Sunday, December 9, 2018

IMA S.p.A. : chart update.

With a weekly chart, we can get an overview of the stock.
We can notice the break of the uptrend (mid/long-term): see the dotted line. Now, we are at the test of the 61.80% FIBO level that it is also the previous resistance (see the rectangle). The last one could represent a new support (maybe, let's look at the next trading sessions). 
It is interesting also to see the volatility exhaust, marked by the BB: the stock is on the lower side of the band and it could be a rebound (see the previous ones and the yellow circled area, from overbought to oversold and vice-versa, of the RSI). However, it is too early to speak about a trend change for the above reasons. It needs other confirmations. According to me, at now, it is only a break in the downtrend.

Chart from

It is premature to buy on the basis of technical conditions (see the MOMENTUM, MACD and EMA bundle 20-50-100) although it can be a good price on the basis of fundamental analysis (see the previous article,, "The price still could go down for the reason that the trend is clearly bearish. However, the current market price is beginning to be interesting.").

Chart from

The view is the same if we use a smaller time frame, like a daily chart: see the following image. 

Chart from

Sunday, November 18, 2018

IMA S.p.A. : relative valuation (historical market multiples).

With regard to the valuation, it is interesting to consider also its historical market multiples.
However, it needs to mark the following considerations :

  • Every time period has its own market multiples, due to the macroeconomics factors and to the economic cycle ; in this way, the comparison term loses its value ; 
  • The market anticipates the events and prices the expectations ; for this reason, the past valuations had always incorporated the whole scenarios ; the valuations and future market multiples are more important ; 

Here, we have the historical market multiple P/S. I used this market multiple with the aim to reduce the bias : the results at the top of the income statement are less influenced by several factors. 
We can notice that the last multiples are higher than the past multiples but we must consider the previous paragraphs, of course.
Then, the market valuation tends to assign higher multiples to a growing company, over time, like IMA S.p.A.
In this way, it is advisable to consider also a median of the multiple or a weighted average (the past prices are less important than the current prices). 
The expected market multiples (the yellow columnes) are substancially lower than the mean, median and weighted average (black and dashed lines in the chart). The gap is not so wide (that confirms the previous valuation). 

Monday, November 5, 2018

IMA S.p.A. : relative valuation.

Here we have a relative valuation of IMA S.p.A. It operates in the industrial machinery and equipment, like the peers of the sample. In particular, its business is focused on the packaging industry, through the segment lines : tea, food and other ; pharmaceutical sector. 
In order to select the peers, I considered the following requirements : similar business and geographical area and similar size (revenues or market cap as the proxy of the size), having regard to the differences, like the profitability, the growth, the risk and the financial structure (in this way, I adjusted the market multiples, appropriately or I considered the difference as a discount or as a premium in the valuation ; about the financial position, the differences are very small).
I used a leading market multiple (expected results in the year 2018, 2019, 2020, data source : I also considered the management assumptions, expectations and business plans.

Let's look at the market multiples, in the following table.

It needs to consider that about the equity story and size GIMA TT ("recent history") seems to be a a distortion compared to the other firms. It can be interesting, regarding its similarity to IMA, however, it is more advisable to exclude it from the peers group.
Then, we can calculate the mean and the median, respectively :

EV/EBITDA (10.08 | 9.44) ; P/S (1.60 | 1,70) ; P/E (18,45 | 17)

At a glance, we can notice the discount of IMA S.p.A, apart price to earnings.

Secondly, it is more useful to link the market multiples to the fundamental variables (profitability and growth, above all). In this way, see the next table.

We can calulate the mean and median, excluding GIMA TT again and IMA, for obvious reasons.

EBITDA margin (15.72% | 18.12%) ; EBIT margin (12.55% | 15.03%) ; NI margin (8.71% | 10.40%)

CAGR EBITDA (8.94% | 7.58%) ; CAGR revenues (6.66% | 5.94%) ; CAGR NI (12,85% | 12.74%)

Substantially, IMA marginality is slighy lower compared to the sector profitability ; however, the growth is rather higher.

Finally, let's put the variables together, thanks to a regression line.

