Machine Learning In Stock Trading: An Easy Introduction

Its holiday season. The wifey is out and what better to do than invest time in reviewing some basic application of machine learning applied to the field of Finance. This is a post I have been wanting to write for a long time. All of the Code has been written in R and is easily reproducible. I will not share it here as I dont know how to do it best. Nonetheless the most important packages for achieving this level of black magic are:

1.  Caret
2.  Forecast
3.  Kenrlab
4.  Neuralnet
5.  Xgboost
6.  tseries (sub to PewDiePie)

I will not be reviewing any of the statistical concepts applied but will merely focus on their application and see if we can find any viable/useful results. I feel I should not be saying this as everyon here is a mature adult. BUT this is no financial advice and you should always be doing you due diligence when investing any of your money, not taking advice from a random stranger in the Internet. And bear in mind just because a strategy has worked in the past does not mean it will work in the future.

 

 

 We will be taking a closer look at the share price of the german football behemoth from the Ruhrpott who has been the eternal second after Bayern Munich, Borussia Dortmund.  As can be decuded the share price is highly related to the clubs sporting. So we shouldn’t be expecting too many conclusive results. The stock has also been known to attract some rather peculiar stories as someone bombing the team bus, hoping to hurt members of the staff to financially benefit from it. The time-seris can be seen below. As can be seen the share price has profited from some healthy growth reahcing an all-time high this year.

 

 

But how will proceed? Here a brief overview:

First we will be looking at some feature selection methods such as:

1. Filter Methods
2. Wrapper Methods
3. Embedded Methods

Second we will consider multiple machine learning methods such as:

1. Extreme Gradient Boosting Machine (XGB)
2. Support Vector Machine (SVM)
3. Artifical Neural Networks (ANN)

Third, we will conisder all results and compare them.

After this brief introduction we will finally get our hands dirty. First we will start by simply looking at some feature selection methods. At this point you might be thinking to yourself: “AWWW HELL NAH. JUST SHOW ME HOW TO DO THE THANG” let me tell you that feature selection is one of the most important factors when applying machine learning, so I will briefly run through it. This method consists of simply choosing input predictors. This has multiple advantages such as easy model interpretation, faster learning time, reduced dimensionality and reduced over-fitting. The principal techniques for feature selection are filter, wrapper and ensemble methods.

 

 

Filter methods consist of selecting input predictors based on certain statistical criteria before using them in a learning algorithm.

So first we can try to regress the returns of the share price on themselves using linear regression. Then we can trim down the input predictors down using the p-values. So we lagged the returns up to lag 9 (for no particular reason). Only lag 4 is statistically significant at the 5% level. Nonetheless we will also be looking at lag 3 as it still i statistically significant at level 10%. We have an adjusted r-squared value of 0.006 which is a rather poor result. Hence we will be eliminating all the input predictors unless the aforementioned ones.

 

 

Re-running the linear regression only using lag 3 and lag 4, we get the summary as can be seen below. As we can see re-running the test with less input predictors yields quite different results. The estimates for the single predictors are now different; furthermore, both of the estimates have become more statistically significant. Additionally the Adjusted R-squared has increased, even though still painfully low.

 

 

So we can advance to further ways of selecting our ideal predictor variables. So we can try to find our input predictors wrapper methods. The main advantage of wrappers compared to filter methods is considering interaction with output target features. The downsides of wrapper methods is obviously the increased computational power needed and the risk of over-fitting. Some of the most common Wrapper Methods are:

• Forward selection
• Backward elimination
• Recursive Feature elimination

I personally use backward elimination, where we start with all the features and removes the least significant feature at each iteration which improves the performance of the model. We repeat this until no improvement is observed on removal of features.

 

So using the Caret package we can run this rather simply in R. By the result we can see that the ideal model is composed of four variables, which is able to minimize the mean absolute error (MAE). The lags chosen by the recursive feature selection (rfe) are 4, 5, 1, 7. The results from this little more advanced feature selection is obviously already very different from the results achieved by our simple selection method.

Last but not least we will be looking at embedded methods. These consist of selecting input predictors while using them in learning algorithms and simultaneously maximizing model performance. Embedded methods combine the qualities’ of filter and wrapper methods. It’s implemented by algorithms that have their own built-in feature selection methods. Some of the most popular examples of these methods are LASSO and RIDGE regression which have inbuilt penalization functions to reduce overfitting. I will be using the Lasso regression which performs L1 regularization which adds penalty equivalent to absolute value of the magnitude of coefficients.

Using the Lasso we get a similar result to what we had when we just used the simple linear regression model.

Now that we are done with the feature selection, we can advance to the more juicy stuff.

Going forward we will be using the 4 input predictors we obtained using the recursive feature selection. So this means that we will be using lags 1, 4, 5, 7. Furthermore we will try to run our models via pre-processing our data by using principal component analysis.

So the first machine learning tool we will be using is an Extreme Gradient Boosting (XGB), which is a very commo algorithm (seems to be the favourite from the Kaggle Nerds, joking please don’t boot my nerds). This algorithm is great for supervised learning tasks such as Regression, Classification, and Ranking. EGB has the following parameters.

1. Tree boosting algorithm: it predicts output target feature of weighted sequentially built decision trees
2. Algorithm optimization: it finds local optimal weight coefficients of sequentially built decision trees. For regression, gradient descent algorithm is used for locally minimizing regularized sum of squared errors function, among others.

Running the XGB in R, this is the output we get. So we notice that the number of rounds which minimized our RMSE was 50 and the max tree depth is 1. This can furthermore be observed when looking at the bottom right window, with eta 0.3 and subsample 1. What we could also try (and which I actually did) is to see whether feature extraction via PCA could improve our results.

Principal component analysis (PCA) is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables (entities each of which takes on various numerical values) into a set of values of linearly uncorrelated variables called principal components. This transformation is defined in such a way that the first principal component has the largest possible variance (that is, accounts for as much of the variability in the data as possible), and each succeeding component in turn has the highest variance possible under the constraint that it is orthogonal to the preceding components.

So quick check if our input predictors are in any shape or form correlated. As we can see none of the input predictors are very much correlated to each other. The most prominent correlation we can observe are at lag 5, which as a positive correlation of 0.08. In this environment using PCA makes not a lot of sense but keep in mind it is a viable tool in a highly correlated environment, such as when checking for interest rate products. Using the PCA pre-processing we finally arrive at an RMSE of 0.02720604 which is actually slightly better than the 0.02723055 RMSE achieved by selection features. Obviously in real-life you would still opt to having as little as possible input predictors. Nonetheless as the results are better and my computer is not suffering too much under the additional computational requirements we will move forward using PCA.

So moving forward, we now will visualize how our residuals behave and try to make sense of our results. Below we can see how our model behaves with respect to the actual time-series of the returns from the share price. The black line represents the actual returns whereas the red line is the estimates from our XGB. You now might be thinking to yourself: “Well this is quite underwhelming…”.

Nonetheless before you rage-quit, keep in mind we want the model to give us directional predictions and not an exact estimate of exactly how much the share price will move. This is exactly what it does, we do not expect the model to reproduce the exact moves of the share, as this would simply mean that the time-series is overfit.

