Property buyers in some Australian cities experienced a very strong housing market in the last half of 2013. The second last weekend in September saw an auction clearance rate in Sydney’s Inner West of 95%. At the beginning of December, there were around 1000 properties under the hammer on just one Saturday of auctions.
This brings us very close to the record high of the housing boom more than 10 years ago. Melbourne also experienced increased clearance rates. Part of the reason for this boom is that interest rate cuts made borrowing a more affordable option for people keen to step away from the rental cycle. Investors, both local and international, made aggressive moves which contributed to the rising market. Media coverage and chatter at barbecues also meant the property market attracted interest from those previously not considering real estate. Clearly, the property market was hot and has not really cooled down in the New Year.
Given the increased interest in buying and investing in property, we thought we would look at some factors that may be surprising about the property market.
1. Supply and demand pricing rules don’t always work with property
Typically the scarcer the supply, the higher the price, and the greater the supply the lower the price. However, when it comes to the property market traded volume and price move together. For example, for a typical home with three bedrooms in Australia we saw a positive correlation between sale prices and sales volume in all states and territories during a period of 26 months starting from Jan 2010. We found this phenomenon extended beyond Australia. The same correlation was also observed in other housing markets during different periods 2, for example, significant price-volume correlation was seen in the US in the 1990s 3, and in Netherland during 1985 - 2007
2. Highest prices occur in the last quarter of the year
We often hear about the ‘January effect’ in the stock market, where securities prices rise more in January than in any other month. We considered if there was a seasonal anomaly in the housing market as well. Interestingly enough, there is. We found during the same sample period as in the previous example, the median price of a four-bedroom house peaked in the final quarter of the year. Perhaps the joyous mood before Christmas or the desire to close the deal by the end of the year helped inflate prices.
3. Less can be more in property
Logically, more bedrooms should mean a higher price. However, this is not the case in NSW and Victoria. Both states experienced a higher median sale price for two-bedroom homes than three-bedroom homes. Surprisingly, in NSW, even the median sale price for one-bedroom properties is higher than three-bedroom properties. One explanation may be that with Sydney and Melbourne being the two busiest commercial cities Sydney and Melbourne, there is a greater preference for smaller but better maintained/serviced and more centrally- located properties for young single professionals or young professional couples. The shorter supply of one- and two-bedroom dwellings, as shown in Figure 4, may also push prices up.
4. Staying power of bears
Prospect theory states that loss hurts more than gain of the same amount comforts . Consequently, sellers expecting that they may be subject to loss of profit on their property sale set higher asking prices, on average 25-35% of the difference between the expected selling price (market price at the time) and their original purchase price. As a result, these properties stayed on the market a much longer time, and while some sellers managed to achieve higher sale prices, many dropped out of the market without a sale. This loss aversion is true for both owner-occupier sellers and investor sellers, but especially strong with owners.
Bulls vs Bears
In a bull market, we can see exactly the opposite, properties sell very quickly after listing and buyers achieve more than the asking price. In the past few weeks, many parts of Sydney had auctions brought forward achieving both high clearance rates and prices much higher than the reserve.
This presents an interesting contrast: in a bear market sellers are much less willing to budge in terms of price than buyers in a rising market. This observation is especially interesting because most moves are local, therefore, the typical owner seller is also a buyer in that same market, so even if a seller suffers a loss in a bear market s/he can buy a new property more cheaply as well; similarly, sellers in a rising market may sell at a higher price but they will also have to pay a higher price for a new property.
Why pay more?
There are certainly rational explanations why buyers do not mind paying more. One is that a bull housing market is typically associated with stronger economy and higher affordability as well as greater confidence. However, it may also be the result of representativeness bias, which refers to making predictions based on what is representative, but not necessarily what is more likely. For example, when people see higher sale prices with some properties, they believe this to be representative of the entire real estate market, and any purchase they make in this market will guarantee a good return in the future regardless of how much they paid. This judgement of future price simply by relying on past performance also adds heat to a hot property market.
Buying and selling property are the biggest financial decisions many of us make. Sometimes the timing of your decision is taken from us. However, if you are putting off selling your home because you are in a bear market and it might have to be sold at a loss, you might be suffering from loss aversion. Many people sell and buy in the same market so if your sale price is lower the buying price for your next property will be lower also; it’s all relative. If you are a buyer in a bull market are leaning towards a purchase in a particular certain suburb because of its 40 % investment return reported in the media, you may like to consider if you are buying for rational reasons or if you are being influenced by representativeness bias.
January Effect: is a seasonal anomaly in the financial market where share prices increase in the month of January more than in any other month. This creates an opportunity for investors to buy stock for lower prices before January and sell them after their value increases.
Prospect Theory: is a behavioural theory developed by behavioural economists Daniel Kahneman and Amos Tversky. It states that from a certain reference point, losses hurt more than gains of the same amount satisfy.
Representativeness Bias: is one of the behavioural heuristics defined by Daniel Kahneman and Amos Tversky. It is used for making judgement about probability under uncertainties. Representativeness is defined as being similar to the parent population and reflecting the salient features of the generating process. Judgements based on representativeness are likely to be wrong because what is representative is not more likely to happen again.
This research is a joint project between CMCRC and BT Financial Group (BT), a division of Westpac Banking Corporation. BT, through online newsletters and its network of financial advisers, regularly provides financial advice to clients and the general public. BT strives to be a market leader in investment research to help BT financial advisers develop a greater understanding of their clients’ behaviour to help them successfully manage their financial wellbeing and make decisions that will maximise their wealth. In this collaboration, we currently study investor decision-making and analyse how certain behavioural biases affect customer wealth.
This information is current as at 16/01/2014.
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