/ Built for Systematic Investing
The quantitative layer for every portfolio
Explain returns, control risk, and optimize outcomes on one robust SaaS platform.
/ What is Systematic Investing?
A disciplined, data-driven playbook using advanced models to transform market insight into repeatable, risk-aware edge and smarter, consistent investing decisions.
/ What is MethodTech?
MethodTech is a full-stack systematic investment platform for institutional investors. Built with a practitioner-first approach and global best practices, it unifies structured data, an in-house multi-factor risk model, research & backtesting, portfolio optimization, and advanced analytics—on one robust SaaS platform.
Risk Model
Built in-house and integrated across the platform
A Risk Model sits at
the Core of Systematic Investing
What is a Risk Model?
A statistical framework that converts every position into systematic factor exposures and stock specific (idiosyncratic) risk, letting you gauge future volatility and return drivers before you trade.
Why use a Risk Model?
Decomposes each holding into Factor vs Idiosyncratic Risk.
Quantify risk in a standardised manner.
Adjusts weights in real time to hit your target
IR, instantly reflected on the dashboard.
Lets you size bets, not just rupees, before
they hit the blotter.
Why use a Risk Model?
Decomposes each holding into Factor vs Idiosyncratic Risk.
Quantify risk in a standardised manner.
Adjusts weights in real time to hit your target
IR, instantly reflected on the dashboard.
Lets you size bets, not just rupees, before
they hit the blotter.
Use Cases
Build systematic strategies without the stack. India-first data, a 39-factor risk model, explicit Objectives and Constraints, and point-in-time backtests all in one platform. Understand portfolio risks, decompose to single stocks, and isolate idiosyncratic returns with advanced analytics.
/ From first data pull to live decisions - six ways MethodTech upgrades the workflow.
Data you can defend
(point-in-time)
Easily grow your site with a built-in CMS, AI-powered localization,
and maintenance tools, designed to handle projects of any size.
Data you can defend
(point-in-time)
Easily grow your site with a built-in CMS, AI-powered localization,
and maintenance tools, designed to handle projects of any size.
Expose Hidden Risks Before They Hit P&L
Real-time factor tilts, ownership metrics, and idiosyncratic flags highlight vulnerabilities early, so managers can neutralise blind spots instead of explaining losses.
Expose Hidden Risks Before They Hit P&L
Real-time factor tilts, ownership metrics, and idiosyncratic flags highlight vulnerabilities early, so managers can neutralise blind spots instead of explaining losses.
Validate Every Strategy with 15 Years of Robust Back-Tests & Stress Scenarios
Event-driven simulations and
point-in-time data let you de-risk concepts long before real capital is deployed, accelerating conviction cycles.
Validate Every Strategy with 15 Years of Robust Back-Tests & Stress Scenarios
Event-driven simulations and
point-in-time data let you de-risk concepts long before real capital is deployed, accelerating conviction cycles.
From idea to mandate-checked portfolio
Optimize under objectives—maximize IR, minimize variance or tracking error, target factors, or cap drawdowns—within constraints for single-name, sector, liquidity, turnover, derivatives, and benchmark bands.
From idea to mandate-checked portfolio
Optimize under objectives—maximize IR, minimize variance or tracking error, target factors, or cap drawdowns—within constraints for single-name, sector, liquidity, turnover, derivatives, and benchmark bands.
Explain performance, fast
Attribution across any period separates factor, sector, and stock contributions; drill from portfolio to position to clearly see which names actually drove each factor.
Explain performance, fast
Attribution across any period separates factor, sector, and stock contributions; drill from portfolio to position to clearly see which names actually drove each factor.
Built for fundamental and quant teams
No-code dashboards for PMs and risk, with Python APIs for quants, so each team works natively while staying aligned through shared data and controls.
Built for fundamental and quant teams
No-code dashboards for PMs and risk, with Python APIs for quants, so each team works natively while staying aligned through shared data and controls.
/ About Us
MethodTech, founded in 2024, melds state-of-the-art machine-learning with rigorous quantitative finance to deliver an ML-powered operating system for institutional portfolio managers, whether they pursue systematic or fundamentally driven strategies.
