Timing the turning point

With housing prices falling and many markets in disarray, there’s been a lot of talk in the property media about the benefits of counter cyclical investing, or buying at the bottom.

It seems simple enough to follow the advice of experts such as Warren Buffet, who advises investors to “buy when everyone is selling, and sell when they’re buying”, or Baron Rothschild who even more dramatically, told investors to “buy when there’s blood in the streets”.  But if that was all there was to it, we could all easily become highly successful investors with little more effort than to do the opposite of everyone else.

In reality, such advice is almost impossible to follow successfully because it flies in the face of perceived logic – if everyone is selling and prices are falling, how do we know that this trend won’t continue and leave us even worse off? Unless we are sure that the market has bottomed out, and we have reached the turning point, our efforts are likely to be futile and costly.

Most investors and analysts attempt to time the bottoming out of market by relying on lagging indicators such as sales and sale prices, but these can only reveal the past, not the future. It’s a bit like trying to navigate a car by looking through the rear-view mirror. Only leading indicators, such as the number of properties on the market, asking price trends and search trends can forecast a likely change in direction.   

Even if the turning point has really arrived and it’s time to buy, it becomes impossible for most of us to take any action, because the price crash has left us with insufficient cash reserves and we discover that the banks are unwilling or unable to lend. The solution to this dilemma is to look for low priced properties in areas which have price growth potential and high rental yields driven by genuine rental demand

Such investments are low risk and will give your lender more confidence in providing finance. Then you can look forward to positive cash flow from day one with healthy price growth over time.