Taking a closer look at the results achieved by the PCA we can see that the results are very similar. Nonetheless the results achieved by pre-processing are much more prominent (simply take my word for this) .

We will now us the model to predict give us a signal and change our position in the stock. We will only consider long or no position, as shorting stocks is just a whole different story.

So when running this all we get the following table. The first column “xgbmret” describes simply the returns generated by the model. The second column “xgbmretc” describes the returns generated by the model adjusted for commissions. The commissions were calculated at 10 bps per trade, which actually cuts of fair share or annualized returns. The last column “rbr” simply is the returns generated by a long position. As we can see the model can clearly outperform a simple buy and hold position as it is able to generate higher annualized returns at a much lower risk. Nonetheless the picture changes a little when considering commissions, which place a heavy toll on the performance. When considering any sort of commission, the annualized returns drop by a total of 7 (!!!!!!)percent points. Algebraically it also makes sense that the standard deviation increases. So even though our returns have come down drastically, the Sharpe ratio is still much more performant than a simple buy and hold position.

Furthermore we can check the equity curve to see how the time-series evolved over time. This is useful information as it will help us infer if any of those performances were just lucky at a certain point in time. By looking at the graph we can see that the performance was quite consistent over time. Additionally it allows to infer one of the big advantages of the model, which is the protection against drawdown which the model ensures.

Ok now that we have tested for this model, let us try some other models. I will be proceeding in a similar way but only present you with the results and spare you all the tedious stuff in between.

So next we will be looking at Maximum Margin Methods. These methods consist of supervised boundary based learning algorithms for predicting output target feature by separating output target and input predictor features data into optimal hyper-planes. The most common method for regression learning tasks are support vector machines. Support vector machines are usually used for classification tasks which is obviously our case. Here again we will be using the pre-processed PCA time-series, again because the RMSE is lower. I will spare you most of the previously discussed details. Nonetheless I would like to guide your attention toward this graph below. This graph was already discussed when having a more detailed look at the XGB. What we can see now is that the SVM is more volatile when it comes to projections. So even though it might be more accurate but might cost us more money with respect to commissions we will have to pay.

Here again we can observe what we have observed previously. Nonetheless we can already see that one of the downfalls of the Support Vector Machine is its increased volatility which forces us to change our position many times, forcing us to pay up a lot (hey maybe the broker will send you over some goodies for that). Adjusting for commissions we have to pass on half of our earnings to the broker, which is very hefty. Considering commissions the risk-adjusted performance even becomes worse than the simple Buy and Hold position. This makes clear that it is critical for any signal to be able to blend out random noise. Even though the SVM performed much better than the XGB in an ideal world without commissions, it performed much worse when considering commissions. Now it may be that the commission I am considering is way too high or low, strongly skewing the results. This is the fine balance someone has to consider when setting up any kind of model.

And we can again observe that the trading strategy provides good protection against any sort of downside risk compared to Buy and Hold strategy.

 

Last but not least we will move on to the Artificial Neural Network (ANN), which is part of the Multi-Layer Perceptron Methods. Multi-layer perceptron methods consist of supervised learning algorithms for predicting output target feature by dynamically processing output target and input predictors data through multi-layer network of optimally weighted connections of nodes. The nodes are usually organised in input, hidden and output layers.

In this case we are running the ANN using the features we selected at the beginning. Just to remind you in case of short-term memory loss, these were lag 1, 4, 5, 7. The results, are to say, at the very least very underwhelming. Even though we were able to bring down the standard deviation net or not of commission the returns are just horrendously bad. This obviously does not de-classify the application of ANN, but it just shows that you don’t need the most complicated of machine learning to be able to solve problems related to finance.

So finally we can compare the results of all the algorithms and see which one performed best. When considering the results generated without considering commissions we get see that machine learning algorithms can provide valuable insights. The only machine learning algo which was not able to outperform the Buy and Hold position was the ANN. As previously mentioned the algos are able to provide some existential protection against downside risk. The retuns generated by any of the rules are anyway rather substantial.

Now ignoring commissions simply is not wise. So the returns worsen a lot when considering commissions. Nontheles we are also able to bring down Std. Dev. drastically, which is a plus. Nonetheless this is still not enough to have a better Sharpe Ratio than the benchmark.

Is the Federal Reserve running out of time?

The Federal Reserve was steamrolled by a perfectly hedged move by the POTUS, who escalated the Chinese tariffs conflict, imposing a 10% tariff on 300 bln of Chinese goods. The POTUS and his team decided to further escalated trade wars, after a calculated move urging the FED to cut the IOER by 50 bps during the FOMC July meeting. Since then the market has rallied to long duration trades, which has led to more curve flattening and further inversion of the 3s10y TSY curve. At this point the 2y10y has still not inverted but has come under massive pressure following recent days. Even though long duration trades are not any novelty, due to the fact that financial institutions are chasing yields at every price possible, the sharp decrease in TSY is astonishing.

Generally a flattening of the curve does not mean a downfall for equities. Nonetheless such a flattening emphasizes the fear of escalating trade wars and a Federal Reserve which is not able to communicate its policy in an effective way. The risk of a market correction/downtrend have risen dramatically and market participants are slowly positioning towards a risk-off scenario, with gold slowly but surely crawling back to the levels of the GFC, trading at USD 1502 with no real profit-taking in sight. The aforementioned global tensions are reflected by equities, most notably the S&P 500, who saw a harsh and quick drawdown. The S&P ended up drawing down 205 points, losing 6.78% of its total market cap.

As of recent the distress is also felt in the interbank market with the 3M LOIS widening back to the yearly high, showing a worsening in credit. The move in credit is widely off-set by liquidity constraints, driving towards a wider the EURUSD XCCY basis. This comes as no surprise with the Treasuries decision of increasing the debt ceiling and the earlier than expected stop in balance sheet unwinding. At this moment the XCCY basis is at some sort of a sweet spot. On the one side Europe investors are looking for high yields in the U.S. zone and on the other side U.S. debt managers are looking at tendering low-yield debt. This can be observed by the growth in reverse Yankee funding.

The 5y5y forward rates on inflation levels have come down from the highs off 2.30 to well below the inflation target of 2% set forth by the Federal Reserve. This comes as an aftermath of the slowing in Economic data and the dovishness of most central banks.

The crucial factors which could impact equities are:

1. Forward Guidance of the Central Banks: As other central banks have proceeded to react to growing worries with respect to global trade tensions, like the RBNZ who cut its rate by 50 bps the FED has come under increasing pressure. Fed Fund Futures are pricing in a total of 100 bps cuts up to December 2020. This is not observable in TSY, where the 2Y Yield is trading at 1.5978. If the Fed is unable to put markets at ease ad keeps running behind the curve we could see a correction in equities. In essence, the September FOMC could be absolutely pivotal to resetting animal spirits. The Fed has plenty of excuses to do this, trade-escalations being the primary factor, particularly as Chair Powell has consistently noted that the biggest risks to the economy are those that are external. Nonetheless compared to the rest of the globe US yields are still very attractive compared to other jurisdiction, like the German 10Y Bund who is yielding at -0,587%.
2. Fading fiscal stimulus: With the fiscal easing under Trump, stocks saw an artificial rejuvenation. Since then fiscal stimulus has faded away and makes the comparison of companies earnings rather difficult. This phenomenon could be observed when fiscal easing began an economic surprise was very high, now with fading effects of fiscal stimulus the Citi Economic Surprise Index has been trending lower.
3. Further Escalation in Trade Wars: In the initial rounds of tariffs President Trump raised tariffs to 25% after having levied an initial 10%. This could well become a deja-vu in the newest round of discussions, between the US and CHINA.

