Presented at QuantCon Singapore 2016, Quantopian's quantitative finance and algorithmic trading conference, November 11th. Despite being ‘discovered’ over 20 years ago, there is still confusion on what a momentum strategy entails and people ‘invest in momentum’. There are two generally accepted definitions of momentum in academic literature. In the quantitative equity investment sphere, momentum is frequently referred to as across securities or assets (cross-sectional or relative) and typically traded in a long-short or hedged manner. In futures trading, momentum is often referred to the past return of the security (time-series) and normally traded in a directional fashion. Following from the above, we conducted an analysis on the performance of a momentum strategy of different asset classes: equity, fixed income, futures, and currencies. The study showed that both types of momentum are prevalent and persistent across all asset classes. Furthermore, as the correlations between the two types of momentum strategies and amongst the asset classes are quite low, substantial diversification benefit can be derived by combining them.

1. MOMENTUM
STILL RELEVANT TODAY?
Anthony NG
anthonytyng@gmail.com
11 November 2016

2. None of the contents constitute an offer
to sell, a solicitation to buy, or a
recommendation or endorsement for any
security or strategy, nor does it constitute
an offer to provide investment advisory
services
Past performance is no indicator of future
performance
Provided for informational purposes only
All investments involve risk, including
loss of principal.
DISCLAIMER

3. https://blog.quantopian.com/a-professional-quant-equity-workflow/

4. MOMENTUM
Cross-Sectional Momentum. Jegadeesh and
Titman (1993)
Rank the cross-section of stocks each month
based on their return over the past 6 mths
Form decile portfolios each month
Time Series Momentum. Moskowitz, Ooi and
Pedersen (2012)
Takes long or short position on an asset by only
looking back at its own performance during the
formation period, and not based on its relative
rank across a cross-section

5. Value/Carry/Momentum
FX/equity/commodity/interest rate
Sharpe ratio, average 0.40 per asset class
Maximum drawdowns 1.8x - 3.1x volatility
Positive skew for value and momentum
Negative skew for carry
Sharpe ratio 1.4
*BAZ, JAMIL AND GRANGER, NICOLAS M. AND HARVEY, CAMPBELL R. AND LE ROUX, NICOLAS AND RATTRAY, SANDY,
DISSECTING INVESTMENT STRATEGIES IN THE CROSS SECTION AND TIME SERIES (DECEMBER 4, 2015).
CROSS-SECTIONAL
MOMENTUM*

6. Persistence in asset returns
Buy assets that out-performed
Sell assets that under-performed
Negative auto-correlation for < 1-month
and > 3-years
Positive auto-correlation for 6-12 months
Sample period: 1990 - 2015
*BAZ, JAMIL AND GRANGER, NICOLAS M. AND HARVEY, CAMPBELL R. AND LE ROUX, NICOLAS AND RATTRAY, SANDY,
DISSECTING INVESTMENT STRATEGIES IN THE CROSS SECTION AND TIME SERIES (DECEMBER 4, 2015).
CROSS-SECTIONAL
MOMENTUM*

7. Value/Carry/Momentum
FX/equity/commodity/interest rate
Sharpe ratio, average 0.45 per asset class
Maximum drawdowns 2.4x - 4.4x volatility
Positive skew for value and momentum
Negative skew for carry
Sharpe ratio: 1.37
*BAZ, JAMIL AND GRANGER, NICOLAS M. AND HARVEY, CAMPBELL R. AND LE ROUX, NICOLAS AND RATTRAY, SANDY,
DISSECTING INVESTMENT STRATEGIES IN THE CROSS SECTION AND TIME SERIES (DECEMBER 4, 2015).
TIME-SERIES
MOMENTUM*

8. TIME-SERIES
MOMENTUM*
58 liquid futures contracts
12-month time series momentum, 1-month
holding period
Sample period: 1985 - 2009
Alpha 1.58% per month with respect to
MSCI World Index, Fama-French (1993)
and Carhart (1997) SML (Size), HML (Value)
and UMD (Cross-Sectional Momentum)
* TOBIAS MOSKOWITZ, YAO HUA OOI AND LASSE PEDERSEN, TIME SERIES MOMENTUM (2012)

9. TIME-SERIES
MOMENTUM*
Size each position to match ex ante
annualized volatility of 40%
* TOBIAS MOSKOWITZ, YAO HUA OOI AND LASSE PEDERSEN, TIME SERIES MOMENTUM (2012)

10. TIME-SERIES
MOMENTUM*
Sharpe ratio > 1, 1985 - 2009
Sharpe ratio = 1.1, 1966 - 1985
MSCI World, Beta = 0.09 (t-stat, 1.89)
SMB, Beta =-0.05 (t-stat, -0.84)
HML, Beta = -0.01 (t-stat, -0.21)
UMD, Beta = 0.28 (t-stat, 6.78)
Only significant with UMD (MOM), the
cross-sectional momentum factor
* TOBIAS MOSKOWITZ, YAO HUA OOI AND LASSE PEDERSEN, TIME SERIES MOMENTUM (2012)

11. TIME-SERIES MOMENTUM AND
VOLATILITY SCALING*
Without scaling by volatility, time series
and a buy-and-hold strategy offer similar
cumulative returns, and their alphas are
not significantly different
Cross-sectional momentum offers a
higher alpha than unscaled (scaled) time
series momentum
* ABBY KIM, YIUMAN TSE, JOHN WALD, TIME SERIES MOMENTUM AND VOLATILITY SCALING (2016)

12. OTHER LITERATURE*
48 currencies against USD
Sample period: 1976 - 2010
Currency portfolio, long currencies with
high past excess returns ("winners") and
short currencies with low past excess
returns ("losers")
1-mth formation, 1-mth holding: SR = 0.95
12-mth formation, 1-mth holding: SR = 0.61
* LUKAS MENKHOFF, LUCIO SARNO, MAIK SCHMELING AND ANDREAS SCHRIMPF, CURRENCY MOMENTUM STRATEGIES (2012)

13. DATA
Futures returns - sourced from Bloomberg
9 developed countries index futures
24 commodities futures
13 bond futures
9 currencies futures
Jul 1959 - Oct 2016

14. SUMMARY STATISTICS
Bond
Annualized return: [0.44%, 5.96%]
Annualized Volatility: [1.36%, 10.28%]
Commodities
Annualized return: [-5.52%, 20.16%]
Annualized Volatility: [14.53%, 53.12%]
Currencies
Annualized return: [-0.01%, 6.28%]
Annualized Volatility: [7.24%, 13.91%]
Equities
Annualized return: [-2.92%, 9.90%]
Annualized volatility: [16.74%, 25.00%]

15. BENCHMARKS
EQUITY - MSCI World equity index
BOND - Barclay's Aggregate Bond Index
COMMODITY - S&P GSCI Index
SMB - Size
HML - Value vs growth
MOM - Cross sectional Momentum

16. REPLICATE
MOP, SR = 1.65

17. REPLICATE
MOP

18. REPLICATE
MOP

19. REPLICATE
MOP

20. BUY-AND-HOLD
FACTOR ANALYSIS
REPLICATE MOP

22. SUMMARY AND
FUTURE RESEARCH
Time series momentum is a viable alpha
generating strategy
Risk parity / volatility scaling
Correlation with S&P 500, returns analysis
Post-2008 Analysis
Adding more futures as well as currencies

23. Thankyou
Pleasedon'thesitatetocontactusif
youhaveanyquestions
anthonytyng@gmail.com
@algo_hunter

24. POST-2008

25. POST-2008

26. POST-2008