Rachit Parasrampuria, a Computer Science and Economics grad from Cornell University, Rachit led Portfolio Monetization within Citadel’s Equity Quant Research team, building systematic strategies and scalable investment pipelines for multibillion dollar portfolios.
Siddhartha Kochar, an MBA from Columbia University, Siddhartha established and led the India business for a global credit infrastructure firm and previously co-founded an additive manufacturing venture. He brings fundamental investing experience of over a decade.
FAQs
What is Methodtech?
MethodTech is India's first full-stack platform for systematic investing and it combines clean financial data, quant research tools, portfolio optimizers, execution infrastructure, and analytics, all in one modular SaaS platform.
Who is MethodTech built for?
We serve asset managers, PMS/AIF firms, brokers, and distributors looking to modernize their investment processes. Whether you're running complex quant strategies or advising retail clients, MethodTech offers tailored tools to fit your workflow.
Do I need a technical team to use the platform?
Not at all. MethodTech features a no-code/low-code interface designed for portfolio managers, analysts, and advisors. Quant teams can still access deeper control via code and APIs.
Can I use only specific modules of the platform?
Yes. We're built with Indian market regulation in mind. Our execution stack, analytics tools, and audit logs are designed to align with SEBI guidelines from day one.
What is Methodtech?
MethodTech is India's first full-stack platform for systematic investing and it combines clean financial data, quant research tools, portfolio optimizers, execution infrastructure, and analytics, all in one modular SaaS platform.
Who is MethodTech built for?
We serve asset managers, PMS/AIF firms, brokers, and distributors looking to modernize their investment processes. Whether you're running complex quant strategies or advising retail clients, MethodTech offers tailored tools to fit your workflow.
Do I need a technical team to use the platform?
Not at all. MethodTech features a no-code/low-code interface designed for portfolio managers, analysts, and advisors. Quant teams can still access deeper control via code and APIs.
Can I use only specific modules of the platform?
Yes. We're built with Indian market regulation in mind. Our execution stack, analytics tools, and audit logs are designed to align with SEBI guidelines from day one.
Experience MethodTech,
Book a founder demo and
elevate portfolios today.
/ Join Our Newsletter
Be a part of the MethodTech network. Subscribe now to get information about updates, new releases and more.
Subscribe
Subscribe
Subscribe
Subscribe
/ Use Cases
Quant PMs & Research Teams
Quant PMs & Research Teams
Build and scale systematic strategies end-to-end.
Create alphas, optimise with clear objectives, and enforce real-world constraints.
Powered by a 40-factor India-first risk model.
Backtest on point-in-time data with costs at each step.
Monitor exposures, tracking error, and attribution live.
Achieve faster idea-to-portfolio, higher IR, lower slippage, and full auditability.
Build and scale systematic strategies end-to-end.
Create alphas, optimise with clear objectives, and enforce real-world constraints.
Powered by a 40-factor India-first risk model.
Backtest on point-in-time data with costs at each step.
Monitor exposures, tracking error, and attribution live.
Achieve faster idea-to-portfolio, higher IR, lower slippage, and full auditability.
Fundamental PMs & Analysts
Fundamental PMs & Analysts
Fundamental PMs and Analysts can pinpoint where risk and returns come from with the multi-factor model, separating market/style effects from true stock moves. Track any name’s real drivers, cut unintended factor winds, and preserve conviction with position, idiosyncratic, and factor-band controls. Backtest hedge or sizing tweaks and see instant impact on drawdowns and capture. The outcome: cleaner alpha, fewer style surprises, sharper single-name calls, and IC-ready narratives without building the stack.
Fundamental PMs and Analysts can pinpoint where risk and returns come from with the multi-factor model, separating market/style effects from true stock moves. Track any name’s real drivers, cut unintended factor winds, and preserve conviction with position, idiosyncratic, and factor-band controls. Backtest hedge or sizing tweaks and see instant impact on drawdowns and capture. The outcome: cleaner alpha, fewer style surprises, sharper single-name calls, and IC-ready narratives without building the stack.
