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In Portfolioticker today
Today at the stock market
“All three major U.S. stock index rose to record closing highs on Monday, with the Dow Jones Industrial Average less than 50 points below 23,000, ahead of a long list of earnings this week and as financial shares recovered from last week’s losses.
JPMorgan Chase and Bank of America led gains in bank stocks, tracking a climb in U.S. Treasury yields, which benefits banks. JPMorgan was up 2.1%, while Bank of America was up 1.6%.
The S&P 500 financial index rose 0.6% after 3 days of losses. Shares of banks mostly slipped last week after they reported results.
Netflix gained 1.6% during the session and rose another 2% after the bell following the release of its results. Report
Apple shares gained 1.8% following a bullish brokerage call.
The reporting period heats up this week, and with the S&P 500 already up 14% so far this year, investors are hoping results and guidance will justify the relatively high valuation of stocks.
“Big companies are going to start reporting earnings, and I think that’s going to drive the direction of the market for the next two or three weeks. There’s a lot of optimism built in, and hopefully it will be reflected in the earnings. You saw decent numbers from the banks but quirks here and there. But for the bigger tech companies, people have high hopes,” said Peter Tuz, president of Chase Investment Counsel in Charlottesville, Virginia.
Investors will keep a close eye on the Senate, which is trying this week to pass a partisan budget blueprint that would help guide federal spending.
The Republicans want to use the “budget resolution” to pave the way for the party later this year or next year to pass a major tax-cut bill without any Democratic support.
U.S. President Donald Trump said Republicans and Democrats in Congress are working on a short-term fix for healthcare insurance markets after he last week scrapped subsidies to insurers.
S&P healthcare stocks were among the biggest laggards, with the index falling 0.4%.” Reuters
The S&P500, Dow Jones Industrial Average and NASDAQ Composite indices closed on record highs.
^ Market indices today (mouseover for 12 month view) Chart: Google Finance
|Index||Ticker||Today||Change||31 Dec 16||YTD|
|S&P 500||SPX (INX)||2,557.64||+0.17%||2,238.83||+14.24%|
^ USD and AUD denominated indices over the past 52 weeks Chart: Bunting
|Index||Currency||Today||Change||31 Dec 16||YTD|
Portfolio stock prices
Alphabet Class A shares closed on a record high of $1,009.35 – up 0.15% on Friday’s record of $1,007.87.
Alphabet Class C shares closed on a record high of $992.00 – up 0.23% on Friday’s record of $989.68.
Alphabet Class A+C shares closed on a record high of $2,001.35 – up 0.19% on Friday’s record of $1,997.55.
Facebook closed on a record $174.52 – up 0.45% on Friday’s record of $173.74.
VMware closed on a record $115.15. VMW has finally exceeded its 5-year old record of $114.53 set on 3 Apr 2012. That was a long time between drinks!
|Stock||Ticker||Today||Change||31 Dec 16||YTD|
^ Bloomberg Dollar Spot Index (DXY) movements today (mouseover for 12 month view) Chart: Bloomberg
“The Bloomberg Dollar Spot Index (DXY) rose 0.2%.
The euro fell 0.2% to USD 1.1792.
Britain’s GBP fell 0.3% to USD1.3249, the first retreat in a week.
Japan’s JPY fell 0.3% to 112.16 per USD.” Bloomberg
^ AUD movements against the USD today (mouseover for 12 month view) Chart: xe.com
Oil and Gas Futures
Prices are as at 15:48 EDT
- NYMEX West Texas Intermediate (WTI): $51.85/barrel +0.78% Chart
- ICE (London) Brent North Sea Crude: $57.84/barrel +1.17% Chart
- NYMEX Natural gas futures: $2.96/MMBTU -1.27% Chart
BIS: Interest Rates and House Prices
“Conclusion Most empirical studies assume that short-term interest rates do not influence house price growth other than through the domestic cost of borrowing, ie by their influence on long-term interest rates. The findings in this paper suggest that this view might be mistaken: changes in short-term interest rates seem to have a strong and persistent impact on house price growth. Moreover, global, ie US short-term interest rates – not just domestic ones – seem to matter, both in advanced economies and EMEs. We interpret the relative importance of short-term interest rates in driving house prices as indicating an important role for the bank lending channel of monetary policy in determining housing financing conditions, especially outside the United States, where securitisation of home mortgages is less prevalent.
The larger effect of interest rates on house prices we find reflects in part the use in our regressions of a long distributed lag of interest rate changes. For the United States, our estimates for the period from 1970 to the end of 1999 suggest that a 100 basis-point fall in the nominal short-term rate, accompanied by an equivalent fall in the real short-term rate, generated a 5 percentage point rise in real house prices, relative to baseline, after three years. We find an even larger effect if we include the data through end-2015. For other advanced economies and EMEs, we estimate that a 100 basis-point fall in domestic short-term interest rates, combined with an equivalent fall in the US real rate, generates an increase in house prices of up to 31⁄2 percentage points, relative to baseline, after three years.
