Indian Banking – Risk Metrics

Banking is an early economic sector. How banks will perform in the coming future will decide whether markets are going to head lower or bottom here. This is because banking is a part of the early economic sector and markets don’t rise of the early economic sector (technology and banking) does not participate. The first look suggests that Indian banks are still polarized. Based on Jiseki performance rankings a half of the Indian banks (7 of them) are showing outperformance while the other half are stagnating.
The picture is different on the intermediate multi week price trend filter. We have discussed running signals on the 15 banking components in the report. The key levels for NSEBANK lie at 9,000. If respective levels break we are in for a larger drawdown on banks. It is then the current ranking neutrality should change to a clear negative bias on the sector.
In this update we have added new elements to the Indian Banks subgroup. We have added a Risk Matrix based on ranking, a risk matrix based on price, group analysis, ranking histograms, Jiseki cycles and price SIGNALS. The latest ALPHA goes about analysing the Indian Banking components based on performance rankings and cycles.
Our Jiseki Time cycles are seasonal patterns of strength or weakness in assets. They are derived from percentile rankings from 1 to 100. The higher the percentile more the chance for an asset to weaken and worst the ranking, better the chance for the respective asset to outperform. 100 is top relative performance and 1 is worst performance. The idea is that performance is cyclical. A top performer will underperform in future and vice versa. A top relative performer is also the worst value pick and the top relative underperformer is the best value pick. Jiseki is another name for Performance cycles, time triads and time fractals. The signals are illustrated as a running portfolio and as Jiseki Indices. These signals can be used by fund managers for relative allocations, traders for leverage bets and high net worth clients for selective trades.
Jiseki Interpretation. Signals are interpreted as crossovers between various Jiseki Cycles. All three Jiseki cycles (Jiseki 1,2 and 3) depict different time frames. Example: An asset is ranked above 80 percentile and all the three Jiseki cycles are pointing lower, this suggests a running SHORT SIGNAL. Our Jiseki Indices use different kind of exits based on price and Jiseki Cycles. We have color coded the (Jiseki 1>Jiseki 2) SHORT zones with brown sandy (burlywood) and grey (Jiseki 1>Jiseki2) for LONG SIGNALS.
Enjoy the latest Alpha.

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Our Jiseki Time cycles are seasonal patterns of strength or weakness in assets. They are derived from percentile rankings from 1 to 100. The higher the percentile more the chance for an asset to weaken and worst the ranking, better the chance for the respective asset to outperform. 100 is top relative performance and 1 is worst performance. The idea is that performance is cyclical. A top performer will underperform in future and vice versa. A top relative performer is also the worst value pick and the top relative underperformer is the best value pick. Jiseki is another name for Performance cycles, time triads and time fractals. The signals are illustrated as a running portfolio and as Jiseki Indices. These signals can be used by fund managers for relative allocations, traders for leverage bets and high net worth clients for selective trades.
Jiseki Interpretation. Signals are interpreted as crossovers between various Jiseki Cycles. All three Jiseki cycles (Jiseki 1,2 and 3) depict different time frames. Example: An asset is ranked above 80 percentile and all the three Jiseki cycles are pointing lower, this suggests a running SHORT SIGNAL. Our Jiseki Indices use different kind of exits based on price and Jiseki Cycles. We have color coded the (Jiseki 1>Jiseki 2) SHORT zones with brown sandy (burlywood) and grey (Jiseki 1>Jiseki2) for LONG SIGNALS.

Domnita Pascut is the founding member of Orpheus Capitals.  Her interest in charts and market patterns was an extension of her keen understanding of social mood and sentiment. How charts could say so much intrigued her. She worked on market patterns, economic research, cyclicality and economic history. It was her liking for history which helped her see the cyclical natures of markets and patterns. Domnita now spearheads the extreme reversion anlaytics developed at Orpheus. She uses Jiseki Performance cycles and combines them with various risk metrics to analyse markets and filter out trading signals.