Wealth & Investment Managers
Wealth & Investment Managers
Wealth & Investment Managers can separate skill from luck using multi-period diagnostics powered by the multi-factor model, then design client-fit baskets with objectives like Benchmark Tracking or Risk Minimisation and constraints for capital, positions, and factor/beta bands. Backtest to set clear expectations, generate client-ready, factor-aware explanations, and view all client assets—stocks, mutual funds, PMS—through one consolidated factor lens. The result: better manager selection, goal-aligned baskets, and higher client trust through transparent analytics.
Wealth & Investment Managers can separate skill from luck using multi-period diagnostics powered by the multi-factor model, then design client-fit baskets with objectives like Benchmark Tracking or Risk Minimisation and constraints for capital, positions, and factor/beta bands. Backtest to set clear expectations, generate client-ready, factor-aware explanations, and view all client assets—stocks, mutual funds, PMS—through one consolidated factor lens. The result: better manager selection, goal-aligned baskets, and higher client trust through transparent analytics.
Product & ETF Teams
Product & ETF Teams
Product & ETF Teams can design, simulate, and validate factor or thematic products directly through the multi-factor model, ensuring intentional exposures and minimal overlap. Set objectives like Benchmark Tracking, Factor Targeting, or Risk Minimisation with real-world constraints on capital, turnover, tracking error, and factor/beta bands. Backtest pre-launch performance with full cost modelling at each rebalance to build transparent, factor-aware products with clear, client-ready attribution.
Product & ETF Teams can design, simulate, and validate factor or thematic products directly through the multi-factor model, ensuring intentional exposures and minimal overlap. Set objectives like Benchmark Tracking, Factor Targeting, or Risk Minimisation with real-world constraints on capital, turnover, tracking error, and factor/beta bands. Backtest pre-launch performance with full cost modelling at each rebalance to build transparent, factor-aware products with clear, client-ready attribution.
/ Built for Systematic Investing
The quantitative layer for every portfolio
Explain returns, control risk, and optimize outcomes on one robust SaaS platform.
/ What is Systematic Investing?
A disciplined, data-driven playbook using advanced models to transform market insight into repeatable, risk-aware edge and smarter, consistent investing decisions.
/ What is MethodTech?
MethodTech is a full-stack systematic investment platform for institutional investors. Built with a practitioner-first approach and global best practices, it unifies structured data, an in-house multi-factor risk model, research & backtesting, portfolio optimization, and advanced analytics—on one robust SaaS platform.
Risk Model
Built in-house and integrated across the platform
A Risk Model sits at the
Core of Systematic Investing
What is a Risk Model?
A statistical framework that converts every position into systematic factor exposures and stock specific (idiosyncratic) risk, letting you gauge future volatility and return drivers before you trade.
Why use a Risk Model?
Decomposes each holding into Factor vs Idiosyncratic Risk.
Adjusts weights in real time to hit your target IR, instantly reflected on the dashboard.
Quantify risk in a standardised manner.
Lets you size bets, not just rupees, before they hit the blotter.
/ Use Cases
Quant PMs & Research Teams
Build and scale systematic strategies end-to-end.
Create alphas, optimise with clear objectives, and enforce real-world constraints.
Powered by a 40-factor India-first risk model.
Backtest on point-in-time data with costs at each step.
Monitor exposures, tracking error, and attribution live.
Achieve faster idea-to-portfolio, higher IR, lower slippage, and full auditability.
Fundamental PMs & Analysts
Identify true stock-specific returns by separating market/style effects.
Track each name’s real drivers and remove unintended factor exposures.
Use position limits, idiosyncratic controls, and factor bands to preserve conviction.
Backtest hedge or sizing tweaks and see immediate impact on drawdowns and capture.
Result: cleaner alpha, fewer style surprises, sharper single-name decisions, and IC-ready narratives.
Wealth & Investment Managers
Separate skill from luck with multi-period diagnostics and the multi-factor model.
Build client-fit baskets with clear objectives and real-world constraints.
Backtest to set expectations and produce factor-aware client explanations.
View all client assets—stocks, mutual funds, PMS—through one consolidated factor lens.
Result: better manager selection, goal-aligned baskets, and higher client trust.
Product & ETF Teams
Build and scale systematic strategies end-to-end.
Create alphas, optimise with clear objectives, and enforce real-world constraints.
Powered by a 40-factor India-first risk model.
Backtest on point-in-time data with costs at each step.
Monitor exposures, tracking error, and attribution live.
