally a nightmare to most of the traders.
  10. MOK ji, one can make 10 points everyday. Because all three situations discussed above are present intraday!
  11. My heartfelt thanks to Sureela ji, Amirishali ji, Mohan ji, Genius Jaggu ji, Kris ji, JK ji, and Shiv Shankar ji, Raj ji, Rajamani ji