Copyright © 2018 T Leitch & J Liew
Agenda
- Definition: Managed Futures/CTAs
- Background Color
- Father of Trend-Following
- The Amazing Experiment
- Managed Futures Indices
- Trend-Following vs Momentum
- CAIA – Trends on Known-Factors
- Global Systematic Futures Model
- Trend-Following on Equities
- HWK#2 Assigned
Definition: Managed Futures/CTAs
Managed Futures refer to investments that are offered by professional money managers known as “Commodity Trading Advisors” (CTAs). CTAs are required to register with the CFTC through the NFA prior to providing public money management services.
CTAs may employ both discretionary and systematic trading styles across liquid futures markets, such as equities, gov’t bonds, softs, metals, grains, and fx. Trend and counter-trend strategies are typically employed across this industry.
Historically, CTAs have, on average, generated returns that have low correlation to typical hedge fund strategies. Managed futures are characterized as having higher capacity and slightly higher volatilities compared to other hedge fund strategies. 
Managed Futures/CTAs Correlation
Diversification benefits exist when included with almost all other hedge fund strategies, so why are they not even more popular as investment vehicles?
Perception vs Reality
- The ugly step-child of the modern day hedge fund, fights for legitimacy
- Longer history of money management, but less credentials
- Much more advanced and established as respectable industry in London/Europe
- More (pit) trader mentality, especially managers who cut their teeth in Chi-town
- However, convergence towards institutionalization has been pervasive
Pop Quiz: Who’s the Father of Hedge Funds?
Who’s the Father of Trend-Following?
Father of Trend-Following: Richard Donchian
1. Beware of acting immediately on a widespread public opinion. Even if correct, it will usually delay the move.
2. From a period of dullness and inactivity, watch for and prepare to follow a move in the direction in which volume increases.
3. LIMIT LOSSES and ride profits, irrespective of all other rules.
4. Light commitments are advisable when market position is not certain. Clearly defined moves are signaled frequently enough to make life interesting and concentration on these moves will prevent unprofitable “whip-sawing.”
5. Seldom take a position in the direction of an immediately preceding three-day move. Wait for a one-day reversal.
6. Judicious use of stop orders is a valuable aid to profitable trading. Stops may be used to protect profits, to limit losses and to take positions from certain formations such as triangular foci. Stop orders are apt to be more valuable and less treacherous if used in proper relation to the chart information.
7. In a market in which upswings are likely to equal or exceed downswings, heavier position should be taken for the upswings for percentage reasons – a decline from 50 to 25 will net only 50% profit, whereas an advance from 25 to 50 will net 100%.
8. In taking a position, price orders are allowable. In closing a position, use market orders.
9. Buy strong-acting, strong-background commodities and sell weak ones, subject to all other rules.
10. Moves in which rails (transportation) lead or participate strongly are usually more worth following than moves in which rails lag.
The amazing experiment..
Drill Down:
CTAs AUM Growth
Futures/CTAs Indices
This industry will only continue to grow, but why?
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Compare BTOP50 with S&P500 yearly returns from 1987 to 2011
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Compare BTOP50 with S&P500 yearly returns from 1987 to 2011
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Examples of CTAs
Trend-Following vs Momentum
Momentum
“In an important study Narasim Jegadeesh and Sheridan Titman (1993) document the existence of a momentum effect. Jegadeesh and Titman attribute this effect to the fact that investors under-react to the release of firm-specific information, a cognitive bias.”
Behavioural Finance
Momentum
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“Value and Momentum Everywhere”
Asness, Moskowitz, and Pedersen
Time Period: 01/1974-10/2008
Journal
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Examine SMB, HML, and the “Market” - from Fama-French’s 3-factor model
Comparing EW vs EW* (+36%!)
Momentum Across Asset Classes
Constructing A Simple Momentum Strategy
Momentum Strategy
Medium-term Model: Global Systematic Futures
Model Description
- Quantitatively driven trading model that attempts to capitalize on the predictable movements within liquid global futures markets based on technical indicators
- The model identifies markets that have inherent momentum based on proprietary transformation of inputs with the key component of identifying entry and exit points to period of “valued-momentum”
- Model consists of a blend of scientific-rigor and artistic-experience
- Future markets traded include but limited to: (1) Stocks Indices, (2) Fixed Income (both Bonds and Short-term Rates), (3) Currencies, (4) Energies, (5) Metals (both Precious and Industrial); (6) Agricultural (both Grains/Oil Seeds and Softs); and (7) Livestocks
A natural extension would be to see if trend-following works in stocks…
Does Trend Following Work on Stocks? –Wilcox and Crittenden (2005)
Abstract Over the years many commodity trading advisors, proprietary traders, and global macro hedge funds have successfully applied various trend following methods to profitably trade in global futures markets. Very little research, however, has been published regarding trend following strategies applied to stocks. Is it reasonable to assume that trend following works on futures but not stocks? We decided to put a long only trend following strategy to the test by running it against a comprehensive database of U.S. stocks that have been adjusted for corporate actions. Delisted companies were included to account for survivorship bias. Realistic transaction cost estimates (slippage & commission) were applied. Liquidity filters were used to limit hypothetical trading to only stocks that would have been liquid enough to trade, at the time of the trade. Coverage included 24,000+ securities spanning 22 years. The empirical results strongly suggest that trend following on stocks does offer a positive mathematical expectancy, an essential building block of an effective investing or trading system.
Methodology
- Database: 1983 to 2004
- Corporate actions properly back adjusted, cash/stock dividends, delisted, mergers,
- spin-offs, reverse splits/splits, etc.
- Filter out penny stocks and filter for minimum daily liquidity
Methodology (cont’d)
- Entry – All-time highest close – “if today’s close is greater than or equal to the highest close during the stock’s entire history then buy tomorrow on the open”
Methodology (cont’d)
- Exit, function of Average True Range
- Define “True Range”
\[TR = max(High - Low,|High - Close_{-1}|,|Close_{-1}-Low|)\]
The true range is the largest of the: - Most recent period’s high minus the most recent period’s low - Absolute value of the most recent period’s high minus the previous close - Absolute value of the most recent period’s low minus the previous close
Methodology (cont’d)
- Exit, function of Average True Range
- Average True Range
\[ATR = \frac{1}{T} \Sigma^{T}_{i=1}TR_{i}\]
Methodology (cont’d)
- Exit, function of Average True Range
- Average True Range
\[ATR = \frac{1}{T} \Sigma^{T}_{i=1}TR_{i}\]
Methodology (cont’d)
- Exit, function of Average True Range
- Average True Range
\[ATR = \frac{1}{T} \Sigma^{T}_{i=1}TR_{i}\]
Methodology (cont’d)
- Exit, function of Average True Range
- Average True Range
\[ATR = \frac{1}{T} \Sigma^{T}_{i=1}TR_{i}\]
True Range
Methodology (cont’d)
- Exit, function of Average True Range
- Average True Range
\[ATR = \frac{1}{T} \Sigma^{T}_{i=1}TR_{i}\]
True Range
Methodology (cont’d)
- Exit, function of Average True Range
- Average True Range
\[ATR = \frac{1}{T} \Sigma^{T}_{i=1}TR_{i}\]
True Range
ARR
Examples of 10x ATR from Entry
Examples of 10x ATR from Entry
Examples of Trades
Results: +18,000 trades, over 22yr period, 10-unit ATR stop, 0.5% round-turn
Homework #2 - Building Your Own ETF/CTA