Achieve faster idea-to-portfolio, higher IR, lower slippage, and full auditability.
/ From first data pull to live decisions - six ways MethodTech upgrades the workflow.
Data you can defend
(point-in-time)
We store data exactly as it appears each day, with audit trails and point-in-time snapshots, so backtests and decisions remain fully reproducible and regulator-ready.
See risk before it hits P&L
Live factor and exposure dashboards flag liquidity pockets and stock-specific outliers, with a factor view that shows which stocks load onto which underlying drivers.
From idea to mandate-checked portfolio
Optimize under objectives—maximize IR, minimize variance or tracking error, target factors, or cap drawdowns—within constraints for single-name, sector, liquidity, turnover, derivatives, and benchmark bands.
Validate with history and stress
Re-run every idea on long, audited point-in-time history and event stresses to quantify robustness, reveal hidden sensitivities, and understand outcomes before real capital moves.
Explain performance, fast
Attribution across any period separates factor, sector, and stock contributions; drill from portfolio to position to clearly see which names actually drove each factor.
Built for fundamental and quant teams
No-code dashboards for PMs and risk, with Python APIs for quants, so each team works natively while staying aligned through shared data and controls.
/ About Us
MethodTech, founded in 2024, melds state-of-the-art machine-learning with rigorous quantitative finance to deliver an ML-powered operating system for institutional portfolio managers, whether they pursue systematic or fundamentally driven strategies.
Rachit Parasrampuria, a Computer Science and Economics grad from Cornell University, Rachit led Portfolio Monetization within Citadel’s Equity Quant Research team, building systematic strategies and scalable investment pipelines for multibillion dollar portfolios.
Siddhartha Kochar, an MBA from Columbia University, established and led the India business at Nova Credit and co-founded an additive manufacturing venture prior to that. He brings venture building and fundamental investing experience.
FAQs
What is MethodTech?
MethodTech is India’s first full-stack platform for systematic investing. It combines clean financial data, quant research tools, portfolio optimizers, execution infrastructure, and analytics—all in one modular SaaS platform.
Who is MethodTech built for?
We serve asset managers, PMS/AIF firms, brokers, and distributors looking to modernize their investment processes. Whether you're running complex quant strategies or advising retail clients, MethodTech offers tailored tools to fit your workflow.
Do I need a technical team to use the platform?
Not at all. MethodTech features a no-code/low-code interface designed for portfolio managers, analysts, and advisors. Quant teams can still access deeper control via code and APIs.
Can I use only specific modules of the platform?
Our entire platform is modular. We offer each component separately, in two different formats - UI and API.
Experience MethodTech,
Book a founder demo and
elevate portfolios today.
/ Join Our Newsletter
Be a part of the MethodTech network. Subscribe now to get information about updates, new releases and more.
Subscribe
Subscribe
/ Built for Systematic Investing
The quantitative layer for every portfolio
Explain returns, control risk, and optimize outcomes on one robust SaaS platform.
/ What is Systematic Investing?
A disciplined, data-driven playbook using advanced models to transform market insight into repeatable, risk-aware edge and smarter, consistent investing decisions.
/ What is MethodTech?
MethodTech is a full-stack systematic investment platform for institutional investors. Built with a practitioner-first approach and global best practices, it unifies structured data, an in-house multi-factor risk model, research & backtesting, portfolio optimization, and advanced analytics—on one robust SaaS platform.
Risk Model
Built in-house and integrated across the platform
A Risk Model sits at the
Core of Systematic Investing
What is a Risk Model?
A statistical framework that converts every position into systematic factor exposures and stock specific (idiosyncratic) risk, letting you gauge future volatility and return drivers before you trade.
Why use a Risk Model?
Decomposes each holding into Factor vs Idiosyncratic Risk.
Adjusts weights in real time to hit your target IR, instantly reflected on the dashboard.
Quantify risk in a standardised manner.
Lets you size bets, not just rupees, before they hit the blotter.
Why use a Risk Model?
Decomposes each holding into Factor vs Idiosyncratic Risk.
Adjusts weights in real time to hit your target IR, instantly reflected on the dashboard.
Quantify risk in a standardised manner.
Lets you size bets, not just rupees, before they hit the blotter.
