vGRE*

Trade Nasdaq100 (NAS100) based on vGRE* (volume-weighted Golden-Ratio Estimator with *genetic-optimization for >66% efficacy estimated from signal probability). Financial markets are inefficient. At any particular price, there are buyers who believe that the price is relatively cheap and vice versa. vGRE* helps members uncover this inefficiency for profit. New investors in NAS100 at higher prices support previous investors.

NAS100: vGRE* Weekly Strategy 16-May-2022 Analyzing data from the previous week can shed light on the coming week. For the week of 9-May-2022 to 13-May-2022, the vGRE* displayed a relatively stable trend indicating a stable NAS100. The vGRE*-CR volatility was in a defined, controlled range suggesting a stable NAS100. NAS100 ended lower at 12,387 (NAS100 futures: 12,358) from 12,693 (NAS100 futures: 12,664).

A total of 5 buy/hold signals against 0 sell/shorts suggest an overall buy/long strategy for the coming week of 16-May-2022, prices below the price of 12,358 are opportunities for accumulation with a 100% (5/5) probability of upside from 12,358 to 12,387 for the week.

Based on the expected average price range of +/-300 points per week and depending on personal risk-reward ratios, averaging down (steps of 150) for entries and trailing stops (steps of 25) for exits can be performed. Bollinger Bands W1 (20,2) provides a good quarterly guide.

Do not over-leverage from over-trading and be forced to close your positions due to margin calls. As a general rule, divide your capital by a factor of 100,000 to calculate your first entry lot size and do not trade more than 5 lots for every US$10,000 to provide a sufficient buffer from volatile conditions. Ensure sufficient funds in your trading account. Traders are responsible for their own trading decisions.

  • vGRE* as a Technical Indicator for Risk Analysis on NAS100.
  • Risk-cybernetics is applied to the GR-Estimator as a technical indicator, which includes trading volume and golden-ratio segments as input parameters, computed with genetic-optimization.
  • The quantification of risk is probably the most important activity for investments. Both public and private sectors spend millions on beefing up infrastructure for the purpose of enhancing risk management processes.
  • Here we provide the vGRE* which helps account for the self-fulfilling prophecy in technical analysis.
  • The vGRE* incorporates a random parameter optimization function based on the Golden-Ratio (GR) where GR≈1.618.
  • The inputs of open price, high price, low price, close price are split into line segments a and b where:
  • a = | minimum price minus mean price |
  • b = | mean price minus maximum price |
  • where a>b : hypothesized ratio=1.618
  • where b>a : hypothesized ratio=0.618
  • We then compute the Genetic-Factor (GF) via our proprietary genetic-optimization process where the GF-estimate is an optimized best-fit result between 0 to 1.618 subject to the calculated a and b data as constraints.
  • The GR-Estimator (GRE) is computed as GF/GR and the vGRE is the adjusted (GF/GR) for easy reference, multiplied by the trading volume in that period.
  • The vGRE* is thus a technical indicator that reflects the potential volume-weighted price change and any spike represents a potential downside that can be a potential short or exit, while a dip represents a potential upside that can be a good entry point. This serves as a check with other familiar technical indicators and addresses the self-fulfilling prophecy debate with volume-weighted optimization.
  • The Signal (Sig) of 1 (buy/hold) and 0 (sell/short) are reported below per trading day. To use it, refer to every trading week which reports 5 signals. For eg. 3 buys to 2 sells would indicate an overall a buy/hold signal. Again, this is not definitive and is also used as a check with common indicators.
  • The first derivative of vGRE* or the Continuous Return (CR) statistic is also reported for 2021 YTD to serve as a check for stationarity of the vGRE* statistic. vGRE*-CR should be a stationary/stochastic process with constant variance and a change of variance indicates deviation from the normal and deserves attention for the specific period.

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