- having completed the coding of market_type.cc ensure that all production indicator calculations used as input to the function conform to those used in the MC generation of the market_type.cc look-up tables - specifically

- prices are smoothed in a 1 2 2 1 FIR filter prior to the Cybercycle being calculated
- Tukey chart ucl/lcl calculations are applied to this cybercycle calculation without any further smoothing
- the price_cl_mults & cyber to price cl_mults in production indicators are the same as those used in the above mentioned MC generations
- lookback in production indicators is period + 1

- apply the elliptic smooth in current version of the 1,2,3,4 day oscillator leading signals of cybercyle
- adjust/check coding for adaptive tukey indicator to account for period+1 (done) and reoptimise with MC & do the same for indicators which use full or half period lookbacks i.e. stochastic(done), myrsi(done), adaptive lookback max_min(done), imi(done), lin_predict, highpass(done), bandpass(not nec?)
- apply osc_lead signal with ellip smooth to all bounded oscillators
- redo the zerocrosscount to use the inphase component of the leading oscillator functions (done for inphase_cybercycle)
- all the below in java code for submission to algodeal testing (long term plan)
- slope of control lines as switch for band trading?
- full period repeated median slope as a switch?
- divergences in cyber and fish_cyber
- investigate the crossovers of cyber, smooth cyber and fish_cyber as possible turn indicator
- test these on real prices
- guppy momentum indicator?
- optimise indicator input price (close, typical price, mid price, my price...... ) and the smooth thereof i.e. elliptic, kalman etc.
- full period/other periods of repeated median slope momentum as indicator? divergences? optimise?
- make synthetic price series function period adaptive and incorporate recent volatility aspect
- optimise default repeated median slope using MC synthetic price series in a "run-off"
- detrend via highpass before applying channel bandpass?
- tukey bands around highpass filter trend as indicator
- Bayesian analysis of ols line fit/sinewave fit as market mode switch?
- twicing of the Adam Projection
- apply the reflection principle to set limit entries and stops
- direct comparison of cyber, highpass and bandpass and maybe zerocrosscounts for highpass and bandpass
- set targets based on zerocrosscounts for cyber, highpass and bandpass when market is cycling
- volatility-differentials-highlow-volatility-versus-closeclose-volatility-hlv-ccv/
- the AFIRMA trend line as set up for pyramiding or continuation trades?
- develop a DSP torture test suite
- a cycle quality indicator as in here which looks like this. Use this as a further input to the Naive Bayes Classifier indicator?
- investigate differences in sinewave indicator - see sinewave_3.1.mq4 in Metatrader library
- Ehler's fractal dimension as input to Naive Bayes Classifier?
- Goertzel algorithm to detect period?
- The medcouple adjusted boxplot for extreme moves?
- Adapt the IMI according to this adjusted RSI calculation
- use the VWAP formula according to this link for input price or as a predictive indicator i.e VWAP > pivot is bullish or < pivot is bearish
- use candlestick maths to create new charts
- Structural break package in R
- Andrew Ng's Neural net stuff for market mode
- Enter, and win, a stock picking contest. such as this.
- Investigate time-series-analysis-and-order-prediction to supplement my prediction function.
- Use equity factor analysis, as per this post, for analysis of portfolio level back test results.
- Incorporate the Shark Machine Learning Library into future NN work.
- investigate Hedgeit Python software.
- Time series similarity measures
- investigate thepatternsite.com for ideas
- Ehler's code links.
- Eureqa software
- Runs charts for congestion periods
- Data Smashing
- Turning Point Prediction of Oscillating Time Series using Local Dynamic Regression Models
- Better Hilbert Sine Wave Indicator
- Useful Savitzky-Golay stuff here and here and here.
- Time series features webpage
- Using the generalized lambda distribution to simulate market returns
- Time Frequency Analysis
- power spectral density matlab code
- Time Frequency Representation stuff
- Alpha curves and dtw barycenter averaging
- Effect size pdf and nice webpage
- detecting and measuring lead-lag effect
- Identifying Granger Causality
- Forex NN
- Field Guide to Genetic Programming
- stackexchange questions - how to do exploratory data-analysis for machine-learning
- Link to course from above stackexchange question
- optunity a ML hyper-parameter tuning suite
- Linear Regression
- determinism and entropy - choosing what to trade
- Dynamic time warping and clustering
- Intoduction to ARIMA models
- Independent Component Analysis
- Dr. Keogh's papers
- Extreme learning machines
- Andrew Patton's homepage
- Timothy Masters' homepage
- Causal Impact and its R package.
- datagrapple.com
- deep learning libraries
- measuring market risk
- Quantopian
- QuantConnect
- cloud9trader
- algotrader
- boruta_py all relevant feature selection
- worked example using the boruta package
- select important variables boruta package
- Rattle
- Caret R package and recursive feature elimination
- variable selection with random forests
- R Machine Learning view
- portfolioeffect.com for some useful HF tools
- 15 years of forex tick data to mongodb using python
- mechanicalforex, machine learning, choosing a library
- predicting chaos and r in trading time series forecasting using chaos part 3
- Empirical Dynamic Modelling, the rEDM package for it, the package vignette and Taken's Theorem.
- Bressert Double Stochastic
- automl and tpot for automating the machine learning pipeline.
- financial time series segmentation turning points
- ema trading strategy, full version here, and the Heidke Skill Score
- Reinforcement Learning Github
- residual neural networks
- MLBox, a blog on it, and Entity Embedding.
- currency strength indicator based on log movements of currency indices
- denoising autoencoder (mSDA) based on currency indices
- Yarin Gal - What my deep model doesn't know - application for kalman filter?
- Mitigating over-fitting-on-financial-datasets-with-generative-adversarial-networks and its linked https://github.com/FernandoDeMeer/Mitigating-Overfitting-Experiment
- Pairs trading on my currency strength indices using ideas of kalman-filter-pairs-trading-with-zorro-and-r, the pairs-trading-analysis-with-r course and general pairs trading strategies.
- Weight Agnostic Neural Net training