Archive for the ‘XTR’ category



We introduce a new numeric ranking screen for the XTR 100 stocks and sectors. The screen is based on three broad categories of market capitalization viz. small cap, mid cap and large cap. We have illustrated the capitalization categories with the weekly and monthly price performance in the annexure. We have already categorized market screens in broad indices, sectors and in individual stock price performance. Now the capitalization screen allows us to filter and rank stocks based on their price performance, capitalization and economic sector.

For example, the large cap outperformance comes out clearly from this screen. The large cap components have fallen the least followed by small and mid cap. Among the large capitalization category (LC), ALRO (ALR) is the top performer for the month and the week. This is a positive alert considering broad markets have fallen in August. The material major has delivered a net relative return of 7% compared to all other Indices. This outperformance is owing to its late economic characteristic. Out of 20 positive performers of August, more than half came from the late economic sector. The LE components also screened out as outperformers in the mid cap category with TRANSGAZ, OIL TERMINAL and MECHEL as the only three positive august performers.

Till the time weekly performance is not matched by monthly performance the signal remains week. Small cap category August top performers were LAFARGE AGREGATE SI BETOANE (AGEM) at positive 16.92% for the month, energy component CONPET (COTE) and DUCTIL. These were the only three stocks which were positive both on weekly and monthly time frames.

Another interesting aspect of the current screens is how it can illustrate inter sector performance. EFO and TUFE are two discretionary tourism majors. THR MAREA NEAGRA (EFO) is a small capitalization company and it’s performance was opposite to it’s Discretionary peer TURISM FELIX (TUFE), which was the worst performing mid cap company for the month. Though small cap companies might be prone to volatility, such a clear performance extreme suggests EFO is indeed a better sector peer compared to TUFE. EFO is a part of XTR 30. On sector leaders, SIF MOLDOVA (SIF2) topped the rankings, with a positive performance of 5.26%. What happened starting Monday (01 sep 2008), when SIFs moved up was just a follow up on SIF2 previous week outperformance signal.

Despite the good gains registered by individual stocks the broad market ended the week lower along with the other Indices. BETFI was the top performer for this week with the least drop at 1.50%. Though XTR 21 does not include EFO and SIFs, it still managed to be the third best performer of the week with a marginal loss at 2.82%. Among the underperformers was the Blue Chip Index BET with a loss of 4.67%. XTR 21 is still the top index performer year to date.

Enjoy the latest XTR INDICES.010908


XTR.INDICES is our analytics product, which creates and manages Romanian market indices like XTR 21, XTR 100 and XTR 30 (Free Float). We also run models based on breadth indicators (Advance Decline ratio) and statistical parameters (correlations, betas, volatilities, top price changes, 200 day moving average etc.) XTR 21 - THE BLUE CHIP INDEX. REUTERS RICS COVERED.TRPS.BX, VNCA.BX, AMSL.BX, PEXI.BX, BATR.BX, ARTM.BX, COMI.BX, PTRI.BX, BRDX.BX, BRKU.BX, ARTM.BX, SNOS.BX, ARSB.BX, ALRO.BX, AZOM.BX, OTSP.BX, ALUM.BX, MOPN.BX, TSEL.BX, TGNM.BX XTR 100 - BROAD MARKET INDEX. XTR 30 - FREE FLOAT INDEX. XTR – EE (XTR EARLY ECONOMIC INDEX), XTR – ME (MID ECONOMIC SECTOR), XTR – LE (LATE ECONOMIC SECTOR)



Recession proof stockpicking

Attractive valuations should lead to price performance. This statement may be partially true in secular bull markets. But when markets fall for more than a year, we need more than attractive valuations to recession proof our investments. As good valuations necessarily don’t outperform and even if they do, there is no fast retribution. Things take more time in slowdowns. So how to pick stocks that can deliver in tough times?

In XTR INDICES, we lay down a complete step by step process to pick up the top picks. First and foremost, if a stock figures in the XTR 21, it has gone through a serious filtering on statistical, fundamental and sectoral aspects. If a stock is there, it has already been filtered once. Second, if the same stock figures in the free float index XTR 30, it passes through the tough tradability criterion. Third, we give you the late economic filter. Any stock from the materials, energy, staples, utilities, chemicals and Pharma suggest more insulation to tougher times. And even if globally we are witnessing pauses in the OIL upmove ( read the latest WAVES.OIL), the energy boom is far from over and Energy and Metals still have a few years of upside left. Fourth, if you still want to filter your stock shortlist a bit more, run the classic price and fundamental screens and you can rest assured that your final results will definitely conserve capital, if not make you rich. And the way we see markets evolving over the next two quarters, we see more of a profitable than a mere capital conservation strategy here.

