summary: edgeful algos give you fine control over risk management — here's what you can adjust and how it all works together.
adjustable parameters
position size: how many contracts or shares per trade
stop-loss (SL): max loss per trade
take-profit (TP): profit target that closes the trade
trading hours: when the algo executes trades. a window may cross midnight (18:00 to 09:00, say) and edgeful works the crossing out for you, the same way it handles a report session that spans midnight, including how the day of the week is attributed. if you would rather the window did not straddle midnight at all, set the timezone so it doesn't: an Asia timezone such as UTC+9 can place an overnight New York window inside a single calendar day
max loss ($): the most you'll lose on a single trade, in dollars. available on the ORB and engulfing algos, not the IB algo (more on that below)
timeframes: the chart timeframe the algo reads. the algos are intraday and flatten at the end of your trading-hours window
what affects performance
trading goals: high return vs. low-risk — this shapes everything else. adjust risk tolerance and expectations to match your goals.
asset choices: stocks, currencies, futures — they behave differently. pick what fits your strategy.
timeframes: short-term intraday or long-term positions — choose based on your objectives, not the chart you're looking at.
default settings and optimization
negative performance often comes from restrictive defaults — like a max loss that's too tight, which can cut trades too early.
here's a 5-step optimization process:
define your objectives — goals, risk tolerance, assets
select and configure parameters — assets, timeframes, risk metrics
backtest with historical data
iterate and optimize based on results
deploy in live markets — monitor and adjust as needed
ORB is the simplest place to start. always backtest or use demo accounts before going live.
how stop-loss and max loss interact
your stop-loss is set as a % of the range, and max loss caps the same trade in dollars. whichever is hit first closes the position. on fast moves, slippage on the market exit can still push the final loss past your max loss.
note — the IB algo does not have a max loss setting. the IB algo enters trades on a retracement back into the initial balance range, so a dollar max loss could interfere with the retracement entry logic. risk on the IB algo is managed through your stop-loss and position size instead.
in manual trading, max loss doesn't apply — execution happens directly on your broker's platform.
this layered approach gives you control but needs careful setup.
daily operations
most edgeful algos close all positions at the end of the trading day or session. no overnight holds. this keeps risk managed and results clear.
multiple take-profit targets
IB, 2TP ORB, and 2TP engulfing algos support 2 take-profit levels. other algos use a single TP.
you can also configure position sizing — how many contracts per trade. that number lives on the default order size line in the indicator's properties tab, and the type next to it must stay on quantity. TradingView's latest update defaults that type to % of equity, which sizes futures orders to 0 contracts — no trades in the strategy report (this report requires trade data) and no alerts. see strategy report says "this report requires trade data".
entry and exit orders
when you create a strategy, you pick the order type for your entry and your take-profit: market or limit. limit gives you price control but can miss the fill. market gets you in or out but accepts slippage.
the stop-loss is always a market order, so you get out when you need to. the full tradeoff is in execution, slippage, and order types in algo automation.
key takeaways
edgeful's algos are flexible. understand how max loss and SL interact (and that IB handles risk differently — through SL and position size only). test parameter changes thoroughly. optimize your defaults — this level of control means you can design strategies that match your exact risk-reward profile.