Capital Management Platform with Machine Learning.
Grow with Confidence.

SaaS capital management

Make Better Decisions when It Counts

Our Capital Management Platform not only streamline management and optimization processes, but we also build trust. By focusing on rule-based approaches, professional users built stronger principles with higher levels of capability and consistency. As a result, stronger advisory relationships were formed. A great decision tree is built by many good decisions, start making yours today.

Build Scientific Process with Machine Learning

Capital Management Platform

Collect Data

Modeling on Cloud

modeling

Analyze & Test

Momentum

Manage & Execute

Synertree April Report Card

Solutions

Integrate sciences into your capital management process. Focus on the BIG picture.

Optimize asset allocation

Set up asset allocation rules and keep the portfolio running as you intended. Reblance investment portfolios according to the total risk metrics or individual asset risk levels. Optimize asset allocations for the portfolio based on risk or risk adjusted return metrics.

Minimize fixed costs

Lower your infrastructure cost to — Zero. Portfolio managers can simply initiate and quickly scale immediately. All while keeping their overhead costs low. Updates and maintenance are automatic. Run your portfolio management practice with less headaches and more powers.

Manage risks with data

Risks can happen without a warning. A systematic risk management approach is required to keep your portfolios in check. The risk engine automatically provides updates on the dollar amount that is at risk. Instead of approximating risks, portfolio managers can monitor portfolio volatility and asset price risks on the dashboard.

Engage with visual results

Our capital management software are built with your clients in mind.  We combine data and behavioural science to generate quality inputs and meaningful insights for your clients’ financial goals. Focus on client engagement and let the automated system guides the discovery process.

Integrate familiar technologies

Use your data to enrich your portfolio management practice. Works with Factset, Microsoft Excel and CSV, Interactive Brokers. Analyze your past performances and draw down risks. Build, test, and optimize trading strategies based on different technical rules.

Generate signals and act

Visualize how a trade could affect the portfolio risk quantum — before you make the trade. With data science, you can preview risks using historical data, allowing you to better manage your compulsions and respond to risks orderly and systematically. Market is always unpredictable; your actions don’t have to be.

Technical Features

Data Analytics & Visualization
Data plotting with Java scripts, Python lib, and Excel
Multi-level vectorization for super fast simulations
Task and schedule automation
Python Scikit-learn and Numpy for data analytics and machine learning

Quantitative Finance
Functional and non functional programming
Structured arrays for asset allocation
Financial time series modeling and regression analysis
Parallel computing and the Monte Carlo Algorithm
Constrained optimizations

Security Data Management
Historical EOD data for North American ETFs and Stocks
Fundamental data for stocks
Cloud-based interface built by Django
Security data management with Postgres database
Generate and export stock data in CSV

Helping Professionals helping others

Fund Manager
Risk Management

Price Simulations

Backtesting

Equity Analysis

Momentum tests

Portfolio Manager
Asset optimizations

Risk Analysis

Financial profiling

Equity Research

ETF management

Chief Investment Officer
Data-driven Modeling

Event-driven Modeling

Hedging Strategies

Risk Analytics

Model Management

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