We ran the steps for you and came with the following stocks AMO, AZO, VRANCART, ALU, PTR. If you add to them the Energy Major SNP and utility majors TGN and TEL, you have an eight stock portfolio that should weather all your recession storms for the next two quarters. If you take out TEL, all the rest have an average P/E multiple of around 12. All the respective stocks are from Late Economic Sector and are present in XTR 21. And half of them also pass the tough free float criterion of the XTR 30 Index. Now what’s left is conviction that such extreme filtering has more chances of success than failure.

The last week’s XTR INDICES performance highlights the XTR recession filtering yet again. XTR 21 was top Mid Cap performer at 10%. XTR 30 components topped the Small Cap category. On a month over month basis XTR 21 shined again with a 12% relative performance over the universe components. Our flagship Index XTR 21 is back near neutral territory for the year with relative gains of more than 50% above BETFI (the financial sector Index). COMI, TEL and COS breached the 10% performance screen for XTR 21. TEL also figured in the utility sector screen along with COVG and SCTO utility components. ATPA topped the discretionary sector. ATB topped Pharma sector screen. CEON, COS and AMO topped the materials screen. ARS, COMI, COBS and EPT topped the Industrials. PRAE was the staple outperformer. Another interesting and profitable week for recession proof stocks.

Enjoy the latest XTR INDICES


XTR.INDICES is our analytics product, which creates and manages Romanian market indices like XTR 21, XTR 100 and XTR 30 (Free Float). We also run models based on breadth indicators (Advance Decline ratio) and statistical parameters (correlations, betas, volatilities, top price changes, 200 day moving average etc.) XTR 21 - THE BLUE CHIP INDEX. REUTERS RICS COVERED.TRPS.BX, VNCA.BX, AMSL.BX, PEXI.BX, BATR.BX, ARTM.BX, COMI.BX, PTRI.BX, BRDX.BX, BRKU.BX, ARTM.BX, SNOS.BX, ARSB.BX, ALRO.BX, AZOM.BX, OTSP.BX, ALUM.BX, MOPN.BX, TSEL.BX, TGNM.BX XTR 100 - BROAD MARKET INDEX. XTR 30 - FREE FLOAT INDEX. XTR – EE (XTR EARLY ECONOMIC INDEX), XTR – ME (MID ECONOMIC SECTOR), XTR – LE (LATE ECONOMIC SECTOR)



The 10 percent FILTER

10 per cent moves may be a normal volatility on an emerging market like ROMANIA. But when a stock makes a year high while broad market is still making new lows, we have more than a bad volatility case here, we have outperformance. There are only seven stocks which are positive for the year and only six of them delivered a 10% positive performance. And all this six have been highlighted by us over the last few months. These stocks are AZO (275%), UARG (34%), AMO (31%), VEGA (30%), SOCEP (19%) and ERCA (12%). While these stocks were performing and conserving capital, there are stocks that fell 91% over the last 12 months.

There is nothing that speaks like price performance. Hence catching or tracking it early in the day is a key indicator. This is one of the key objectives of XTR INDICES to keep you updated with the price changes. This week, Energy topped the sectoral performance. Except Oil Terminal, which witnessed a marginal loss (down 1.83%), all Energy stocks gave a positive performance. Energy is also the top performer of the year. Staples major ALBALACT (up 12%) outshined in the XTR 30 Index.

In the market capitalization category chart (Slide 4), LC (Large Capitalization) category perform better (week over week) compared to the other categories. Between the SC (Small Capitalization) category, XTR 100 and XTR 30 constituents also gave a positive return. Among the indices, XTR LE (Late Economic) continues to be the best performer, with a positive return of 3.37%. As expected, XTR EE (Early Economic) and XTR ME (Mid Economic) underperformed. All the rest Orpheus indices delivered a positive performance. BET NG, the new BVB index was down -10.89% and BETFI (-5.68%) continued to fall registering the worst performance for the week.

The best performance for the week, was of 30.77%, given by the Materials stock component ELECTROPRECIZIA (ELZY). Utilities outperformer for the week was NAVROM (24.62%). The stock remains in a positive mode above its 50 days moving average since the 5 July. Even energy sector component ROMETROL (VEGA), remained above its 50 days moving average. Materials component VRANCART (9.24%), which was the top performer for the previous week also remains positive on the moving average crossover. The 10 per cent filter should witness more winners screened out in the weeks ahead.

Enjoy the latest XTR INDICES.


