Tag Archives: fail

Python call any C++ library FAIL

Python call any C++ library FAIL

I have tried many options from ctype, Boost Python, and painful. Nothing worked for Linux or MAC OSX. I gave up as I don’t have patience to figure it out. I abandonded the idea as none of the simpler options worked. I will just stick with what I got pushing it all through Redis.

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Visual Studio for Linux review One word FAIL

Visual Studio for Linux review One word FAIL

What a mess. Not as intuitive in Windows and nor easy to import a C/C++ project into it. I have no patience to figure it out.

https://code.visualstudio.com/Docs/editor/setup

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Why Open source business startup fail

Why Open source business startup  fail

I find this a very good article and true! Oh the horror! The example of Red Hat example is perfect when you compare it to other sizes. Also, the examples used for Facebook is good to.

For me, this does not effect me  since I like using smart open source projects like Redis or even Ubuntu Linux. I still like my proprietary solutions like Matlab vs Python. Python and R are very popular but I am pretty sure these solutions are not the right mix for my operation as it stands. So there is a decent mix out there but it just depends on your outlook and goals.

http://www.networkworld.com/article/2944222/opensource-subnet/why-the-open-source-business-model-is-a-failure.html

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Professional trading: Why 94 % of you will fail!

Professional trading: Why 94 % of you will fail!

Honestly with all the crap teaching out there, many fail. This article spells it out quite nicely on a legit website called Business Insider. It is not some sh*tty affiliate marketing site wasting your time setting up these fake reviews of some ‘bigger’ financial institute!

http://www.businessinsider.com/what-percentage-of-traders-make-it-2011-6

Highlights include:

Lack of education

There are so many teachers, strategies, books, seminars, workshops and webinars available. Where many fall short is that they do not do the research to choose the best teachers to work with. You will save a great deal of time, energy and money if you decide what type of trading you want to do before you choose a teacher.

Too many choose teachers based on the teacher’s ability to sell them, on the teacher’s reputation for making huge profits or the ability for a teacher to make it look like there will be instant profits with little effort. In my seminars I hear traders telling their war stories about the bad experiences they have had with teachers and the thousands that it cost them.

Trade without testing

The only way that you will trust your strategy is if you back and forward test it. If you do not, when you have a drawdown, you will start to question it and yourself. Then it might be too late because you could run out of money and run out of passion. Additionally, where there was support from your family, you now have conflict.

 

So you really want to further waste your money? I hope you are not that stupid cause you see some moron flying in a helicopter or sitting on a beach in Bora Bora with some 19 litle girl wanna be porn star. Gawd, the world is full of suckersw who  want to live this fake lifestyle.

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My Windows system is scaring me again why oh why do I stay on it #windows #system #fail

My Windows system is scaring me again why oh why do I stay on it

[igp-video src=”https://quantlabs.net/blog/wp-content/uploads/2015/03/My-Windows-system-is-scaring-me-again-why-oh-why-do-I-stay-on-it-windows-system-fail.mp4″ poster=”https://quantlabs.net/blog/wp-content/uploads/2015/03/My-Windows-system-is-scaring-me-again-why-oh-why-do-I-stay-on-it-windows-system-fail.jpg” size=”large”]
My Windows system is scaring me again why oh why do I stay on it #windows #system #fail

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Congrats! Open Source language MAJOR #FAIL with hell of install of working with Python and R. UGH!

Congrats! Open Source language MAJOR  #FAIL with hell of install of configuring with Python and R. UGH! Hello Microsoft DotNET?

Despite my sort of further experiments in both languages. I have failed. What horrid mess both are, As for the false hope of Python  with Anaconda, it showed some promise but when you see messages like:

If MySQLdb’s now distributed in a way that requires setuptools, your choices are either to download the latter (e.g. from here) or refactor MySQLdb’s setup.py to bypass setuptools (maybe just importing setup and Extension from plain distutils instead might work, but you may also need to edit some of the setup_*.py files in the same directory).