As observed by Citi equity markets seem to be essentially trading like a two-factor model, with the input variables Trump Tweets and FED pricing:

1. The end of 2018 brought about more conciliatory tweets from Trump in November but crucially these were unable to prevent the equity market from correcting ~20% due to a hawkishly delivered Fed hike. An almost immediate dovish turn by Powell in conjunction with a friendly Trump tweet reversed the market sell-off at the turn of the year. At this stage, the money market curve hadn’t yet started to price cuts but did price out further hikes.
2. By the beginning of March stocks were up 18% from the December lows, but an abysmal non-farm payrolls number spooked the money markets into pricing an entire cut by the end of the month. Ironically, this is where the “bad-data = good-news” regime emerged. Data weakness gave lower projected discount rates which helped the equity market rally back to all-time highs in May, supercharged by pacifying Trump tweets.
3. The May escalation of trade wars started the vicious circle of the risk assets relying almost entirely on the premise of Fed cuts. The market recovered as ~70bps worth of Fed cuts were priced by June. Sentiment recovered following what looked like a temporary end to trade escalations in the G20.
4. As of now, the Fed has disappointed the market with a ‘hawkish cut’ whilst there looks to be no sight of trade détente in the short term given the move higher in USD/CNH and the subsequent branding of China as a currency manipulator by the US Administration.

ProSiebenSat1 stock down 13%

Today the DAX fell to the 11900 point mark and is accounting for a loss of 1,60% one hour before close, standing at the 11930 point mark. At this time no stock is in the green range with the biggest loss coming from the German Media Behemoth ProsiebenSat1 with a booming 13% loss. Investors seem to be looking to invest in assets deemed safe such as Gold, which is up 0,6%.

ProsiebenSat1 warned that TV advertising revenues in German-language markets would decline in the third quarter and said it may look for external investors. The top German free-to-air broadcaster had already cut its TV advertising market outlook twice this year but said as recently as earlier this month it still expected a bounce-back in the second half of the year. Many major companies that rely on ad revenue have reported spending cuts by makers of fast-moving consumer goods such as Unilever, Nestle and Procter & Gamble – the world’s biggest advertisers – as they respond to weak global economic growth. Goldman Sachs downgraded ProSieben to “neutral” from “buy”. “We believe shares will remain under pressure until the first signs of market improvement (this is likely to affect other ad-exposed stocks as well),” it wrote. ProSieben shares were down 11.6 percent to 28.90 euros by 0820 GMT, at the bottom of the German blue-chip DAX and dragging the European media index down 2.5 percent.

Following a brief early tease to the upside, which saw the Dow Jones Industrial Average rise close to 50 points in minutes after yesterday’s market open, further reflections on the widespread damage caused by the hurricane that ravaged Houston and other parts of the southeastern portion of Texas over the weekend, the equity market quickly turned lower. As has been the case for much of this year, however, the pullback was relatively mild, with the Dow continuing to trade between 20 and 40 points lower, while the S&P 500 held just below the breakeven line. Breaking things down, the most of the morning saw more stocks decline than rise on the NYSE, although the differential was modest. One outlier was the NASDAQ, which gained nicely during this time. As for individual stocks, the Dow was pushed lower by a multi-point early decline in shares of Travelers. Energy prices also faltered on the damage brought on by the hurricane, with driller Schlumberger pulling back, and nearing a 52-week low in the process. As to other trading influences, with a heavy week of economic news before us, headlined by this Friday’s reports on employment and unemployment, along with key data on manufacturing, Wall Street was also consumed with the latest political news, where, this week, President Trump is expected to push his tax reform package, the timing of which could be in some jeopardy if costs to pay for the hurricane balloon in the months to come. Also, with pivotal data due on the economy, some focus will logically turn to the Federal Reserve, as it prepares to meet this month. Meanwhile, after this mid-morning Dow reversal, stocks steadied somewhat, so that as we neared the noon hour in New York, the blue-chip composite was nearing breakeven, while the NASDAQ’s gain was increasing. Then, as the afternoon got under way, stocks slipped anew, and within an hour, or so, the Dow and the S&P 500 were well into the red, while the NASDAQ’s gain, once 27 points, had eased to nine. Joining Schlumberger in the red, meantime, was food giant General Mills , with its setback bringing that quality issue to within a point of a new low. Stocks then stayed range-bound into the late afternoon, before some last minute buying almost wiped out the Dow’s deficit. Even so, at the conclusion of the session, that composite was off by only five points. A token gain, meantime, was tallied by the S&P 500 Index and a 17-point advance was inked by the NASDAQ. In the end, much of the day’s focus was on Hurricane Harvey, which was crippling the energy industry in Texas. As for the ultimate cost of the tragedy, above and beyond the human toll, it will be steep, with a partial offset from rebuilding. The potential of such rebuilding, in fact, did help one Dow stock to a hefty gain on the day, as The Home Depot jumped nearly $2.00 a share. Elsewhere, there was little excitement on this Monday in late August. Looking ahead to a new day now, we see that stocks were tumbling across Asia overnight, on jitters about North Korea that emerged late yesterday, while in Europe, the major bourses are now trading much lower, as well, on those same fears. In other markets, oil is little changed; gold, up sharply in recent weeks, is soaring again after North Korea launched another missile; and Treasury yields are down notably in a flight to safety. Finally, our futures are moving decidedly lower at this early hour, with the Dow suggesting an opening loss in excess of 100 points.

Alibaba has another blockbuster quarter

After a strong week, the DAX is slowing down today and losing some of its momentum, quoting a downward movement. The German Index started out strong but reverted back to the mean very quickly. 2 hours before close, the German DAX is down 0,20% from its previous close. A reason for this cool down in the German markets might be that German investors are on their tiptoe amid the AirBerlin and Lufthansa deal. Oil and Gold are down 0,39% and 0,22% respectively.