Use Cases For
/ From first data pull to live decisions - six ways MethodTech upgrades the workflow.
Data you can defend
(point-in-time)
We store data exactly as it appears each day, with audit trails and point-in-time snapshots, so backtests and decisions remain fully reproducible and regulator-ready.
Data you can defend
(point-in-time)
We store data exactly as it appears each day, with audit trails and point-in-time snapshots, so backtests and decisions remain fully reproducible and regulator-ready.
See risk before it hits P&L
Live factor and exposure dashboards flag liquidity pockets and stock-specific outliers, with a factor view that shows which stocks load onto which underlying drivers.
See risk before it hits P&L
Live factor and exposure dashboards flag liquidity pockets and stock-specific outliers, with a factor view that shows which stocks load onto which underlying drivers.
From idea to mandate-checked portfolio
Optimize under objectives—maximize IR, minimize variance or tracking error, target factors, or cap drawdowns—within constraints for single-name, sector, liquidity, turnover, derivatives, and benchmark bands.
From idea to mandate-checked portfolio
Optimize under objectives—maximize IR, minimize variance or tracking error, target factors, or cap drawdowns—within constraints for single-name, sector, liquidity, turnover, derivatives, and benchmark bands.
Validate with history and stress
Re-run every idea on long, audited point-in-time history and event stresses to quantify robustness, reveal hidden sensitivities, and understand outcomes before real capital moves.
Validate with history and stress
Re-run every idea on long, audited point-in-time history and event stresses to quantify robustness, reveal hidden sensitivities, and understand outcomes before real capital moves.
Explain performance, fast
Attribution across any period separates factor, sector, and stock contributions; drill from portfolio to position to clearly see which names actually drove each factor.
Explain performance, fast
Attribution across any period separates factor, sector, and stock contributions; drill from portfolio to position to clearly see which names actually drove each factor.
Built for fundamental and quant teams
No-code dashboards for PMs and risk, with Python APIs for quants, so each team works natively while staying aligned through shared data and controls.
Built for fundamental and quant teams
No-code dashboards for PMs and risk, with Python APIs for quants, so each team works natively while staying aligned through shared data and controls.
/ About Us
MethodTech, founded in 2024, melds state-of-the-art machine-learning with rigorous quantitative finance to deliver an ML-powered operating system for institutional portfolio managers, whether they pursue systematic or fundamentally driven strategies.
Rachit Parasrampuria, a Computer Science and Economics grad from Cornell University, Rachit led Portfolio Monetization within Citadel’s Equity Quant Research team, building systematic strategies and scalable investment pipelines for multibillion dollar portfolios.
Siddhartha Kochar, an MBA from Columbia University, established and led the India business at Nova Credit and co-founded an additive manufacturing venture prior to that. He brings venture building and fundamental investing experience.
FAQs
What is MethodTech?
MethodTech is India’s first full-stack platform for systematic investing. It combines clean financial data, quant research tools, portfolio optimizers, execution infrastructure, and analytics—all in one modular SaaS platform.
Who is MethodTech built for?
We serve asset managers, PMS/AIF firms, brokers, and distributors looking to modernize their investment processes. Whether you're running complex quant strategies or advising retail clients, MethodTech offers tailored tools to fit your workflow.
Do I need a technical team to use the platform?
Not at all. MethodTech features a no-code/low-code interface designed for portfolio managers, analysts, and advisors. Quant teams can still access deeper control via code and APIs.
Can I use only specific modules of the platform?
Our entire platform is modular. We offer each component separately, in two different formats - UI and API.
What is MethodTech?
MethodTech is India’s first full-stack platform for systematic investing. It combines clean financial data, quant research tools, portfolio optimizers, execution infrastructure, and analytics—all in one modular SaaS platform.
Who is MethodTech built for?
We serve asset managers, PMS/AIF firms, brokers, and distributors looking to modernize their investment processes. Whether you're running complex quant strategies or advising retail clients, MethodTech offers tailored tools to fit your workflow.
Do I need a technical team to use the platform?
Not at all. MethodTech features a no-code/low-code interface designed for portfolio managers, analysts, and advisors. Quant teams can still access deeper control via code and APIs.
Can I use only specific modules of the platform?