Depending on how your site’s Python installation is configured, installing extensions for your own individual use without requiring sysadm rights may be hard, but it’s never truly impossible if you have shell access. You’ll need to tweak your Python’s sys.path to start with a directory of your own that’s your personal equivalent of the system-wide site pacages directory, e.g. by setting PYTHONPATH persistently in your own environment, and then manually place in said personal directory what normal installs would normally place in site-packages (and/or subdirectories thereof).

 

or:

I resolved this issue on centos5.4 by running the following command to install setuptools

 

Or:

this was sort of tricky for me too, I did the following

 

or

I am experiencing the same problem right now.

http://stackoverflow.com/questions/1449130/how-to-install-mysqldb-package-importerror-no-module-named-setuptools

I still don’t know how to install MySQLdb module or Quandl. I will give RStudio credit, it has an excellent package manager where you don’t need to do this wonky crap on the command line. I gave up.

But it seems so easy on Linux. Well, I am Windows so I crawl back to all .NET and Excel and Matlab.

I tried but seriously, I think I would rather bang my head against the wall in peace. I don’t have time to waste on stuff like this. It looked promising but tossed it after than I patience could handle. It was not a good start or shall I say? Reset.

 

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#FAIL R and FSharp R provider cannot be integrated. Frig!

#FAIL R and FSharp R provider cannot be integrated. Frig!

Maybe I am missing something but finally, this path is dead after three attempts. Despite my attempts from  helpful Twitter user , I still don’get it. Maybe I ain’t smart enough but have had no issues working with many Visual Studio projects. This would be have been good.

Frig! I still cannot get R FSharp R Provider working despite this blog posted as suggested:

http://www.clear-lines.com/blog/post/Create-maps-using-R-Deedle-and-FSharp-type-providers.aspx

Other hints from:

https://github.com/david-terk/FSharpRProvider

http://bluemountaincapital.github.io/FSharpRProvider/

https://github.com/BlueMountainCapital/FSharpRProvider

http://rdotnet.codeplex.com/SourceControl/latest

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The secret shortcut to valuation when regular analysis fails: Using Monte Carlo and a ARIMA models with MA AR(1) or AR(2) simulation

The secret shortcut to valuation when regular analysis fails: Using Monte Carlo and a ARIMA models with MA AR(1) or AR(2) simulation

Hi there,

Are you interested in accurately valuing complex options and other derivatives … as well as fixed income instruments?

And doing it faster than your competition?

It’s not very straightforward to get an accurate valuation, you know. That’s because you’ll never have enough data to get a perfect picture of a given instrument or portfolio. You have to “approximate” the data or your computations will never finish!

Unless you know how to use the Monte Carlo method, of course. It’s an ingenious shortcut not many traders understand. Here’s how it works:

1. First you define a domain of possible inputs. Then …
2. Generate inputs randomly from a probability distribution over the domain. And …
3. Perform a deterministic computation on the inputs.
4. Finally, you aggregate the results.

Done correctly, this method is surprisingly accurate. Not just for individual instruments, but entire portfolios. You can even simulate an entire stock market to practice trading stocks without risk!

In fact, for situations with more than 3 or 4 degrees of freedom, formulae such as Black Scholes (i.e. analytic solutions) don’t even exist, while other numerical methods such as the Binomial options pricing model and finite difference methods face several difficulties and are impractical.

In these cases, Monte Carlo methods converge to the solution more quickly, require less memory and are easier to program.

The programming gets even easier with my latest offering to Premium members. You see, I’m just finishing up a walkthrough video that explains what you need to know about using Monte Carlo simulations.

It’s absolutely essential if you want to minimize your learning curve for this very powerful tool. Especially when I’m including all the relevant source code in R for you. It doesn’t get any easier than this!

Get get access to this tutorial now:

–>http://quantlabs.net/dlg/sell.php?prodData=m%2C3<–

Other videos will cover Stochastic Volatility … Markov Chain … Autoregressive (AR(1)) and GARCH forecasting … Bootstrapping … Dynamic Linear Modeling … and more!