In the U.S. the bulls began trading yesterday with a new head of steam, as the leading averages all moved out to impressive early gains. On point, after we had passed the first half hour of market action, the Dow Jones Industrial Average had rung up a gain of some 70 points. Modest rallies also were under way on the S&P 500 and the NASDAQ. Also, yesterday, unlike Tuesday, the S&P Mid-Cap 400 and the small-cap Russell 2000 were comfortably in the black, as well. As to the Fed minutes, Wall Street was looking for clues about the Fed’s interest rate intentions. The report, meantime, suggested that there was now a split developing on the Fed regarding whether to tighten the monetary reins again this year, citing concerns about low inflation balanced out by improving GDP growth. Our sense continues to be that the Fed will raise rates just once more in 2017, and that such an adjustment might not come until late this year. Meantime, the market’s advance remained in place as the morning wound down, with the Dow’s advance holding in the 60-85 point range as noon arrived in New York. The NASDAQ, up haltingly early in the session, strengthened as the afternoon approached, with its advance surpassing 25 points. The stock market then stayed near the upper levels of its range for the next hour, or so, but ill winds politically, as other companies now have decided to abandon the President’s manufacturing council following last weekend’s violence in Charlottesville and the Administration’s changing response to it, fueled some selling as the 2:00 PM hour approached. In all, the Dow’s advance went from more than 85 points down to fewer than 30 points at one time. Still, the market had a generally strong tone to it, which suggested at the time that unless the minutes held some unwanted surprises, the day would end higher for stocks. The Fed minutes had little impact, with stocks initially rising then pulling back, with the Dow’s gain at one point nearly evaporating. Our thinking is that this Fed release will have little meaningful impact, with political headwinds probably more of an influence at this moment on market behavior. Traders, meantime, then backed off somewhat as we headed into the close, with the Dow ending the session ahead by a modest 26 points, while the NASDAQ, which waxed and waned late in the day, finally ending matters up by 12 points. Meantime, the Russell 2000, once ahead strongly, edged down a trifle at the conclusion of the day’s action.

Walmart has poured billions into its e-commerce and tech to integrate its digital business with its stores, and the strategy is paying off handsomely. The retailer said comparable sales at its 4,000 U.S. stores, a $300 billion a year business, rose 1.8% on the year in the three months to June, well above Wall Street expectations for 1.3% according to Consensus Metrix. That gave Walmart U.S. its 12th straight quarter of growth. More crucially for the world’s largest retailer, shopper visits also increased, rising 1.3% and showing that Walmart’s massive investments in features like grocery curbside pickup, in-store order retrieval, its own mobile payment app and the expansion of its online assortment are spurring shoppers to come into stores. In an effort to be able to compete with Amazon, Walmart made some big investments in its e-commerce division. But investments, along with more aggressive pricing generally, cost money. The company disappointed Wall Street with a profit forecast of 90 cents to 98 cents per share for the current quarter, compared with the 98 cents analysts expected. Wal-Mart Stores shares, which had been on a tear of late, slipped 1.5% in pre-market trading. “Sales growth is coming from across the business – including stores, e-commerce and a combination of both,” CEO Doug McMillon said in a statement. The chain also got a boost from its massive grocery business, which generates 56% of its revenue. Food saw its best quarter in five years, aided in large part by an overhaul of the fresh food business that aimed at better competing with the likes of Whole Foods Market, which is being acquired by Amazon. Other bright spots for the company included the performance of Sam’s Club, which chronically underperforms its rival Costco Wholesale. Comparable sales, a metric that strips out the impact of newly-opened or closed stores, rose 1.2%, but shopper traffic was up 2%. Further afield, nine of Wal-Mart Stores’ eleven markets saw comparable sales increases, including a first rise in sales in three years at its Asda unit in the U.K. Still, the investments took a toll: Walmart earned $1.08 per share, slightly above $1.07 expected by analysts and roughly on par with a year-ago levels. Total sales were $123.36 billion, a hair above the $123.15 billion markets were expecting. Short after opening Wal-Mart is down 2,20%

Ireland’s finance minister said the European Commission’s demand that Dublin collect up to €13bn in back taxes from Apple was unjustified, in an interview with Germany’s Frankfurter Allgemeine newspaper. The European Commission ordered Apple to repay taxes to Ireland after ruling last year that the US technology company paid so little tax on its Ireland-based operations that it amounted to state aid.

Cisco reported FY4Q17 earnings on 8/16, after the close. Revenue and EPS came in as expected. Looking at revenue by products, there are puts and takes but nothing major to note. Gross margin for the quarter came in at 63.7%, or 20 bps lower than expectation, while non-GAAP operating margins came in 40 bps ahead of expectations at 31.5%. However, guidance is a tad weak. FY1Q18 revenue and EPS are about in-line, but non-GAAP gross margin was guided to 63-64% vs. 64.1% consensus, and non-GAAP operating margin was guided to 29.5%-30.5% vs. 31.3% consensus. Overall, the quarter is uninspiring, which is reflected in the stock trading down 2.5% in the aftermarket on high volumes.

Alibaba had another blockbuster quarter of business as its profits almost doubled. The Chinese e-commerce giant reported net profit of 14 billion RMB ($2.1 billion) for its recent quarter that finished June 30 — that’s up 96 percent year-on-year. Total revenue grew 56 percent to reach 50.2 billion CNY ($7.4 billion), easily exceeding estimates, with the firm reporting 466 million active buyers over the previous 12-month period. Alibaba’s core commerce business brought in the majority of revenue — 43 billion ($6.4 billion) — but its 58 percent annual growth was topped by its smaller business units. That’s a sign of the future, according to CEO Daniel Zhang. “Alibaba had a strong start to fiscal 2018, reflecting the strength and diversity of our businesses and the value we bring to customers on our platforms. Our technology is driving significant growth across our business and strengthening our position beyond core commerce,” Zhang said. Of those units, its aggressive cloud computing business, which TechCrunch profiled earlier this year, was one of the more impressive. It grew 96 percent to reach 2.4 billion RMB ($359 million) in revenue while losses narrowed to 103 million RMB, or $15 million. The company noted that its cloud computing customer base passed one million for the first time. Alibaba’s digital media and entertainment business, which includes video service Youku Tudou, saw revenue jump 30 percent to four billion RMB ($602 million). The company has spent the past year expanding its business outside of China, which this quarter again shows accounts for the lion’s share of revenue, and the results are beginning to bear fruit. Alibaba said its international e-commerce services reached “meaningful scale” with 2.6 billion RMB ($389 million) in revenue. It credited Lazada, its business in Southeast Asia which it recently invested a further $1 billion in this year, and AliExpress for increasing revenue by 136 percent from last year.

 The Earnings Outlook for tomorrow are Deere with an Actual EPS of 1,95, Foot Locker with an EPS of 0,902.

Todays Economic Calendar:

I) Jobless Claims

II) Industrial Production

III) Leading Indicators

IV) Fed Balance

V) Money Supply

 

 

 

Sysco down albeit strong earnings.

As there have been no further major escalations in the North-Korea conflict DAX investors took a bullish stance. After a strong opening,rallieing up to the 12200 point mark, the German DAX closed on the 12165 point mark, an intraday increase of 1.26%. With the highly expected German Economic Data about to be revealed tomorrow, the Investors seem to expect a positive development in Germany.

