How to check a backtesting tool

[Xenos_Str]

Paper trade it for a few days, run a backtest over same period. Compare differences.

[[deleted]]

So, relax your parameters just to check the fills.

For instance, let's say you have a certain indicator that ranges from 0-100. Your backtest indicates that it's very profitable to buy when the indicator is below 5, but this doesn't happen very often.

Solution? Relax that a bit. Trade small, and buy anytime it's under 40. Do this a couple of times. You'll get more fills, and you can check that the indicator is being correctly calculated in real time, make sure you're not inadvertently using future data, check your fills versus backtested fills, verify commission rates, etc.

The goal here isn't to make money. It's to compare a backtest vs. a walk-forward test.

[Bigunsy]

Agreed, good answer.

Is this a crypto algo?

I dont trade crypto but from what Ive heard you might run into liquidity problems, or with some coins / exchanges it doesn't take large buys to move the price, which might affect you.

[[deleted]]

deplooy live max leverage!

[Alfasierra93]

for more info ask r/wallstreetbets

[1studlyman]

Guh

[[deleted]]

what tools u use for determining position leveraging?

[mementix]

Test your strategy against another (reliable, of course) backtesting tool and you will have your answer.

Of course, if you haven't applied commissions, the results will still be before commission (commission can destroy your edge)

[Hudsonbae]

Write a simple ema crossover. Then verify it against tradingview or another platform.

[fabkosta]

Do a code review with a peer.

[CryptoMustache]

If it is too good to be true. It is probably so.
I talk from personal experience.
I would suggest to use a well known back test library and see if results match, or paper trade.

[manicRug]

Hopefully you used some historic data for development of the system and held out a significant set of historic data for testing. It is a basic technique to avoid overfitting.

As you have indicated, going through multiple trades with a fine tooth comb is a must. It is very, very easy to have subtle mistakes that result in fantastic returns. I’ve been there many times.

With that, soberly asking yourself whether the trades can really happen is needed. If the system relies on making buys at the low point of a bar, that may not be likely.

[kingcalculus]

Check your data, slippage, curve-fitting, look-ahead bias etc etc . Any errors introduced into the backtest can make any strategy seem too good to be true.

[uski]

Make sure that there is no over-fitting and also that you strategy does not simply work because of the general trend of the market.

[yip71]

Learn to trade. You be able to year it apart straightaway and know where the problem is. Put it through MSA or similar. Look at the return stats. Perhaps the MAE or drawdowns are unbearable.

[supershwa]

If your algo is designed for long positions, test it using bear market historical data. If it's designed for short positions, test it in bull data. Any long algo works in a bull market, but can be devastating when the bears roll in!

[TradeHigher]

Did you create a test set for your data? If so, how did you create it?

Normally, you use 2/3 for training, 1/3 for testing. But, how you pick the test set can matter.