TechnologyOne RSI Strategy

No. RSI < 30 indicates the stock is oversold but doesn't guarantee a bounce. Wait for RSI to cross back above 30 (exit oversold) with a bullish candle confirmation. Also apply filters: trend context, volume, sector. Blindly buying at RSI < 30 leads to catching falling knives.

RSI 14 (14-period) is standard - smoother, fewer signals, more reliable. RSI 9 is faster - more signals but also more noise and false signals. For swing trading TNE, RSI 14 is recommended. RSI 9 might work for intraday but requires quicker reaction time.

Yes, especially in strong downtrends. During major selloffs, RSI can stay below 30 for days or weeks. This is why waiting for RSI to EXIT oversold (cross back above 30) is important - it confirms selling pressure is actually abating, not just pausing.

TechnologyOne is a profitable quality compounder with steady earnings growth and a Consulting/services segment, whereas high-growth SaaS peers (such as WiseTech and Xero) carry higher volatility and are more prone to violent, news-driven drawdowns. For RSI trading, TNE's pullbacks tend to mean-revert more cleanly, making it a more disciplined, lower-drama vehicle - though its extremes occur less frequently.

Daily timeframe is recommended for beginners - it's less noisy and requires checking only once per day at market close. Hourly can be used for entry timing once you have a daily signal. Avoid lower timeframes (15-min, 5-min) until you're experienced - they generate too many false RSI signals.

Divergence shows potential reversal but isn't an immediate signal. Wait for price confirmation: for bullish divergence (lower price low, higher RSI low), wait for price to break above a recent swing high. Combine with support/resistance levels. Divergence at support is more actionable than divergence in 'air'.

Use mean reversion (extremes) when ADX < 20-22 (ranging market). Use momentum (RSI > 55 or < 45 with trend) when ADX > 25 (trending market). Check trend context too - mean reversion works better when the RSI extreme is counter to the primary trend (oversold in an uptrend).

Weekly RSI sets primary bias (above/below 50). Daily RSI provides signals. Hourly RSI times entries. Best trades: Weekly bullish + Daily oversold bounce = high probability long. Avoid: Weekly bearish but buying daily oversold - lower probability as the primary trend is against you.

For an oversold bounce: buy ATM calls or bull call spreads (reduced cost). For an overbought reversal: buy ATM puts or bear put spreads. Use near-month options for quick mean reversion expected in 3-5 days. Longer-dated options for longer setups. Spreads are cost-effective for moderate conviction signals.

Very important. Volume confirms RSI signals. Oversold bounce with volume spike = buyers arriving (good). Oversold bounce with no volume = weak signal. High volume new lows despite RSI < 30 = more downside likely. Always check the volume pattern before acting on RSI signals.

Calculate ATR percentile over 100 days. High ATR (top 20%): use 25/75 thresholds. Low ATR (bottom 20%): use 35/65. Alternatively, use RSI Bollinger Bands - oversold when RSI touches its own lower band regardless of absolute level. This adapts to the current volatility regime automatically.

A failure swing is an internal RSI pattern. Bullish: RSI < 30, bounces to 40-50, retests but stays > 30, breaks above the prior bounce high. This shows momentum shift before price confirms. Trade when RSI breaks its prior bounce high, with a stop below the retest low. Higher probability than simple oversold readings.

Train a classification model on RSI signal features (RSI value, rate of change, ADX, volume ratio, sector RSI, days to earnings). Target: signal success/failure. The model learns non-linear patterns like 'RSI works when ADX < 22 but fails when ADX > 30.' Use the probability output for position sizing. Can improve win rate by 5-7%.

Use walk-forward analysis: train on 3 years, test on 1 year, roll forward and repeat. Test multiple parameters but don't over-optimize. Measure Sharpe ratio and max drawdown, not just win rate. Require 100+ trades for statistical significance. Compare to a buy-and-hold benchmark. Recalibrate every 1-2 years.

Calculate the strategy's historical volatility. Target an overall portfolio volatility contribution. If the strategy has 18% volatility and you target 12%, scale the allocation by 12/18 = 0.67. Use fractional Kelly for position sizing within the allocation. Limit correlation with other technology strategies - they move together, so treat them as a single strategy for diversification purposes.