Intermod.in is an e-commerce retailer of urban work-wear for modern women .

Archiverse.ai develops visualisation communication products for Real Estate participants

Whats new?My approach solves a classic Recognition problem. There can be millions of time scales. One can use 5-d data or 504-d data. And one can see the current point becoming a part of infinite patterns. A very elementary example of a short-term trend becoming a long-term range is not far-off. My approach resolves these multitudinous time-scales into a very few relevant and dominant time-scales. Toolkit: Machine Learning, ANN, AIFramework:Stage 1: Phase… Show more Whats new?My approach solves a classic Recognition problem. There can be millions of time scales. One can use 5-d data or 504-d data. And one can see the current point becoming a part of infinite patterns. A very elementary example of a short-term trend becoming a long-term range is not far-off. My approach resolves these multitudinous time-scales into a very few relevant and dominant time-scales. Toolkit: Machine Learning, ANN, AIFramework:Stage 1: Phase Estimation: For present time-period, estimate the mutual-relationship between Volatility and Return and classify the Phase as High/ Medium / Low Volatility.Stage 2: Phase Horizon - Time and Return : For the current phase, if it is a HV phase, compute Time horizon; for a LV phase compute Return Horizon. These will be obtained as Ratios from Relevant History (stage 3).Stage 3: Choosing Relevant Data-set: Choose a phase in near past proximity to current phase. Vary only the time-scale, (which will mean inclusion of more historical past phases) till the ratio of Time (of HV Phases) vs Return (of LV phases) becomes internally consistent for the data-set. This ratio will now be used to compute the Phase Horizon. Stage 4: Phase Changeover: The Phase Horizon itself gives an estimate of Time and Return Horizons. Phase Changeover can be expected post this horizon. Additionally, simple price barriers and trend-lines from Relevant Data-Set give important trading signals in this vicinity. Stage 5: Timing Triggers: A proprietary suite of Trading patterns is employed to trade during the horizon and changeover. These patterns have been developed from examination of multitude of liquid assets over extensive history. Stage 6: Trading Execution: Classical Option-based strategies are used for HV and LV phases. Show less

Proprietary Trader in Forex - Spot, Forward,options; Interest Rates- Sovereign bonds, Swaps, futures, options; Equity Indexes: Cash and options ALM book management: Managing interest rate and basis risks on ALM book. Maintaining ALM ratios. Monitoring & presenting (to ALCO) summary of Cost of Funds, transfer pricing, deposit rates, NII, ALM ratios etc. Cash flow and Liquidity management: Funding currencies. Managing major cash flows. Managing liquidity ratios.

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