XTR.INDICES is our analytics product, which creates and manages Romanian market indices like XTR 21, XTR 100 and XTR 30 (Free Float). We also run models based on breadth indicators (Advance Decline ratio) and statistical parameters (correlations, betas, volatilities, top price changes, 200 day moving average etc.) XTR 21 - THE BLUE CHIP INDEX. REUTERS RICS COVERED.TRPS.BX, VNCA.BX, AMSL.BX, PEXI.BX, BATR.BX, ARTM.BX, COMI.BX, PTRI.BX, BRDX.BX, BRKU.BX, ARTM.BX, SNOS.BX, ARSB.BX, ALRO.BX, AZOM.BX, OTSP.BX, ALUM.BX, MOPN.BX, TSEL.BX, TGNM.BX XTR 100 - BROAD MARKET INDEX. XTR 30 - FREE FLOAT INDEX. XTR – EE (XTR EARLY ECONOMIC INDEX), XTR – ME (MID ECONOMIC SECTOR), XTR – LE (LATE ECONOMIC SECTOR)


XTR 21 - The new components

Last whole week we have been working on the new issue of XTR 21. Our leading blue chip index is 6 months old and a clear market leader. We have some performance history now and we wanted to rerun the model before we start the second half of the year. As we mentioned prior, statistical models are emotion free and clear rule based. The only discretionary work that we have done on the XTR 21 model is to set up limits and caps for stocks and sectors. The current model was updated with forward estimates. Rest everything was similar to what we did last time when we created the Index. It’s a clear system based approach.

The results are exciting. Last time in FEB, the model did not select SIFs and PHARMA stocks. We know what happened? Health sector and BETFI have the worst performing sector components of the year. Even now the model refused to select SIFs and popular health majors. But despite all this filtering, the model has changed a third of the XTR components.
Seven stocks got out and were replaced by new stocks. The model churned out a lot of INDUSTRIALS and a DISCRETIONARY major and selected four new material components. The model has selected one new BANKING stock and two fresh INDUSTRIALS. The new XTR 21 has both the utility majors. 75% of XTR 21 is allocated to the late economic sector components. For us, it’s not a coincidence that model valuations, sector rotation and price performance continue to point to late economic sector stocks. We have detailed out the specifics in SLIDE 11.

Week over Week, we had few gainers. PRSN and ELMA were positive gainers from the XTR 30. XTR 100 had eight gainers from late economic sector viz. ZAREA, SIOR, REFE, BUCUR, PRAE, VEGA, ALU and UARG. The broad market index also filtered out one DISCRETIONARY (NEPTUN) and one INDUSTRIAL component (CMVX). Week over Week XTR 21 continued to outperform all other market benchmarks. Year to date, XTR 21 remained the top performer followed by XTR LE (Late Economic Sector) and Materials sector.

Overall another interesting week, polarizing the market between future winners, outperformers and laggards. The current issue also contains the regular updates on XTR 30, XTR 100 along with the market annexure. We continue to believe in the late economic sector component stories and with barely 10% negativity on XTR 21 for the first half, we are confident of expected outperformance on the late economic sector components in the time ahead.

XTR is our analytics product, which creates and manages Romanian market indices like XTR 21, XTR 100 and XTR 30 (Free Float). We also run models based on breadth indicators (Advance Decline ratio) and statistical parameters (correlations, betas, volatilities, top price changes, 200 day moving average etc.)


ORPHEUS RESEARCH is also available on Reuters Knowledge, Yahoo Finance, Thompson ONE and Thompson Research. And can be accessed at the following links.



We cover Romanian capital markets, Indian Capital markets, Metals, Currencies, Agro Softs, Grains, Energy markets and Alternative Energy (Solar, Bio Energy, Water and Wind).

XTR - free float

A free float index of 30 stocks XTR -30 FREE FLOAT can not be constructed just from BVB stocks. We need to combine the RASDAQ and BVB offering. And since there was no available broad market index, which we could just rehash and present the XTR – 30, we got to work on the XTR – 100, Romanian broad market index. An index basket of top 100 market capitalized and tradable stocks that represented the Romanian market universe. We combined the list of stocks from RASDAQ and BVB and made a composite list of 150 stocks, screened them on basis of market capitalization, economic sectors, economic cycle sectors based on global classification (GICS).
This exercise not only brought out interesting observations about the Rasdaq market, but also that there is a broad investable market existing in Romania as demonstrated by the XTR 100. Just like blue chip indices (XTR 21 and BET), broad indices play a significant role in the market. Internationally we have the MSCI US Broad Market Index, which represents approximately 99.5% of the capitalization of the US equity market. It is the aggregation of the MSCI US Investable Market 2500 and the Micro Cap Indices. The MSCI US Broad Market Index represents a greater proportion of the US equity market cap than the most commonly used broad market indices. Then we have the Russell broad indices which replicate the total market through a limited number of stocks.

