# Algorithmic Trading Strategies, Walk Forward Optimization & Out-Of-Sample Testing For TradeStation, MultiCharts & NeuroShell

**Six Trading Strategies** In One Package: Click On Strategy For Detail.

**The KeyTrSys v5t is thread safe and can run on multi-core, multi-thread platforms**

** Available for TradeStation, MultiCharts ***and* NeuroShell Pro

### The Power Walk-Forward Optimizer (PWFO)

is a cutting-edge automatic walk forward/out-of-sample analysis program that eliminates the ad hoc curve fitted performance and data mining results produced by combinatorial and genetic(grail) optimization of strategy input values on spurious price movements(noise). Included in the in-sample section output for each set of input parameters are 30 new robust and superior performance metrics. The in-sample and out-of-sample periods are user selectable. The PWFO can generate up to 500 different in-sample and out-of-sample date files in one TS run. Statistically speaking, walk forward out-of-sample (oos) analysis must be performed over many(>30) in-sample/oos sections to be statistically valid.

**Videos On How To Use The Power Walk Forward Optimizer**

**The Power Walk Forward Optimizer v5t is thread safe and can run on multi-core, multi-thread platforms**

** Available for TradeStation, MultiCharts 32bit and 64bit**
**The Walk Forward Metric Explorer (WFME)** reads all files generated by the PWFO and searches each PWFO file for performance Metrics that generate statistically best average out-of-sample performance. The Top N Metric filter chooses the PWFO file rows that contain then Top N (N=10 or 50 or etc) values of a PWFO Performance Metric. From the N rows chosen, the WFME chooses the maximum of another PWFO performance metric. This allows two performance metrics in the in-sample section to be used to find the strategy inputs that give the best out-of-sample returns. Experience has shown that the use of only one in-sample performance metric to choose strategy inputs from the in-sample section does not produce good out-of-sample results. The Top N criteria ranges are user selectable generating many filter searches in one run. The WFME is a stand alone 64bit exe program that is super fast and automatically displays it's extensive statistical results, equity plots and strategy inputs from each filter in Excel. In addition, using modern "Bootstrap" techniques, the WFME calculates the probability of whether or not each filter's out-of-sample results were due to chance.

**Videos On How To Use The Walk Forward Metric Explorer**
**The Walk Forward/Out-Of-Sample Input Parameter Explorer (WFINP)** reads all files generated by the PWFO and searches the performance metrics of profit factor(PF) and losing trades-in-a-row(LR) in those files for those performance metrics that generate the statistically best average out-of-sample returns. The WFINP eliminates the curve fitted results by filtering out from the PWFO file's in-sample sections those strategy inputs that have Profit Factors(PF) greater than x and that have losing trades in a row(LR) of greater than y. The WFINP then determines which strategy filtered inputs generate the statistically best average out-of-sample returns. The PF and LR criteria are user selectable so you can choose which PF and LR values suit you. The WFINP is a stand alone exe program that is super fast and automatically displays it's statistical summary and results in Excel. In addition, using modern "Bootstrap" techniques, the WFINP calculates the probability of whether or not each filter's out-of-sample results were due to chance.

**The Walk Forward/Out-Of-Sample Metric Surface Explorer(WFSE)** reads each of the files generated by the PWFO and calculates the flattest metric surface plateaus vs the input parameters for each performance metric's (Total Net Profits, Profit Factor, etc) surface. The WFSE can find the flattest surface for up to a 7 dimensional(7D) surface. A 7D surface consists of six input parameter axis vs a performance metric variable. A performance metric flat surface plateaus represent robust input parameters that have a greater chance of producing good out-of-sample results. The WFSE then finds the out-of-sample profits associated with each in-sample section surface's flattest plateau (minimum gradient) for each file. The WFSE sums each file's out-of-sample results for each of the surface's minimum gradients and finds the statistically best out-of-sample returns for each performance metric surface. The WFSE is a stand alone exe program that is super fast and automatically displays it's extensive surface statistical summary and results in Excel.

### The n^{th} Order *Fading* Memory Polynomial

Using fast advanced mathematical rocket science algorithms, the price series is modeled using an nth order fading memory polynomial of the form: ** price(t) = a**_{0}(t)+a_{1}(t)*t+a_{2}(t)*t^{2}+a_{3}(t)*t^{3}+a_{4}(t)*t^{4}+...+a_{n}(t)*t^{n} The **a**_{n}(t) coefficients are updated *recursively* with each new price bar and then used to give the polynomial's** ***next bar forecast* of price,velocity and acceleration.
As our demonstrate the ** n**^{th} Order Fading Memory Adaptive Polynomial is an effective strategy for trading stocks, futures and currencies.

**The FadmXVAn v3t is thread safe and can run on multi-core, multi-thread platforms**
** Available for TradeStation, MultiCharts ***and* NeuroShell Pro

### n^{th} Order Fixed Memory Adaptive Polynomial

Using fast advanced mathematical rocket science algorithms that use discrete orthogonal polynomials, the price series is modeled using an n^{th} order polynomial of the form:
** price(t) = a**_{0}+a_{1}*t+a_{2}*t^{2}+a_{3}*t^{3}+a_{4}*t^{4}+...+a_{n}*t^{n}
The **a**_{n} coefficients are recalculated at each new price bar and are then used to give the polynomial's *next bar forecast* of price,velocity and acceleration. As our demonstrate the **n**^{th} Order Fixed Memory Adaptive Polynomial is an effective strategy for trading stocks, futures and currencies.

**The FixmXVA v3t is thread safe and can run on multi-core, multi-thread platforms**

** Available for TradeStation, MultiCharts ***and* NeuroShell Pro

### The Goertzel Algorithm for Frequency Cycle Detection (GZ)

super fast DLL finds the N(user selectable) cycles(frequencies) with the highest amplitudes at each price bar, and creates a x bars ahead (x is user selectable) noise filtered projected momentum curve. This process gives a more robust noise filtered signal than a single frequency (dominant cycle) procedure. You are no longer constrained to using only a single frequency. The nCycleGZ algorithm is faster and superior to MESA in finding cycles in noisy price series. As our demonstrate the nCycleGZ is an effective strategy for trading stocks, futures and currencies.

**The Goertzel Strategy is thread safe and can run on multi-core, multi-thread platforms**

** Available for TradeStation, MultiCharts ***and* NeuroShell Pro

### The End Point Fast Fourier Transform System (EPFFT)

super fast DLL takes the *Fast Fourier Transform* at each price bar, filters the noisy price series using a unique noise filter in the frequency domain, and creates a one bar ahead noise filtered projected price. The EPFFT DLL produces an adaptive broadband (many frequencies) noise filtered signal. This process gives a more robust noise filtered signal than a single frequency (dominant cycle) procedure.
As our demonstrate the EPFFT is an effective strategy for trading stocks, futures and currencies.

**The EPFFT v3t is thread safe and can run on multi-core, multi-thread platforms**

** Available for TradeStation, MultiCharts **
**The five parameter parabolic** adds a noise filter and changeable starting stop value that minimizes the whipsaw losses that can occur with the regular parabolic indicator. Here this new system is applied to stock and Futures prices to minimize the noise process.

**The Parabolic v2t is thread safe and can run on multi-core, multi-thread platforms**

** Available for TradeStation, MultiCharts**

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