Our entire platform is modular. We offer each component separately, in two different formats - UI and API.
Experience MethodTech,
Book a founder demo and
elevate portfolios today.
/ Join Our Newsletter
Be a part of the MethodTech network. Subscribe now to get information about updates, new releases and more.
Subscribe
Subscribe
Subscribe
Subscribe
/ Use Cases
Quant PMs & Research Teams
Quant PMs & Research Teams
Build and scale systematic strategies end-to-end.
Create alphas, optimise with clear objectives, and enforce real-world constraints.
Powered by a 40-factor India-first risk model.
Backtest on point-in-time data with costs at each step.
Monitor exposures, tracking error, and attribution live.
Achieve faster idea-to-portfolio, higher IR, lower slippage, and full auditability.
Build and scale systematic strategies end-to-end.
Create alphas, optimise with clear objectives, and enforce real-world constraints.
Powered by a 40-factor India-first risk model.
Backtest on point-in-time data with costs at each step.
Monitor exposures, tracking error, and attribution live.
Achieve faster idea-to-portfolio, higher IR, lower slippage, and full auditability.
Fundamental PMs & Analysts
Fundamental PMs & Analysts
Identify true stock-specific returns by separating market/style effects.
Track each name’s real drivers and remove unintended factor exposures.
Use position limits, idiosyncratic controls, and factor bands to preserve conviction.
Backtest hedge or sizing tweaks and see immediate impact on drawdowns and capture.
Result: cleaner alpha, fewer style surprises, sharper single-name decisions, and IC-ready narratives.
Identify true stock-specific returns by separating market/style effects.
Track each name’s real drivers and remove unintended factor exposures.
Use position limits, idiosyncratic controls, and factor bands to preserve conviction.
Backtest hedge or sizing tweaks and see immediate impact on drawdowns and capture.
Result: cleaner alpha, fewer style surprises, sharper single-name decisions, and IC-ready narratives.
Wealth & Investment Managers
Wealth & Investment Managers
Separate skill from luck with multi-period diagnostics and the multi-factor model.
Build client-fit baskets with clear objectives and real-world constraints.
Backtest to set expectations and produce factor-aware client explanations.
View all client assets—stocks, mutual funds, PMS—through one consolidated factor lens.
Result: better manager selection, goal-aligned baskets, and higher client trust.
Separate skill from luck with multi-period diagnostics and the multi-factor model.
Build client-fit baskets with clear objectives and real-world constraints.
Backtest to set expectations and produce factor-aware client explanations.
View all client assets—stocks, mutual funds, PMS—through one consolidated factor lens.
Result: better manager selection, goal-aligned baskets, and higher client trust.
Product & ETF Teams
Product & ETF Teams
Build and scale systematic strategies end-to-end.
Create alphas, optimise with clear objectives, and enforce real-world constraints.
Powered by a 40-factor India-first risk model.
Backtest on point-in-time data with costs at each step.
Monitor exposures, tracking error, and attribution live.
Achieve faster idea-to-portfolio, higher IR, lower slippage, and full auditability.
Build and scale systematic strategies end-to-end.
Create alphas, optimise with clear objectives, and enforce real-world constraints.
Powered by a 40-factor India-first risk model.
Backtest on point-in-time data with costs at each step.
Monitor exposures, tracking error, and attribution live.
Achieve faster idea-to-portfolio, higher IR, lower slippage, and full auditability.
/ Built for Systematic Investing
The quantitative layer for every portfolio
Explain returns, control risk, and optimize outcomes on one robust SaaS platform.
/ What is Systematic Investing?
A disciplined, data-driven playbook using advanced models to transform market insight into repeatable, risk-aware edge and smarter, consistent investing decisions.
/ What is MethodTech?
MethodTech is a full-stack systematic investment platform for institutional investors. Built with a practitioner-first approach and global best practices, it unifies structured data, an in-house multi-factor risk model, research & backtesting, portfolio optimization, and advanced analytics—on one robust SaaS platform.
Risk Model
Built in-house and integrated across the platform
A Risk Model sits at the
Core of Systematic Investing
What is a Risk Model?
A statistical framework that converts every position into systematic factor exposures and stock specific (idiosyncratic) risk, letting you gauge future volatility and return drivers before you trade.