Market Multiples (Y) vs Profitability (X)
Market Multiples (Y) vs Growth (X)

In the two charts, the intercept is not considered because it is not important, in a statistical point of view (statistical significance). However, the angular coefficient is good. The R-squared is excellent, in the following order (from the lowest to the highest) : P/E regression, EV/EBITDA regression and P/S regression.

So, we can determine the fair value of IMA and its premium or discount. In other words, its intrinsic market multiple.

FV (I) = P/E = 181,61*7,30% = 13,25                       
premium : +36,7%

FV (II) = EV/EBITDA = 60,513*15,65% = 9,47     
discount : -7,82%

FV (III) = P/S = 12,88*12,85% = 1,65
discount : -20,24%

FV (IV) = P/E = 120,66*17,54% = 21,16                 
discount : -14,4%

FV (V) = EV/EBITDA = 100,75*12,15% = 12,24   
discount : -28,7%

FV (VI) = P/S = 23,794*7,14% = 1,7                       
discount : -22,3%

Finally, we can conclude than the discount is higher (as I said) with the growth. With the margins, the discount is smaller and we have a premium with the P/E regression. At a glance, IMA is traded at a slighty lower market price compared to its hypothetical fair value. Of course, it does not represent a safety margin, at the moment. The price still could go down for the reason that the trend is clearly bearish. However, the current market price is beginning to be interesting.

Saturday, October 20, 2018

Servizi Italia S.p.A. : plain DCF and target price.

In the following image, we have an example of DCF valuation. 
The firm is Servizi Italia S.p.A. The valuation date was August 18, 2016 and the target was 6.06 EURO (plus a range with regard to the fair value, +/-5%). The target was achieved on November 23, 2017 (in this way, the holding period was about one year and 3 months or 462 days, exactly). For this purpose, consult the following link and see the second one image : 
The upside was about +73%, with regard to the current market price at the time of the coverage :
[6.06 - 3.50] / 3.50 = + 73.14 %

Let's look at the assumptions of the model :
  1. The revenues were the proxy of the model : it means that all the variables depended directly on sales as a percentage.
  2. For the estimation of the revenues of the next three years (2016-2017-2018), I assumed a CAGR of about 3% (the business of the firm is quite steady) ; I looked also at the trend of the past three years. 
  3. For the other items (D&A, NFC, net income, NWC, capex), as I said previously, I assumed a percentage of the revenues : 20%, 1.5%, 5%, 0.5%, 20%. I looked also at the past trend and I considered the evolution of the sector and of the firm, in the next years (for the formula, consult the notes). 
  4. For the estimation of the ERP and tax rate, I used the data source of A. Damodaran (ITA).
  5. For the risk-free rate, I assumed the weighted average yield of BTP 10 years.
  6. For the estimation of the beta, I used the regression between FTSE-mib and Servizi Italia with a time frame of 5 years and with monthly returns (I added a spread of 0.10 to consider the additional risk, due to the reduced liquidity of the stock). 
  7. For the cost of debt and for the financial structure, see the notes.
  8. For the growth rate (g), I assumed a conservative rate of 1% (see the litterature). 
  9. With regard to the calculation of the EV and of the fair value, see the following formula and consult the notes:

Sunday, October 14, 2018

INFINEON TECHNOLOGIES : chart framework.

From a uptrend beginned in the first half of the year 2013, the stock showed a correction in the year 2018. The chart framework is highlighted by the two trendlines (we speak about a long-term period), in particular by the break of the second one (see the gray circled area). 
The trend change is also marked by the crossing of the two EMAs (fast, 100 periods and slow, 200 periods). The slope of the EMAs shows the market direction. 
If we look at the FIBO retracements, we got another confirmation of that picture.
There is the break of the first FIBO level (23.60%, at 20.31 EURO). Then, we are at the test of the second FIBO level (38.20%, at 17.22 EURO). See the yellow circled areas. 

Chart from

The previous chart shows the graphic framework at a glance. We can reduce the objective with the aim to closely analyze the situation, in this way. 
The following chart shows an excess market. We can notice it trough the excess volatility from the BBs, the crossing of the two lines of the MACD (MACD and signal line) and the crossing of the RSI line, from overbought to a hypothetical oversold. How long this trend change/excess market will last ? It needs to monitor the next trading sessions to get a response (see also the test of the above named FIBO level). 

