12 votes

Theoretical justification for technical analysis

The answer to your question about the theoretical justification for technical analysis depends on the price series being analyzed. There is some evidence for a few technical indicators to have ...
kurtosis's user avatar
  • 2,900
7 votes

Theoretical justification for technical analysis

Really great question. Having studied finance academically, in an academic setting, you will always be told that technical analysis is non-sense. In the world of pure academics, the efficient market ...
Jan Stuller's user avatar
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6 votes
Accepted

Open source software for stock screening and scanning using technical analysis?

I think the most sophisticated solutions are to be found within the R universe. One package that comes to mind is the quantmod package. You can use it to download ...
vonjd's user avatar
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6 votes

How to calculate the JdK RS-Ratio

I think the normalisation step is incorrect. Since we would like have 100 as our baseline, it should be 100 + ((value-mean)/stddev + 1). Then we get fairly realistic results. See the following Python ...
Amateur's user avatar
  • 67
5 votes

Technical Analysis in HFT

Quantitative Finance is different from Technical Analysis. The essense of the difference is succinctly summarized in "Foundations of Technical Analysis: Computational Algorithms, Statistical Inference,...
zer0hedge's user avatar
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5 votes

Open source software for stock screening and scanning using technical analysis?

Being the question tagged as python and given I look for small challenges for my platform, backtrader, I took the chance to see ...
mementum's user avatar
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5 votes

Theoretical justification for technical analysis

The theoretical justification for technical analysis (TA) is less about market (in)efficiency; and more about prices as a signal of sentiment and positioning biases, that are neither always neutral ...
demully's user avatar
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4 votes

Reference request : Introductory technical analysis

For me as a beginner, the best book was Technical Analysis of the Financial Markets: A Comprehensive Guide to Trading Methods and Applications from John Murphy. It was published in 1999 (or so),...
Peter's user avatar
  • 299
4 votes

Data mining of financial time series and pattern discovery - beyond technical analysis?

I think it is important to understand the following: Technical analysis is not rigorous not because of the used data per se but because of the used methodology! Classical technical analysis uses ill-...
vonjd's user avatar
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4 votes
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Information available to traders

Unmatched buyers and sellers prices are called bid/ask offers. What you are referring to is the order book. Yes, this is something you can see in real time if you subscribe to it with your broker (L2 ...
Yannick's user avatar
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4 votes
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Should there be a relation between stocks when used as input data for integrating Technical Analysis with Machine Learning?

There are a few exclusions that I have commonly seen: Excluding thinly traded stocks. The price that shows up in your data feed may not relate to actual tradable prices. Filtering for ADR/Pink ...
JoshK's user avatar
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3 votes

Appropriate way to normalize Bollinger Bands?

Specifically for using Bollinger bands, you could use the %B indicator. This will scale your price data to the 0 to 1 range ( easily adjusted to -1 to +1 range ) which is convenient for the Sigmoid or ...
babelproofreader's user avatar
3 votes
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Appropriate way to normalize Bollinger Bands?

You may notice that the difference between the middle bands and upper and lower bands is simply a constant of realized standard deviation of price. If you want to feed a prediction algorithm some ...
David Addison's user avatar
3 votes

Technical Analysis in HFT

HFTs use market microstructure analysis to construct their own trading signals. MACD/RSI etc are all timeseries based indicators, whereas HFT data is not uniformly spaced so if those signals had any ...
wildbunny's user avatar
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3 votes

Stateful Technical Analysis Indicator Libray For Python

Have you tried TA-lib? It supports RSI.
brilhana's user avatar
3 votes

Backtesting of value and technical analysis

I think that it may be very simple but since I just started in the quant finance it would be great to have some feedback and recommendations about how to improve my backtesting. From my ...
amdopt's user avatar
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3 votes

Data mining of financial time series and pattern discovery - beyond technical analysis?

Here is my understanding of when technical analysis and mathematical techniques differ. Technical analysis predominantly utilizes three things: Price levels Indicators on price levels Trading using ...
Donny Lee's user avatar
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3 votes
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Do we need to lag values for backtesting?

Because SMA value for a certain day includes that day's closing price. But before the market closing time, obviously it isn't known (because it's in the future), you only know yesterday's closing ...
sashkello's user avatar
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3 votes

Using candlesticks for Stock price direction prediction

The accuracy of a model is only 1 factor in determining usefulness. Aside from the accuracy, it would help to determine how you would implement it in a simulated trading environment and look into the ...
amdopt's user avatar
  • 4,338
2 votes

Open source software for stock screening and scanning using technical analysis?

I would recommend using Python because it can be downloaded for Windows or Mac and is available in almost all Linux repositories as standard. Once you have Python installed you can use any of the ...
babelproofreader's user avatar
2 votes

Open source code based on quandl for security analysis and options priming

This Quandl Page provides you the informations you need: a lot of programming languages and other tools are linked to Quandl.
simmy's user avatar
  • 585
2 votes

Reference request : Introductory technical analysis

A good book is Technical Analysis Explained by Martin J. Pring Its very well written and very intuitive. Its a very important book on the topic.
EconJohn's user avatar
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2 votes
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Calculate Exponential Moving Average for a specific time frame

First, let's assume (hypothetically) you want to compute 5-day EMA from data sampled daily. Then $k_D=2/(N+1)$, here $N=5$, so $k_D=0.333$ Now assume you want to use data sampled every 5 minutes. ...
nbbo2's user avatar
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2 votes

What is an Efficient way to calculate Simple moving average without saving previous N period values?

This is impossible. You need to remember the tail. I'd suggest using exponential smoothing in this case. Otherwise, for a simple moving average you'd have to apply some kind of an approximation. ...
Aksakal almost surely binary's user avatar
2 votes
Accepted

How can I reproduce the experimental verification of the “False Strategy” theorem plot?

Up to the presentation details, the combination of beta and Sharpe distribution function gives the plot data. Below is the code to compute and plot the median value and a ribbon between the 25th and ...
shabbychef's user avatar
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2 votes

Does historical backtest data mean anything?

There's a field of study called Statistics, which to a large extent tries to answer questions like that both in a financial setting and in experimental sciences. Try to read something about it. To ...
LazyCat's user avatar
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2 votes
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Does historical backtest data mean anything?

If your model is only relating to historical price data of that single stock, then the model wouldn’t be useful. Historical price data is stochastic, and a lot of theory in financial mathematics is ...
aalberti333's user avatar
2 votes
Accepted

stochastic fast vs. williams r

Both measures express where C is within the interval from L14 to H14. %K ranges from 0 when C is at the 14 day low, to 100 when C is at the 14 day high. %R ranges from -100 when C is at the 14 day ...
Alex C's user avatar
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2 votes
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How can I forecast the Exponential Moving Average of the next day?

You can forecast your time series $(X_t)$ as follows $$F_{t+1} = k X_t + (1-k)F_t,$$ where $F_t$ is your forecast for today and $X_t$ the observed value for today (today's log-return). Note that the ...
Kevin's user avatar
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2 votes

What is market sensitivity and momentum sensitivity?

Market sensitivity is beta of your portfolio returns to market return, momentum sensitivity is beta against your momentum returns. You'd likely want to run a multiple regression of your portfolio ...
Chris's user avatar
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