Why use a Risk Model?
Decomposes each holding into Factor vs Idiosyncratic Risk.
Adjusts weights in real time to hit your target IR, instantly reflected on the dashboard.
Quantify risk in a standardised manner.
Lets you size bets, not just rupees, before they hit the blotter.
Why use a Risk Model?
Decomposes each holding into Factor vs Idiosyncratic Risk.
Adjusts weights in real time to hit your target IR, instantly reflected on the dashboard.
Quantify risk in a standardised manner.
Lets you size bets, not just rupees, before they hit the blotter.
Use Cases For
/ From first data pull to live decisions - six ways MethodTech upgrades the workflow.
Data you can defend
(point-in-time)
We store data exactly as it appears each day, with audit trails and point-in-time snapshots, so backtests and decisions remain fully reproducible and regulator-ready.
Data you can defend
(point-in-time)
We store data exactly as it appears each day, with audit trails and point-in-time snapshots, so backtests and decisions remain fully reproducible and regulator-ready.
Expose Hidden Risks before They Hit P&L
Real-time factor tilts, ownership metrics, and idiosyncratic flags highlight vulnerabilities early, so managers can neutralise blind spots instead of explaining losses.
Expose Hidden Risks before They Hit P&L
Real-time factor tilts, ownership metrics, and idiosyncratic flags highlight vulnerabilities early, so managers can neutralise blind spots instead of explaining losses.
From idea to mandate-checked portfolio
Optimize under objectives—maximize IR, minimize variance or tracking error, target factors, or cap drawdowns—within constraints for single-name, sector, liquidity, turnover, derivatives, and benchmark bands.
From idea to mandate-checked portfolio
Optimize under objectives—maximize IR, minimize variance or tracking error, target factors, or cap drawdowns—within constraints for single-name, sector, liquidity, turnover, derivatives, and benchmark bands.
Validate with history and stress
Re-run every idea on long, audited point-in-time history and event stresses to quantify robustness, reveal hidden sensitivities, and understand outcomes before real capital moves.
Validate with history and stress
Re-run every idea on long, audited point-in-time history and event stresses to quantify robustness, reveal hidden sensitivities, and understand outcomes before real capital moves.
Explain performance, fast
Attribution across any period separates factor, sector, and stock contributions; drill from portfolio to position to clearly see which names actually drove each factor.
Explain performance, fast
Attribution across any period separates factor, sector, and stock contributions; drill from portfolio to position to clearly see which names actually drove each factor.
Empower Fundamental Desks without Extra Headcount, while Quants Keep Their APIs
No-code dashboards deliver factor insight to fundamental PMs; Python endpoints slot straight into quant pipelines, everyone works in their native habitat with zero heavy lifting.
Empower Fundamental Desks without Extra Headcount, while Quants Keep Their APIs
No-code dashboards deliver factor insight to fundamental PMs; Python endpoints slot straight into quant pipelines, everyone works in their native habitat with zero heavy lifting.
/ About Us
MethodTech, founded in 2024, melds state-of-the-art machine-learning with rigorous quantitative finance to deliver an ML-powered operating system for institutional portfolio managers, whether they pursue systematic or fundamentally driven strategies.
Rachit Parasrampuria, a Computer Science and Economics grad from Cornell University, Rachit led Portfolio Monetization within Citadel’s Equity Quant Research team, building systematic strategies and scalable investment pipelines for multibillion dollar portfolios.
Siddhartha Kochar, an MBA from Columbia University, Siddhartha established and led the India business for a global credit infrastructure firm and previously co-founded an additive manufacturing venture. He brings fundamental investing experience of over a decade.
FAQs
What is MethodTech?
MethodTech is India’s first full-stack platform for systematic investing. It combines clean financial data, quant research tools, portfolio optimizers, execution infrastructure, and analytics—all in one modular SaaS platform.
Who is MethodTech built for?
We serve asset managers, PMS/AIF firms, brokers, and distributors looking to modernize their investment processes. Whether you're running complex quant strategies or advising retail clients, MethodTech offers tailored tools to fit your workflow.
Do I need a technical team to use the platform?
Not at all. MethodTech features a no-code/low-code interface designed for portfolio managers, analysts, and advisors. Quant teams can still access deeper control via code and APIs.