Broad indices assist in many ways. First, they allow to rank each company in the investable universe according to its total market capitalization. Second, the ranking based on capitalization helps eliminate non tradable shares. Third, after float adjustments the broad benchmark most accurately reflect the market. Fourth, broad market indices objectively allow the market to determine the index composition according to clear, published rules and not on a subjective vote of a selection committee. Fifth, the respective broad index matches manager’s behavior and include all the securities that investment managers could actually buy.

To answer some questions that may arise now, like how is XTR 100 a broad market based index for Romania? XTR 100 is composed of 48 stocks from BVB and 52 stocks from RASDAQ. All this 100 stocks together cover 85% (excluding ERSTE*) of Romania market universe. This is the reason XTR 100 is the most broad based investible index in the market today.

How does the XTR 100 rank among the other indices available in the market today? The very fact that XTR 100 sectoral composition is similar to that of BVB places it within the existing universe of indices well while retaining its broad based characteristics. XTR 100 is composed of 37% Financials, 34% Energy, 11% Materials, 6% Utilities and 6% Industrials. The other sectors like Pharma, Discretionary and Staples weigh around 1.5% each. From the economic cycle sector point of view, just like the market universe and BETC, XTR 100 has a large part coming from Late Economic cycle at 39% and Early economic cycle at 54%. Middle expansion economic sector (i.e. Industrials etc.) make 6% of the universe.

What are the most interesting aspects of the XTR 100? The most interesting aspect of the index is that unlike popular belief RASDAQ is a more significant part of Romanian investible universe today. XTR 100 has more stocks coming from RASDAQ than from BVB stock list. And this might look strange as BVB is assumed to have the larger capitalized stock list. Another interesting aspect is that though the filters for stock selection were based on market cap and tradability there were a homogeneous representation across both markets viz. BVB and RASDAQ across individual sectors and economic cycle sectors. For example there are 14 Industrials stock from BVB and 14 from RASDAQ which make the list. A similar situation exists for Materials stock 11 come from BVB and 13 from RASDAQ. The similarities extend into Energy sector which has a break of 4 (BVB) and 3 (RASDAQ).

Speaking sectorally, how different is RASDAQ market from BVB? RASDAQ is more homogeneous than BVB composition as most of the sectors like Industrials, Materials, Discretionary, Financials and Staples are represented well. It is the Energy, Pharma and Utility stocks that are underrepresented in RASDAQ. Even from a market capitalization perspective, barring Pharma and Utilities sector all the other six sectors are well represented. Industrials is the largest market capitalized sector. Even from the economic cycle sectors the market is balanced. All the three economic cycle sectors have more the 30 stocks each.

We will be introducing XTR 100 performance along with other indices we track viz. XTR 21, BET, BETC and BETFI. The week that went saw XTR 21 once again outperforming the BETFI. The XTR 21 large and small caps did better than the universe large and small cap. The index was up 2 percent for the week ending 04 April 2008.

Enjoy the latest XTR.070408

XTR 100 - the broad Index

XTR 21 is market cap and fundamental weighted index. And to make it more replicable (tradable) we have studied the underlying free float for the market, to introduce the benchmarks FREE FLOAT version. Moreover the current statistics do suggest that XTR 21 could better its performance with a free float review.

However, since this will be the first attempt to create a free float benchmark in the country we wanted to be devote it some more time. And since we are in an emerging market, it is necessary to consider if float adjustment alters the structure, return characteristics, composition, liquidity and risk profile of the indices. Float adjustment reduces market capitalization of different stocks by different amounts, and might, therefore, alter index structure. To capture the change in relative weights in the full list of index constituents, we have plotted the sectoral free float rankings. This helps us understand the homogeneity and other characteristics of the universe free float.

From a sector rotation perspective, Financials are the top free floating sector at 69%. This might look coincidental, but considering Financials are the early economic cycle, a higher tradability and outperformance owing to high public appeal can only be balanced through a higher free float share. Industrials, Discretionary and Pharma are the other top free float share sectors. Materials, Energy and Utilities are low on the free float share. And if sector analogy is extended to these late economic sectors, market forces might effect an improvement here. Just like the market universe, Energy and Financials are the two top sectors in free float as a percentage of market capitalization. Another interesting aspect was the large capitalization free float at 79%. Mid capitalization and small capitalization free float share stood at 12% and 10% respectively. This statistics once again reinforces our large cap hypothesis (XTR.250208) and suggests that free float factors might reinforce XTR 21 positively. We also plotted the free float shares for Late Expansion, Early Expansion and Middle Expansion economic cycles. We have carried the annexure with the free float rankings (slide 14). Bank of Transylvania (BATR.BX) is top free float stock, followed closely by SSIF BROKER (BRKU.BX) and Transportation Major SOCEP (SOCC.BX) at 85%, 77% and 66% respectively. MECHEL (OTSP.BX) is the lowest free float stock ruling at 0.2.