Learn about the rest of Premium benefits including our HFT and Algo Development courses, software tool kits, and more!

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Good trading,

Bryan

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Which forex automated system is best, and why do so many trading robots fail within 60 day

Which forex automated system is best, and why do so many trading robots fail within 60 days?

 

==

Personally I wouldn’t use automated systems, it takes the human judgement side of things out of the equation. If you need an automated helper for FX trading, you probably shouldn’t be trading in the first place!

 

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Why popular methods of technical analysis fail to work but quant analytics or statistical analytics may

Why popular methods of technical analysis fail to work but quant analytics  or statistical  analytics may

http://www.faunusanalytics.com/marketing/article/Why_popular_methods_of_technical_analysis_fail_to_work.pdf

 

how right you are. I agree 100% with all your findings and conclusions. I have reached the same conclusions years ago. The expected value of playing heads or tails is zero, no matter what time frame is used or time horizon considered. It has been known for centuries that the outcome of a 50/50 game is zero expected gains.

You conclusions could also be viewed with the added twist that there is no harm in using a random entry, or any other decision surrogate, since your expected profit will still remain zero; which is another form of saying your expected loss is also zero. No gain, No loss.

Appreciated reading your paper, great work.

Regards,

 

The naive and unduly complicated methods is ineffective. Statistical tests show it. Efficient methods such as log-regression, being built on 10 years of historical data on multiple instruments (4-50 trading instruments with similar behavior covered by the general universal model). In this case, statistical tests show a dependence. But even then, you can not expect low-risk, incredibly high returns. Must expect loss-making quarters or half-years, and long periods of low trading activity.

You can not limit yourself to a few trading instruments. Need all the time to look for other more predictability trading instruments. For example, last year, well predicted precious metals, and this year they are harder to predict.

The problem is that all this is difficult to explain to beginners, it is difficult to sell the analyst honestly showing all the risks. Our company makes a market analyst (forecasts, trading signals) and is often sees the naive expectations of clients.

 

I have read hundreds of those academic papers and usually agree with their conclusions as I agreed with yours. But somewhere you say: “The problem is that all this is difficult to explain to beginners”. I’ll pass on that one.

I’ve posted some remarkable charts on this thread with let’s say performance results somewhat higher than the Buy & Hold strategy. I’ve said many times that I do not predict prices, that I often use random entries to get in a position. But all that is not the point.

My methods are the execution of administrative procedures, investment policies that you set from the inception of a portfolio, nothing more. As in this is what we will do if this happens. And the major point I am making is that simply by re-investing the accumulating profits, instead of doing nothing with them, one can easily achieve an exponential Jensen ratio and increase his/her portfolio performance above the Buy & Hold by default due to administrative procedures. Oh, I do make a prediction using these methods and that is in 20 years from now, the markets will probably be higher than today.

I’ve just posted on my web page a more elaborate research note:
http://alphapowertrading.com/index.php/papers/90-on-optimal-portfolio-ii

I agree with you for the most you are saying in your paper but I have different opinion in some points. Some things I see in different way.

For example in your article (page 6) “Summing up the results”, “2.Simple technical Analysis tools, including popular indicators and instruments…prevent traders from making money” – I party agree, but for “Popular tools do not allow a trader to stand out from the crowd to get bigger piece of the trader’s pie.” I fully agree.

Regarding the role of the technical analysis in trading, before 1980s most researchers criticised it and concluded that is not able to produce as good results as the buy-hold strategy (Alexander, 1961; Jensen and Bennington, 1970; Fama, 1970). However, later studies have proven the opposite (Pruitt and White 1988, Bessembinder and Chan 1995). Trading rules/systems (using technical indicators) based on past data could create excess returns and prove that usefulness of technical analysis. Such conclusions had Brock, Lakonishok and Lebaron (1992), later Bessembinder and Chan (1995, 1998), Lo, Mamaysky and Wang (2000) and many others.

