– National Forecast Indicates Home Prices Will Increase 4.9% by March 2018
– Home Prices Projected to Increase 0.6% between March and April 2017
– Home Prices Increased 1.6% between February and March 2017
By Peggy Harbuck — CoreLogic released its CoreLogic Home Price Index (HPI™) and HPI Forecast™ for March 2017 which shows home prices are up both year over year and month over month. Home prices nationwide, including distressed sales, increased year over year by 7.1% in March 2017 compared with March 2016 and increased month over month by 1.6% in March 2017 compared with February 2017,* according to the CoreLogic HPI. The CoreLogic HPI Forecast indicates that home prices will increase by 4.9% on a year-over-year basis from March 2017 to March 2018, and on a month-over-month basis home prices are expected to increase by 0.6% from March 2017 to April 2017. The CoreLogic HPI Forecast is a projection of home prices using the CoreLogic HPI and other economic variables. Values are derived from state-level forecasts by weighting indices according to the number of owner-occupied households for each state. “Home prices posted strong gains in March 2017, and the CoreLogic Home Price Index is only 2.8% from its 2006 peak,” said Dr. Frank Nothaft, chief economist for CoreLogic. “With a forecasted increase of almost 5% over the next 12 months, the index is expected to reach the previous peak during the second half of this year.
Prices in more than half the country have already surpassed their previous peaks, and almost 20% of metropolitan areas are now at their price peaks. Nationally, price growth has gradually accelerated over the past half-year, while rent growth for single-family rental homes has slowly decelerated over the same period, according to the CoreLogic Single-Family Rental Index, recording a 3% rise over the year through March.” “A potent mix of strong job gains, household formation, population growth and still-attractive mortgage rates in the face of tight inventories are fueling a continuing surge in home prices across the US,” said Frank Martell, president and CEO of CoreLogic. “Price gains were broad-based with 90% of metropolitan areas posting year-over-year gains. Major metropolitan areas were especially hot with CoreLogic data indicating that four of the largest 10 markets are now overvalued. Geographically, gains were strongest in the West with Washington showing the highest appreciation at almost 13%, and Seattle, Tacoma and Bellingham posting gains of 13 to 14%.
Oil dips on small US crude stock drop, weak gasoline demand
Oil prices edged lower Wednesday after US government data showed a smaller-than-expected decline in domestic crude inventories and weak demand for gasoline, feeding concerns about a supply glut. US West Texas Intermediate (WTI) crude was down 18 cents at $47.48 a barrel at 11:33 EST (1633 GMT). Benchmark Brent crude was down 8 cents at $50.38 a barrel. The US Energy Information Administration (EIA) said weekly crude stocks fell by 930,000 barrels to 527.8 million, less than half the 2.3 million-barrel draw that had been forecast. “US domestic production rose again, and continues its steady climb,” said John Kilduff, partner at energy hedge fund Again Capital in New York. He noted that a sharp decline in imports turned what would have been an increase in stocks into a small drawdown. EIA data also showed gasoline stocks rose by 191,000 barrels, which was much less than the 1.3 million-barrel gain that had been forecast. However, gasoline demand slipped 2.7% over the last four weeks from the same period a year ago. “This is continuing a trend since the beginning of the year in which sales have been lower and that is casting a shadow on the market and pressuring crude oil prices,” said Andrew Lipow, president of Lipow Oil Associates in Houston. “Gasoline demand is going to be the story going forward.”
While the market remains fixated on US production, oil investors continue to watch whether producing countries have been complying with their 2016 deal to cut output around 1.8 million barrels per day (bpd) by the middle of the year. Russia, contributing the largest production cut outside OPEC, said that as of May 1, it had curbed output by more than 300,000 bpd since hitting peak production in October. This means Russia has achieved its reduction target a month ahead of schedule, just as the latest Reuters survey of OPEC production showed the group’s compliance had fallen slightly. More oil from Angola and higher UAE output than originally thought meant OPEC compliance with its production-cutting deal slipped to 90% in April from a revised 92% in March, the Reuters survey showed. “Although OPEC is expected to extend a self-imposed output cap by another six months, it would be a challenge convincing several non-OPEC members to join the endeavor,” said Abhishek Kumar, senior energy analyst at Interfax Energy’s Global Gas Analytics in London.