Chart from

Finally, with a monthly time frame, we come to the same conclusions : crossing of the zero line from above to below (MOM) and crossing of the level 80 (MFI) ; see the yellow ellipses, in this way.
The structure of the PSAR also shows the trend change : in the bullish trend the slope is very different from the last bearish trend. 
As I said previously, it needs to look at the next trading sessions to understand if the current bearish trend is still valid or not. 

Chart from

Of course, there is no fundamental consideration that would clearly complement the analysis, especially with regard to a long-term perspective. 

Sunday, August 19, 2018

EUR/CHF : chart framework.

From a bullish trend, the currency cross began a bearish trend (May 2018). The parallel channel was broken and then also the bullish TL (long and short-term). We can notice a volatility exhaust (see the BB) highlighted  by the overbought and by the oversold of the RSI (see the yellow ellipses). 
The current bearish trend is still valid : however, if we look at the following chart, there is a rebound from the low at 1.127. As I said, it represents just an exhaust of the excess market. To consider it a change of trend, it needs other confirmations in the following trading sessions and it needs a test of area 1.145 (the previous support). 

Chart from

Let's look at the FIBO retracements : the main references are 1.06 (100%), 1.13 (50%) and the previous low, 1.14 (38.20%), 1.16 (23.60%), 1.20 (0%). The mentioned references are important to set a trading strategy, bearish or bullish. See the following chart.

Chart from

If we look closely, we have two options :

  1. We can anticipate the market moves (there is a higher risk but with a higher expected return due to our prior involvement to the price rebound) ; in other words, we right away consider the overcoming of the MOMENTUM above the zero line, the intersection of the MACD and of the signal line and the test of the support at 1.145 ;
  2. We don't anticipate the market moves (the risk is lower as the expected return) ; in other words, we wait for the mentioned technical signals and we wait for other confirmations in the following trading sessions (see the red arrows). 

Chart from

Finally, at a glance, with a weekly timeframe, we can notice that : the EMA bundle (20, 30, 50) shows the direction (lateral trend, uptrend, bearish trend), see also the intersection of the light blue line, of the red line and of the yellow line (red ellipses) ; the structure of the Parabolic SAR shows the market direction, too. 

Chart from

Saturday, July 28, 2018

EUR/GBP : chart framework.

From a bullish trend (beginning in the end of the year 2016 and lasted until september, in the year 2018), the cross started a lateral trend. This is showed by the following chart where the uptrend is highlighted by the trendline and by the support lines and by the resistance lines (it means the main references : 0,83 and 0.93 ; 0.86 and 0.89). 

Chart from

We get the same view if we use a different time frame, for example a month. The monthly time frame shows the chart framework in a better way for the reason that it provides a general overview. 
We can notice the same references and then at now we can notice that the price is testing the resistance area at about 0.89. This price level is important because it represents also both the closing and the opening price of the previous green candle and of the previous red candle (see the circled area) : there was a price retracement and a volatility exhaust ; the green candle represented a long upper shadow candle ; in other words, at the end, the sellers prevailed over the buyers. 
The BB are emblematic, in this way : see the median line compared to the price and see the light blue lines compared to the price. 

Chart from

We have a confirmation of the trade change (bearish - bullish - lateral trend) also by the indications provided by MACD : we can notice the intersection of the yellow and red line (MACD and signal line) at the time of the overcoming of the zero line (see the light blue histograms), from the bottom upwards ; symmetrically, from the trend change bullish-lateral, from the top downwards. 

Chart from

Lastly, the EMA bundle shows the market direction : the following chart shows the slope of the EMA bundle where the trend is bullish and it shows the lack of slope of the EMA bundle where the trend is lateral ; then, the distance between the exponential moving averages is more marked for obvious reasons, in the uptrend (in this way, the EMA bundle provides a useful indication). 
The RSI shows the overbought and the oversold, in the levels of 70 and 30, respectively, as usual : the passageway through the two areas marks the change of trend in the chart, inevitably.
Of course, as I said previously, it needs to pay attention to the test of the resistance area at about 0.89.

