Category: Your Money

Investment Theme Performance Roundup

What is a “Theme”?

A StockViz Investment Theme is a portfolio of stocks that follows a particular strategy. It is a convenient way for you to:

  1. stick to a strategy
  2. follow a preset rebalancing schedule
  3. think in terms of your portfolio strategy rather than individual stocks
  4. avoid common behavioral pitfalls
  5. systematically track your P&L and strategy performance

What is an investment strategy?

An investment strategy is a specific way of going about the process of investing. It identifies specific variables that define a stock. Variables can be anything: risk, style, sector, balance-sheet items, etc..

By mapping specific Themes to your account, you ensure that you stay pure to your strategy allocation. And that there is no “flying by the seat of your pants” investing.

How have Investment Themes performed?

Splendidly. Here’s a roundup:

Theme Inception Date Returns (%) Annualized Returns(%)
Quality to Price 2013-08-28 57.99 116.31
Balance-sheet Strength 2013-09-11 41.75 90.7
Growth with Moat 2013-08-05 22.2 39.54
Financial Strength Value 2013-09-13 21.72 47.76
IT 3rd Benchers 2013-11-06 18.95 61.77
Velocity 2013-11-12 18.21 62.73
Momentum 200 2013-08-19 17.39 33.23
Market Elephants 2013-09-02 15.32 31.61
Magic Formula Investing 2013-08-19 15.06 28.78
Efficient Growth 2013-08-05 11.19 19.93
Enterprise Yield 2013-09-16 10.27 23.01
Consistent10 2013-11-18 9.82 35.87
Long Term Equity 2013-11-18 7.81 28.5
ADAG Mania 2013-07-25 4.44 7.51
Market Fliers 2013-10-28 -6.67 -20.12

What should I do next?

You should open a demat account with StockViz and invest through our Themes.

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Shark-fin Innovation – Part II

A recent post on our innovation series discussed how the low cost of technology innovation is impacting incumbent industries. We also highlighted the acquisition of Simple, an online only bank by Spain’s BBVA.

Its not only BBVA that is worried about new entrants dis-intermediating traditional banking roles. Now J.P. Morgan’s CEO, Jamie Dimon has joined the chorus: “When I go to Silicon Valley… they all want to eat our lunch. Every single one of them is going to try.” (WSJ)

J.P. Morgan, the biggest Kahuna in the most tightly regulated industry is worried about Silicon Valley. That says a lot.

Prakash brought out an interesting point in our comments thread on our shark-fin post:

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Shouldn’t individual investors diversify for themselves? Isn’t it beyond the mandate of the firm’s management and board to invest in startups?
 

This article on Techcrunch sums up the argument for corporate VC investments:

“Over the last few decades one of the things that has definitely been happening with corporations is that they’ve moved to an open innovation model or outsourced R&D. They’re doing less basic research in house and essentially looking to bring that in through acquisitions,” Hochberg said.

With the cost of developing new technologies coming down so dramatically, it makes sense for corporations to take smaller bets on new technology offerings, according to Hochberg and her peers.

“A lot of what startups are about is experimentation. [Now] you can experiment at a cost of about a tenth of what it was a decade ago,” Hochberg said. “[Businesses] can actually go out and get a sense of whether these things are going to be successful a lot more quickly and at a much lower cost.”

It kills a lot of birds with one stone:

  1. Attracting quality talent into a large organization is always a challenge.
  2. Most startup-founder remuneration is back-ended – bonus only if the experiment succeeds.
  3. #2 lowers the total cost of R&D for large organizations. They lose lesser amounts on things that don’t pan out – of which there are many.
  4. Most companies may not have R&D in their DNA and are better off outsourcing it.
  5. Making seed/early-stage investments is an insurance against “big bang” disruption.

#4 should make readers reflect on the recent experience of Infosys. Their turn-around strategy is to refocus on services and hive off products into a separate company. They tried version 3.0 but decided to stick with version 2.0. (ET)

#5, along with the fact that ten-year VC returns have trailed S&P-500 (WSJ) could mean that corporate VCs might be modeling these investments as an insurance policy.
 

The jury is still out there on whether individual investors derive economic benefit from the VC activity of a corporation. But it is prudent risk-management in the face of “big bang” disruption.

[stockquote]INFY[/stockquote] [stockquote]NAUKRI[/stockquote]

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Bad Idea: Indian banks selling insurance

This is a bit of a rant and I am generalizing my experience to the entire system. But something tells me that I am not too far off.

The RBI briefly flirted with the idea of allowing Indian banks to sell insurance. But have you met your bank manager? Most bank employees, managers included, are aces at accounting and process. They can point out the exact color of the forms you need to fill out, how many people up and down the chain it needs to get signed by, documents required for taking out a loan, etc. But when it comes to having a grip on finance, economy or the markets, those are not the people you want to be taking advice from. However, most people can’t tell the difference between accounting and [finance, markets, economy] and look up to them for advice in those areas. Advice that bank employees are more than willing to give.

The escape hatch is built into the system. Most employees get transferred around. My dad, who used to work for a public sector bank, was transferred almost every 3-5 years. The concept of “roots in the community” doesn’t really apply. Add to this is the fact that most insurance commissions are front-loaded. And employees don’t get a commission for taking fixed deposits. Most people follow the advice that their bank manager gives them.

