Posts Tagged ‘system evaluation’
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December 2017
November 2017
October 2017
July 2017
- Building "the switch" using machine learning
- Predicting trading system out-of-sample success using chaos properties of financial time series
April 2017
March 2017
- Finding out which simple system selections have worked in the past using a GPU
- Visualizing IS/OS relationships in our price action based repository
- A script to retrieve account results from Oanda using the RESTv20 API
- Three basic ways to classify trading system backtesting statistics
January 2017
November 2016
- Introducing pKantuRL: GPU enabled mining for reinforcement learning based systems
- Reinforcement learning in trading: What about random data?
October 2016
- New credit card sized computers for back-testing, system mining and trading
- Making OS predictions using FX symbol market conditions
- Getting an account performance summary directly from Oanda using their REST API and Python
August 2016
- Using QQPat: Calculate and plot the Losing Period Overlap Index
- Finally an out-of-sample performance predicting model that works (a bit)
- How long does it take to see in-sample/out-of-sample variable correlations?
- The Sharpe Ratio: Be careful with comparisons
July 2016
June 2016
- The Omega ratio: A much better performance metric than the Sharpe?
- Getting your backtesting results out of Quantopian and into QQPat
- Automatically downloading and saving 1M from FXDD using Python
- Are islands always better than peaks? About system parameters in Forex trading
- Dealing with Forex data time zones using Pandas
- Relationship between returns and market conditions viewed from the fractal dimension
- Measuring trading system correlation using Python
- Using qqpat: Analyzing your MT4 back-testing results using Python
May 2016
- Do Monte Carlo simulations say anything about system robustness?
- Looking at an old Forex system: The God's Gift ATR
- Using qqpat: When should you expect to see long term statistics?
- What do top out of sample performing trading strategies have in common
March 2016
- After more than one year of trading: Are there any in-sample/out-of-sample correlations?
- Backtesting Trading Systems in Python: Not a really good choice
February 2016
- Using Monte Carlo simulations in trading: Key assumptions
- Graphically identifying trading system worst cases using qq-pat
- Trading System Failure: Easy worst case detection using qq-pat
- Monte Carlo Simulations: Updating failure detection
- Reducing Drawdown Length: Why you can only go so far
- The Rolling Correlation Index: A better measurement for system relationships
- Using qq-pat to find your trading system's worst case statistics
January 2016
December 2015
- Know your data: Find your Forex data's GMT shift and DST offset using the NFP news release
- Oanda's not-so-good 1M data: Can you trust your own broker's historical data?
- Is your trading system under-performing? Properly comparing statistics using python
- Using qq-pat: Getting Monte Carlo simulations for your trading system
- The Maximum Drawdown: Extreme statistics are a poor proxy for true risk
- The brick wall in trading system design: Understanding the limitations of historical data
- Using OpenKantu in Practice: Is old Forex data irrelevant in today's market?
- Is your Forex data full of holes? A script for the evaluation of Forex data quality using Python
- Introducing qq-pat, an open source library for the calculation of financial time series statistics
- Understanding financial time series data: Why a 1D bar is not the same as a 1M bar
- Using OpenKantu in Practice: Analyzing system generation results using R
- Looking into the Sharpe Ratio: Problems, solutions and improvements
November 2015
- Compiler Optimizations: How your backtesting speeds can change depending on how you compile your software
- Powerful Statistical Analysis: Using Pyfolio to analyse your MT4 backtesting results
- Updating OpenKantu to v2.10: Fixing my open source trading system generator for a wider trader audience
- Powerful statistical analysis: Take your MT4 backtesting results to R
October 2015
May 2015
- How far should we go into the past for Forex simulations: Is old data really useless?
- Some algorithmic trading systems from 2010: Revisiting three trend following strategies (BB, CCI and RSI)
January 2015
September 2014
March 2014
- Accurate and systematic evaluation of Data Mining Bias (DMB) in trading strategy creation
- Going below the one minute timeframe: Implementing simulations with Tick-by-tick resolution
February 2014
- What trading system failure means: Defining and quantifying strategy failure, Part 2
- What trading system failure means: Defining and quantifying strategy failure, Part 1
- Using R in Algorithmic Trading: Performing a portfolio test using a rolling window Markowitz optimization
- Beyond Simple Linear Regression: Calculating the Ideal R (IR) for a trading strategy
January 2014
- Choosing trading system combinations: A practical example using rolling correlations
- Using R in Algorithmic Trading: Calculating system weights using Markowitz portfolio theory
- Using R in Algorithmic Trading: Analysing your Trading System's Historical Results
September 2013
June 2013
- Getting data from non-Forex instruments for Forex trading in F4: Dynamically communicating with the Yahoo Finance API using curl
- No more MT4 Back-testing! :o) Moving to a professional, C/Python Backtester for the F4 Framework
- Accurate Forex Trading Simulations Including Historically Accurate Swap Rates: Why interest is so important
May 2013
February 2013
December 2012
- Seasonal Effects: Finding and Using Them to Improve Your Forex Trading Systems
- Can the Lower Time Frames be Useful? : Discussing Information, Robustness and Reliability
- Implementing Another Front-end: Asirikuy Systems Now Trading on MT5 using the F4 Framework
November 2012
- Time Filtering Doesn't Reduce Robustness: Qallaryi's 25 Year Simulated Results
- Cutting Out the Fat at Asirikuy: Changing To Higher Requirements for Trading Strategies
- Enhancing Robustness: Implementing Modifications to Remove a Strategy's Feed Dependency
- Feed Dependency in Higher Time Frame Algorithmic Systems in the Forex Market: Causes and Effects
October 2012
- Walk Forward Analysis: Does the data you use matter ? Looking into some assumptions made by WFA
- One Size Doesn't Fit All: Taking Care of Explicit Correlations in Monte Carlo Simulations
- Judging Trading Strategy Survivability: Looking at Systems like the Military
- Implementing Next-Generation Testing: The Power of the New F4 Strategy Tester Module
- Understanding the Parameter Space: Some Frequently Asked Questions (FAQ)
- Signal Problems: Obtaining Reliable Historical System Correlations for Portfolio Trading
September 2012
- Learning from the past, moving towards the future: Updating to F4 Atinalla Portfolios
- Trading System Walk Forward Analysis: Are you sure you're adapting?
