nextSignals employs a multi-factor trading strategy that emphasizes the charting of data-driven indicators to help conceptualize the following:

  • valuation measured by structural relationships in the dual auction,
  • time series momentum as a function of volatility weighting,
  • evidence of asymmetric information in options market pricing and order flows,
  • detection of AI-enabled algorithms (low-latency and liquidity-consuming), and
  • scenario planning for tail events related to geopolitical and macroeconomic shocks.

The auction market price discovery process presents two trade opportunities:
  1. determined shifts in order flow that occur during well-delineated periods of balance, and
  2. rejection of extremes in sentiment when price deviates significantly from value.

Options with low implied volatility tend to have the greatest under-pricing and attract the bids of traders with superior knowledge. Identifying options with new activity, high liquidity, and volatility mispricing can provide one measure of anticipated direction.

The nextSignals A01 indicator estimates the concurrence of  order book fade and momentum ignition to unmask AI-enabled trading. Given small predictive power and a sufficiently large number of independent bets, a high Information Ratio drives profit.

HFT data has shown that jump risk premium is large and positive. Furthermore, it is concentrated in periods when the index options market is closed. Jump skew premium in index options is compensation for an investor’s inability to adjust their risk exposure. Preparedness via short-term hedges or getting flat can markedly reduce drawdowns


Expect to be wrong.

  1. Predetermine and respect the level you will cut a loss “mercilessly” and then move on.  (Use chart alerts as “mental stops” to avoid getting taken out by short-term volatility.)
  2. Exit decisions should be based primarily upon one of two conditions:
    a) the position is richly valued and has more to lose than it has to gain, and
    b) the position has performed poorly from the outset. (Early adversity is a poor prognostic indicator, especially for long OTM options trades.)

Note: A decision not to take profit should represent the view that the current market remains undervalued.

Profits are not real until they are taken.

  • Perfect timing efforts can cost a lot; exit when nearing a profit target. (Financial academic studies suggest that scaling out reduces profits, over the long run.)
  • Selling into strength during rally climaxes ensures the least slippage, tightest spreads – and thus, the best fills.

Event risk happens.

  • Ultimately, the only way to avoid drawdowns is to forecast them and evade them.
  • As event risk is amplified by machines, consider closing vulnerable positions ahead of known market moving events (e.g. FOMC announcements, corporate earnings). Alternatively, a near-term protective put should be considered.



Simple Options Portfolio Allocation Methodology: Calculating “Capital at Risk”

  • In a $10,000 account – 3(-5)% of the net allocation to options trading (e.g. 20%)
  • In a $150,000 account – 1(-2)% of the net allocation to options trading (e.g. 20%)

So for a $10,000 account …with 20% of that allocated to options trading …you’ve got $2,000 to put at risk and you do it at 3 – 5% per trade = $60-100 per trade.

Note: Generally speaking, the more capital in one’s account, the more trades one has to do. Experienced traders trade small and have more occurences.

Basic Trading Goal for Index Futures

  • Focus on one market (e.g. /ES) and one chart (1600t).
  • “2-10-40” – Trading 2 contracts and gaining 2 points per day ($200) equals 10 points per week ($1,000) and thus 40 points ($4,000) per month.