Tag Archives: Quant Analytics

Introducing my New entry level Quant Analytics Lite version

Introducing my New entry level Quant Analytics Lite version

This is only execlusive through my new broadcast email which you can access here

 

Mobile friendly sign up (corrected)
http://quantlabs.us8.list-manage2.com/subscribe?u=2ac8a458242a819e941db485f&id=a25df28306

or Desktop

http://quantlabs.net/membership.htm

Here are the purchase links as described

 

Paypal:

http://www.quantlabs.net/academy/?wp_eStore_subscribe=47

Stripe Purchase (NEW)
http://quantlabs.net/academy/quant-analytics-lite-registration/

 

 

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3 month HALF PRICE deal of Quant Analytics with no need to renew

3 month HALF PRICE deal of Quant Analytics with no need to renew

Listen up! Not everyone is getting this last chance deal I will be posting for my 3 month subscription deal on my Quant Analytics service. This brings down your cost to under $50 per month. This is just a 1 time payment for 3 months access.
Remember I already added my systematically generated reports which include:

 

1. Federal Reserve deep dive reports with forward looking data to identify USA economic trading opportunities and ideas

2. Forex volatility to showcase the best currency pairs for maximum opportunity. So why trade currency pairs you may never earn from unless you are willing to use extra risky leverage from your broker?

3. A new European Stats report to identify short and long opportunities for major EU member countries.

I did checked a series of 5 trading calls last week which resulted in ALL being  profitable when the markets were slightly down for the same period! I am getting sort of confident with this process.

In the meantime, I decided to test out the response of a 3 month subscription (e.g. $149) to my Quant Analytics. I may pull this if there is not enough interest in this price point. In summary, consider this deal on for a very limited time.

>> Get your LIMITED deal here <<

 

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Trial offer to Quant Analytics monthly service removed

Trial offer to Quant Analytics monthly service removed

Due to abuse, I have removed this trial offers. Also, note that there are no refunds at all. We need to ensure we have FULLY COMMITTED members into our high performing members.

If you want to join and are full committed, JOIN HERE 

https://quantlabs.net/analytics/order-analytics/

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!

Quant analytics: Options Pricing Greeks delta, gamme, vega, rho, theta, C++ programming

 

Quant analytics: Options Pricing Greeks delta, gamme, vega, rho, theta, C++ programming

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algo

 

Shows sensitivity to an options price

 

Example:

Contractual time life of 1 year T = 1.00

S(stock price)=100

K=100

v=30 percent

r=4 percent

Div yield=0% (no dividend)

OPTION price also known as Black Scholes (BS)=13.75

 

Delta = change in OPTIOn price with respect to change in Stock price.

if stock price changes, how sensitive will BS be. All Greeks are first derivatives. If

 

detlta is .6, if stock price changes so will the option price but by 60% of the stock price

 

change. Delta is a sensitivity for the stock price. Delta is a percentage between 0 – 1.0.

 

As it converges to 1, the stock price increases faster. As stock prices lower, option

 

prices converges out of the money.

 

Gamma=Change ins DELTA with respect to change in stock price. Gamma is second derivative of

 

stock price but first derivative of delta. Longer term of gamma of call option vs time to

 

expire also indicates lower delta. Delta peaks at the money when the option is at the

 

money. This is where the delta is changing the most rapidly. After the peak, the delta

 

converges to 1 but becoming more stable. Delta converges more stable as it converges from 0

 

and the rate of change is slower.

 

Vega=Change in OPTION price with respect to CHANGE in volatility. This is significant since

 

the sensitivity is high. The higher vega means the option price is change (or more

 

sensitive) to changes in volatility. The longer the term, the more sensitive as vega grows

 

as the option life grows. Gamma peaks at the in the money.

 

Rho=Change in OPTION price with respect to change in interest rate. It is less sensitive as

 

compare to other inputs of volality. Option price is more sensitive to changes in

 

volatitlity versus interest rate.

 

Theta=Change in OPTION price with respect to change in Term (T). This is known as time

 

decay. This is always negative. As time passes, the option and gets closer to expiration,

 

it becomes less valueable. Time erodes the value of the option.

 

 

C++ Programmatic calculations include:

 

Options Pricing Greeks (check Option type is Call or Put as well)

 

// Black-Scholes Delta

double BSDelta(double S, double K, double T, double r, double v, char OpType)

{

double d = (log(S/K) + T*(r + 0.5*v*v)) / (v*sqrt(T));

if (OpType==’C’)

return N(d);

else

return N(d) – 1;

}

 

// Black-Scholes Gamma

double BSGamma(double S, double K, double T, double r, double v)

{

double d = (log(S/K) + T*(r + 0.5*v*v)) / (v*sqrt(T));

return f(d) / S / v / sqrt(T);

}

 

// Black-Scholes Vega

double BSVega(double S, double K, double T, double r, double v)

{

double d = (log(S/K) + T*(r + 0.5*v*v)) / (v*sqrt(T));

return S*f(d)*sqrt(T);

}

 

// Black-Scholes Rho

double BSRho(double S, double K, double T, double r, double v, char OpType)

