Fund Characteristics

Fund Size

At Damora Capital, Ideal size of the AUM is 1-2b$. Maximum amount of assets that we will manage would be upto 10b$. The reason behind this is to provide a reasonable Return on Investment on the managed assets. Also, It is possible to identify several opportunities for this fund size. When the fund size is big enough, the options available for investment with better returns would be far lesser.

Our unique value proposition

  1. Our investment planning, strategy and trade execution – each individually follow the 3P philosophy of Quality. (People, Process and Performance management)
  2. Use technology across the business operations
    1. Market research
      1. Use data science methods based market research and signals generation for short and medium term strategy
      2. Build correlation of attributes in time frames for asset price prediction and volatility levels
    2. Capital growth activities
      1. Use mathematical models and data science based decision making to generate trade signals
      2. Use algorithmic trading
      3. Use ML based monitoring to decide trade close
    3. Risk management
      1.  data science methods for risk management, portfolio construction and, trading
    4. Human Resource evaluation
      1. Use tools to measure the performance of “Contracted consultants”, “Advisors” and “Data science employees”, “Traders”
    5. Capital growth Monitoring
      1. Use tools to Monitor and measure the process quality from “Data gathering”, “Analysis”, “Trade execution” & ”Trade Review”
      2. Use tools to measure the quality of “Capital allocation”, “Risk management”
  3. Strategic Planning and Investor newsletter at the beginning of each year
  4. Team hiring policy is based on 
    1. { past proven expertise, consistency and clarity, profit-sharing and consulting approach }
    2. {Expertise in computer science, mathematical models, risk management, statistics, AI/ML, creativity, investigative mindset}
  5. Business Culture { expertise in role, ability to learn, professional work ethics, independence, excellence, integrity, learning from mistakes, stakeholder satisfaction being socially responsible}
  6. Collaboration
    1. Share and receive unique insights and market research with other experts with a technology platform. 
    2. Build relationships to leverage the capital when needed from the capital partners 

Portfolio Planning

  1. Define the financial goals for the short term and long term
  2. Define the risks and volatility the firm is willing to take on and the returns to be generated
  3. Define the risk-return profile and benchmarks to track portfolio performance
  4. Create an asset allocation strategy which is both diversified and structured for maximum returns
  5. Monitor the investment and trades to reassess goals quarterly and trades monthly
  6. Combine several strategies to increase the risk adjusted return of the Portfolio
    1. Use the positive effect of minimally correlated strategies
  7. Having at least one strategy in a portfolio to benefit from times, when markets go up, when markets go down and when markets go through stress.
  8. Utilize time horizon diversification (Have strategies in your portfolio with holding periods ranging from short term (a couple of days), intermediate term (weeks to months) and long term (month to years)
  9. Systematically combine fundamental analysis, technical analysis and quantitative analysis.
  10. Trade strategies that are based on inherent human behavioral biases.

Quantitative Trading

  1. Implementation of Trading strategies in a disciplined and systematic manner
    1. Research (quantitative analysis) 
    2. Risk exposure
    3. Back testing
    4. Automatic or Manual trading via MetaTrader or Alpaca  API 
  2. Trading Strategies
    1. Momentum
      1. Quantitative methods or technical indicators (Buy or sell based on market trends based on statistics of historical data or current data)
    2. Mean reversion (markets are ranging 80% of the time, determine the price, based on the historical price)
    3. Market making (make money out of bid and ask spread, and provide liquidity)
    4. Statistical Arbitraging 
      1. Statistical mispricing of one or more assets based on the expected value of these assets
      2. Pairs trading. (underperforming assets is expected to rise and the outperforming asset is expected to decline in value)
    5. Sentiment based
      1. Gather the news information from sources like CNBC, Reuters, Financial news and Others
      2. Preprocess these data
      3. Quantify the information
      4. Understand market consensus on previous information
      5. If sentiment is bullish, then buy otherwise sell

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