CCI Strategy Reversed Backtest The Commodity Channel Index (CCI) is best used with markets that display cyclical or
seasonal characteristics, and is formulated to detect the beginning and ending of these
cycles by incorporating a moving average together with a divisor that reflects both possible
and actual trading ranges. The final index measures the deviation from normal, which indicates
major changes in market trend.
To put it simply, the Commodity Channel Index (CCI) value shows how the instrument is trading
relative to its mean (average) price. When the CCI value is high, it means that the prices are
high compared to the average price; when the CCI value is down, it means that the prices are low
compared to the average price. The CCI value usually does not fall outside the -300 to 300 range
and, in fact, is usually in the -100 to 100 range.
You can change long to short in the Input Settings
Please, use it only for learning or paper trading. Do not for real trading.
Algotrading
Breakout Range Short Strategy BacktestBreakout Range Short Strategy
You can change long to short in the Input Settings
Please, use it only for learning or paper trading. Do not for real trading.
Breakout Range Long Strategy Backtest Breakout Range Long Strategy
You can change long to short in the Input Settings
Please, use it only for learning or paper trading. Do not for real trading.
Bill Williams. Awesome Oscillator (AC) Strategy Backtest This indicator plots the oscillator as a histogram where blue denotes
periods suited for buying and red . for selling. If the current value
of AO (Awesome Oscillator) is above previous, the period is considered
suited for buying and the period is marked blue. If the AO value is not
above previous, the period is considered suited for selling and the
indicator marks it as red.
You can make changes in the property for set calculating strategy MA, EMA, WMA
Please, use it only for learning or paper trading. Do not for real trading.
Bandpass Filter Reversed Strategy BacktestThe related article is copyrighted material from
Stocks & Commodities Mar 2010
You can use in the xPrice any series: Open, High, Low, Close, HL2, HLC3, OHLC4 and ect...
Please, use it only for learning or paper trading. Do not for real trading.
Average True Range Reversed Strategy Average True Range Trailing Stops Strategy, by Sylvain Vervoort
The related article is copyrighted material from Stocks & Commodities Jun 2009
Please, use it only for learning or paper trading. Do not for real trading.
3-Bar-Reversal-Pattern Strategy Backtest This startegy based on 3-day pattern reversal described in "Are Three-Bar
Patterns Reliable For Stocks" article by Thomas Bulkowski, presented in
January, 2000 issue of Stocks&Commodities magazine.
That pattern conforms to the following rules:
- It uses daily prices, not intraday or weekly prices;
- The middle day of the three-day pattern has the lowest low of the three days, with no ties allowed;
- The last day must have a close above the prior day's high, with no ties allowed;
- Each day must have a nonzero trading range.
Please, use it only for learning or paper trading. Do not for real trading.
2/20 Exponential Moving Average StrategyThis indicator plots 2/20 exponential moving average. For the Mov
Avg X 2/20 Indicator, the EMA bar will be painted when the Alert criteria is met.
Please, use it only for learning or paper trading. Do not for real trading.
MACD, backtest 2015+ only, cut in half and doubledThis is only a slight modification to the existing "MACD Strategy" strategy plugin!
found the default MACD strategy to be lacking, although impressive for its simplicity. I added "year>2014" to the IF buy/sell conditions so it will only backtest from 2015 and beyond ** .
I also had a problem with the standard MACD trading late, per se. To that end I modified the inputs for fast/slow/signal to double. Example: my defaults are 10, 21, 10 so I put 20, 42, 20 in. This has the effect of making a 30min interval the same as 1 hour at 10,21,10. So if you want to backtest at 4hr, you would set your time interval to 2hr on the main chart. This is a handy way to make shorter time periods more useful even regardless of strategy/testing, since you can view 15min with alot less noise but a better response.
Used on BTCCNY OKcoin, with the chart set at 45 min (so really 90min in the strategy) this gave me a percent profitable of 42% and a profit factor of 1.998 on 189 trades.
Personally, I like to set the length/signals to 30,63,30. Meaning you need to triple the time, it allows for much better use of shorter time periods and the backtests are remarkably profitable. (i.e. 15min chart view = 45min on script, 30min= 1.5hr on script)
** If you want more specific time periods you need to try plugging in different bar values: replace "year" with "n" and "2014" with "5500". The bars are based on unix time I believe so you will need to play around with the number for n, with n being the numbers of bars.
BACKTEST SCRIPT 0.999 ALPHATRADINGVIEW BACKTEST SCRIPT by Lionshare (c) 2015
THS IS A REAL ALTERNATIVE FOR LONG AWAITED TV NATIVE BACKTEST ENGINE.
READY FOR USE JUST RIGHT NOW.
For user provided trading strategy, executes the trades on pricedata history and continues to make it over live datafeed.
Calculates and (plots on premise) the next performance statistics:
profit - i.e. gross profit/loss.
profit_max - maximum value of gross profit/loss.
profit_per_trade - each trade's profit/loss.
profit_per_stop_trade - profit/loss per "stop order" trade.
profit_stop - gross profit/loss caused by stop orders.
profit_stop_p - percentage of "stop orders" profit/loss in gross profit/loss.
security_if_bought_back - size of security portfolio if bought back.
trades_count_conseq_profit - consecutive gain from profitable series.
trades_count_conseq_profit_max - maxmimum gain from consecutive profitable series achieved.
trades_count_conseq_loss - same as for profit, but for loss.
trades_count_conseq_loss_max - same as for profit, but for loss.
trades_count_conseq_won - number of trades, that were won consecutively.
trades_count_conseq_won_max - maximum number of trades, won consecutively.
trades_count_conseq_lost - same as for won trades, but for lost.
trades_count_conseq_lost_max - same as for won trades, but for lost.
drawdown - difference between local equity highs and lows.
profit_factor - profit-t-loss ratio.
profit_factor_r - profit(without biggest winning trade)-to-loss ratio.
recovery_factor - equity-to-drawdown ratio.
expected_value - median gain value of all wins and loss.
zscore - shows how much your seriality of consecutive wins/loss diverges from the one of normal distributed process. valued in sigmas. zscore of +3 or -3 sigmas means nonrandom realitonship of wins series-to-loss series.
confidence_limit - the limit of confidence in zscore result. values under 0.95 are considered inconclusive.
sharpe - sharpe ratio - shows the level of strategy stability. basically it is how the profit/loss is deviated around the expected value.
sortino - the same as sharpe, but is calculated over the negative gains.
k - Kelly criterion value, means the percentage of your portfolio, you can trade the scripted strategy for optimal risk management.
k_margin - Kelly criterion recalculated to be meant as optimal margin value.
DISCLAIMER :
The SCRIPT is in ALPHA stage. So there could be some hidden bugs.
Though the basic functionality seems to work fine.
Initial documentation is not detailed. There could be english grammar mistakes also.
NOW Working hard on optimizing the script. Seems, some heavier strategies (especially those using the multiple SECURITY functions) call TV processing power limitation errors.
Docs are here:
docs.google.com