MBA – purchase applications up
Mortgage applications decreased 0.1% from one week earlier, according to data from the Mortgage Bankers Association’s (MBA) Weekly Mortgage Applications Survey for the week ending April 28, 2017. The Market Composite Index, a measure of mortgage loan application volume, decreased 0.1% on a seasonally adjusted basis from one week earlier. On an unadjusted basis, the Index increased 1% compared with the previous week. The Refinance Index decreased 5% from the previous week. The seasonally adjusted Purchase Index increased 4% from one week earlier. The unadjusted Purchase Index increased 5% compared with the previous week and was 5% higher than the same week one year ago. The refinance share of mortgage activity decreased to 41.6% of total applications from 44.0% the previous week. The adjustable-rate mortgage (ARM) share of activity decreased to 8.4% of total applications. The FHA share of total applications increased to 10.4% from 10.0% the week prior. The VA share of total applications decreased to 10.8% from 10.9% the week prior. The USDA share of total applications remained unchanged at 0.8% from the week prior.
GOP heath care bill gains key support
The Latest on congressional action on the GOP health care bill and the $1.1 trillion government-wide spending bill: Two pivotal Republican lawmakers who had opposed GOP health care legislation are now prepared to support it after meeting with President Donald Trump. Congressmen Fred Upton of Michigan and Billy Long of Missouri made their announcement to reporters at the White House after meeting with Trump Wednesday. They said they will back the bill with inclusion of a new amendment Upton authored adding more money to protect people with pre-existing conditions. Upton and Long both had announced their opposition earlier this week over the pre-existing conditions issue. Their defections dealt a major blow as House GOP leaders hunt for votes to salvage their top legislative priority. Upton, a respected leader on health care issues, says he now believes the bill will be able to pass the House. House Speaker Paul Ryan sought to assure conservatives on Wednesday that a massive government-wide spending bill is a win for President Donald Trump and Capitol Hill Republicans, citing “a really good down payment” on rebuilding the military and “the biggest increase in border security in a decade.”
Ryan told conservative radio host Hugh Hewitt that the most important win for Republicans was breaking loose from former President Barack Obama’s edict that increases in defense spending be matched with equal hikes for nondefense programs. The House is scheduled to vote on the bipartisan $1.1 trillion measure Wednesday afternoon. It is a product of weeks of Capitol Hill negotiations in which top Democrats like House Minority Leader Nancy Pelosi successfully blocked Trump’s most controversial proposals. A government-wide spending bill that President Donald Trump seemed to criticize Tuesday morning but now calls “a clear win for the American people” is headed for a House vote. The House is scheduled to vote on the bipartisan $1.1 trillion measure Wednesday afternoon. It is a product of weeks of Capitol Hill negotiations in which top Democrats like House Minority Leader Nancy Pelosi successfully blocked Trump’s most controversial proposals, including a down payment on oft-promised Trump’s Mexico border wall, cuts to popular domestic programs, and new punishments for so-called sanctuary cities. The White House instead boasted of $15 billion in emergency funding to jumpstart Trump’s promise to rebuild the military and an extra $1.5 billion for border security.
Olick – home prices will not fully recover until 2025?
Check out any one of the many national home price reports, and headlines scream of new peaks and growing gains each month. Home prices are rising faster than inflation, faster than incomes and faster than some potential buyers can bear. Those reports are heavily weighted toward large metropolitan housing markets. In fact, most of the US housing market has not recovered from the epic crash of the last decade. Only about one-third of homes have surpassed their pre-recession peak value, according to a new report from Trulia, a real estate listing and analytics company. Price growth in most markets is so slow that it will take about eight years for the national housing market to fully recover — that is, for all home values either reaching or surpassing their previous peaks. Huge price gains during the last housing boom were juiced almost entirely by an incredibly loose mortgage lending market that no longer exists. To say that the housing recovery has been uneven is an understatement. Some markets that have seen huge employment and population growth in the last decade, such as Denver, Seattle and San Francisco, lead the news with bubble-worthy headlines. Not only have home prices there surpassed their recent peaks, they continue to rise at double-digit paces. Nearly all the homes in Denver and San Francisco (98%) have exceeded their pre-recession peak, according to Trulia. Other less obvious markets, like Oklahoma City and Nashville, Tennessee, have also seen the prices of most homes surpass their peak. In areas hit hardest by the foreclosure crisis, fewer than 4% of homes have recovered to pre-recession price peaks. These include Las Vegas; Tucson, Arizona; Camden, New Jersey; Fort Lauderdale, Florida; and New Haven, Connecticut.
