# Tag Info

12

Seeing a pattern in a chart is the finance equivalence of a Rorschach test---the discerned pattern says more about the person than the image. And really, if you want to trade that way, you may as well use astrology. Your real question seems to be: How can I accept or reject the hypothesis that Bollinger bands are an acceptable trading signal? For ...

12

You can either reuse the last computed EMA, or fill-forward the previous period's sample data and recompute the EMA. I generally prefer the second option, which should cause a decay. Only go for the first option if your application won't change its logic based on missing data.

9

These moving strategies are also known as trend-following. If returns have positive autocorrelation, hurst exponent > 0.5 that would be good for these strategies.

5

Just like everyone else that's been down this path, you'll have to prove this stuff to yourself. Make sure that one of your competing tests is a "noise test" where the decision to go long or short is driven by a meaningless random number generator. If your method can't statistically outperform noise, then your method is not doing anything meaningful.

3

As can be seen from this example from Yahoo!Finance this should not happen (click on "+ The adjusted close"): https://help.yahoo.com/kb/finance/SLN2311.html?impressions=true Another more complete example can be found here: http://luminouslogic.com/how-to-normalize-historical-data-for-splits-dividends-etc.htm So my explanation is that this is a glitch in ...

3

In fact there is an exhaustive paper on this issue available now: "The Trend is not Your Friend! Why Empirical Timing Success is Determined by the Underlying’s Price Characteristics and Market Efficiency is Irrelevant" by Peter Scholz and Ursula Walther, Frankfurt School Working Paper, CPQF No. 29, 2011 Fascinating read - highly recommended!

2

You should look into inhomogeneous time series operators. The original reference for this work is Zumbach and Muller (2001). An excellent introduction to the material can be found in An Introduction to High-Frequency Finance, starting on page 59. I also found online a book chapter from Modeling Financial Time Series with S-PLUS that includes code for the ...

2

Trading days.................. Days where there is pricing information. Any moving average is a moving average of pricing information. Not the times where there can be no pricing information.

2

Let's approach the answer to your question from a pure trading and risk management perspective because looking at it from a mathematical standpoint nor quant standpoint does not yield you much here: 1) Bollinger bands are nothing else than standard deviation envelopes around the mean of past prices of the underlying. So, as far as simple probabilities go, ...

2

def bbands(price, length=30, numsd=2): """ returns average, upper band, and lower band""" ave = pd.stats.moments.rolling_mean(price,length) sd = pd.stats.moments.rolling_std(price,length) upband = ave + (sd*numsd) dnband = ave - (sd*numsd) return np.round(ave,3), np.round(upband,3), np.round(dnband,3) sp['ave'], sp['upper'], ...

2

The TA_lib Technical Analysis library here has open source code for numerous indicators.

2

First of all, I do not believe the "optimal smoothing" of an estimator (like the mean or the variance) and the "regression case" are the same. The smoothing of an existing estimator (like mean or variance in the blog post), is an univariate problem, where the regression is a multivariate one. In the regression case, you should be able to change the ...

2

Did you try solving for $w_k$? $$\bar{r}_t = \sum_{k=0}^p w_k r_{t-k}$$ $$\bar R = W R$$ Since you probably have $t>>k$, you can solve for $W$ using OLS $$\bar R = W R +\varepsilon$$ -- UPDATE You can try applying Kalman filter. Here, your state evolution is $$r_t=\mu+\varepsilon_t$$. You introduce new vector $x_t=(r_t, r_{t-1}, \dots, ... 1 Thanks @Aksakal for suggesting Kalman Filter. Here I provide more details. We will view it as a state-space model: $$\begin{split} z_t &= A_t z_{t-1} + B_t u_t + \epsilon_t, \\ y_t &= C_t z_t + D_t u_t + \delta_t, \\ \epsilon_t &\sim \mathcal{N}(0, Q_t),\ \delta_t \sim \mathcal{N}(0, R_t), \end{split}$$ where$z_t\$ is the latent variable, ...

1

The Technical Analysis of Financial markets is considered as a milestone of the matter. I suggest to read that before starting to test your strategy. It explains well the use of each indicator, providing the economic reason behind that and when it is useful to use that; moreover, the book deals the stock market with mainly, as you need for. In my humble ...

1

A very good reference can be found here: http://www.asiapacfinance.com/trading-strategies/technicalindicators

1

I think wiki calculated upon new way and your excel calculated upon Wilder way (Wilder book). I have same issue when use both method. Look like new Metastock 5 software offer both method.

1

Try to plot the rolling mean against your quotes for SP and see if it makes sense. Although you line of code to compute the rolling mean is correct, there might be something wrong in the data that you pass as input.

1

Two good starting points are here: Allen, Helen, and Mark Taylor. “The Use of Technical Analysis in the Foreign Exchange Market.” The Journal of International Money and Finance, June 1992, pp. 304-314. Lui, Y.H., and D. Mole. “The Use of Fundamental and Technical Analyses by Foreign Exchange Dealers: Hong Kong Evidence.” The Journal of International Money ...

1

A simple solution to what you may be looking for is: Bollinger Bands: It is an a channel with the center being an MA with a roof of being K Stddevs and a floor of -K stdves. See also: http://en.wikipedia.org/wiki/Bollinger_Bands You can use this to see "how far outside of the channel of "reality" does your model go, i.e. by creating a tight band around ...

1

Apparently in Forex markets, technical analysis is becoming less and less effective: http://forextradingtipsdaily.com/fed-paper-power-of-technical-analysis-in-forex-is-declining/ I wonder if this is also the case for equity.

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