As we are off-schedule today, we will be reporting on today’s stock market developments. Stocks are moving nicely higher today, as we embark on a new trading week. Of note, traders are likely pleased that geopolitical tensions seem to be easing. At just past noon in New York, the Dow Jones Industrial Average is up roughly 147 points; the broader S&P 500 Index is ahead 25 points; and the NASDAQ is higher by 73 points. Market breadth shows broad based support for stocks, as winners are well ahead of losers on the NYSE. From a sector view, leadership can be found in the technology and financial issues. Meanwhile, the energy stocks, while still ahead, are logging more moderate gains. Elsewhere, traders received no major economic news items this morning. However, tomorrow should be a busier day for reports. Specifically, retail sales for the month of July, the latest monthly import and export prices, the Empire Manufacturing Survey, and a business inventories report, will all be released. These items won’t likely go unnoticed by traders. Finally, although the second-quarter corporate reporting season has largely concluded, we are still receiving some profit announcements. Specifically, Sysco stock is trading lower today, even though the food services company delivered a respectable quarterly report. In addition, shares of JD.com are lower, after the China-based Internet operator posted weaker-than-anticipated numbers. Technically, stocks are recovering some ground today, after a pulling back in price over the past week, or so. It remains to be seen, if the bulls can push the market higher from here, or if some consolidation will be in order. Traders will be looking at the corporate outlook, and also will likely be turning their attention to the domestic and international political arenas

Sysco Corp. reported earnings for its fourth quarter that advanced compared to the same period last year. The company said its bottom line came in at $388.30 million, or $0.72 per share. This was higher than $365.67 million, or $0.64 per share, in last year’s fourth quarter. Analysts had expected the company to earn $0.72 per share, according figures compiled by Thomson Reuters. Analysts’ estimates typically exclude special items. The company said revenue for the quarter rose 5.6% to $14.42 billion. This was up from $13.65 billion last year.

Sysco Corp. earnings at a glance:

• Earnings Growth (Y-o-Y): 6.2%
• EPS Growth (Y-o-Y): 12.5%
• Revenue Change (Y-o-Y): 5.6%

German technology startup investor Rocket Internet has announced a share buy-back with a total maximum consideration of up to 100 million Euros ($118 million). The buy-back scheme will include up to 5,000,000 shares, representing a maximum of up to 3.03 per cent of the outstanding share capital of the company, Rocket Internet said in a statement. The buy-back will be executed via Xetra trading on the Frankfurt Stock Exchange and will begin on August 14, 2017, ending on April 30.

 

Technical Analysis: Elliott Waves

In todays Weekend Special Edition we will be discussing Elliott Waves. For some technical analytsts Elliott Waves are a vital tool. As any investor the Technical Investor will want to have a reliable forecasting method. The possibility of easy profits by forecasting the market has been the underlying force that motivates so many investors. Elliott’s market model relies heavily on looking at price charts. Practitioners study developing trends to distinguish the waves and waves structures that we will refer to later in this article. The application of the Wave Principle is a form of pattern recognition. To obtain a full understanding of the Wave Principle including the terms and patterns, I recommend Elliott Wave Principle by A.J. Frost and Robert Prechter.

The Elliott Wave Theory was introduced by Ralph Nelson Elliott during the 1930’s. Elliott a full-time accountant believed that stock trends follow a repeating pattern which can be forecasted both in the long and in the short term. The Elliott Wave Theory was published in his book “The Elliott Wave Principle” in 1938. Using data from stocks he concluded that what seems to be a chaotic movement, actually outlines a harmony found in nature. Elliott’s discovery was completely based on empirical data, but he tried to explain his findings using psychological reasons. The main principle of this theory was that a pattern consists of eight waves as can be seen in the Image below.

It is visible that Wave 1, Wave 3 and Wave 5 follow the cyclical trend while waves 2 and 4 correct the underlying trend waves A, B and C correct the overall trend , while Wave A and C follow the correction and Wave B resists. Elliot observed that each wave consists of smaller waves which follow the exact same pattern as is shown in the Image below, thereby forming a super-cycle. The numbers in the Image represent the number of waves when counted in a different scope. For example the whole diagram represents two big waves, the impulse and the correction. The impulse consists of 21 usb-waves which in turn consist of 89 smaller waves, while the Correction wave consists of 13 sub-waves, which in turn, consist of 55 even smaller waves. As can be observed all of the above numbers are part of the Fibonacci series. According to the Elliott wave theory, when Elliott first expressed his theory he was not aware of the Fibonacci series.

Elliot believed that there are nine cycles, of different durations, the bigger of which, is formed by the smaller ones. From the largest to the smallest cycles there are:

1. Grand supercycle: multi-century
2. Super-Cycle: multi-decade (40 to 70 years)
3. Cycle: one year to several years
4. Primary: a few months to a couple of years
5. Intermediate: weeks to months
6. Minor: weeks
7. Minute: days
8. Minuette: hours
9. Subminuette:minutes

The duration of these cycles varies from minutes to decades. Each pattern (cycle) is outlined by the following rules:

1. The Second Wave cannot be longer than the first wave and cannot return to a lower price than that set at the beginning of the first wave
2. The third wave is never the smallest wave compared to the first and the fifth.
3. The fourth wave does not return to a lower price than the price found at the end of the first wave. The same applies for wave a.
4. Usually the third wave shows a greater dynamic, except in some cases where the fifth wave is extended (the case when the fifth wave is made up of five smaller waves)
5. The fifth wave usually leads to a higher point than the third.

When it comes to the interpretation of the waves we will present a short overview of the general dynamic of the waves. The first wave is the “new beginning” of an impulse. Opening a position at this point will be the most profitable scenario. It is difficult to differentiate it from a correction of a previous downtrend, and therefore it is not a powerful wave. Most investors prefer to wait for better timing. The force behind the wave pattern is the number of investors that decide to enter and exit the market at a given time. After some initial winnings, investors decide to exit the market as the price becomes higher, and the stock becomes overpriced for these few investors. This behavior translates in the second wave. As the price begins falling, the stock becomes more attractive for a great number of investors that regretted not having entered the market during the first wave. As the price begins falling, the stock becomes more attractive for a greater number of of investors that regretted not having entered the market at a higher price. Those who entered in the beginning of the wave, are satisfied with their winnings, and have most likely exited the market. Investors realize that the price has reached a level making it difficult to attract any further investors. Demand begins falling, which leads to the fourth wave. Major investors are out of the market, waiting for the end of the fourth wave, to enter again and reap in the profits of the fifth wave. It is important to note that the fourth and the fifth wave are the easiest ones to follow, as they come after the third wave which is the easiest to spot, due to its length, power and speed. Major investors have bought stocks on lower prices, from investors that had bought them during the end of the third wave who feared the price might go lower. However as the major investors enter the market again, they create a small hype, the fifth wave, smaller than the third wave, which usually reaches the peak of the third wave and sometimes even higher. Investors who know the market, know that the market is extremely overrated and therefore have exited the market. Wave A is a corrective wave which is often mistaken for a second wave. This explains wave B. Smaller investors think that wave A corrected the price enough, so that it can lead to an upward trend. Unfortunately, this is the Wave where most smaller, and occasional investors lose huge amounts of money, as Wave C starts, pushing the price lower until the price gets underrated again, for a new pattern to start.