So imagine this scenario where you have scraped together some savings and you go to your bank to make a fixed deposit. The banker makes more money for himself if he convinces you to take out an insurance product instead. You are a farmer with only basic knowledge of personal finance. What are you likely to do?

The skewed incentives that this presents can only lead to disaster. Plus, there is proof that agent-sold insurance in general doesn’t actually benefit the consumer:

Prices of online term plans are much lower than that of agent-sold policies and the sum assured is significantly higher. An online term policy is as much as 50% cheaper than an offline term plan for some companies. More importantly, the sum assured (money your family gets if you die) of online term plans is an average of Rs.72 lakh as compared to Rs.1.47 lakh for the insurance industry in India.

 

Private insurance agents obviously don’t like the idea and neither does LIC. Hopefully, this will be buried and the whole market moves online.

Source:

  • Why the global insurance industry is wrong (LiveMint)
  • RBI plan to turn banks into insurance brokers bad idea (IndianExpress)
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The Little Book of Behavioral Investing: Conclusion

Why promising to be good just isn’t good enough…

This is the close of the The Little Book of Behavioral Investing. I must admit that while I expected the review to be an edifying experience, I didn’t expect it to be such fun. Many thanks to James Montier for making what could have been dreary an engaging, relevant and enriching read.

The book is on its last page but what about you and me? It’s certainly not the end for us, it’s a beginning of our journey to becoming better investors.

And why only investors?

Like I mentioned before, the teachings in this book go far beyond the circle of investors. The wisdom is universal as are the traits that make us a victim of our own biases. And the secret sauce here, as Kung Fu panda realized, is that there’s no secret sauce. The only weapon to defeat all biases is you. Through this book, we can learn the tools and strategy to achieve bias nirvana.

But promising to improve won’t do the magic. In fact, there is no magic, just commitment, perseverance and focus.

Montier admits he’s as bad as the rest. He may keep an investment diary and stick to an investment plan but he’s vulnerable when it comes to his eating habits. If eating is his nemesis, change aversion is mine. And though I realize this trait could hurt me in the long run, I don’t do much about it.

Access to knowledge certainly doesn’t guarantee obeisance.

There are some habits we just don’t want to change. It’s too much trouble or maybe, the outcome of harbouring this habit hasn’t hit us yet. Remember “after loss” versus the “risk of incurring a loss” behaviour?

Till the worst hasn’t happened, we don’t push ourselves to change. Montier observes that this happens even when a negligence is of life-threatening proportions. In a group of men and women who were educated on how a condom could prevent the spread of HIV/AIDS, a good percentage still chose not to use one. It’s their very life they’re risking but for some unfathomable reason, they’re supremely optimistic about their chances.

The traits Montier talks about through the book inflict people across the board. Especially over-optimism and excessive self-confidence. Now, I’m not an early riser. So when I set my alarm for 5.15am, I know there’s a good chance I won’t wake up. I even keep the alarm near me, so it’s easy to switch off without opening my eyes! Yet, over the last month, I did this every night, promising myself tomorrow would be different. Where did my optimism come from? I have no idea.

The only way I managed to break this record was keeping the alarm in the next room so I had to walk 20 feet to switch it off. By which time, I can usually usurp my inner devil and head to the washroom instead of the bed.

What I needed was an actionable step, not just a resolve.

Montier gives us actionable steps to alter our habits too. It’s not easy to change and unadvisable to try and change too much at a time. Our body and mind won’t take it.

So, start easy. Apply some rebiasing and simple rules.

To do this, follow a process. For investors, the investment plan provides the process. It is our strongest weapon against all behavioural pitfalls.

Remember, even the world’s leading investors are prone to weaknesses. That’s why they stay away from stock dashboards and media noise themselves, focusing only on their investment plan and giving the responsibility of execution to others.

So don’t be too hard on yourself. Even the best can go wrong without process. The important thing is to recognize and accept your weaknesses, and take steps to control them. Once you’ve figured that out, you’re on the road to becoming a better investor.

Let this be a new beginning.

 

Monica Samuel is doing a chapter-wise review of the book: The Little Book of Behavioral Investing: How not to be your worst enemy by James Montier. You can follow the series by following this tag: tlbbinvesting or by subscribing to this rss feed: tlbbifeed

 

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A Simple Bollinger Band Trading Model

Bollinger Bands have quickly become one of the most commonly used tools in technical analysis. Bollinger Bands consist of three bands – an upper, middle and lower band – that are used to spotlight extreme short-term prices in a security. The upper band represents overbought territory, while the lower band can show you when a security is oversold. Most technicians will use Bollinger Bands in conjunction with other analysis tools.

A simple BBand strategy is buying stocks that break the lower Bollinger Band. It is expected that the price of the stock will revert back above the lower band and head toward the middle band.

You can build you own Bollinger Band based strategy that scans all the Nifty 50 stocks for a potential break using the StockViz Technical API in a few lines of code.

# get the index constituents and loop through them
constituents = common.getConstituents("CNX NIFTY") 

for cc in cleanConsts:
     ticker = cc["SYMBOL"]
     # get the latest technicals
     techs = common.getTechnicals(ticker) 
     t = techs[len(techs)-1]
     # get the latest price
     price = common.getLivePrice(ticker)

     #make the decision
     if t["BB_DN"] > price:
		#there was a breakdown

		print "Buy:", ticker
		common.placeTrade(ticker, 1, "buy")

You can read the whole code on GitHub

Source: investopedia

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