Chart from

Sunday, July 1, 2018

"Average down" strategy : a path to disaster.

The strategy describes the process of buying additional shares at lower prices compared to the original purchase price. The aim is the following : it brings the average price that we've paid for all the shares down. It can be a discount but just apparently. In this way, in my opinion, that is the only reason that drives the investor to do it. 
It a somewhat obsolete technique and personally, I should not consider it a strategy. Against this background, it is just a state of mind and a mechanical process, without logic. 
Of course, the disadvantages are greater than the benefits. The reasons are the following :
  • With repeated purchases of the same financial asset, we increase the risk of the portfolio : there is an excessive exposure of the portfolio, focused on the same stock. This is in contrast with a proper diversification principle ;
  • The process involves the purchase of additional shares as the stock price goes down ; in this way, we are purchasing an asset for which the trend is bearish, clearly. A trader should follow the trend. We should increase the exposure with the uptrend and with strong fundamentals. At least, we should buy with clear reversal signals and respecting a logical investment plan ;
  • At the end of the process, the investor obtained the following result : his portfolio is composed by a huge amount of shares of the same asset and if he reduced the loss (due to the lower average purchase price), on the other, his recovery rate (it means the percentage upside required to get the feed capital) is always higher in absolute terms than the current loss. This is especially true the more the final purchase price is lower than the original purchase price. In other words, the more the stock performance worsened. The following table explains the situation. 

We are assuming that the trend is bearish, of course. There are neither broker commissions nor financial fees, for simplicity. Then, the multiple purchases are of a same amount. 
With the multiple purchases, we bring the average price down, compared to the initial price and with regard to the situation without subsequent purchases. However, we can notice that the recovery rate is always higher than the loss percentage (in absolute value). Obviously, the gap is higher without subsequent purchases.
Nevertheless, it is reductive to focus on it : we should necessarily consider the higher exposure and risk. Then, with a proper investment plan, we should have cutted the losses and the purchase price at 0,50 EUR would have never exist (and the same for the lower prices). With the respect of the stop loss and of the target price, we really reduce the risk and we really build a proper trading strategy. 

The chart below shows what I said. Gain/loss % is better than Stock performance (equal to the gain/loss % without multiple purchases). Recovery rate (**) > Recovery rate (*). Recovery rate (**) > ABS (Stock performance) and Recovery rate (*) > ABS (Gain/loss %). 

Finally, I don't recommend the "average down" for the reasons above (apart from some exceptions, like change of trend or with other reversal signals). Instead, I highly recommend the respect of the risk management, of the SL&TP and in general of a suitable trading/investment plan.

Saturday, May 5, 2018

Markowitz efficient frontier : backtesting.

The aim of the analysis is to build the efficient frontier that compares the average return (y) to the risk or standard deviation (x) of the top 100 Italian stocks (the market cap is the proxy of the size). Secondly, I will build one hundred portfolios (each portfolio is composed by one stock and each stock has the same weight, for simplicity), by decreasing order of best risk-reward ratio.
Thirdly, I will test the following assumption : the order of best risk-reward ratio should be the same also for the future performances (at least, substantially). 
In this way, the third step will be the backtesting that will cover a medium/long time frame, for obvious reasons and it will be a continuous updating.

The time frame of the past returns is 5 years : it means sixty returns (monthly returns), from April 30, 2013 to April 30, 2018. The source of the data is the following (historical data) :
The source of the stock screener is the following : Stock Screener -

About the data, I converted the monthly returns into annual returns, for greater significance. 

Average Return (annual) = Average Return (monthly) * 12
Standard Deviation (annual) = SQRT [(Standard Deviation (monthly) )^2*12]

So, I adjusted the return for the risk (Standard Deviation), through the following formula : 

Risk Adjusted Return = Average Return / Standard Deviation

Finally, I ranked the stocks, according to the abovementioned ratio (best risk-reward ratio). 
For simplicity, I built ten groups, always respecting the previous order. 
According to the portofolio theory (please consult the links : Markowitz efficient frontier ; images), the best stocks are those with the best ratio : they offers a greater return, given a risk rate or they offers a lower risk, given a return rate. Then, we have the following assumption : the expected returns and the expected risks are based on the past data. Of course, this is a limit and the aim of the analysis is also to implement a backtesting and to test the assumption. 