Another reason we find larger interest rate effects is by allowing for inertia in house price movements. We find strong evidence against the random walk hypothesis: real house prices around the world tend to move in the same direction for about a year after being hit by a disturbance, then exhibit a modest reversal. We think that this inertia in house prices reflects the large search and transaction costs associated with trading residential real estate and shifting between owner-occupied and rental housing. These costs are ignored in the user cost model, which predicts a fairly high interest rate sensitivity for house prices.
Our findings also suggest a potentially important role for monetary policy in countering financial instability. While higher short-term interest rates alone cannot significantly dampen the demand for housing, slower house price growth can give supervisors more time to implement measures to strengthen the financial system. At the same time, the finding that house prices adjust to interest rate changes gradually over time suggests that modest cuts in policy rates are not likely to rapidly fuel house price bubbles.
Our paper leaves a number of unanswered questions for future research. First, why are house prices in the United States more responsive to changes in interest rates than is the case for other countries? One possibility is that house price sensitivity to interest rates is inversely related to the size of the transaction costs for trading real estate, which are relatively small in the United States. While we think this is a reasonable conjecture, we offer no direct evidence that it is true. Second, in the United States, we find a roughly equal contribution to house price fluctuations from real and nominal interest rates. While this could arise from a large number of potential home buyers suffering from money illusion, we cannot offer direct evidence that this is the case. Third, the relatively large response of house prices in EMEs to US short-term interest rates suggests that US rates may have a larger global impact than previously recognised. This could arise, for example, if house prices in EMEs were especially sensitive to global liquidity conditions.
The bank lending channel of monetary policy gives us confidence that our use of the US short-term interest rate to capture global liquidity is reasonable; however, we recognise that there are other proxies. Cerrutti et al (2014) suggest, along with other measures, the term spread as an indicator of the availability of global liquidity. A low term spread implies reduced profit opportunities from borrowing short and lending long domestically. This can encourage banks to increase their risk-taking, extending loans to those who were previously denied credit, including borrowers abroad. Another candidate is repo borrowing: Adrian et al (2015), for instance, argue that the extent of repo borrowing by the US Federal Reserve’s primary dealers is a measure of their risk appetite. Bruno and Shin (2015) present evidence consistent with the view that greater risk appetite is associated with greater cross-border bank lending. And the thesis that greater cross-border bank lending would affect house prices around the world is supported by the findings of Cesa-Bianchi et al (2015).
Future research could also investigate which measures of global liquidity are most correlated with house prices in advanced economies and EMEs and how sensitive these findings are to the inclusion of the 2000–06 period in the analysis. This is for the same reason that our preferred estimates for the impact of interest rates on US house prices rely on data only through the end of 1999: the 2000–06 period may be unusual. Shiller (2008) argues that the period was associated with a feedback loop between the demand for housing and expected capital gains on housing assets: price increases fuelled demand by raising expected capital gains, and the greater demand fed back on prices. He also suggests that “new era” stories that supported boom thinking, in the United States and elsewhere in the world, played an important role in this feedback loop. Ample global liquidity arguably helped this process along, but the effects of global liquidity on house prices might be smaller in the absence of a strong feedback loop from capital gains on housing assets to demand.“
Gregory D Sutton, Dubravko Mihaljek and Agne Subelyte, Bank for International Settlements 2017, “BIS Working Papers No 665: Interest rates and house prices in the United States and around the world” Paper
AU: Lending Finance. Aug 2017
Press Release Extract [ser_au_finance]
August Key Figures Jul 2017 Aug 2017 Jul-Aug TREND ESTIMATES Housing finance for owner occupation $ 20.996 bn $ 21.176 bn +0.9% Personal finance $ 5.966 bn $ 5.999 bn +0.5% Commercial finance $43.687 bn $ 43.665 bn +0.0% Lease finance $ 0.576 bn $ 0.585 bn +1.5% SEASONALLY ADJUSTED ESTIMATES Housing finance for owner occupation $ 21.071 bn $ 21.265 bn +0.9% Personal finance $ 6.005 bn $ 6.151 bn +2.4% Commercial finance $ 42.528 bn $ 43.505 bn +2.3% Lease finance $ 0.578 bn $ 0.574 bn -0.65%
“AUGUST 2017 COMPARED WITH JULY 2017:
Housing Finance for Personal Occupation
The total value of owner occupied housing commitments excluding alterations and additions rose 0.9% in trend terms, and the seasonally adjusted series rose 0.9%.
The trend series for the value of total personal finance commitments rose 0.5%. Revolving credit commitments rose 0.8% and fixed lending commitments rose 0.4%.
The seasonally adjusted series for the value of total personal finance commitments rose 2.4%. Revolving credit commitments rose 6.4% while fixed lending commitments was flat.
The trend series for the value of total commercial finance commitments was flat. Fixed lending commitments rose 0.4% while revolving credit commitments fell 1.7%.
The seasonally adjusted series for the value of total commercial finance commitments rose 2.3%. Revolving credit commitments rose 4.3% and fixed lending commitments rose 1.8%.
