Nine Trading Systems In One Package- The Robust Velocity System, The Acceleration System, The Velocity System, The Next Bar Forecast System, The Polychromatic Momentum System, The Maximum Likelihood Range System, The Noise Channel Breakout I & II, The 2-P NextBar Forecast System Available for TradeStation and NeuroShell Pro

The Power Walk Forward Optimizer (PWFO) is a cutting-edge automatic walk forward testing program that eliminates the ad hoc curve fitted performance results produced by optimization of strategy input values on spurious price movements. The PWFO allows you to perform a K-fold cross-validation on your strategy. No other walk forward software offers this ability. The PWFO prints the in-sample(test) performance results with the out-of-sample performance results on the same line to a spreadsheet comma delimited file for each case (input variable combination) of an optimization run. Included in the optimization output for each input case are new superior and robust in-sample performance metrics. The in-sample and out-of-sample dates are user selectable. The PWFO allows the user to code his own performance metric in EasyLanguage which is then added to the performance statistics on each case line. The PWFO can generate up to 500 different in-sample and out-of-sample date optimization files in one TS run saving the user from having to generate optimization runs one at a time. The PWFO output allows you to quickly determine whether your procedure for selecting input parameters for your strategy just curve fits the data and noise or produces statistically valid positive out-of-sample results. A Walk Forward Input vs Out-of-Sample(OOS) Explorer (WFINP) is included that allows one to quickly determine which strategy inputs generate the statistically best average out-of-sample returns after the curve fitted performance results have been filtered out. Click here for description of the WFINP. Available for TradeStation

The Walk Forward Performance Explorer (WFPE) reads all files generated by the PWFO and searches the performance metrics in those files for those performance metrics that generate the statistically best average out-of-sample returns. The WFPE eliminates all cases in the PWFO test files that do not meet certain Profit Factor (PF), Losers in a row (LR),and PWFO Performance metrics criteria . The PF, LR and METRIC criteria/search ranges are user selectable generating many filter searches in one run. The WFPE is a stand alone exe program that is super fast and automatically displays it's extensive K-fold cross-validation statistical summary and results in Excel. In addition, using modern "Bootstrap" techniques, the WFPE calculates the probability of whether or not the filter's results were due to chance. No other Walk Forward software offers this capability.

The Walk Forward Performance Metric Explorer (WFPME) reads all files generated by the PWFO and searches each PWFO file for a Top N-Metric-PF-LR filter that generates the best average out-of-sample performance. Here we define the “Top N” as the TOP 5 or Top 10 or Top user selectable number N. The Top N Metric-PF-LR filter first eliminates all cases in the PWFO test files that do not meet certain Profit Factor (PF), Losers in a row (LR) criteria. Then from the cases(rows) that are left meeting the PF-LR criteria, the WFPME chooses the rows that contain then Top N values of a PWFO Performance Metric. The PF, LR and Top N criteria ranges are user selectable generating many filter searches in one run. The WFPME is a stand alone exe program that is super fast and automatically displays it's extensive K-fold cross-validation statistical summary and results in Excel. In addition, using modern "Bootstrap" techniques, the WFPME calculates the probability of whether or not each filter's results were due to chance.

The Walk Forward Surface Explorer(WFSE) reads each of the files generated by the PWFO and calculates the flattest surface plateaus vs the input parameters for each performance metric's (Total Net Profits, Profit Factor, etc) surface. The WFPE 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 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 K-fold cross-validation statistical summary and results in Excel.

Using fast advanced mathematical rocket science algorithms, the price series is modeled using an nth order fading memory polynomial of the form:
price(t) = a₀(t)+a₁(t)*t+a₂(t)*t²+a₃(t)*t³+a₄(t)*t⁴+...+a_n(t)*tⁿ
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 working papers demonstrate the n^th Order Fading Memory Adaptive Polynomial is an effective strategy for trading stocks, futures and currencies. Available for TradeStation and NeuroShell Pro

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) = a₀+a₁*t+a₂*t²+a₃*t³+a₄*t⁴+...+a_n*tⁿ 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 working papers demonstrate the n^th Order Fixed Memory Adaptive Polynomial is an effective strategy for trading stocks, futures and currencies. Available for TradeStation and NeuroShell Pro

The Adaptive n Cycle Goertzel Discrete Fourier Transform (nCycleGZ) super fast DLL finds the N 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. Click here for working papers on the Goertzel-DFT Available for TradeStation and NeuroShell Pro

The EPFFT super fast DLL takes the FFT 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. Click here for working papers on the EPFFT Available for TradeStation

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 Parabxot system is available for TradeStation