TA-MR Basic: Trading Signals for Market Timing

For maximum responsiveness, the model's historical implementation uses the S&P 500 Futures Contract, which can trade outside regular U.S. equity-market hours. An investor could choose another S&P 500-linked instrument such as SPY or VOO, but differences in trading hours, tracking, financing, taxes, and execution can cause realized results to diverge from the modeled record. The model state itself alternates between 100% long SPX and 100% cash. A sell signal can also be used as a hedge overlay rather than a full liquidation, but hedge sizing and tax effects depend on the user's implementation and are not modeled here.

TA-MR Basic is our most frequently trading model with 581 total trades over the 17.45 year period. On average, the model made one trade per 7.57 trading days. However, the trades are not uniformly distributed; during periods of higher market volatility, more trades were made compared to relatively calm periods.

TA-MR Basic has a reviewed historical trade win rate of 89.67%. Because the strategy uses relatively frequent mean-reversion trades, win rate is only one part of the profile; average gains and losses, drawdown, turnover, and implementation costs matter too. A historical hit rate does not imply that future trades will behave the same way.

This model focuses on searching for mean reversion opportunities, a theory used in finance that suggests that asset price volatility and historical returns eventually will revert to the long-run mean or average level of the entire dataset.

Indicator Overview

A few of the indicators this model uses behind the scenes are:

1. Bollinger Bands
2. Chande Momentum Oscillator (CMO)
3. Relative Strength Index (RSI)

The model uses these and other indicators across varying time windows to identify short-horizon mean-reversion entries. During development, candidate relationships are evaluated with a proprietary anti-overfitting workflow that uses machine learning and heuristics. The process is intended to reduce overfitting risk; it cannot prove that a historical relationship will persist out of sample.

Indicator Analysis

Technical analysis (TA) is a trading discipline used to identify trading opportunities by analyzing statistical trends gathered from trading activity, such as price movement and volume. In aggregate, TA is about analyzing the psychology of market participants through their transactions. Some examples of TA used in this model:

• Bollinger Bands with RSI and SMA synchronicity on multiple time frames. Bollinger Bands (BB) draw two lines around a simple moving average (SMA) based on a positive and negative standard deviation. During times of volatility, the bands widen and then contract when volatility subsides. When price moves well outside the bands in either direction, it can be a warning sign that the price action has been unsustainable and that price is likely to mean-revert back inside the bands soon. Combining these extreme movements with the relative strength index (RSI) as well as where the current price rests in relation to important SMAs (such as 20 day, 50 day and 200 day) can be a tip to the model that we are likely near a local minima or maxima.
• Chande Momentum Oscillator (CMO) uses momentum to identify relative strength or weakness, classifying periods by degree of overbought or oversold. By itself, CMO can be noisy, but when combined with RSI, SMA, BB width and other TA indicators and analyzed across multiple time frames for synchronicity, it can be a valuable tool in guiding the model to certain signals.

TA-MR Basic recorded an annual CAGR of 17.56% versus 13.62% for SPX over the reviewed historical sample, a CAGR gap of 3.94% per year. In that same sample, $100,000 following the modeled trades would have grown to $8,410,000. The record combines a backtest period with subsequent live performance disclosed on the page, so it should not be treated as one uniform body of evidence. Historical results do not establish an expected future return, and a user's realized result can differ because of execution, slippage, taxes, position sizing, and changing market regimes.

The model's historical maximum drawdown was -24.85% versus -36.01% for SPX, equivalent to a 30.99% relative reduction in the reviewed sample. Drawdown complements return by showing the worst peak-to-trough decline observed in that period. It is not a ceiling on future losses, and the historical relationship to SPX can change in a different market regime.