Posts Tagged ‘LinkedIn’

Incredible India: A Bubble About to Pop?

February 19th, 2010 6 comments

Can you imagine being able to rewind time and watch the U.S. real estate bubble as it’s about to pop? While none of us has the ability to time-travel just yet, I did have the opportunity to witness something remarkably similar to the U.S. real estate bubble while on a recent trip to India with my family.

Just like tech stocks were the talk of the late 1990′s in the U.S. (everyone from your barber to the grocery store clerk had a winning stock pick and was a market expert), real estate is the current hot topic of conversation in India. This in itself, in my opinion, is indication that a growing bubble is afoot – when everyone from the professional investor to the gardener is talking about how to make lots of money in a particular asset class, the prudent investor should start looking for an exit.

Another factor supporting the not-so-distant decline in Indian real estate prices is the excess leverage in personal balance sheets. Just as we saw in the U.S., residents of India are now taking out mortgages that they can just about afford. The availability of credit and the shifting mindset in favor of borrowing (traditionally Indians like to pay for everything, from groceries to housing, with cash; this trend is rapidly changing with the younger, more affluent middle class opening up to mortgages and credit cards) is creating demand for housing, and pushing up prices. The opening up of credit is actually a good thing. The issue is that people can barely afford their mortgages. So, when the Indian economy slows a bit and people lose jobs, their mortgages will immediately be at risk, just as was the case here.

Excess foreign invesment also plays a significant role in Indian real estate prices. It’s a well known fact that investable assets chase returns. In this instance, NRI (Non-Resident Indian) assets that had, until recently, been invested in the U.S. and European stock markets, are migrating to India. This is natural; older Indians living abroad have accumulated a lot of wealth, which was parked in cash, gold, and financial markets. With the collapse of equity markets around the world and the drop in interest rates, there aren’t many good places to park cash. In such an environment it’s no surprise that these assets flow into housing “back home” in India. The older Indian population applies the following logic: “Should I chose to move back home once my kids are settled, I’ll have a place to live. If I choose not to move back home, I can always sell the investment in Indian real estate for a handsome profit since the market is so hot”.

The net effect of these factors is that real estate prices in India have about tripled over the last three years. This is an alarming rate of appreciation given that I see no sustainable demand for real estate. Yes, it is true that many corporations are moving to India and the economy there is growing at a brisk rate. However, the jobs created by these actions aren’t enough, in my opinion, to support the kind of national real estate price appreciation India is experiencing. Rather, I’m concerned that there are too many speculators in the market, which will result in an inevitable, and painful crash. In addition to the foreign speculators I mentioned above, there are also the domestic type – those buying a house with the hope of selling it in the next six months to a year and turning a profit (much like what we saw in the U.S.). In one conversation I learned that about 40% of the purchasers in a new subdivision that was being built were investors; they wouldn’t actually be living in the house. 40%! That’s huge! 4 out of 10 homes will sit empty when built – either awaiting immediate sale by a domestic speculator, or awaiting an NRI family that, in a few years, may live there or, in the more likely scenario, will sell the home to turn a profit.

The risk of this speculation is clear. As soon as the Indian economy slows and those young, affluent borrowers face difficulty paying the mortgages they can barely afford now, there’ll be panic, fueled by memories of what happened in the U.S. This panic will be further exacerbated by the immediate dumping of homes by investors who fear the loss of capital experienced in 2008-2009, creating a snowball effect in the decline of real estate prices. Though I can’t say for certain when this will happen (if I could, I’d have made millions on it), my intuition is that it’ll be within the next 3-5 years.

Though the issue in India is certainly not identical to what happened in the U.S. (high risk mortgages aren’t as prevalent as they were in the U.S. and the secondary mortgage and derivatives market is no where near as large as it was in the U.S.), there are many alarming similarities. That being the case, the prudent investor should be mindful of the similarities and be aware and history can very well repeat itself.

Portfolio Page

October 5th, 2009 No comments

I’ve finally got the portfolio page up! On this page you’ll find all kinds of information regarding the quantitative strategy I’ve started investing in, in summer 2009.

To give you an idea of the kinds of things you’ll find there (over time – I’ve got a lot of work to do here!):

  • My to-do list: explore long-short rather than long only, think about a portable alpha structure with a beta overlay, explore leverage using options, look into sector-allocation and how that affects risk, …
  • Continue to dig into historical results: do the numbers make sense? Are there any biases? What could be missed?
  • Continue to dig into the model itself: do the factors make sense individually? Does the method of combination make sense? How are the factors and the model results affected by data availability?
  • Think about risk: what are the appropriate risk measures to consider? How can these risks be mitigated or controlled?