Can I use only specific modules of the platform?
Our entire platform is modular. We offer each component separately, in two different formats - UI and API.
What is MethodTech?
MethodTech is India’s first full-stack platform for systematic investing. It combines clean financial data, quant research tools, portfolio optimizers, execution infrastructure, and analytics—all in one modular SaaS platform.
Who is MethodTech built for?
We serve asset managers, PMS/AIF firms, brokers, and distributors looking to modernize their investment processes. Whether you're running complex quant strategies or advising retail clients, MethodTech offers tailored tools to fit your workflow.
Do I need a technical team to use the platform?
Not at all. MethodTech features a no-code/low-code interface designed for portfolio managers, analysts, and advisors. Quant teams can still access deeper control via code and APIs.
Can I use only specific modules of the platform?
Our entire platform is modular. We offer each component separately, in two different formats - UI and API.
Experience MethodTech,
Book a founder demo and
elevate portfolios today.
/ Join Our Newsletter
Be a part of the MethodTech network. Subscribe now to get information about updates, new releases and more.
Subscribe
Subscribe
Subscribe
Subscribe
/ Use Cases
Quant PMs & Research Teams
Quant PMs & Research Teams
Build and scale systematic strategies end-to-end.
Create alphas, optimise with clear objectives, and enforce real-world constraints.
Powered by a 40-factor India-first risk model.
Backtest on point-in-time data with costs at each step.
Monitor exposures, tracking error, and attribution live.
Achieve faster idea-to-portfolio, higher IR, lower slippage, and full auditability.
Build and scale systematic strategies end-to-end.
Create alphas, optimise with clear objectives, and enforce real-world constraints.
Powered by a 40-factor India-first risk model.
Backtest on point-in-time data with costs at each step.
Monitor exposures, tracking error, and attribution live.
Achieve faster idea-to-portfolio, higher IR, lower slippage, and full auditability.
Fundamental PMs & Analysts
Fundamental PMs & Analysts
Identify true stock-specific returns by separating market/style effects.
Track each name’s real drivers and remove unintended factor exposures.
Use position limits, idiosyncratic controls, and factor bands to preserve conviction.
Backtest hedge or sizing tweaks and see immediate impact on drawdowns and capture.
Result: cleaner alpha, fewer style surprises, sharper single-name decisions, and IC-ready narratives.
Identify true stock-specific returns by separating market/style effects.
Track each name’s real drivers and remove unintended factor exposures.
Use position limits, idiosyncratic controls, and factor bands to preserve conviction.
Backtest hedge or sizing tweaks and see immediate impact on drawdowns and capture.
Result: cleaner alpha, fewer style surprises, sharper single-name decisions, and IC-ready narratives.
Wealth & Investment Managers
Wealth & Investment Managers
Separate skill from luck with multi-period diagnostics and the multi-factor model.
Build client-fit baskets with clear objectives and real-world constraints.
Backtest to set expectations and produce factor-aware client explanations.
View all client assets—stocks, mutual funds, PMS—through one consolidated factor lens.
Result: better manager selection, goal-aligned baskets, and higher client trust.
Separate skill from luck with multi-period diagnostics and the multi-factor model.
Build client-fit baskets with clear objectives and real-world constraints.
Backtest to set expectations and produce factor-aware client explanations.
View all client assets—stocks, mutual funds, PMS—through one consolidated factor lens.
Result: better manager selection, goal-aligned baskets, and higher client trust.
Product & ETF Teams
Product & ETF Teams
Build and scale systematic strategies end-to-end.
Create alphas, optimise with clear objectives, and enforce real-world constraints.
Powered by a 40-factor India-first risk model.
Backtest on point-in-time data with costs at each step.
Monitor exposures, tracking error, and attribution live.
Achieve faster idea-to-portfolio, higher IR, lower slippage, and full auditability.
Build and scale systematic strategies end-to-end.
Create alphas, optimise with clear objectives, and enforce real-world constraints.
Powered by a 40-factor India-first risk model.
Backtest on point-in-time data with costs at each step.
Monitor exposures, tracking error, and attribution live.
Achieve faster idea-to-portfolio, higher IR, lower slippage, and full auditability.