Another view is from psychological aspect as behavioural finance. The premise of behavioural finance is that conventional finance theory ignores how real people make decisions and that people make a difference (Constantinides, et al., 2003). While conventional finance presumes that investors are rational, behaviour finance starts with the assumption that they might not be. As a result, we can discover market anomalies such as mispricing (psychological bias could cause prices to deviate from their correct level) and take the advantage to apply proper strategies ( such as arbitrage) to make profit.

Generally, behavioural biases may be consistent with technical analysis (Bodie, et al., 2009, pp. 395). There are chart/price patterns in technical analysis that are repeated many times in the past depicting specific investors behaviours. For example, the process of price underreaction and overreaction to public information might become visible in the form of the technical analysis as abnormal (upwards or downwards) trends.

 

“technical analysis” vs “statistical analysis”

“Technical analysis” is pseudoscience (numerology). This is only a “good” selection of the conditions and facts.

“Statistical analysis” is a science. This is an exact description of the restrictions, the definition of hypotheses and their mathematical proof or disproof. Statistical analysis was successfully applied in many fields.

Let’s use a statistical analysis for the markets.

 

Here we are all to exchange ideas and say our opinion.

I did not say that Technical Analysis (TA) is science. I implied that TA is useful as assistant tool to make trading decisions. Lately, most academics agree with that.
We all know the debate between academics and practitioners regarding TA (art or science). Most say that TA is art not science, ok? Let’s say technical analysis is ‘Art’. I will present only the following:

John R. Kirby, seeking to clear-up the art vs. science debate, quoted highly regarded Technical Analyst Ralph Acampora: “‘Art’ means a skill acquired by experience, study,
or observation. ‘Science’ is a body of knowledge with its own axioms, rules, and language (Technically Speaking, 2005, January).”.

TA is not a standalone “art’ – it requires the help of statistics. Statistics give an indication of the strength of a trading system or set of trades at any point in time. Technical stock analysis and trading statistics are important to identify areas of your trading which require improvement and help to illustrate your trading characteristics. They inform you if you are on the right road to success.

Finally, the goal is to make profits with low risk in a consistency way. Every one has developed his own style (TA, statistics, data mining, AI, etc).

 

Statistics give an indication of the strength of a trading system or set of trades at any point in time.

Can you please give examples of TA articles, which assess the probability of non-randomness of the results of testing of the trading systems? I have not seen the TA where the notion of “probability” is not in the most naive form of the arithmetic mean.

 

There are pockets of non-randomness caused by trader effects and other events such as news events. These are what the pro discretionary trader seeks to exploit.

Standard statistic methods are far too crude a tool to apply to price action.

 

Consider the Brownian processes. Without statistical analysis, we find a lot of false “are pockets of non-randomness”.

 

The markets are not a true random brownian process. You need to learn about ‘trader effects’. A skilled trader can find an edge.

Many people have been down the statistical analysis road. It leads nowhere.

 

Models simplify reality and require assumptions and /or simplifications – so one model cannot capture all aspects of the real situation (world). Brownian motion, allthough it helps, is just one theory that attempts to explain stock market fluctuations, along with the random walk theory and Markov process.

If the stock market is truly random, as described by Brownian Motion, then the market is unpredictable and efficient. Efficient market is that it is impossible to ‘beat the market’ since all relevant information is already reflected in the market price.

 

I agree that the market does not Brownian process. Brownian process is an idealization, and all real processes different from Brownian process.

But, warning! First experiment. If you observe and analyze the time series is actually the ideal generated by the Brownian process (but you do not know it), you “find” many “patterns” But these patterns are false and not will be confirmed by new data.

In the second experiment, you’ll observe the nonideal Brownian process with a small deterministic components. But in this case, the randomly noise can hide the real pattern.

Market data is like that. The market is a composition of two processes – the strong randomly proccess and weak deterministic process. Without statistics, you’ll never be able to distinguish between false and true patterns. Technical Indicators result of systematic detection of false patterns.

 

 

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