I’ll be updating the portfolio page monthly with realized returns, and will address some of the issues above over time. Every now and then I’ll post a “portfolio update” entry to keep you current on new information regarding the portfolio. If you have comments or questions, please let me know!

Categories: Equity Portfolio Tags: ,

Long, short, or put?

August 12th, 2009 No comments

As you know, I recently started investing in a quantitative equity portfolio. I’m a big fan of long-short strategies (on paper at least!). For folks that aren’t familiar with the term, it refers to strategies where investors borrow stocks they think will do poorly and sell them in the market. They then use these funds to buy stocks they think will do well. Later they sell the stock that hopefully did well to realize a profit, and then buy back the stock that hopefully did poorly at a discount to what they got for it when they sold it, and finally repay the stock loan. For example, suppose both Stock A and Stock B are currently priced at $100. It’s my belief that Stock A will do very well over the coming month and that Stock B will get decimated. In this case I short Stock B – that is, I borrow it and sell it in the market for $100. I then use that $100 to buy Stock A. Note, there is no investment of my own money at this point (ignoring transaction costs, that is). Now, suppose that one month later Stock A is trading at $110 and Stock B has fallen to $25. In this example, I was correct about both stocks. In this case I would sell Stock A for $110 (realizing a profit of $10, since it cost me $100 to buy), and I would purchase Stock B for $25. At this point my net cash position is the $110 I got from selling Stock A less the $25 it cost me to buy back Stock B, for a total of $85. I now return Stock B to the person I borrowed it from, and the transaction is done (again, ignoring interest cost for borrowing Stock B). I invested $0 of my money in the strategy and walked away with $85! Note that I could also have just invested $100 in Stock A since I thought it would go up. In this case I would have made $10. The short transaction in my example simply augments my income if I am correct.

As a side note, note what happens if I’m wrong. What if I though Stock A would tank and Stock B would rise. In this case I’d short Stock A and buy Stock B. One month later I’d sell Stock B for $25 (for a loss of $75, since it cost $100), and I’d buy back Stock A for $110 (for a loss of $10, since I got $100 when I sold it) and repay the stock loan. My net cash position is $25 from selling Stock B less $110 for buying Stock A, or a total loss of $85. I invested nothing and lost $85!

Back to the portfolio… I had intended for it to be a long-short portfolio where I’d buy the names the model thinks are the best, and sell those it thinks are the worst. After looking through some recent data I realized that I could lose as much as 10% of my portfolio in two weeks doing this (if the short stocks take off), and so I decided against that. However, I really wanted to incorporate the model’s views about poor stocks into the trades. One way to do this is to buy put options on the poor stocks. Again, for those not familiar, a put option is basically an option to sell a stock at a pre-determined price. If Stock B is trading at $100 now and I think it’ll be at $50 in a month, I can buy a put option struck at $100. That means that I now have the right to sell the stock at $100 at some time in the future. Now, a month later if the stock does go to $50, I can but it in the open market for $50 and then exercise my option to sell it to the person who sold me the option at the strike price of $100. This would result in a profit of $50. Note, the option is not free, I would have had to pay for it when I bought it. The price depends on many factors, but would have certainly been much less than the $50 profit. On the flip side, if Stock B rallied, I simply choose not to exercise the option. I don’t make any money, and my only loss is the premium I paid to buy the option. You see how this can be more attractive than naked shorting – when stocks really take off, my losses using a put option are limited to the premium whereas my losses from shorting are unlimited.

In case of my portfolio the options would allow me to bet on the downside. The problem here is that a single option contract is for 100 stocks. That is, they are sold in bundles of 100. So, if it costs $5 for a single stock option, I’m forced into buying 100 for $500. This is an issue for two reasons: 1) I need a lot more money up front to buy the options, and 2) if the stocks take off, I have a lot more premium to lose. In my case the total premium for a single contract on each of the stocks I wanted to short exceeds the total amount of my portfolio, so it’s just not doable. Yes, it is true that if I’m right and the stocks in question tank I’ll make a lot more money, but the risk is just too high right now.

So, it seems as if I’ll have to forget about the short side of the equation for now and just place my bets on stocks I think will go up. However, it does leave us with some food for thought: if options limit losses in case the stocks take off, why would I ever short?

