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1 Commodity Trading Advisors Managed futures. 2  30 yr old industry of professional money managers k/a CTAs  Objective: seek profit potential  Lower.

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Presentation on theme: "1 Commodity Trading Advisors Managed futures. 2  30 yr old industry of professional money managers k/a CTAs  Objective: seek profit potential  Lower."— Presentation transcript:

1 1 Commodity Trading Advisors Managed futures

2 2  30 yr old industry of professional money managers k/a CTAs  Objective: seek profit potential  Lower portfolio risk: diversification  Negative correlation : stocks & bonds  Maintain positive returns even in bear markets

3 3 1. CTAs are traders (individual, firm) qualified & licensed by the CFTC 2. Provide specific futures trading advice for commodity trading 3. Provide specific trading recommendations 4. When to establish long/ short positions in  Metals  Grains  Soft commodities

4 4 Regulation Held accountable, & have to comply with many rules and regulations set forth by the CFTC Register with CFTC Furnish Rigorous disclosure documents reviewed by NFA

5 5 HISTORY  Exchange traded equity derivatives 4-6 yrs old  Future exchange physical commodities 1875  Cotton was the 1 st product to be traded, oilseeds, jute, wheat etc  After independence UK 1947 set back  1952:cash settlement & option trading was banned  FMC: commodity futures market began taking shape  2002: NMCE  2003: MCX & NCDEX

6 6 Exchanges list a no. of products But trading is only in handful  NMCE: 61 listed, 6 actively traded (jute, pepper, coffee)  MCX: 9 of the 50 listed (precious metals, crude oil)  NCDEX: 16 of the 39 listed (gaur & soy)  NBOT: 1 of the 6 listed

7 7 Evaluating CTAs  Fees  Trading program (trend followers, market neutrals)  Trend followers:  proprietary technical or fundamental trading systems or both  When to go long/short in certain futures market  Market Neutral Traders:  profit from spreading different commodity markets, delta neutral programs, non-directional trading strategies

8 8 Drawdowns  Peak to valley drawdown  Largest cumulative decline in trading account  How long a CTA took to make back the losses  Shorter the time required to recover from drawdown the better the performance

9 9 Annualized rate of return  These performance numbers are provided in the disclosure document, but may not represent the most recent month of trading.  want to know, for example, if there have been any substantial drawdowns that are not showing in the most recent version of the disclosure document.

10 10 Risk-Adjusted Return  Dispersion of losses  Calmar ratio  Sharpe ratio  Alpha coefficients  Compare performance in relation to certain std benchmarks like sensex, nifty

11 11 Top 10 CTA- (2004-07) Ranked compounded annual return Programme name or manager3- yrs comp. ann. return Chicago capital mgmt75.37% Pixley capital mgt66.59% Dighton worldwide54.15% Dighton capital USA49.36% Financial commodity investments42.73% AAA Capital mgt (energy)42.04% Rosetta capital mgmt28.67% CKP finance associates28.24% Commodity futures services26.74% LJM Partners (neutral S&P Option)24.35%

12 12 Top 10 CTA- (2004-07) Ranked by sharpe ratio Programme name or manager K4 Capital mgmt3.03 Chicago capital mgmt2.43 AAA capital mgmt2.19 Financial commodity invsts2.12 Zenith resources (index options)1.76 Witter & lester (stock index)1.71 LJM partners1.68 Newton capital partners1.57 Zephyr asset mngmt1.19 Dightpon worldwide1.11

13 13 Literature review  Literature on CTA efficiency non-existent (4 std)  CTAs use long/short positions coupled with leverage to enhance portfolio returns  Traditionally CTAs trade 50-100 futures contracts on various global markets & Attempt to minimize their losses as they occur

14 14  International derivatives & securities mkts database CISDM, MSCI world index, HFR hedge fund composite index, zurich CTA index  Cross efficiency model help to examine the trading efficiency of CTAs Following optimization obtained max Σu r y ro + u o / Σ v i x io

15 15  Small CTAs trade less frequently  Are less efficient as large CTAs  Large CTAs take less risk (high fees )  Efficient CTAs also have high sharpe ratio & spearman correlation ranking is positive significant  Amount of leverage is related to performance

16 16  Simple efficiency, Cross efficiency & super efficiency models can be used to select the CTAs  CTA have been found to reduce the volatility of portfolio in down markets  CTAs improve portfolio's mean variance characteristics, reduce incidence of kurtosis  CTAs truly add the importance of diversification

17 17  CTAs provide greater shelter than hedge funds, mutual funds in bear markets because of their negative correlation to markets  All investors benefit by allocating resources via CTAs  SEBI must provide for adequate role of CTAs in Indian market

18 18  The CTAs must be encouraged to participate in Indian market directly  They must ensure the benefit of the investors  They must be designed to add benefit to portfolios in downside market as shown by empirical results  Efficiency of CTAs must be monitored with help of efficiency models to safeguard the investors

19 19  The government must sponsor studies on CTAs as trading advisors and their role in India  These studies must assess the need, relevance and efficiency of CTAs in Indian capital market  These studies should aim at maximizing the return to the individual as well as the institutional investor  With protection during downside market and lesser volatility, CTAs will definitely provide a thrust to portfolio returns for both government as well as the private institutional portfolios.

20 20  Thank you


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