Rising incomes are the leading cause of home price growth, according to Trulia, which looked at four factors: job growth, income growth, population growth and post-recession housing vacancy rates. Income growth showed the greatest correlation to home price growth. The intuition here is this: “Housing is what economists call a ‘normal good,’ so when incomes rise, households tend to spend more on housing, which pushes up prices,” wrote Ralph McLaughlin, Trulia’s chief economist, in the report. Job growth didn’t correlate at all because more jobs don’t necessarily mean higher incomes. Of course job growth does matter tangentially, as more jobs often mean a growing population. More people create more demand, which can push prices higher if there is not enough supply. Colorado Springs, Colorado, is a good example of that: Population has grown dramatically in the last decade, but incomes have not followed pace. Home prices are near their pre-recession peak there and continue to rise. The very limited supply of homes for sale has dominated the narrative in this spring’s market and also been blamed for bubble-like prices in some areas. That is definitely a factor, but only at certain price points and in certain areas. “In essence, income growth led home value recovery coming out of the recession, but low inventory is now increasingly playing a role in recent price appreciation across the largest US housing markets,” said McLaughlin. Overall, the housing recovery has been limited to a mix of markets in the West seeing huge economic growth and in parts of the South where the housing crash didn’t hit as hard. Outside of major markets, the recovery is strongest in the heartland and the Pacific Northwest, which are both seeing bigger employment and income growth.
CoreLogic – earthquake risk: spotlight on probabilistic loss modeling
Catastrophic risk models and analytics are commonly used by the insurance, reinsurance, financial and mortgage industries to help understand and quantify risk exposed to natural catastrophes including earthquakes, hurricanes, floods, wildfires and hail storms. The first step in developing a view of risk is understanding the landscape of the hazard. For earthquakes, the preferred view of hazard is generally a country-specific national seismic hazard map. As their names suggest, seismic hazard maps assess hazard, but the insurance and financial industries often require more information and seek to obtain a quantitative view of risk. When hazard intersects with exposure – what can potentially be damaged by the hazard – it changes the focus from hazard to risk. For example, there can be areas of extremely high hazard, but if there is nothing in the areas to be damaged, the risk will be lower. When quantifying catastrophe risk, the full spectrum of risk must be evaluated, ranging from the more frequent and generally less damaging events to the extreme, catastrophically damaging events. This is where probabilistic modeling is advantageous. Probabilistic modeling – or more specifically, probabilistic loss modeling – offers a quantitative view of risk for all potentially feasible events that may occur, including their frequency of occurrence. Risk managers in the insurance and financial industries use these models to estimate financial losses from catastrophic events. From a financial perspective, the higher-frequency events are often smaller and less damaging, but multiple events in one year can have an impact on the cash flow of a company. On the opposite end of the spectrum, low-frequency, high-consequence events can impact the solvency of a company. To assess the financial losses for each event through a probabilistic loss model, much more is required than an understanding of the hazard.
Typically, there are four components that make up a probabilistic loss model: hazard definition of all possible events, determination of hazard footprint for each event, vulnerability assessment of structures impacted by each event, and financial loss calculation.
– Component 1: Definition of hazard through development of a stochastic event set. This is defined by defining all possible earthquake sources (i.e. faults or areas of active earthquake activity), defining a range of magnitudes on each source and a probability of each magnitude occurring on each source.
– Component 2: For each possible event in the stochastic event set, the ground motion propagation is calculated to understand the extent of potential impact of each event. This step involves an understanding of the underlying soil conditions and equations for propagation of earthquake ground motion.
– Component 3: Relates hazard to damage by assessing the vulnerability or damageability of each structure (e.g. residential, commercial or industrial properties) within the footprint of hazard for each event. To assess the vulnerability of structures, local building codes, building practices and features including the age, type of construction and height of the building are used.
– Component 4: The final step relates damage to loss through a sophisticated financial calculation to estimate a quantitative loss estimate for each possible event.
Risk managers utilizing probabilistic loss models use portfolios of their assets as input to understand the loss impact specific to their exposure. With the goal of being able to measure and manage their risk, risk managers seek to understand the specific details of their exposure – where are their assets, how concentrated are they, how vulnerable are they? This allows them to measure the financial losses for their portfolio of assets and understand which features are driving their risk. When understanding drivers of earthquake risk, a probabilistic loss model can help risk managers understand which fault sources or magnitudes are the greatest contributors to the risk. By obtaining a deeper understanding of the distribution and severity of the risk, risk managers can more adequately manage their risk. An assessment of hazard is often the quickest and simplest way to get a snapshot of areas to be concerned with, but by evolving this method to include the vulnerability of different types of structures exposed to the hazard, risk managers can obtain a more comprehensive view of risk and financial losses. Risk managers have several tasks when it comes to managing earthquake risk within the insurance and financial industries, ranging from policy pricing, to capital management, capital allocation or meeting solvency requirements. Every step forward in evaluation of catastrophe risk is a step towards the ultimate goal of becoming more resilient. By leveraging analytical tools like probabilistic loss models to help quantify financial losses, identify the distribution risk and additional impacts such as business continuity, the industry can achieve a more measurable view of their risk and ultimately become more resilient.