We will delve on the real construction in the next issue of XTR. This week we are introducing the Free-float (FF) factor and how numeric ranking for BVB stocks can be based on Free flat factors. The FF methodology refers to an index construction methodology that takes into consideration only the free-float market capitalization of a company for the purpose of index calculation and assigning weight to stocks in Index. Free-float market capitalization is defined as that proportion of total shares issued by the company that are readily available for trading in the market. It generally excludes promoters holding, government holding, strategic holding and other locked-in shares that will not come to the market for trading in the normal course. In other words, the market capitalization of each company in a Free-float index is reduced to the extent of its readily available shares in the market. Under the ‘full-market capitalization’ methodology, the total market capitalization of a company, irrespective of who is holding the shares, is taken into consideration for computation of an index. However, if instead of taking the total market capitalization, only the Free-float market capitalization of a company is considered for index calculation, it is called the Free-float methodology.

There are many advantages of Free-float Methodology. It aids both active and passive investing styles. It aids active managers by enabling them to benchmark their fund returns vis-à-vis an investable index. And it enables passive managers to track the index with the least tracking error. Free-float Methodology improves index flexibility in terms of including any stock from the universe of listed stocks. This improves market coverage and sector coverage of the index. For example, under a Full-market capitalization methodology, companies with large market capitalization and low free-float cannot generally be included in the Index because they tend to distort the index by having an undue influence on the index movement. However, under the Free-float Methodology, since only the free-float market capitalization of each company is considered for index calculation, it becomes possible to include such closely held companies in the index while at the same time preventing their undue influence on the index movement.
Globally, the Free-float Methodology of index construction is considered to be an industry best practice and all major index providers like MSCI, FTSE, S&P and STOXX have adopted the same. MSCI, a leading global index provider, shifted all its indices to the Free-float Methodology in 2002. The MSCI India Standard Index, which is followed by Foreign Institutional Investors (FIIs) to track Indian equities, is also based on the Free-float Methodology. NASDAQ-100, the underlying index to the famous Exchange Traded Fund (ETF) - QQQ is based on the Free-float Methodology.

To construct the free float index, one needs to determine the Free-float factor for each Index Company. A few exchanges around the world have designed a detailed Free-float format to be filled and submitted by all index companies on a quarterly basis with the Exchange. The Exchange determines the Free-float factor for each company based on the detailed information submitted by the companies. Free-float factor is the multiple with which the total market capitalization of a company is adjusted to arrive at the Free-float market capitalization.

Apart from the free float factors, a few other considerations need to be explored. The first is breadth of coverage — how complete is the benchmark in covering the investment opportunity set? Does it take into account the sector rotation cycle? Does the index accurately reflect what the investor can actually buy? The second is transparency of construction — the portfolio construction rules should be clear and unambiguous. These rules ought to be predictable and consistently applied. We will try to address all these issues in the following issues of XTR. Owing to some special ownership rules, free float issues regarding SIFs are unclear and how to determine the free float factor for the respective stocks. The free float data taken for XTR was reported on 29 Feb 2008.

About the XTR21 performance week over week, the benchmark outperformed all the other indices.

To read the latest issue of XTR.310308 write to us for a free trial today or download the report from REUTERS KNOWLEDGE, YAHOO FINANCE, THOMPSON ONE or THOMPSON RESEARCH.

Enjoy the latest XTR.310308

XTR - Correlation

In probability theory and statistics, correlation indicates the strength and direction of a linear relationship between two random variables. This statistical parameter can not only help in stock selection but also create structured products based on market neutralizing.

Suggesting a hedging strategy, a week before market fell more than 8% was nothing short of timing. Whether the markets run up this week or not, March futures expiry should make your hedged portfolios richer. And the way we see thing at Orpheus, market neutral strategies should become more than a bread earner in the time ahead, especially if volatility continues to rise.

Building on where we left last time, the primary aim of creating correlation matrices is to formulate high integrity pairs. For this we have studied correlations over various time frames (historical, few years, quarterly, weekly and daily). The current XTR illustrates some of the historical correlation matrices.

