Tag Archives: reduce

Google says machine learning AI reduce data center energy consumption by 30%

 

\Another claim of fame. This is good for mankind but there are the other nefarious. I just talked to a content editor of a large book publisher who told me most banking/hedge fund managers are not real believers in machine learning stuff for the company. They will however put together small teams to research to appease their clients who expect them to explore these topics. This is the result of a hyped industry. Also, remember these same managers are the ones who are ultimately signing the paychecks of these researchers.

Anyhow, this is the general concept until some team comes up with an entire approach to machine learning working for the automated space. As you know many of us can be wrong. I made some videos on this below.

 

Don’t forget this Monday Aug 27, I will be doing my webinar on this topic. I just been asked to ass Easy Language for Tradestation as well.

 

How to convert forex mt4 to python programming webinar

 

Gold Price Prediction Using Python Machine Learning

 

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USA Fed battle to reduce balance sheet vs GDP %

USA Fed battle to reduce balance sheet vs GDP %

The battle is on after 2016 where they recognize this needs to be drastically reduced going 2021

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Will quantum computing reduce the importance of HFT?

Will quantum computing reduce the importance of HFT?

This will be affected by the next generation of computing for banks like Goldman Sachs, RBS, etc

http://www.bbc.com/news/business-35886456

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New Facebook Instragram C++ pattern to reduce latency for HFT?

New Facebook Instragram C++ pattern to reduce latency for HFT?

Facebook engineering is quite smart with thesse new C++ patters. Remember they brought Cassandra NOSQL

https://code.facebook.com/posts/1661982097368498
http://instagram-engineering.tumblr.com/post/121930298932/c-futures-at-instagram

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Use statistics and probability with normal distribution returns for price movement analysis and exposure to reduce risk of trading loss?

Use statistics and probability with normal distribution returns for price movement analysis and exposure to reduce risk of trading loss?

There is a video in the link!

Can you predict which days will be up or down for trading potential? If not, see below using stats and probability as those days are not much as it appears. There are many things against you. What is below is sort of mumbo jumbo but this is a crust of my upcoming analytics signalling service. This could be scary if you fully don’t understand so see the last two paragraphs.

Sometimes, your bell curve may show fat tails which could spell out extreme profit potential or high risk potential:

See more

There is so much learn at this posting.

I will be posting some exciting resource for all my members of my Quant Elite service.

NOTE I now post my TRADING ALERTS into my personal FACEBOOK ACCOUNT and TWITTER. Don't worry as I don't post stupid cat videos or what I eat!

How to use statistics and probability with normal distribution for price movement analysis and exposure to reduce risk of trading loss?

How to use statistics and probability with normal distribution returns for price movement analysis and exposure to reduce risk of trading loss?

There is a video below!

Can you predict which days will be up or down for trading potential? If not, see below using stats and probability as those days are not much as it appears. There are many things against you. What is below is sort of mumbo jumbo but this is a crust of my upcoming analytics signalling service. This could be scary if you fully don’t understand so see the last two paragraphs.

Sometimes, your bell curve may show fat tails which could spell out extreme profit potential or high risk potential:

Fat Tail, Risk Budgeting, Factor Analysis & Stress Testing

http://www.risk.net/risk-magazine/analysis/1603830/capturing-fat-tails

In Excel, you could use Data Analysis add in with Descriptive Statistics for summary stats. Use returns for input.

Mean is average return of index (i.e. S&P 500) over historical period of asset your analyze. It should be always be positive if you analyze S&P since 1960s.

Median is middle of data set. If median is higher than mean that says the average is more positive over the mean or opposite would be more extreme if negative.

Standard deviation (SD) is dispersion of the distribution data. i.e. 68% of standard deviation 1 lies within the mean. Could also calculate normal vs actual with percentage for each. 68% of trading days that lie within SD 1the mean of the trading distribution. 95% will be for SD 2 and 99% of SD 3.

Kurtosis and skewness means if data is normally distributed. Kurtosis is a measure of how the data has peaked. High skewness can show the data could peak more than usual within a normal distribution with fatter tails. If you have a negative skewness, that means the fat tail are negative which means than the positive tail. Extreme negative movements are more likely to happen than positive.

Probabilities for new bins of frequencies within the distribution table. Thus the frequency of ranges from within the distribution table

=# of trading days in interval/total number of trading days in distribution table (in formula cell, press F4 for $ around on denominator to fix cell). This is represented in a cumulative representation.

You could also filter returns to understand subsets of data. We could look at an average of a subset.

Data->Filter

Average return is calculated is the same as mean.

Want to understand the negative and positive of the returns of each average return with Data->Filter

If you calculate the frequency of positive vs negative, you could estimate market direction with probability. Predict average return when S&P 500 will go up when you long for x days, you forecast the daily return of this period. ****You will soon see that the percentage the market goes up is slim with negative days, transactions costs, and volatility against you. The forecasted’ “Average return” tells you this.

Also calculate the standard deviation (SD) returns as well with SD of 1-3 above the mean. Calculate the upper and lower of each SD above/below the mean. You could find the average number of days that lie within these ranges.

In summary, be aware:

In essence, since S&P 500 moves less at the extreme, it is harder to generate revenue with other assets. In OTW, our trading opportunities are minimal when you factor in AVERAGE returns on a daily basis when volatility is low.

*** You can also say that there are greater risks in the extremity of the tails of the distribution. They can be more probable than you think so there could be days where you could get wiped out in your account. There could be for example of 1 day per 100 where the market moves more than 3% which could wipe you out if you have the position the wrong way.

You could apply this logic over any period on any asset.

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How does one reduce latency in your high frequency trading platform aka HFT by 20x?

How does one reduce latency in your high frequency trading platform aka HFT by 20x?

According to this marketing hype:

Reducing Latency By 20 x

Thread Manager vs numactl taskset hwloc

I read it, but yeh Deltix claimed the same. Unless you got millions in your trading account, I don’t think you need to worry.

Thanks to Sholom for sending

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How to use performance metric like Sharpe Ratio to reduce your drawdown in your trading?

How to use performance metric like Sharpe Ratio to reduce your drawdown in your trading?

Again, thank to my NYC source for providing this

http://www.stat.cmu.edu/~abrock/algotrading/page9.html

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Finally RHadoop running with R and Hadoop with rmr Map and Reduce bridged thanks to this tutorial

Finally RHadoop running with R and Hadoop with rmr Map and Reduce bridged thanks to this tutorial

These links made it happens to someone who commented on my last post on what started this whole journey. Thanks to them.

https://github.com/jeffreybreen/tutorial-201203-big-data

https://github.com/jeffreybreen/tutorial-201203-big-data/blob/master/README

http://jeffreybreen.wordpress.com/2012/03/10/big-data-step-by-step-slides/

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Indian Finance ministry planning to reduce STT & Stamp Duty.

Indian Finance ministry planning to reduce STT & Stamp Duty.

algotradingindia.blogspot.com

Indian finance ministry is planning to reduce duties on transactions in equities and currency derivatives. It is considering a cut in the securities transaction tax (STT) as well as a reduction in stamp duty on ‘futures and…

 

heating up with cool reforms underway. time to gear up!

 

 

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