The above explanation is by no means a statistical explanation of the wave behavior, but explains the difference between major and occasional investors and their knowledge of the market. It is exact to know the exact wave patterns , otherwise it is very easy to misinterpret signs. It is important to note that the following explanation regards an overall impulse trend. The opposite would happen in case of an overall correction.

Atsalakis et al (2011) compared the Elliott Wave principle to a Buy and Hold Strategy with remarkable results. The Elliott Wave Principle was tested with the stock of the National Bank of Greece. A paper portfolio worth 10.000 Euros was simulated. Buy and sell decisions did not take into account the confidence index, as it is subjective, depending on the risk the investor is willing to take, even though a threshold of 52% is widely acceptable. Stocks were bought whenever the forecast was positive, and the position was closed when the forecast became negative. Transaction costs were not taken into consideration. The system was tested for period April 2007 to November 2008, for a total of 400 trading days.s. It is worthy to note that this period also includes the great recession of October 2008, were the system achieved interesting results. For the whole period of 400 trading days, the hit rate was 58.75%, mainly due to the crisis. By breaking this period in four sub-periods of 100 observations, the hit rates achieved are 58%, 64%, 60% and 53%, respectively. During this period of 400 trading days, the WASP system made 63 transactions. This gives a rough average of 1 transaction every 6 days.

Dow Jones opens with 100 point loss

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• DAX Review
• Wall Street Review
• Bechtle Earnings
• Macy’s Earnings
• Kohls Earnings

After record-breaking weeks, Equities have had a hard time in the European Markets. Some catalysts for the week development in the Eurozone were the strengthening EURUSD, fueling the European Markets and therefore increasing liquidity in U.S. Markets. German Earnings and the German auto- cartel have been weighting down investor-sentiment. The North-Korea conflict seems to be the most recent agitator for the sell-off on the German markets. For the current trading day the DAX has not been quoting any green digits with the Index going down since its opening without any resistance. 2 Hours before close the German DAX is down 0,91% from its previous close.

Following another record closing high by the Dow Jones Industrial Average to start the trading week on Monday and a late reversal on Tuesday amid growing tensions with North Korea, the stock market, on an extension of those heightened geopolitical concerns yesterday morning, started the middle session of the week, notably to the downside. Of course, the threats and counter threats involving North Korea was not the only influence on Wall Street, as a disappointing revenue release from entertainment mogul Walt Disney also rattled the street and helped to push the Dow down notably to start the day.  In all, the Dow fell back 80 points early, and the NASDAQ, under pressure from declines in several high-profile technology names, tumbled 60 points at the morning’s nadir. In fact, that composite remained the large-cap’s weak link throughout the morning. But it was mainly a story of growing geopolitical risk, as U.S.-North Korean relations continued to deteriorate. Leading the way lower was the consumer discretionary category, which takes in the aforementioned entertainment giant, which lost some 5% of its value in the morning. What did do well early yesterday were traditional safe havens, such as Treasuries and gold. Meanwhile, there was no bounce of note as the morning moved along, as all 10 of the principal equity groups were trading in the red as we approached the noon hour in New York, while losing stocks were sustaining a 2.3 to 1.0 ratio on the Big Board. Further underscoring the weak nature of the day’s action to that point, the CBOE Volatility Index (VIX), widely considered the fear gauge, was up some 7%, to near 12, a one-month high. Overall, we think the market’s response to the threats from North Korea seems rather muted, in part because the consensus seems to be that tensions will eventually subside. The market’s decline then moderated for a time as the afternoon got under way, with the Dow’s loss narrowing to about 40 points. However, that proved to be a brief respite, and stocks soon faltered again, but not dramatically so. In truth, the stock market is a bit frothy, with P/E’s up to around 20 for companies with earnings. That is high, albeit not dangerously so in this low inflationary environment. Still, if traders needed some excuse to sell, the news out of North Korea and the revenue miss at Disney were reason enough. So, stocks wilted, as the afternoon progressed, and as we moved inside two hours, the Dow was near the day’s low. This downturn would then persist up until the final half hour, or so, with few periods of sustained buying to interrupt the downtrend. However, as the session neared its close, some selective buying took hold, enabling the larger-cap composites to notably pare the day’s losses. However, the comeback did not fully encompass the smaller-cap indexes, where the Russell 2000 still ended matters off more than 13 points. As for the various equity sectors, there was only a breakeven performance by the health care group, while the other nine categories posted declines of generally half a percentage point, or less. In the Morning the Dow Jones is down 100 points shortly after open, dropping under the 22’000 point mark, with Goldman Sachs contributing the most losses. The S&P 500 declined 0.6 percent, with information technology and financials leading all sectors lower. The Nasdaq composite pulled back 0.75 percent, with Apple, Alphabet, Amazon and Netflix all trading lower. The CBOE Volatility Index (VIX), widely considered the best gauge of fear in the market, soared more than 24 percent to trade at 13.79.

Information technology company Bechtle AG said its second-quarter earnings after tax rose 11 percent to 25.39 million euros from 22.71 million euros last year. Earnings per share grew to 1.21 euro from 1.08 euro a year ago. Earnings before interest and taxes or EBIT in the second quarter reached 36.5 million euros, an increase of 13.2 percent from 32.3 million euros last year. Quarterly revenue increased 13.7 percent to 822.2 million euros from 723.4 million euros a year ago. Looking ahead, the company’s Executive Board continues to expect significant revenue and earnings growth for the year as a whole and confirms the forecast for 2017 published in March.

Macy’s is taking its victories where it can. On Thursday, the department store chain said comparable sales fell 2.8% in the second quarter, the 10th straight quarter of decline for the retailer. That said, the results were not as bad as investors had feared. Wall Street had predicted comparable sales would drop by 3.5%, according to Consensus Metrix. (Comparable sales exclude recently opened or closed stores.) And profit by one measure came in at 48 cents a share, better than the 45 cents analysts were projecting. Total net sales fell 5.4% to $5.55 billion, slightly above expectations. Despite the not-as-bad-as-expected results, Macy’s did not raise its full year forecast, which suggests the retailer views these improvements as fragile. Investors were sufficiently spooked: Macy’s shares were down 2% in premarket trading to $22.50, about half the level of their 52-week high.

Kohl, who has a recorded success of undermining Macys, has released its and they look crispy. Kohl’s reported a narrower, 0.4 decline in same-store sales, compared to a drop of 1.8 percent during the same quarter last year. Analysts were expecting comparable sales to fall 1.5 percent, according to FactSet. Shares of Kohl’s were recently down 9 percent on the news, after initially jumping 4 percent in premarket hours. “The traffic momentum that we saw in the combined March/April period accelerated in the second quarter,” CEO Kevin Mansell said in a statement. “Though transactions for the quarter were lower than last year, July transactions increased. … We are also excited by the sequential sales trend improvement in all our lines.” Trying to drive shoppers back to its stores, Kohl’s has been testing new initiatives, like entering a partnership with Under Armour to sell the sports retailers merchandise. Management said on Tuesday that it’s also beginning to see benefits from initiatives in place with the goals of better managing inventory and cutting costs. “Under Armour in particular continued a very strong performance and beat the sales plan across almost all categories,” Mansell said on Thursday’s earnings conference call. “We’ve gained significant share in active apparel and footwear in the first half of the year and expect that to continue in the back half based on assortment improvements and our momentum.” The company’s net income rose to $208 million, or $1.24 per share, in the second quarter, from $140 million, or 77 cents per share, a year earlier. Net sales fell 1 percent, to $4.14 billion, notably declining for the sixth straight quarter. Analysts on average were expecting Kohl’s to report an adjusted profit of $1.19 per share and revenue of $4.13 billion, according to a survey by Thomson Reuters.