The highest correlation pair stands at 0.985 between SIF 1 and SIF2. But SIF2 (SIF2.BX) and SIF5 (SIF5.BX) make a better active pair, owing to their tradability in futures. A long – short strategy can be a continuous market neutral strategy between SIF2 and SIF 5. And just like the SIF pairs, TLV (BATR.BX) and BRD (BRDX.BX) (Romanian banking majors) have the highest correlation at 0.95. This means irrespective of their separate fundamental drivers BRD and TLV make a good pair. And from a statistical view, exposure to one bank would have compensated for the exposure to the other or both the stocks.

To illustrate this case further, we can compare the price performance of the banking majors. Though on a short term basis say July 07 to Feb low BRD fell 13% more than TLV. From Jan 07 to July high the comparisons stood at 68%, 48% for BRD and TLV respectively. And if you look at overall performance starting Jan 2006, both the stocks returned similar price performances at around 45%. This is what a good correlation pair does. Annualized returns for good pairs are similar irrespective of the underlying events, which drive the respective stocks. It’s also to do with the large cap hypothesis we talked about. Two blue chips in a high correlation pair, which are also sector leaders can’t deliver divergent price performances. And a difference, if any can only be in the short term, over a few weeks to a few months like we have illustrated in our case above.

And as markets mature even these short term price inefficiencies (example BRD returning 13% less than TLV since July 07) can be taken care by arbitrageurs or strategists who play between such highly correlated pairs (Short BRD, Long TLV and vice versa). This is where market neutral comes in. We at Orpheus have highlighted these market neutral strategies between TLV vs. BRD, SIF2 vs. SIF5, SNP (SNPP.BX) vs. OIL (BRT-) on prior occasions. A few market neutral pairs (long one, short other) out of the many we illustrated in Orpheus market letters failed to give consistent results. One of them was the SNP-RRC (ROMP.BX) pair, which as we illustrated in the correlation matrices last time (XTR.170308) is a low correlation pair at 0.59, the very reason a continuous running long – short strategy is not very successful in the respective case. This is despite the fact the both stocks are from the same sector. Sector grouping can enhance a pair integrity, but it does not guarantee it.

And correlations are not just local, they are global in their scalability. We talk about them all the time. Like for example the correlation of OIL (Brent) with SNP. Many of our readers have expressed surprise at SNP an OIL relationship. How SNP fell despite the net rise in

OIL prices from $ 50 to $ 100? How BETFI fell despite DOW rise? And how is Euro Ron connected to BET or BETFI? Over the long term OIL and SNP has a 0.85 correlation (this makes it a better pair than the local RRC - SNP pair). However, owing to the long termism of the correlation indicator, price inefficiencies between stock and its underlying commodity (in this case, OIL and SNP) can extend for more than a few months. This is what happened, OIL rose and SNP fell (We will explain SNP-OIL pair more in our next issue on Intermarket). A similar relationship is assumed to be in DOW Jones Industrial and local market indices (BETFI, BET, BETC). However, the correlations are weaker when we consider the DOW and BETFI. And if you are really looking at CAC or DAX for trading BETFI, you are on a heading towards a losing streak. The DOW and BETFI correlation is higher when markets fall and extremely poor and sometimes negative. This means that we had many occasions when local indices were rising while the DOW was falling. The correlation has never reached 0.9 between DOW and BET.

Hungarian BUX (slide 14) on the other hand (has the highest correlation with BET) and can tell us more about the Romanian indices than DOW, which is more of a mass psychology play (herding). Panic is a bigger motivator than greed. No wonder when markets go down, the correlations increase all over, and not just with DOW. But with a host of global indices including Russia, Nikkei, Shanghai, India, Brazil etc. It’s the DOW link, which makes more news, the reason it get’s anchored in mass psychology.

Correlation cannot only help identify pairs, but also assist is stock selection. When we need to assume market risk (beta) we can chose highly correlated pair, but when markets are at euphoric levels, stock picking can be based on negative correlation stocks. Globally, negative correlation is a much desired strategy today. Hence the significance of understanding the correlation matrix cannot be undermined. In the previous issue of XTR (100308) we showcased the XTR 21 beta. This week we have shown a correlation matrix (slide 13) between component stocks. As you can see there are many negatively correlated pairs, no wonder XTR 21 falls lesser than BETFI every time we have a negative week. Since inception XTR 21 never fell more than BETFI (week over week). We need more history to validate this, but both portfolio beta and negatively correlated pair among XTR components confirm our view.

Negative correlation has better predictability than low correlation. DOW has a low correlation with local Romanian indices, but EURRON (slide 14)has a negative correlation with BET over the last four years. This also suggests the local currency is a better indicator than the global benchmark. And last but not least all these pair components lead and lag in performance against each other. This is why SNP underperformance against OIL is cyclical. And we might not be far away from the time when OIL corrects and SNP rises. Next week we extend this pair formulation strategy to sectors, to identify outperforming sectors from the ones that are set to underperform.