The answer lies in the cash. When you short a stock, you get money equal to the value of the shorted stock, and your payoff is inversely related to the stock (for each dollar the stock makes you lose a dollar and for each dollar the stock loses, you make a dollar). With options you still get an inversely related payoff, though it’s generally less than one (that is, you won’t make a dollar for each dollar the stock loses. Rather, your payoff will depend on the delta of the option, a detail I’ll save for a later post). The other key difference is that when shorting a stock you get money, but when buying a put option you pay money (the option premium).

In a long-short portfolio of $10,000, you short $10,000 worth of stock and use that money to buy $10,000 worth of stock, leaving you with $10,000 of cash. You can then either keep this cash and earn interest on it, or you can invest it in a benchmark like the S&P 500, or do whatever else you want with it (a sort of portable alpha strategy). The nice part here is that if you’re wrong about your calls on the long side or the short side, you still have the investment in the benchmark to diversify away some risk (assuming you used the extra $10,000 to but the benchmark). However, if you had used options, you would use part of your $10,000 to buy options and the balance to buy the long stocks. Here you have two negative effects: 1) your total investment is less than the long-short (since you’re long fewer assets and you have less short exposure, ignoring contract size for a moment), and 2) you have lost the diversification benefit of owning the benchmark. Your entire return is based on your long and short calls, which may or may not be correct. So, now you see the cost of going with the put option – yes, your loss is limited if the “short” stocks take off, but the price of that is a smaller position and less diversification.

Categories: Equity Portfolio Tags: ,

Kicking off a new strategy

August 12th, 2009 No comments

After much delay, I’m finally kicking off a new stock investment strategy. Before you ask, no, I won’t divulge the details of the strategy. Suffice it to say that it is a quantitative equity strategy which looks at valuation, momentum, and sentiment/risk. Though I won’t spell out the factors here (hey, a magician never gives away his secrets!), I will be tracking returns on a monthly basis and posting them on the Y-Factor (link to follow). Shortly I’ll also include simulated returns for the strategy for some period in the past.

Actually investing money in this strategy (as opposed to simulation and paper-trading) is pretty nerve-racking – there are real gains and losses to be had now. I’ve also come across a few challenges, which you may find of interest:

  1. Unlike at work, capital is much more constrained and transaction costs are much higher. Building a strategy for work is great because we choose our universe (let’s say the stocks in the S&P 500), apply our strategy and buy the top decile (50 names). If we were a hedge fund, we could also short the bottom decile. A couple of things make this easy: 1) when you have millions to invest, it’s very easy to put on your positions (i.e. if I only have $10,000 to invest and Google is to be 1% of my portfolio, or $100, I’m in trouble because the stock costs $450, meaning the smallest position I can take is 4.5%. However, if you have $100 million to invest, you can easily but $1 million worth of Google), and 2) transaction costs at work are a much smaller percentage of capital. Even though I use a very-low cost broker, I’ll still pay a minimum of $1/trade. If you buy the top decile and short the bottom decile, that’s a minimum of $100 in commission, or 1% of a $10,000 portfolio. Paying that every month (since the strategy will rebalance positions monthly) is very costly – 12% a year! To alleviate this problem, I’ll go long the top 25 names and short the bottom 25 names. This will reduce my diversification, but will also reduce transaction costs and allow me more money per name to put on the positions I want.
  2. The had intended the strategy to be a long-short strategy. However, as I think about this more, taking short positions is very risky. For example, over the last two weeks the long positions in my strategy would have returned 2.6% but the short positions would have cost me 10.5%! This is primarily due to some of the stocks the model shorts being financials, which have rallied over the past two weeks (AIG has doubled!!). To get away from the downside risk to shorting, I could buy put options, what is what I was considering. The problem here is that an equity option contract is 100 in size. That means that I have to buy options in multiples of 100. So, if I want to short 10 shares of a stock, I can’t – I have to take on an exposure similar to short 100. This in itself is not bad because if the stock tanks I’ll make 10 times the money. But, the cost of the option is the limiting factor – the cost of the options for my portfolio would be greater than the equity I have! If I had $100,000 or more to invest, this wouldn’t be an issue, but that, unfortunately, if not my case.

So, after considering these annoyances, I’ve made a few last minute adjustments. I’ll go long only (since I can’t afford the options and don’t want the risk of the shorts), and I’ll buy the top 25 names my model chooses rather than the top 50 (as mentioned earlier). If things work well and I find that I am willing to put more money into the strategy, then I can always try to capitalize on the shorts later.