- To Stop or Not to Stop: When is it the Best Time to Stop an Automated Trading System
May 2012
September 2011
August 2011
July 2011
June 2011
- Cause and Effect: Understanding Correlations in Trading Systems and Portfolio Results
- Improving the Asirikuy Performance Analyzer: Towards Better Live Testing Analysis
- Understanding Trading System Evolution: Worst Case Scenarios ARE Dynamic
- Getting Powerful Trading Account Reporting: Using the MyFXBook API
- Back/Live Testing Consistency: Using Different Brokers For Long Term Simulations and Live Trading
- Monte Carlo Simulation Distortions: What They Are Useful For When Developing Portfolios
- The Chi-Squared Test: How to Use This Statistical Tool in Forex Algorithmic Trading
- Analyzing System Results: The Power Of Logarithmic Equity Curves
- Getting to Know Trading Systems Better: Analyzing Strategies Through Custom Ratios
May 2011
- The Time Array Mismatch Problem: A Dark MT4 Secret Comes to Light
- Neural Networks in Trading: Are Trade Results Correlated? Using an NN for Money Management. Part One
- The Golden Problem: Why It is Difficult to Come Up With a Good Trading System for Spot Gold and Some of My Findings
- High Vs Low Reward to Risk: Is One Approach Better Than the Other?
- Getting Asirikuy "Together": Building a Comprehensive Database Solution for Our Results
- How Many Trades are Enough Trades? : Answering the Question of Trade Frequency From a Statistical Perspective
- Understanding Broker Dependency: What Makes Results Different From One Broker to Another
- Re-Evaluating Our Amachay Portfolio: Going the Simple Route
- Diversification in Trading: Not as Simple or Obvious as Most New Traders Think
- Amachay Gets Ready for Its Live Trading Debut: A Full Fibonacci Based Strategy Portfolio
- Missing the Money Train: The Psychological Effect of Positive Performance
- When You Should NOT Trade a Given System: Five Red Flags To Avoid Trading a Strategy
- When the Storm Comes: Five Tips to Deal with the Arrival of Monte Carlo Worst Case Scenarios
April 2011
- Analyzing the Asirikuy System Backtest Database: A Great Excel Analysis Tool
- The Asirikuy Performance Analyzer: A New Convenient Tool For On-The-Fly Analysis
- Trade More or Trade Less: Getting Clearer About This Issue
- Evaluating/Simulating Broker Dependency: What Changes in a System from Broker to Broker?
- Measuring System Quality: Should We Only Use Monte Carlo Criteria?
- The Effects of Increasing System Number: The Deterrents of Big Portfolios
- Indicators Vs Price Action: Is One Better Than the Other ?
- My April Currency Trader Magazine Article: Creating Systems From An Edge Ratio Analysis
- Trade More or Trade Less: The Incidence of Trading Frequency in System Quality
March 2011
- Historical Max Draw Down Abundance in Monte Carlo Simulations: An Excellent System Quality Indicator?
- An Interesting Phenomena: Investigating the Distribution of Return of Trading System Portfolios
- Our First Tests of Indicator Independence: Porting Teyacanani to Use Our TA-Lib MT4 DLL
- Custom Indicators and Back-Testing Speed in MT4: How to Make Your Custom Indis Fast
- Problems with "Big Trading Portfolios": Issues That Show Up When Running Large Arrays of Systems
- Choosing Portfolios Without Bias: Some Strategies Against the "Cherry Picking" of Systems
- Coatl's First Serious Test of Robustness: Facing the JPY During a Week of Intervention and Disaster
- The Ideal Forex Strategy Tester: Features and Key Characteristics
- Improving Our Monte Carlo Simulator: Now With Virtually No Trade/Iteration Size Limitations :o)
- Neural Networks in Trading: How To Properly Evaluate NN Derived Strategies
- Profit Evolution in Asirikuy: Looking at The Asirikuy Index and Its Interpretation
- Walking Forward: Do Asirikuy Systems Yield Profit With Continuous Optimizations ?