The following chart shows the efficient frontier. 

The following tables show the ten groups, by decreasing order of best risk-reward ratio (--> ranking).

In the future, I will test the assumption, as mentioned. The stocks with good past performance (with given risk) should outperform the others. 

Sunday, April 29, 2018

The passive management.

The passive management is a style of investing associated with mutual and exchange-traded funds (ETF) where an investor aims to mirror a market index. 
We can build the passive strategy through the following steps : 
  1. Choice of a panel of funds ;
  2. Ranking of the funds ; 
  3. Choice of the funds in the panel with the best ranking.
The panel is chosen in accordance with particular requirements (filter by class, macrocategory, assets, country, risk, currencies and so on ; it depends on the investor's preferences : see the following link ANIMA sgr products). 

For example, the aim of the analysis is to rank the funds of the system "Anima Italia" ; the fund ISIN codes are respectively : IT0001040051, IT0005158784, IT0004896541. 
The asset allocation is composed by equities, largely ; the currency is EUR ; the equity country is Italy, substantially : for further information, please consult the portfolio breakdown and the fund profile

The site provides a rating and a benchmark for each fund ; however, we can build our benchmark and our rating. For the benchmark, we choose the FTSE-mib index because it can be a good comparative parameter, given the structure of the funds. For the ranking, we use the classic portfolio performance indicators. In this way, we import the NAVs on a excel sheet and then we calculate the daily returns. 
The time frame is from February 22, 2016 to date. I converted the daily returns into annual returns, for greater significance. 

Historical data (hidden cells for space requirements) : data source ANIMA sgr.

The same for the FTSE-mib index, aka benchmark. 

Historical data : data source

In the following chart, we can see the performance of each fund compared to the benchmark performance. 

Now, we can calculate the performance indicators :

  • The Sharp's Measure : the ratio uses standard deviation to measure a fund's risk-adjusted returns ; it quantifies a fund's return in excess of our proxy for a risk-free investment. It is equals to : 
(R - Rf) / Std Dev
R = average return of the fund ; Std Dev = standard deviation of the fund
Rf = risk-free rate (I assume the average return of the BTP 10Y ITA)

  • The Treynor's Measure : the ratio is equal to the previous one ; however, the risk is adjusted for the beta. The index is equal to : 
(R - Rf) / Beta
Beta = beta of the fund

  • The Jensen's Alpha : the index is a risk-adjusted measure that compares the average return of a fund to the estimated return of the Capital Asset Pricing Model (CAPM). The formula is equal to : 
R - [Rf  +  Beta*(Rm - Rf)]
Rm = average return of the benchmark (or market index)

  • The M Squared Measure : it is a risk-adjusted measure ; it explains the surplus return of the fund compared to the risk-free investment, considering that the variability of the fund is equal to the variability of the benchmark. The formula is :
(Sharp's Measure)*(Std Devm) + Rf
Std Devm = standard deviation of the benchmark (or market index)

  • The T Squared Measure : the structure is the same compared to the previous one ; the difference is the risk, systematic risk or beta ; substantially, it calcualtes the surplus return compared to the risk-free rate, under the assumption that the systematic risk of the fund is equal to the systematic risk of the market. The formula is :
[(1 / Beta)*(R - Rf) - (Rm - Rf)]

  • The Sortino Index : rather than considering premiums regarding the risk-free asset, the index explains the surplus return with a minimum accettable return ; then, about the risk, it considers a minimum accettable risk, aka down side risk (the variability not appreciated by the investor ; we calculate a semi-standard deviation, only the negative deviations from the mean). The ratio is equal to : 
(R - Minimum Return) / Down Side Risk
For semplicity, we consider the minimum return equal to the risk-free return

Finally, the higher the ratios, the better fund past performance (we must note that the future performance is not linked to the past performance ; however, it is a good beginning). 
In this way, we can calculate the ratios and rank the three funds (see the following table). 

The ranking is :

1) Fund ISIN code IT0004896541 (the best) ;
2) Fund ISIN code IT0001040051 ;
3) Fund ISIN code IT0005158784 (the worst). 