On the XTR 21 we had another week of drawdown, as the broad market corrected. The benchmark is down 10% from inception. But we are still positive for the coming months and continue to consider these low risk entry points. XTR 21 outperformed BETFI yet again. But since the fall was sizeable most market indices were down. From the late economic cycle sectors, it was the utilities, staples and materials which witnessed marginal losses.

To read the latest issue of XTR.240308 write to us for a free trial today or download the report from REUTERS KNOWLEDGE, YAHOO FINANCE, THOMPSON ONE or THOMPSON RESEARCH.

XTR - Market Neutral

It might look strange, but though the problems are more in America, it’s the Romanian markets that feel the heat. One of the reasons emerging markets like Romania are more volatile is because markets lack the knowledge of risk management. We are ideally speaking still a “LONG ONLY” market. We don’t have mechanisms to short sell, we don’t have many representative benchmarks, no index futures for hedging and just a few stock futures with some trading volume. No wonder emotional content is high owing to lack of hedging instruments. And the only executable strategy when markets fall is to ‘SELL’. This is the reason we want to dedicate some time to risk management. As a good risk management strategy can avoid unwarranted panic.

Market neutralizing of a portfolio can be done using many techniques. We can use market sensitivity indicator beta (XTR.100308), inter market and sectoral correlations and annualized interest rates in the futures market. Just like beta correlations can be used for stock selection. Stock pickers can avoid high beta in euphoric times and select the same stocks in a panic (as the same stocks fall the most and relatively become the most inexpensive) or use negative beta sectors and stocks to bring the overall portfolio beta (sensitivity) down (like we did for XTR 21). Or one can just select stocks with beta at 1 to create a portfolio that just simulates the market.

High and low correlations make stock selection a bit more easy. For example all of the BETFI components (SIFs) have near 1 betas, which makes stock selection easier for anyone wanting to take exposures to BETFI components (he can use any of the SIFs to capture the BETFI growth). The similar analogy can be extended to other sectors of the local equity universe. This is what we have tried to illustrate using sector based correlation matrices. We will be delving into correlation in more detail next issue when we will illustrate the meaning of high and low correlations and how market pairs can be identified using correlation matrices. What is the link of correlation with risk? And how can management of risk mean a profit when you execute a pair trading (market neutral) strategy? Understanding correlations can not only allow the fund manager to neutralize unwanted risk but also create relative alpha despite market negativity.

This issue builds on where we left last time with stock betas. In slide 4 we create two portfolios of different weights and beta and then we use SIF 2 and SIF 5 Futures to hedge the same portfolios. So we are using futures to hedge any portfolio made of various stocks. We can even use SIF Futures to hedge a portfolio without SIFs. Strange as it may sound, statistical hedging is mathematical and sound. Statistical hedging also highlights why thumb rule hedging may not work in markets and can be bad risk management. A simple example are SIF futures. Though conventionally believed that SIF futures are more volatile compared to SIF spot, the reality is opposite. Spot SIFs are more volatile than their respective futures and hence have a lower beta compared to spot SIF components. And this is why SHORTING 10 (10*1000 units) contracts of SIF 2 FUTURES against 10,000 units of SIF 2 spot is far from a perfect hedge and can lose money. We have illustrated the Hedge sheet on slide 4 and 5. How SIF 2 and SIF 5 futures used along and together can be used to hedge the underlying portfolio.

On the XTR 21 front, we had another week of XTR homogeneity compared to the market. It found its place yet again between the market indices. This makes it a good benchmark as it does not spike up or down compared to the overall market. XTR seems very selective about volatility. It captures the positive volatility (upsides) and shuns the negative volatilities (downsides). A model with a less drawdown is always preferred to one with a high drawdown, like BETFI this week, which fell the most out of BET, BETC and XTR 21. This high BETFI beta caused the first divergence in more than six weeks between XTR and BETFI (slide 7). Sectorally too this was another interesting week as energy outperformed all the other sectors. Energy is a late expansion sector and should continue to outperform along with materials followed by staples and utilities.

To read the latest issue of XTR.170308, write to us for a free trial today or download the report from REUTERS KNOWLEDGE, YAHOO FINANCE, THOMPSON ONE or THOMPSON RESEARCH.