 

European stocks fall amid North-Korea conflict

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The North-Korean conflict is staining the stock markets. European stocks fell sharply across the board today as investors around the world piled cash into safe-haven assets amid increasingly dangerous rhetoric between North Korea and the United States. President Trump presented a statement warning North Korea that any threats to the United States would be met with “fires and fury.” Gold and Silver are up 1,26% and 2,84%respectively.On the other hand all major European Stock Indices ,with a few exceptions such as the ATHEX, are quoting a negative net change. The DAX is no different and as such is down 1,17%, two hours before close. After a pretty slow week, the DAX opened by climbing a little and reaching the 12226 point mark 30 minutes after opening. After reaching the intraday high, the DAX went crashing and is now down 1,17%.

Following a mostly higher beginning to the trading week on Monday, Wall Street got off to a somewhat weaker start yesterday, with the Dow Jones Industrial Average, a 26-point winner on the first session of the week, moving down to a 40-point loss in early dealings. With the economic calendar light and no new political headlines of note until late in the day, the focus was again on earnings, which continue to pour in for the second quarter. To be sure, most of the nation’s larger companies have reported already. Now, we are starting to hear from some smaller names, as well as results from a few retailers, which often have July ending periods. As has been the case almost uniformly, however, the bulls didn’t stay down for long, and as we ended the first half hour of trading, the early setback was pared, although the indexes remained a bit under water. That would change in the next half hour, as the Dow would make it back into the black, with the bulls hoping for a 10th straight record close. Meantime, the big item of note on the earnings calendar was yesterday afternoon’s pending quarterly release from Dow stock Walt Disney, which is noted below. Some retailers also were on the docket, as noted above. Indeed, with respect to the latter item, the retail reports made surprisingly good reading, with better-than-expected results from both Ralph Lauren and Michael Kors Holdings helping to turn things around as the morning wound down. In fact, as we approached the noon hour in New York, all three large-cap indexes were securely in the green, with the Dow seemingly on course for a 10th straight record close, with a mid-session gain of some 50 points. All told, corporate earnings have been up some 10% for the second quarter, which is well ahead of the 6% increase that has been forecast. Little wonder stocks are strong. The good news would continue into the first part of the afternoon, affirming that when the focus is on earnings, rather than politics and even the economy, this overbought stock market has continued to do well. And yesterday, the gains extended to the S&P 400, the mid-cap benchmark and the small-cap-dominated Russell 2000. Meantime, the gains increased in the first part of the afternoon, with the Dow’s intraday uptick reaching 60 points. But that would prove to be the high water mark for stocks, and as the afternoon moved along, the sellers entered the fray. However, there was little intensity to that pullback. The mid-afternoon selloff, albeit modest, did continue into the close, with the energy and basic materials sectors leading the way lower, with an assist from health care. Few groups showed any noteworthy strength, although recently soaring Apple Inc. shares did press ahead to an all-time high of just over $161. Still, while the Dow and the S&P 500 Index both set intraday peaks, each fell back below the neutral line in the final hour of trading–especially during the closing half hour. Also, losing stocks held a plurality on winning issues on the Big Board and the NASDAQ. The late selloff, meanwhile, was driven largely, it would seem, by President Trumps statement.The weakness then accelerated somewhat into the close, with the Dow at one time dropping by some 60 points. So, when all the numbers were added up, the blue chip composite was off by 33 points; the S&P 500 Index was lower by six points; and the NASDAQ’s deficit was 13 points, as more stocks fell than gained on the session. Then, after the close, Disney chimed in with a profit beat, but a shortfall on the revenue side, causing that stock to falter in after hours trading.

Walt Disney will stop providing new movies to Netflix starting in 2019 and launch its own streaming service as the world’s biggest entertainment company tries to capture digital viewers who are dumping traditional television. Walt Disney will launch two Netflix-like streaming services, one for sports and another for films and television shows. As a reaction to these news Disney is up 0,19% and Netflix is down 2,61%, as these move could be a predecessor for further pullbacks.

Office Depot‘s profits fell on weaker sales in the second quarter, missing analysts’ estimates. Second-quarter sales declined 9 % to $2.4 billion YoY, the Boca Raton-based office supply retailer said Wednesday. Same-store sales — those open at least a year — fell 6%, Office Depot said. Retail sales were $1.1 billion for the quarter compared with $1.2 billion a year ago. Office Depot had lower traffic, transaction counts and average order value, according to its regulatory filing. It saw lower sales in most categories, including ink and toner, computer and technology products, offset in part by cleaning and break-room products. Office Depot had previously said 2017 sales would be lower due to store closures. The company said it closed 31 stores during the quarter, ending with a total of 1,408. For 2017, 75 stores are scheduled to close.

The airlines of the Lufthansa Group welcomed 13.1 million passengers on board in July 2017. This shows an increase of 16.9% YoY. The available seat kilometers were up 12.4% over the previous year, at the same time, sales increased by 12.8%. The seat load factor improved accordingly, rising 0.3 percentage points to 86.3%, compared to July 2016. In total the airlines of the Lufthansa Group carried more than 73 million passengers this year until July. The overall seat load factor reached a historical record with 80.2 percent.

Todays Economic Calendar:

1. MBA Mortgage Applications
2. Productivity and Costs
3. Wholesale Trade
4. EIA Petroleum Status Report

Michael Kors Income drops 15%, stock is up 14% pre-market.

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The summer season seems to be affecting the German DAX. After a strong start in the afternoon and a slide-off in the afternoon, the Index reverted back to its previous close being off by 0,03%. If there can be a mention of a clear winning stock, REWE the German retail group would be it, being up 1,43% from its previous close.