February 2011
- Ending an Important Cycle: No More Commercial Forex System Reviews for Me :o)
- Looking at myforexdot.org.uk, an Excellent Website with a Lot to Say
- Developing an Iron-Clad Trading Setup: The First 20 Year Coatl System Portfolio
- Out of Sample Testing: The Power and Correct Execution of This Simulation Technique
- The Wonderful Things About Alternative Testing Solutions: A FreePascal Tester Vs MT4
- The Need for Platform Independence: Analyzing the Odd MT4 Indicator Implementations
- Trading Across Important Market Changes : A DEM/USD Designed System Trading the EUR/USD
- Evolving Our Spread Changing Capabilities: An Improved MT4 Spread Changer for Asirikuy
January 2011
- Talking About "Party Time" : For How Long Could We Expect Profitable Strategies to Remain Profitable
- Trying to Measure a Trading System's Robustness : The Hardness Index
- Measuring a System's Psychological Pressure: The Ulcer Index
- Comparing Your System's Profitability Against Random Outcomes : An Edge or Just Luck ?
- Get Your Feet On Earth: Understanding the Difference Between Expected and Real Profits
- Trading System Transparency : The Problems of Blurry Logic
- Why No EUR/CHF or EUR/GBP One Hour Systems? : Looking Into the Problems of Long term Simulations on These Pairs Based on 1M Data
- Banging Trading Systems Against the Wall : Stress-Testing Strategies to Evaluate Their Robustness
- Can a Computer Design a Trading System ? Part Six : A Twenty Instrument Portfolio
- The Big System Portfolios : The Wonderful Effect of "Piling Up" Strategies
- Evaluating System Distributions : How Many Trades are Enough Trades ?
- Improving Our Asirikuy Analysis Tool : Implementing Monthly Return Analysis
December 2010
- Getting Better at Monte Carlo : Distribution Based Simulations of Trading Strategies
- Better System Analysis : Our Own Asirikuy Delphi Monte Carlo Simulator
- Metatrader 4/5 Simulations : Our Intention to Move Beyond
- Modelling Quality in Metatrader 4 : An Almost Meaningless Number
- Accurate Scalper Development : What Needs to Be Done to Reliably Develop Scalping Strategies
- Knowing When Systems Stop Working : Why Learning System Worst-Case Statistics is Vital for Success
- The Lower Time Frame Problem : Why Metatrader Cannot Accurately Simulate Systems Below the 30 Minute Time Frame (NOT even With 99% Testing Quality)
- Are Our Assumptions True ? : Validating the Ten Year Back-testing Hypothesis
November 2010
- One System to Rule Them All : Developing Strategies For All Forex Instruments
- Analyzing System Results On the Run : The Asirikuy "EA Analyzer" Indicator
- The Frequency Distribution of Returns : Developing Further Criteria to Determine When a System Stops Working
- Automated Trading Execution : Dependent Vs Independent Platform Solutions
- Taking Advantage of Control Point Simulations : In-Depth Studies of Simple Strategies
- Stress Testing Systems : Learning About Monte Carlo Simulations
- Destroying a Mechanical Trading Myth : Frequent Short Term Optimization Works
- The Development of Robust Basket Systems : Systematically Improving Their Results
- Changing the Spread in the MT4 Strategy Tester : My SpreadChanger Program Solves the Problem
- The Dangers of Real Live Results : No Understanding, No Meaning
October 2010
- Can a Computer Design a Trading System ? Part Two : Genetic Programming
- Optimizing Without Curve-Fitting : Six Tips to Avoid Over-Optimization
- Robustness : Ideal Trading System Characteristics to Withstand Change
- Monthly Return Analysis : A Basic Tool to Understand Your Trading System
- Backtesting With the New Alpari Data : Some Findings and Changes
- Destroying a Myth : Past Results Do Not Matter
- Can We Run Reliable, Computationally Cheap System Simulations on Metatrader 4 ? : Using the Control Points Method Accurately
September 2010
- Short Term Randmoness and Long Term Statistics : Learning to Evaluate the Live Results of a Trading System
- Why Demo Testing a System is NO Good : Five Reasons Why You Should Always Test Systems With Real Money
August 2010
- The Pain Index : A Measurement of How Hard it is to Trade a System from a Psychological Perspective
- To Trade or Not to Trade : A Little Bit About Friday Trading
- Evaluating Trading Systems : Characteristics and Quality
July 2010
- Why Catastrophic Losses in Forex are Always Possible : A Look at the Forex Worst-Case Scenario
- Judging by the Amount of Trades. Does it Really Matter ?
- How we Have Been Fooled : An Evaluation of Traditional Indicator Setups
June 2010
April 2010
March 2010
February 2010
January 2010
November 2009
June 2009
- You think your expert advisor is profitable ? Profitable, may not mean Profitable
- Testing Every Expert Advisor, The WRONG Strategy !
February 2009
How to download free OHLC historical cryptocurrency daily data using a python script
December 3rd, 2017
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