That’s a lot to digest for now. Keep watching and I’ll put up the simulated returns (soon) and actual returns (at the end of each month). I’ll also write more on the actual model and considerations that went into that as we move forward…

Categories: Equity Portfolio Tags: ,

Housing Defaults: The Next Wave

June 11th, 2009 No comments

So, as you’ve probably read or heard in the the news, evidence that the American housing market is stabilizing is beginning to present itself. Data from the National Association of Realtors showed that the number of signed contracts to buy previously owned homes climbed 6.7 percent in April (granted that not all signed contracts will turn into closings since financing could fall through, it’s still better to have more contracts than fewer). Furthermore the Mortgage Bankers Association’s index of applications to purchase a home gained 1.1% in the week ending June 5th (though total mortgage applications fell and refinancesdropped off with the now higher interest rates). Finally, the fact that rates are higher itself suggests more confidence in the housing market – if there was no demand for loans, rates would keep falling. So, we’re on the path to real estate recovery, no? Well, no. Not so fast.

We have all heard of the recent run up in foreclosures that started two years ago. One would think that with all the economic turmoil we’ve had over the past two years and the fact that we’ve seen so many foreclosures already, maybe we’ve flushed most of the bad loans and things get better from here. In fact, as the chart below shows, we are indeed experiencing a steady decline in the number of subprime mortgage resets (and thus foreclosures since not all borrowers who reset will be able to afford the new payment) – the blue line.

From March 2009 to December 2012

From March 2009 to December 2012

 However, what should be a cause for concern are the yellow and orange lines – Options ARMs and Alt-A loans, respectively. Many people are familiar with Alt-A loans (they’re basically loans that are riskier than conventional mortgages, but not as risky as subprime mortgages). However, not as many people are as familiar with Option ARMs, which is of particular concern since they could be the next wave of foreclosures.

An Option ARM is something like a negative-amortizing mortgage. A negative-mortgage is one in which rather than the loan amount being reduced with each payment, it’s actually increased. For example, suppose you borrow $200,000 and your mortgage payment is $1,000/month. In a typical mortgage $800 of that $1000 may be for interest and the other $200 would pay off principal. Now consider the situation where someone wants to buy a house but can’t afford the $1,000/month mortgage payment. As an alternative, they get into an Option ARM that allows them to make payments of $250/month (yes, the difference between a conventional and option ARM mortgage can be that much!). What’s actually happening here is that they still owe $800 in interest, but since they’re only paying $250/month, the remaining $550 of unpaid interest gets added to the balance of the loan, bringing our hypothetical loan to $200,550 after the first month. Now, since the principal balance is higher, the interest due will be more than $800 next month. But, the borrower still pays $250, so they add an amount greater than $550 to their unpaid balance the following month.

Whereas in a conventional mortgage you pay down the loan a little bit each month, with the amount of pay-down increasing each month, an option ARM results in you increasing the loan a little bit each month, with the amount of the increase, increasing each month. You can see how this can turn into a troublesome situation very quickly, especially in an environment of falling home values. Our borrower continues to happily make his/her $250/month payment (usually completely oblivious to the fact that their loan balance is increasing) until one of two events occurs: 1) they go a certain amount of time specified in the loan agreement at which point they’re forced to start repaying principal, or 2) their loan balance reaches some predetermined amount (think 150% of the original loan balance – in our example $300,000) at which point they’re forced to start repaying principal. Either way, even if interest rates haven’t moved (heck, even if they’ve come down), since the loan amount is so much larger and they now have to pay the complete amount of interest and principal, their payment will radically spike – let’s say from $250 to maybe $3,000. So now the family that bought the home but couldn’t afford the $1,000/month has to pay $3,000/month. In most instances their income is not likely to have gone up enough to make this new mortgage affordable.

So, the family has a higher payment than they can afford, has experienced depreciation of their home, and has a loan balance that’s much higher than where they started, and likely much higher than the value of the house. They’re screwed, and this story does not have a happy ending.

As the chart above shows, the number of Option ARM resets will significantly increase until about the end of 2011. This means that there will be many properties that have depreciated (or even have had the good luck of not depreciating), but are married to loans that are considerably larger than they were at closing. This will most certainly result in more foreclosures, and thus further downside pressure on housing prices.

I certainly wish the worst were over in terms of housing, but unfortunately that just doesn’t seem to be the case. This is yet another example of creative financing, greedy lenders after fees, and uninformed consumers causing considerable damage.

Categories: Economics Tags: , ,