XTR - Stock Picking Using Beta

The Beta coefficient, in terms of finance and investing, is a measure of volatility of a stock or portfolio in relation to the rest of the financial market. An asset with a beta of 0 means that its price is not at all correlated with the market and that the asset is independent. A positive beta means that the asset generally follows the market. A negative beta on the other hand shows that the asset inversely follows the market and generally decreases in value if the market goes up. It might look like a coincidence but XTR 21 has two highest beta stocks viz. Petrom and Broker and two negative beta stocks viz. Turbomecanica and Alro. No wonder last week’s negativity saw XTR as the best performer. The negative beta stocks balancing the high beta stocks. Negative correlation helped reduce losses. We expect a similar performance in the coming future.

Beta correlations are not only evident between companies within the same sector, but also within the same asset class like equities. This is why a majority of the stock components fall or rise together. However, when you talk about emerging markets, this correlated risk, measured by beta can also assist in numeric rankings between sectors and stocks and assist in stock picking.

Emerging markets continue to be a driver for global investment and it’s presumptuous to assume that the degree of a bear market can become large enough to drive out liquidity from the Romanian capital market. Though markets are more integrated today than they were in 1980’s when Japan went into a depression, the very fact that global economy thrived for more than thirty years despite the Japanese slow down clearly highlights that the economic engine growth might come from a different asset class or a different region, but no global depression can stop it completely.

The intermarket factors will continue to play just like they do between large cap and small cap, commodities and equities, developed and emerging markets. High betas of emerging markets will continue to attract investments from both local and international investment pools. And even if things become chaotic, the degree of chaos in emerging markets cannot be compared to one in developed markets.

It’s keeping these comparisons in mind we present this issue of XTR dedicated to betas. Indices are a good measure of judging a fund manager’s performance, as they beat the index. Today we have funds in Romania, which have moved to risk-adjusted performance combining returns with volatility. This is alpha, a measure of a fund manager’s skill, defined as the ability to produce superior risk-adjusted returns. However, most stock market indices just like in Romania are dominated by larger companies.

This means that active manager’s chance of outperforming lies in buying the shares of smaller businesses or outperforming through the value approach i.e. buying the shares of companies that look cheap on valuation measures, such as low price earnings multiples etc.. Hence the fund managers edge of delivering real alpha continues to diminish as market sophistication increases and what fund managers might deliver may be more beta rather than alpha. According to recent research, the correlation between fund returns and the S&P 500 index is already high and getting higher.

And Bill Fung and Narayan Naik of the London Business School suggest that it seems possible that in time ahead the gap between alpha and beta will continue to reduce. And though there will be fund managers outperforming all the time, identifying them early will remain a challenge. Hence a conservative strategy might be to just concentrate on beta and invest in indices and ETFs that allow the relevant exposure. XTR 21 allows small capitalization and value exposure on a appropriate sample of the market universe , classic stock picking using beta.

To read the latest XTR issue write to us for a free trial today or download the report from REUTERS KNOWLEDGE, YAHOO FINANCE, THOMPSON ONE or THOMPSON RESEARCH.

XTR - Fund Managers Average

Also called as the “FUND MANAGER’S AVERAGE”, this is one of the most important indicators for measuring participation. As a general rule, investors, institutions and big players feel comfortable investing in a stock or a market when the asset is trading above it’s 200-day MA. When the stock or market falls below the 200-day MA, they are less likely to put new money to work in that particular stock or market or to defend their position if the stock or market drops.

The 200-day moving average is a long-term smoothing of price movement, and a stock’s price in relation to this moving average is a good indication of its long-term trend. For example, when the price index moves below the 200-day moving average, we can assume the long-term trend is down until the price index moves back above the 200-day moving average.

There are no automatic assumptions that can be made about this index. For example, just because 80% of stocks are above their 200-day moving average, there is no guarantee that a downside reversal can’t happen. In fact, once the index has moved to an extreme end of its range, it’s a good idea to be alert for a change in direction, because the market improves until it is as good as it can get, then it starts to deteriorate. Conversely, as soon as things are as bad as they can get, they start improving. So this is the behavioral pattern that creates an edge for the fund manager, stock pickers and traders.

This XTR issue analyses the BVB indices and stocks in relation to their 200 Day moving average. The results are not surprising. More than 80% of the market is below its respective average. Now this means that apart from the negativity that one can expect, it makes sense to be alert for a change in direction. Above this we have a few stocks that are above the 200 day moving average. We also back tested a long – short model for the three indices and have illustrated the results in the report.

The report also carries an update on the XTR 21 index, which for second week in a row has found its place among the other indices. There is a complete capitalization comparison, index comparisons, updated stock and sector allocations, intermarket sectoral performances and XTR 21 week over week observations.

To read the latest XTR issue write to us for a free trial today or download the report from REUTERS KNOWLEDGE, YAHOO FINANCE, THOMPSON ONE or THOMPSON RESEARCH.

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