{

double d = (log(S/K) + T*(r + 0.5*v*v)) / (v*sqrt(T));

if (OpType==’C’)

return T*K*exp(-r*T)*N(d – v*sqrt(T));

else

return -T*K*exp(-r*T)*N(v*sqrt(T) – d);

}

// Black-Scholes Theta

double BSTheta(double S, double K, double T, double r, double v, char OpType)

{

double d = (log(S/K) + T*(r + 0.5*v*v)) / (v*sqrt(T));

if (OpType==’C’)

return -S*f(d)*v/2/sqrt(T) – r*K*exp(-r*T)*N(d – v*sqrt(T));

else

return -S*f(d)*v/2/sqrt(T) + r*K*exp(-r*T)*N(v*sqrt(T) – d);

}

 

Note:

 

// N(0,1) density

double f(double x) {

double pi =  4.0*atan(1.0);

return exp(-x*x*0.5)/sqrt(2*pi);

}

 

 

 

// Boole’s Rule

double Boole(double StartPoint, double EndPoint, int n) {

vector<double> X(n+1, 0.0);

vector<double> Y(n+1, 0.0);

double delta_x = (EndPoint – StartPoint)/double(n);

for (int i=0; i<=n; i++) {

X[i] = StartPoint + i*delta_x;

Y[i] = f(X[i]);

}

double sum = 0;

for (int t=0; t<=(n-1)/4; t++) {

int ind = 4*t;

sum += (1/45.0)*(14*Y[ind] + 64*Y[ind+1] + 24*Y[ind+2] + 64*Y[ind+3] + 14*Y[ind+4])*delta_x;

}

return sum;

}

 

// N(0,1) cdf by Boole’s Rule

double N(double x) {

return Boole(-10.0, x, 240);

}

 

 

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!

What does this Streambase open source library has impact on my HFT platform? The return of Matlab for quant analytics? #matlab

More and more reasons are piling up why people should join the QuantLAbs.net Memberships as it will start getting to be kind of exclusive for peoiple. It is still affordable but I have some big plans for it!

After my discovering of this Streambase open source alternative, I am finding it is having a huge impact on the direction of my HFT development. I will announce that in coming days but go to my blog for the lastest developments. Here are latest videos I posted on how to build the large components for ths platform:
I am also finding constant bottlenecks with R, here is my alternative backup I plan to use.
I am quickly moving towards a proprietary mode with this platform, as a result you should strongly consider joining my QuantLabs.net Premuim Membership as I intend to release the C++ strategies which will be dropped into the future framework of this HFT platform.
Hope this helps you
Bryan
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!

TOP 10 articles for quant analytics #quant

TOP 10 articles for quant analytics

Hi what does “last look” rule/functionality mean in trading? I came across this
Quant analytics: What is the best causal filter? Wavelets? Mark Jurik’s JMA? …?
Algorithms suitable for FPGA in quant development?
Matlab: Creating Stochastic Differential Equations from Mean-Reverting Drift Cox-Ingersoll-Ross (CIR) Square Root Diffusion Models
How to create Brownian Motion Model and GBM in Matlab
Multivariate Regression open source Quant development APIs, frameworks and Libraries for C++ and C#
Automated Elliott Wave Pattern recognition with Fib Relationships
Quant analytics: Polynomial fitting algorithm?
Best Algo Trading Book for Quant Analytics
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Is Dr Markus Brunnermeier the next in quant analytics genius?

Is Dr Markus K. Brunnermeier the next in quant analytics genius?

I don’t know but this guy does look interesting from Stanford

http://scholar.princeton.edu/markus/publications

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!

Do we record our webinars for quant analytics, quant development, and R learning? Yes we do

Hi Miguel
We do record them but they get posted mostly or members but I may put the odd one up on Youtube depending on the value of it.

Do we record our webinars for quant analytics, quant development, and R learning? Yes we do

> Hello Bryan,
>
> The local time here in Spain is late night.
>
> Are these webminars recorded in order to be able to access them at
> any other time?
>
> Best regards,
>
xxx

 

Hi
We do record them but they get posted mostly for members but I may put the odd one up on Youtube depending on the value of it.

BECOME A MEMBER INSTANTLY!

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!

Quant analytics: Live webinars coming soon on capturing market data, NOSQL to cluster, best fit model with ARIMA. R script included

Quant analytics: Live webinars coming soon on capturing market data, NOSQL to cluster, best fit model with ARIMA.  R script included

 

he live demo and webinars for my members are getting works out:

1. How to capture market data fast with an affordable service

2. Parallelize your analysis and use open source NOSQL for potential tick data repository

3. How to do best fit modelling and implement ARIMA processes and simulations. My next models will include GARCH.

Get instant access to understand the details and be part of theses.

Also, for anyone who has general Q&A about what I do.

Check here for the upcoming schedule

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Quant analytics: Youtube video demo of how to find Best Fit parameters of ARMA or AR autoregressive for your ARIMA model forecast in R

Quant analytics: Youtube video demo of how to find Best Fit parameters of ARMA or AR autoregressive for your ARIMA model forecast in R

Now you don’t need to manually figure your ARMA set of parameters like AR(1,0) or AR(1,1) or AR(2,2). This can automatically done on the fly by this intelligent R script I found and modified. I also include a private video code walkthrough on how this is done

Get instant access to this now by going here or get the benefits here

 

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!