Benchmarks against which to measure performance

In the table, I give three figures which reflect my own performance along with other benchmarks:

Every month, I have been giving out a summary of my trading and investment performance. Here I give my own performance, along with other benchmarks. The question is, what are these benchmarks? Are they appropriate? How should one look at these benchmarks. Here I will just elaborate on these benchmarks.

a) My investment returns: This is for that capital which is deployed on a long term basis, without any leverage. The typical churn in this part of my portfolio is less than 10% a year. My investment returns as given include dividends received on stocks.

b) My trading returns: Trading returns are those returns which are given for the various trading strategies I employ. These returns in percentage terms are only on the actual capital employed (cash+cash equivalents like liquid bees). The percentage returns do not reflect the fact that approx 40% of the capital is in stocks of companies which are pledged as security. These returns must be evaluated accordingly. My trading returns also include my returns on commodity futures and interest rate futures, as well as the occasional option trade. Most such trades are always in the market (i.e., they are not long-flat, they are long-short). When the trend reverses, typically, my trade will move from long to short or vice versa.

c) My returns on traded equity: This is more recent. Since October 2018, I have deployed a significant amount of capital (Approx 15% of the total capital in my investment portfolio) into equity shares on a non-leveraged basis. The basis for selecting these stocks is purely by trend following techniques. These stocks are not meant to be invested for the long term. As soon as the trend reverses, there will be a sell. This is a long-flat strategy. No shorting is done.

Coming to the various benchmarks:

a) I have indicated the Nifty Total Return Index(TRI), Midcap-150 (TRI) and Smallcap-250 (TRI) as the appropriate benchmarks for my portfolio. My current investment portfolio consists of 20% large caps, 50% midcaps and 30% small caps. So my actual returns should be someway better than the returns of these three strategies combined in the above proportion.

b) Among other benchmarks, I have also included 2 mutual funds, both of which are famous outperformers in their respective categories. They are not the category average. These two benchmarks include the HDFC Top 100 fund (Used to be the HDFC Top 200 fund earlier), and the SBI Small Cap Fund (Used to be the SBI Magnum Small and Midcap Fund earlier).

c) I have also indicated the returns from the Centrum-920 Deep Value PMS (in which I have invested a small amount), so that my investment returns can be benchmarked with it.

d) Finally, I have indicated returns provided on a small amount of trading capital to an individual named Chandan Kumar, who trades it on my behalf, using options strategies that he has developed. My trading returns could be compared with his returns, since he uses similar amounts of leverage.

Trading Strategies currently Deployed

Currently, I am employing the following trading strategies in financial markets:

b) Trend Following on the BankNifty Futures on EOD time frame, with a mix of fast responding and slow responding strategies (Approx 30% of total capital)

a) Trend Following on the BankNifty Futures on 5 min, 15 min and 30 min timeframes (Approx 10% of total capital)

c) Mean reversion trades on Stock Futures (Approx 5% of total capital)

d) Trend Following on Interest Rate Futures (Approx 10% of total capital)

e) Momentum and Trend Following on Commodity (Silver, Gold, Zinc, Crudeoil and Copper) Futures (Approx 10% of total Capital).

f) Trend following on NSE500 stocks (non-leveraged) (Approx 35% of total capital)

Capital is employed by means of 50% stocks (with about 25% haircut), 40% liquid bees(10% haircut) and 10% cash. Non leveraged trades on NSE 500 stocks needs cash too.

To protect against black swan events, I generally buy protective puts in BankNifty weekly options in the situation where more than 50% of the maximum position is long.

Trading Performance September 2018

Trading Performance September 2018 

After a very disheartening trading performance in August 2018, September 2018 gave stupendous returns. This was due to an extremely sharp fall in the Bank Nifty, and an extremely sharp rise in bond yields. This behavior is not unexpected, but the correlation of bond yields and the Bank Nifty does lead some degree of correlation, which is not what was expected while diversifying to a new instrument. 

Unfortunately, I stopped trading commodities a few months ago, and I also reduced the position size on bond futures. The commodities was a conscious choice, because I wanted to refine my strategies and also see if existing strategies did have an ‘edge’. The bond futures position size reduction was a ‘fear’ thing. 

Nevertheless, the nice returns on the bank nifty in September were a nice bonus. It also meant that I have positive 1 year returns. And of course, since the inception of measurement, i.e., November 2016, it means a return of almost 200%.

As of now, there are 3 operating trading segments:

a) Trend Following on the Bank Nifty, which constitutes nearly 70% of the total position. This is on various time frames, with shorter time frames having 50% of the positions, and daily time frame having 50% of the position

b) Trend Following on Yields, to trade on bond futures

c) Mean Reversion Systems on individual stock futures

Currently, momentum trading on commodities is in suspension. Also, I very occassionally do options plays. In the beginning of October, I have also started trend following in individual stocks(taking delivery).

Portfolio Returns
Investment and Trading Performance Compared with Various Benchmarks

Great Articles on Momentum and Trend Following

Great Articles on Momentum and Trend Following

This is a great article on the history and academic foundations on momentum and trend following. It gives a great explanation from behavioral science as well as information theory for why momentum works in markets.. Furthermore, it also integrates momentum and trend following, and explains why both are two sides of the same coin. The article is well grounded academically. A great read:

Two Centuries of Momentum