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Dive Into the New Age of Quantitative Investing

A bouquet of simplified analytics to align with market pulse

Market Signals

Market Signals use advanced quantitative analysis to identify market turning points for various benchmark indices like Nifty, Bank Nifty, Nasdaq, Gold and many more.

 

Market signals are detected using multiple analytical models. These models use a combination of quantitative analysis to generate signals. Market signals are rigorously backtested using our advanced Backtesting Engine built using Python & R, on a variety of market scenarios over the last 10 years.

Market Signals reflect the State of Market. While taking positions in Index ETFs / Futures / Options  or in individual stocks, probability of success significantly increases when positions are taken in sync with the State of Market. 

Sentiment Analytics

Sentiment Analytics help to understand emotions inside the minds of market participants and decode state of market and general direction of market trend. Sentiment Analytics provide Signals for multiple sentiment indicators. Signals are generated using sophisticated multi layered process to separate Noise and Signal. 

During market swings, the psychology of investors moves from pessimism and fear to hope, overconfidence, and greed. Usually optimism among market participants reaches its peak around the same point that the market is forming a top or a peak. Conversely, market participants are most pessimistic at market bottoms, which is precisely the point which creates good buying opportunities. 

Signals generated for various Sentiment Indicators, reflects likely change in the State of Market Emotion. Positions in Index ETFs / Futures / Options or in Individual stocks when taken in sync with the State of Market Emotion or Sentiment or Mood; significantly increases the probability of success.

Power Scans

Power Scans provide a curated set of scans running on F&O stocks. Power Scans include multiple scans to detect Uptrend and Downtrend in stocks. These stock scans use combinations of several quantitative analysis and are optimised using rigorous Risk Analysis.

Risk Analysis for stock scans involve millions of computations using our Advanced Backtesting Engine (built with Python & R).


The Advanced Backtesting Engine runs Deep Backtesting on all F&O stocks simultaneously under different market scenarios. The coverage of analysis during Backtesting includes several parameters like Accuracy (Win / Loss ratio), analysis of Average Gain vis-à-vis Average Loss, Return per unit of Loss, Drawdown Duration, analysis on effectiveness of Stop Loss etc.

 

The curated list of power scans are selected based on Deep Backtesting performance analysis on thousands of potential stock scans. This is to ensure that despite your busy professional and personal calendar, you always get in your dashboard, a select bouquet of stock scans along with backtesting analysis for your further research.

Backtesting Analytics

Backtesting is used to evaluate how different combinations of quantitative indicators would have performed, under a variety of historical market scenarios.

 

Alnair Analytics' robust backtesting engine, equipped with Python & R, uses rigorous risk analysis, performing millions of computations to optimise Market & Sentiment Signals and Stock Scans.

Though past performance does not guarantee future returns; backtesting can help to assess certain key aspects of investments. Typically trading style like Target Return, Stop Loss & Time Horizon vary widely among market participants based on their individual risk appetite. Simplified backtesting analytics at alnairanalytics.com help users to analyse and assess their own respective Target Return & Stop Loss levels based on their individual risk appetite and preferred Time Horizon.

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