The trend series for the value of total lease finance commitments rose 1.5% in August 2017 while the seasonally adjusted series fell 0.6%, following a 6.8% fall in July 2017.“
Australian Bureau of Statistics, “5671.0 Lending Finance, Australia, August 2017“, 16 Oct 2017 More
EU: International Trade
Press Release Extract [ser_eu_trade]
The first estimate for euro area (EA19) exports of goods to the rest of the world in August 2017 was €171.5 billion, an increase of 6.8% compared with August 2016 (€160.6 bn). Imports from the rest of the world stood at €155.4 bn, a rise of 8.6% compared with August 2016 (€143.1 bn). As a result, the euro area recorded a €16.1 bn surplus in trade in goods with the rest of the world in August 2017, compared with +€17.5 bn in August 2016. Intra-euro area trade rose to €132.9 bn in August 2017, up by 7.6% compared with August 2016.
In January to August 2017, euro area exports of goods to the rest of the world stood at €1 437.6 bn (an increase of 7.6% compared with January-August 2016) and imports at €1 292.4 bn (an increase of 11.1% compared with January-August 2016). As a result, the euro area recorded a surplus of €145.3 bn, compared with +€172.2 bn in January-August 2016. Intra-euro area trade rose to €1 209.3 bn in January-August 2017, +7.5% compared with January-August 2016.
The first estimate for extra-EU28 exports of goods in August 2017 was €145.5 billion, up by 6.4% compared with August 2016 (€136.7 bn). Imports from the rest of the world stood at €150.5 bn, up by 3.9% compared with August 2016 (€144.8 bn). As a result, the EU28 recorded a €5.1 bn deficit in trade in goods with the rest of the world in August 2017, compared with -€8.2 bn in August 2016. Intra-EU28 trade rose to €249.3 bn in August 2017, +7.7% compared with August 2016.
In January to August 2017, extra-EU28 exports of goods stood at €1 233.3 bn (an increase of 9.3% compared with January-August 2016) and imports at €1 227.8 bn (an increase of 9.4% compared with January-August 2016). As a result, the EU28 recorded a surplus of €5.5 bn, compared with +€5.9 bn in January-August 2016. Intra-EU28 trade rose to €2 192.4 bn in January-August 2017, +7.2% compared with January-August 2016.”
Eurostat, “August 2017: Euro area international trade in goods surplus €16.1 bn, €5.1 bn deficit for EU28“, 16 Oct 2017 More
Capacity Utilisation and Production. Aug 2017
“Capacity utilization in Japan increased to 103.40 Index Points in August from 100.10 Index Points in July of 2017. Capacity Utilization in Japan averaged 112.03 Index Points from 1968 until 2017, reaching an all time high of 137.50 Index Points in November of 1968 and a record low of 69.30 Index Points in February of 2009.
Industrial Production in Japan increased 2 percent in August of 2017 over the previous month. Industrial Production Mom in Japan averaged 0.41 percent from 1953 until 2017, reaching an all time high of 6.80 percent in May of 2011 and a record low of -16.50 percent in March of 2011.
Industrial production in Japan increased 5.30 percent in August of 2017 over the same month in the previous year. Industrial Production in Japan averaged 5.12 percent from 1954 until 2017, reaching an all time high of 30 percent in February of 1960 and a record low of -37.18 percent in February of 2009.” TradingEconomics
^ JPY movements against the USD over the past month (mouseover for inverse) Chart: xe.com
Stockmarket: Nikkei 225
^ Nikkei N225 movements over the past week Chart: Google Finance
Producer Price Index. Sep 2017
“The producer price index in China increased by 6.9% in Sep 2017 from Sep 2016, compared to a 6.3% rise in Aug 2017 and above market estimates of a 6.3% gain. It was the 13th straight month of increase in producer inflation and the highest since Mar 2017, as prices rose more than in a month earlier for means of production (9.1% from 8.3%, namely extraction: 17.2%, raw materials: 11.9% and processing: 7.3%). Also, cost of consumer goods went up slightly faster (0.7% from 0.6%, namely food production: 0.7%, clothing: 1.2% and daily use goods: 1.3%). Meanwhile, prices of consumer durable goods were unchanged, the same as in the prior two months. On a monthly basis, producer prices rose 1.0%, compared to a 0.9% gain in Aug 2017. Producer Prices Change in China averaged 1.15% from 1995 until 2017, reaching an all time high of 13.47% in Jul 1995 and a record low of -8.20% in Jul of 2009.” TradingEconomics NBS
CPI. Sep 2017
“China’s consumer prices rose 1.6% year-on-year in Sep 2017, following a 1.8% rise in Aug 2017 and in line with market consensus. The slowdown was mainly due to falling cost of food while cost of non-food continued to rise. On a monthly basis, consumer prices rose 0.5%, after gaining 0.4% in a month earlier and slightly above estimates a 0.4% rise. It was the highest monthly figure since Jan 2017. Inflation Rate in China averaged 5.32% from 1986 until 2017, reaching an all time high of 28.40% in Feb 1989 and a record low of -2.20% in Apr 1999.” TradingEconomics
^ CNY movements against the USD over the past month (mouseover for inverse) Chart: xe.com
^ Shanghai CSI300 movements over the past week Chart: Google Finance