Monday, April 9, 2018

The "magnitude" of the liquidity.

In the building of a trading strategy, the liquidity is a crucial variable. 
Secondly, the liquidity can be both a positive and a negative factor. 
Of course, we have two market scenarios :
  1. An illiquid market ;
  2. A liquid market. 
In the first one, from the negative point of view, the price of a stock hardly represents the intrinsic value : in other words, the stock price will reflect poorly the underlying drivers of the fundamental analysis. The same is also for the technical analysis. The stock price doesn't correctly respond to the graphic signals. This bias can last for a long time and sometimes the gap cannot be solved. 
In this way, the market context is artificial. 
From the other point of view, we can use that fault to our advantage. That means that it needs to follow the next steps of the market maker. If on one hand, the market maker (aka MM) easily moves the price for lack of liquidity, on the other, we must not suffer this but we must make ourselves part of it. 

In the second scenario, there is not the abovementioned bias because the market price responds quickly to the underlying factors (technical or fundamental). However, we cannot use to our advantage the previous fault. The market context is normal. 

Finally, the first scenario is difficult to manage than the second one because the illiquid market is difficult to interpret. Neverherless, if we are be able to follow the MM's moves, this will lead to higher profits for the reason that the stock price is much more influential to price changes in the face of low traded volume, due to the market structure.   

After this introduction, it is useful to indentify the two scenarios (1. and 2.) and above all the magnitude of the price influenceability. 

The following methodology shows that. The steps are : 

  1. Building the daily returns (%) for a time period (in general, one year is appropriate) ;
  2. Building the daily trading volumes ;
  3. Pondering the first one with the second one ; in other words, we consider the ratios (the daily returns are as absolute returns ; we are interested in the amplifying effect and we are not interested in the direction of the effect). The formula is :

[Absolute Price Change %] / [Trading Volume]

The Absolute Price Change % is equal to ABS(Price Change %)

Finally, we calculate an average value of the previous ratio (=AVERAGE[Absolute Price Change %] / [Trading Volume]). Then, we multiply the average ratio for different and hypothetical volume levels. In this way, we can get an idea of the influence of volume on stock price (-> we get the hypotethical price changes % for given volumes). 

Of course, this represents the market structure and it should not be considered as a correct value a priori. There are many variables that can change the survey data and the past trend is not like the future trend : the trading book and the market environment are some factors. 

In the following chart, we have an example of illiquid market. The stock is COVER 50 S.p.A., a classic example of illiquid stock. The daily volumes are low and we can notice that it needs just a small volume to get a considerable price change (for a trading volume of 1K we have a price change % of 3.48%). 

Daily Returns, from April 10, 2017 to April 6, 2018, hidden cells
for space requirements, data source : Yahoo Finance

We can also analyse the abovementioned effect through a regression line.

In the following charts we have an example of liquid market, the stock is UNICREDIT S.p.A. 
The daily volumes are huge and in this way it needs a huge volume to get a substantial price change (indeed, for a trading volume of 1K we have a price change % of 7.85189E-07). 
For obvious reasons, the slope of the regression line is lower than the previous one. 

Daily Returns, from April 10, 2017 to April 6, 2018, hidden cells
for space requirements, data source : Yahoo Finance

Sunday, April 1, 2018

Estimate of the cost of debt.

The calculation of the firm's cost of debt is an important factor. Then, it has a direct application in various areas ; in particular, it is useful : 
  • to build a DCF model, in order to value a company (it is a variable to estimate the WACC) ;
  • to adjust the market multiples (higher the cost of debt, lower the market multiple and viceversa) ;
  • to understand the risk of a business and the debt sustenaibility (in other words, the cost of debt is the proxy of the financial structure) ; 
  • to value the risk of a stock, indirectly.
And on that note, we can analyze the main calculation methods. 

I. The cost of debt : the accounting method.

The accounting method is based on balance sheet data. It is easy to estimate but it is also quite prone to errors. It means that if on one hand, the data are readly available, on the other the result is purely static because it doens't consider the perspective scenarios. Indeed, it is advisable to integrate the method with a perspective business plan, focused on the financial structure of the target firm. 