The same kind of holiday boredom seems to have hit the Wall Street. Following a rather eventful week on Wall Street, as one month ended and another one began, with a succession of all-time highs being set amid some mixed economic data being issued, the latest five-day span began with prices initially headed somewhat higher. On point, the old week featured confirming evidence that the economy was still pressing ahead, if irregularly. Specifically, the reports showed a solid level of manufacturing growth, a slowing rate of non-manufacturing improvement, and a surprisingly strong employment report. Given that still largely positive backdrop, it is not all that surprising that stocks have been on the ascent. After all, with solid, but not inflationary, economic growth, a cooperative and cautious Fed, and strong earnings, the market backdrop is positive enough to keep the bull alive. On the other hand, multiples are rather stretched, so the margin for error is quite small. Accordingly, although stocks continue to head higher, the gains are not easily secured. And that was the case again yesterday morning, as the initial gain was pared rather quickly. But as has been the case this year, no serious selling took place. Thus, stocks again headed higher as the morning wound down, and the afternoon began. By midday, it looked as though another record in the Dow Jones Industrial Average would be set. The major beneficiaries yesterday were the consumer staples stocks, which performed nicely on the Dow. Slightly weaker performers included the energy stocks, which eased as oil prices fell, and some basic materials names, including recently weak Mosaic. On the other hand, some tech names strengthened, as the NASDAQ, with a mid-afternoon gain of 30 points again led the way. One big tech name doing well yesterday was Apple, which pushed up close to another all-time high. Holding the 30-stock Dow down, with a sharp loss on the day was United Technologies. That issue fell on news that it might be going after a major merger partner in Rockwell Collins. Meanwhile, stocks stayed irregularly higher as the afternoon wound down, but stayed in a tight band throughout the afternoon. As the final bell sounded, the major averages were all in the black, with the Dow’s 26-point gain securing that composite’s ninth straight record close. A four-point advance by the S&P 500 Index and a 32-point surge by the NASDAQ rounded out the session. Going forward, we will get inflation data later in the week along with earnings reports from some of the nation’s retail chains.

Michael Kors said Tuesday that its net income attributable to the company dropped 15 percent to $125.5 million, or 80 cents per share, from $147.1 million, or 83 cents a share, a year ago. Last year’s figure included one-time costs related to the acquisition of a Greater China licensee. Excluding that charge, Kors had earned 90 cents a share. While its profits fell, Tuesday’s results outpaced both the company’s and analysts’ expectations. According to Thomson Reuters, analysts on average were predicting Kors would earn 62 cents per share. That was also the midpoint of the company’s own forecast range. Total revenue for the first quarter came in at $952.4 million, again topping analysts’ estimates for sales of $918.6 million, according to Thomson Reuters. But this was another drop — by 3.6 percent — from last year. The drop in revenue wasn’t a surprise, Saunders commented, but it’s more of a “necessary evil” as Kors gets out of retailers that no longer fit the brand’s fresh strategy. “Reducing ubiquity comes with a price attached.” Michael Kors’ same-store sales dropped 5.9 percent during the period, coming in better than expected. Analysts surveyed by FactSet had predicted a decline of 9 percent. Shares of Michael Kors climbed more than 14 percent higher on the news in premarket hours.

The VW brand said it would offer buyers trading in an old diesel a discount on cars meeting the latest Euro 6 emissions standard, ranging from €2,000 to 10,000€ on its compact cars. And the carmaker proposed an additional discount of between 1,000€ and 2,380€ for those buying more environmentally friendly hybrid, all-electric or natural-gas-powered vehicles. VW was “acknowledging its share of responsibility for climate- and health-friendly mobility on German streets,” it said in a statement.

Ralph Lauren Corp reported better-than-expected quarterly profit and sales as the luxury apparel maker kept a tight leash on discounting and inventory, sending its shares up 5 percent in premarket trading. Ralph Lauren, like other U.S. apparel chains, has been struggling with weak sales due to sluggish spending on clothing and accessories and fierce competition from Amazon.com and fast-fashion retailers.  In a bid to turn its business around, the company has been pulling back inventory from wholesale partners, reducing sales in the off-price channel, engaging in fewer promotional periods, shuttering stores and exiting underperforming brands.  Ralph Lauren’s adjusted gross margins rose 210 basis points to 63.2 percent in the first quarter ended July 1, helped by a double-digit decline in costs.  The company also lowered its inventory levels by 31 percent from a year earlier.  The company’s net income was $59.5 million, or 72 cents per share, in the first quarter ended July 1, compared with a loss of $22.3 million, or 27 cents per share, a year earlier. Excluding items, the company earned $1.11 per share, while sales fell 13.2 percent to $1.35 billion in the quarter. Analysts on average were expecting adjusted earnings of 94 cents per share and revenue of $1.34 billion, according to Thomson Reuters I/B/E/S.

Todays Economic Calendar:

1. NFIB Small Business Optimism Index
2. Redbook
3. Jolts

 

German DAX generates losses on weak German economic data

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After opening at 12’303 the German DAX was able to rally up and peaked at the 12’325 point mark 4 minutes after opening. The joy was off short time, as after reaching the 12’325 point mark, the German DAX started tumbling down on news of weak German economic Data. 2 hours before close the German DAX is down 0,46% from its previous close. The notable winners/losers are Deutsche Telekom (up 1,41%) and Fresenius Medical Care AG & Co KGaA (down 1,49%). After the German healthcare company released solid earning end of July, the emerging news of Fresenius acquiring NXStage seem to shake up investors.

In the States it continues to be mostly about earnings these days, as the dog days of August continue, with favorable reviews from the investment community, interspersed with a few notable setbacks among individual stocks, being the rule. That was the case again on Friday, as generally solid profit reports helped lift the Dow Jones Industrial Average further into record territory, with that index going well past 22,000 in a modest buying campaign. A few headline movers, such as Weight Watchers, benefiting from an earnings beat, paved the way for the early gain that carried the market solidly higher in the morning. As we moved into the early part of the afternoon, the Dow was ahead by 40 points, while the other large and small-cap indexes were up modestly, as well, with gaining stocks retaining a small lead on declining issues. All told, the session was a positive one to that point, even though there were a few headline makers on the downside, such as Fluor, which while posting better-than-forecast second-quarter earnings, still weighed in with lower orders and backlogs, and much-reduced guidance for the 12 months. The stock tumbled to a 52-week low, in response. The equity market remained range-bound over the final few hours of trading, as investors further digested the benign jobs report and the likelihood that the Fed will not be unduly influenced by it. Another generally constructive earnings day proved supportive, as well. So, all of the averages stayed on the plus side of the ledger, but the gains were far from formidable. As to stocks on the Dow, the financials did better, while most other issues on that composite moved little.  The lone negative on the day was a rise in bond yields on the better jobs data, with the 10-yesar Treasury note climbing to a yield of 2.27%. The market drifted until near the close, when there was a late spurt of additional buying, which helped cap off a week of generally higher prices. At the close, the Dow was ahead 67 points; the S&P 500 was better by five points; and the NASDAQ, on selective strength in technology, was in the black by 11 points. Meanwhile, there were more gaining groups than declining sectors, while on the Big Board, the earlier advantage held by advancing issues was retained into the close, with rising stocks holding about a four-to-three lead. Next week will be a lighter one for economic news, while earnings releases will start to slow down.

Sprint Corp.’s resumed talks about a potential merger with T-Mobile US Inc., being held at the same time as discussions with cable companies, shows the lengths billionaire Masayoshi Son is taking to build scale for a wireless carrier facing increasing competition in the U.S. The two wireless operators restarted discussions after Sprint’s exclusive negotiating period with Comcast Corp. and Charter Communications Inc. expired at the end of July, according to people familiar with the situation who asked not to be identified because the information is private. Sprint shares rose as much as 2.9 percent to $8.95 in early trading in New York Monday.

Todays Economic Calendar:

1. Gallup US Consumer Spending Measure
2. Labor Market Conditions Index
3. TD Ameritrade IMX
4. Consumer Credit