House price news & Property Forecasts' press releases

An article contributed by Cathedral Lettings (Durham) Aug09:

Future of the Buy-To-Let Market in the UK

In the space of 12 months the credit crunch has virtually destroyed the buy to let market; and it has been tough for many landlords.  Does this market have a future?

Many of the companies providing buy to let mortgages relied heavily on borrowing from the securitisation market, and were hit hard by the credit crunch.  From 2007 these markets began to jam up due to fear about the quality of these deals.   From late 2008 this market died;  and the number of mortgage products available dived from over 4000 in 2007 to just 200 now.  And because buy to let borrowers are seen as riskier, extra large deposits are now required;  and rates have failed to fall in line with the drop in Base Rate.

Not helping has been the flood of rental properties coming onto the market from people unable to sell who have decided to rent it out instead. This increase in supply has outstripped demand growth and rental yield has fallen by about 10% this year just as lenders have increased their levels of rental cover.

And at the same time property values have fallen.  This may be improving rental yields, which is great for those purchasing property now, but not so great if you are nursing a capital loss from buying when markets were more buoyant.

But there are reasons to be cheerful.

For one there is a chronic shortage of housing in this country. The growth in the number of households continues to exceed the number of new houses being built for owner occupation. And irrespective of the state of the economy and the ease with which people can get onto the housing ladder, rental yields over the medium term will continue to show healthy levels of growth.

Demand too is likely to be driven by people put off by the sharp falls in house prices over the past 12 months as well as by the rising number of re-possessions driven by the recession.  And those whose homes have been re-possessed or who have handed in the keys will look to the rental sector to provide a roof over their heads.  It is reckoned that 75 000 people this year will move from being owner occupiers to renting.   And with mortgages remaining hard to find and requiring large deposits, demand for rental properties can be sustained.

Consider too the increasing numbers of young people going to university and looking for rental accommodation in university or college towns, like Durham.

With interest rates set to remain low and property prices at or near the market bottom, this is a great time to think about buy to let investments. Where else are such great returns on capital on offer?

If you are looking to enter the buy to let market or even have a house to rent in Durham we have people looking for a property like yours today. What have you got to lose?

August 15th 2009 The Independent:   "Home in on the property hotspots"  (article by Rob Griffin)

"They may not appear to have much in common, but Bagshot in Surrey, Liphook in Hampshire, and Salford in Greater Manchester are all places where house prices are predicted to rise over the next five years.

These potentially lucrative locations, along with Gateshead in Tyne and Wear, Dronfield in Derbyshire, and Ebbw Vale in Gwent, have been tipped to recover quickest from the slump by propertyforecasts.co.uk."

For the full article, see The Independent at http://www.independent.co.uk/money/mortgages/home-in-on-the-property-hotspots-1772397.html

Historic Accuracy figures available, July 2005

From July 2005 an indication of the historic accuracy of the forecasts for each postcode area will be shown in the free 1 year summary.

read more about the historic accuracy of our forecasts

Property Forecasts also makes regular contributions to:

• Sunday Express (1st Sunday in every month – Property Price Index)
• Property Forecast magazine (Town or city report approx quarterly. )
  • June 2003 – Ipswich
  • Sept 2003 – Cardiff
  • January 2004 – Nottingham
  • April 2004 - Brighton, E Sussex
  • August 2004 - Sheffield
  • December (upcoming) - Bristol

[ News & Press Archive ]

Books & papers by Company members:

“Pattern Recognition & Trading Decisions” Chris Satchwell (pub. Sep 2004)

What the USA-based publishers, McGraw-Hill, say: “Success in technical analysis is all about recognizing, and quickly acting on, patterns of market behavior. Pattern Recognition and Trading Decisions shows active traders how to realize when a pattern is developing, distinguish between a genuine pattern and a misleading series of events, and apply this recognition for success in specific trading situations. A how-to guide that steers clear of difficult calculations and formulas…”

Dec04:  Chris Satchwell's book is currently number 2 on Amazon's 2004 Top 10 Editor's Picks for the "Investing & Personal Finance" category.

http://www.amazon.com/exec/obidos/tg/feature/-/546894/ref=ed_bb_bb_editors_inv/103-4391572-5230218

 

[The mass forecasting technology used by Property Forecasts was developed primarily by Chris Satchwell, using his expertise in pattern recognition in combination with forecasting methodology unique to Technical Forecasts Ltd, described in the paper below.]

 

'Forecasting values of commercial and residential property using non-linear mathematical and statistical techniques'

- presented at the 2002 Joint Glasgow Conference of the European Real Estate Society (ERES) and the Cutting Edge Conference of the Royal Institute of Chartered Surveyors (RICS):

Forecasting methods currently available to practitioners have been of limited use because of their inability to detect and model the past patterns underlying property data. Additional restrictions on accurate forecasts are imposed by the inherent linear characteristics of most models which fail to recognize the complexities of real property markets. Further complications arise from issues such as lack of reliable historical data, short data histories or temporally sparse data.

Property forecasts can be improved by employing 'associated' or parallel series in forecasting models. Methods are described for matching a model to the complexity of the target data series and combining forecasts from many models to reduce errors in final forecasts. Accuracy statistics and examples of residential and commercial forecasts are included.