According to this method, the cost of debt is equal to the financial expenses divided by the financial debt. There are two options : the first one considers the gross debt minus the cash and cash equivalents (it means that the debt can be paid by the cash ; this hypothesis is not always true) ; the second one considers the gross debt and the interest expenses (this hypothesis is more prudential). 

Here we have an example ; the company is Amplifon S.p.A. We can notice the two options. The accounting data are the fiscal years 2017 and 2016. 
For further info, please consult the following links : 

As shown in the table, the cost of debt is equal to 7,41% if we consider the net debt and it is equal to 4,63% if we consider the gross debt. An important note : the interest expenses are divided by the average debt with the aim to make comparable the two quantities, the item of the income statement ("flow quantity") and the item of the balance sheet ("stock quantity"). 

Another option of the accounting method is the following : we can also consider an average figure of the cost of debt on several years (3-5 years). In the same way, we can build a perspective table with the estimated financial debt and interest expenses (the next 3-5 years at the place of the past ones). 

II. The cost of debt : the relation between the interest coverage ratio and ratings (the fundamental analysis drivers).

We can link the interest coverage ratio (= EBIT/net financial expenses) to the ratings of a sample. 
For example, the professor A. Damodaran (see the link,--> Ratings, Spreads and Interest Coverage Ratios, has built a sample with the rated companies in United States. There are two tables : for large, for smaller and riskier companies (the proxy of the size is the market cap). With the current exchange rate and with the current m. cap, Amplifon belongs to the second group ( 

Data source : Damodaran Online

The cost of debt is equal to :

Risk-free rate (Rf) + Default Spread (DS)

For Amplifon the DS is equal to 0.90% (the EBIT interest coverage ratio is 7.76 and the market cap is about $4 billion). For the Risk-free rate (Rf), we can use the annual return of the 10-year T-bond (see the link ; data source Damodaran Online). For the year 2017, it is equal to 2.80%. In this way, the cost of debt for Amplifon is :

2.80% + 0.90% = 3.70%

As I said, the sample consists of US companies. For a more appropriate sample, of course, it is advisable to use European companies and rate of returns of government bonds, similarly. 

Finally, we must remember that the spread that we add to a base rate can be determined by other fundamental ratios (the interest coverage ratio is just one of the drivers). In this way, the discussed methodology is a part of the framework based on the fundamental analysis. 

III. The cost of debt : the listed bonds.

The last method is among the most reliable and the easiest to apply methods. If we have a firm with listed bonds, the cost of debt is equal to the rate of return of the mentioned bonds (-->yield to maturity, YTM). Alternatively, we can take as a benchmark a panel of similar listed bonds.

For Amplifon, we can consider the bond listed on the Luxembourg Stock Exchange (LuxSE).
See the following link :

Sunday, February 4, 2018

Enel S.p.A. : chart update.

Here we have the chart update of Enel S.p.A. : the previous bullish trend has been confirmed ; indeed, the tops at 4.50 EUR and the top at 4.87 EUR are still valid (the same also for the dashed line, in the medium/long term) ; the pattern recognition (Dark Cloud Cover) has confirmed the change of the uptrend but strictly limited to the short-term. 
In this way, the last view was spot-on (for further info, please see the link In the following charts, I propose the updated analysis with the previous levels. 

Chart from
Chart from

Now, let's look at the chart framework of the current situation. We must pay attention to the levels identified by the yellow circles (see also the FIBO retracements) : from the top to the bottom, 5.60, 4.80, 4.50, 3.40, 2.00. This is an overview to set a bullish or a bearish trading strategy, of course. 

Chart from

We can notice a break in the previous parallel channel. This means that it is a first alert : it represents a price correction in the uptrend (even more so with a break of the support at about 5.00 EUR and then with a break of the top/FIBO level at about 4.80 EUR). The chart shows a volatility excess with the BBs indicator : that can be a rebound of the stock (for example, see the first red circle) or a confirmation of the abovementioned correction. The crossing of the EMA 50 and EMA 100 fits in this view. Therefore, the next trading sessions will be crucial in order to understand the market direction. 

Chart from

If we extend the timeframe, the chart framework is very clear. Here we have a monthly timeframe : the price levels are those already mentioned. 

Chart from