TA-Trend Basic: Trading Signals for Market Timing

Algorithmic Trading Model Description

Overview and Implementation

For maximum responsiveness with 23/5 trading, this model exclusively trades the S&P 500 Futures Contract. However, it can be implemented fairly accurately through any ETF or other instrument that tracks the S&P 500 such as SPY or VOO. The model is always either 100% long SPX or 100% cash. Each trade alternates between these two positions. In practice, many investors implement our models through a hedging system instead. For example, on a buy signal, you would hold your regular diversified portfolio of ETFs and stocks as you do now. During a sell signal, you would sell S&P 500 Futures contracts against the value of your holdings for a net market neutral overall position. This method has the added benefit of lower overall tax liability.

Trade Frequency

TA-Trend Basic is our least frequently trading model with 107 total trades over the 15.65 year period. On average, the model made one trade per 36.86 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-Trend Basic is best for longer term investors and swing traders who want to avoid large drawdowns while not having to make many trades per year. At 67.29% trade win rate, traders following this model will occasionally run into false positives. Think of these as insurance premiums that are well worth paying to avoid the potentially massive drawdowns that are bound to happen from time to time (such as the -36.01% thrashing the SPX took during the COVID-19 crisis).

Key Indicators

This model focuses on searching for trend following opportunities, a trading style that attempts to capture gains through the analysis of an asset's momentum in a particular direction.

Indicator Overview

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

1. Bollinger Bands
2. Moving Average Convergence Divergence (MACD)
3. Simple Moving Average (SMA)

The model uses these and other minor indicators under varying and adaptive time parameters to identify medium-term trend changes. As with all our models, we run the backtest through our proprietary anti-overfitting machine learning system to ensure we are identifying real and repeatable patterns.

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:

• MACD is a trend-following momentum indicator that shows the relationship between two moving averages of a security's price. By itelf, MACD is a lagging indicator that often generates signals too late after the lion's share of the trend has already been established. However, we've discovered ways to combine MACD with our proprietary systems of identifying core market "zones", that make it a much more useful tool. When our system identifies a choppy zone, we disregard MACD as too many false positives arise. However, when in a calm uptrend zone, MACD can help us give an early warning of trend changes by looking at the second derivative of the MACD histogram. Similarly, in a chaotic zone, MACD can help us identify unsustainable declines.
• Simple Moving Averages are among the most basic of all TA indicators; yet they are famous for more than just their simplicity. For example, it's very well-known that the market behaves much differently when above its 200 day moving average than it does when below, all other factors considered equally. This most basic of all market timing systems, the Ivy Portfolio, has had surprisingly decent results in the past by simply buying above the 200 day and selling below the 200 day. While it does not outperform the market by CAGR, it does reduce drawdown and have better risk-adjusted returns. Our models use much more sophisticated applications of SMAs to assist as one input to our system of market "zone" identification discussed above.

When building the model, we took these TA tools and many others into consideration and carefully tested the patterns using machine learning and heuristics to distinguish those with predictive power against those that merely seemed like they had predictive power. This is what we call our proprietary anti-overfitting engine, and although no model can ever perfectly predict market movements, with this engine you can rest easy knowing the model is backed by the latest science and engineering. We leave human emotion at the door; the signals are generated 100% mechanically.

Performance

TA-Trend Basic achieved an annual CAGR of 16.48% vs. 13.56% for SPX which we use as the benchmark. This represents a substantial outperformance of 2.92% per year. $100,000 invested in the model at inception would have grown to $1,088,115. Following the rules of all investment professionals, we must of course disclaim that past performance does not guarantee similar results in the future. However, our testing period covers many different market conditions, from the uber turbulent COVID-19 drawdown in Feb-Mar 2020 to the incredibly complacent 2013 and 2017 years. This lengthy period of analysis, combined with our proprietary anti-overfitting system, gives us confidence that our model has alpha.

Drawdown

Historically, the model had a maximum drawdown of -24.98% vs -36.01% for the SPX. This represents a substantial reduction in drawdown vs. the benchmark of 30.63%. When looking for a great model or market timing system, it's very important to not only consider absolute performance but also drawdown because investors should value risk-adjusted returns above absolute. The model's combination of absolute outperformance and smaller drawdown is exactly what savvy investors should be looking for in an actionable market timing system. However, absolute outperformance is not this model's primary goal. TA-Trend Basic seeks to reduce max drawdown as much as possible in few total trades per year.

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