***Under development***

Table of Contents

  • Investment Approach

    • Investor Profile

    • Investment Objective

  • Investment Strategy

    • Investment Philosophy

    • Quantitative Investing

  • Investment System

    • Technical Indicators

    • Data Science Model

    • Technical Analysis

  • Capital Allocation Strategy

    • Risk Management

  • Subscription Service(s)

    • Dashboards

    • Indicators

    • Alerts

  • Disclaimer

Investment Approach

Investor Profile

The AlphiQuant dashboard is about its Quantitative Investing & Algorithmic Trading system geared towards HNW investors, family offices, private investment groups, and sophisticated investors with a similar mindset. These types of investors understand the importance of capital allocation and risk management strategies.

Investment Objective

The quant based system employs a strategic approach prioritizing low time preference and focuses on patiently building long term wealth. The system helps establish long term investment positions buy buying at opportune times while simultaneously position trading the same assets in attempts to capture significant price increases and avoid large drawdowns. Breakout trades are also executed when high probability opportunities present themselves.

Investment Strategy

Investment Philosophy

Combining Fundamental, Technical, and Quantitative analysis is an investing edge trifecta. AlphiQuant performs fundamental analysis to develop a thesis regarding the asset and then relies upon an emotionless mathematical system that is comprised of technical and quantitative metrics. Price action is paramount and the system is implemented with conviction, discipline, and an unbiased perspective.

Quantitative Investing

Quant investing involves both art and science utilizing data, information, and mathematical models to develop a structured rules-based decision making process. This method helps remove the emotional aspect of investing by trusting the math leading to minimizing losses and maximizing profits.

Investment System

This quant based system is a proprietary dashboard comprised of a suite of technical indicators and a financial data science model. Together, they help identify the following based on high timeframe setups:

  • Trends and Reversals

  • Momentum

  • State of Asset

  • Stage Analysis

  • Breakouts via volatility contraction patterns (VCP)

  • Position trading entries and exits

  • Opportunistic value investments focused on technology assets that exhibit network effects

Technical Indicators

The technical indicators analyze price action of assets through a mathematical lens with an emphasis on an intermediate to long term investment time horizon. State of the asset is identified across various timeframes (i.e. State of Recovery, Accumulation, Bullish, Caution, Distribution, Bearish). Within the asset state, momentum, trend, and risk indicators are monitored for potential trend reversals and associated entry and exit points concentrating on capturing large market moves. For all indicators, higher timeframe analysis statistically yields greater accuracy.

Example of asset state for S&P 500 ($SPX):

S&P 500 - Daily chart w/ State indicator (plus Trend, Momentum)
  • Started 2022 in a bullish (green) state

  • During Q1 identified a state of caution (yellow) followed by state of distribution (fuchsia)

  • Identified states of both recovery (white) and brief accumulation (blue), but they ended up being bear market bounces never advancing to a bullish (green) state.

  • Attempts to break the downtrend in 2022 eventually returned to a bearish (red) state where $SPX ended the year

$SPX with states across multiple timeframes:

S&P 500 - Multi-Timeframe chart (4h, 12h, 1D, 3D, 1W, 2W, 3W, 1M)

Lower timeframes can provide insight to potential trend reversals for the more aggressive investor. The higher timeframes, particularly the 3-day & 1-week, are a good gauge for taking action for more conservative high probability investors.

AlphiQuant Dashboard comprised of proprietary suite of indicators:

  • State Analysis

  • Stage Analysis

  • Bull Market Ribbon (BMR)

  • Trend Meter

  • Trend Model

  • Momentum Meter

  • Momentum Ribbon

  • Deflection Risk Meter (DRM)

  • Digital Asset Dashboards (including Data Science Model):

    • ₿itcoin Dashboard

    • Ethereum Dashboard

Data Science Model

The quantitative financial data science model is primarily based upon Metcalfe’s Law along with other mathematical principles related to exponential growth and on-chain data from glassnode. The network value quant model identifies potentially opportunistic moments to increase long term core investment positions during bull markets and potentially asymmetric investment opportunities during bear markets.

Over the long haul, for assets that exhibit network effects (especially technology related), the valuation models based on data science tend to lead the ones based on traditional finance. These types of valuation models are most useful in bear markets for setting the price floor. Market structure and flow dynamics determine end-state prices at top of bull markets.

Technical Analysis

Classical charting technical analysis techniques supplement the quant system identifying simple, yet elegant, setups that yield the most accurate results based on probabilities and statistics.

Note: The quantitative investment system is implemented in the spot markets avoiding margin, debt, leverage, derivatives, and financially engineered products of any kind.

Capital Allocation Strategy

AlphiQuant manages a concentrated investment portfolio. A core investment position comprising of a few assets is established and held for long term capital appreciation. Simultaneously, these same assets are position traded on a high timeframe basis. Other assets are also opportunistically traded in anticipation of breakouts leveraging stage analysis and VCP setups.

For assets with potential for exponential growth, asymmetric risk/reward, and high volatility (i.e. high α with high β), the following capital allocation profile is established:

Risk Management

The number of assets and portfolio ratio of investment to trading is the discretion of the money manager whose risk profile will differ based upon their investing style and parameters.

Subscription Service(s)

In the future, @AlphiQuant may elect to provide subscription services to TradingView dashboards, indicators, and/or position trading alerts.

Trade Ideas



*** AlphiQuant publishes its research & analysis for purely educational purposes and is not licensed to provide financial advice nor is it registered with any financial regulatory body. Perform your own research and consult your financial advisor for investment advice. ***

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Quantitative Investing & Algorithmic Trading



Quantitative Investing • Algorithmic Trading • Technical Analysis • Financial Data Science • Computer Engineer • @MIT_alumni #Equities #DigitalAssets