Methodology
Discretionary multi-asset medium to low frequency allocation of capital based on fundamental
and quantitative analysis with a focus on mispriced asymmetric upside opportunities.
Process
Macro Event Calendar - for significant releases check market consensus and
positioning concentration
Earnings Calendar - use surprises for idea generation across sector or related
instruments
Insider Trades - check for CEO or cluster buys and potential driving factors,
as well as suspicious option trades volume
Congress Trades - check for trades on privileged information
Bloomberg, The Economist, FT, WSJ, CNBC: Check consensus market views and common
knowledge factual updates, taking care not to follow market move attributions without
independent analysis and confirmation
Google Trends, Facebook, Instagram, X and YouTube - check for new upcoming trends or sentiment
changes, and news not yet reported by mainstream media
Single stocks should have positive earnings trajectory and be net profitable. PE ratio should
not be abnormally high to comparables without a specific driver. Core business should
possess uncapped upside (e.g. not simple rent-collection).
Indices are assessed as macro instruments, used to express view on country and economy
fundamentals or persistent flows based on broader sentiment. This type of trade should aim
to be beta neutral.
Any other alternative data is also assessed during the research process as well as
throughout the holding period.
The assessment of fundamentals should be the primary source of alpha.
Used to provide a broad characterization of the behavior of the instrument based on
momentum vs. reversion, drawdowns, realized volatility and other price or fundamentals
distribution statistics. Can also be used alongside long-term charts to aid in the
determination of price levels of interest but should generally not be used to make predictions
or as a trade signal directly.
Views in which a position is taken must be high conviction. If this is not followed low
confidence in the position will cause self-doubt and skew to premature profit-taking or
stop-out.
Thesis for positions must be documented in detail, including expected upside drivers,
downside risks and stop/pause or take profit criterion during the life cycle of the trade.
Do not chase the market for a quick win or take positions dependent on speedy
execution, given negative edge over other market participants such as HFTs: Empirical observations
of market reactions to new information suggest three core stages:
1) Initial move on wrong-side positioning stop-loss/negative gamma related orders combined with
pulling of wrong-side liquidity.
2) Slowdown or partial reversal on right-side participant profit taking or data significance
skepticism e.g. 'fading'. This stage could offer temporary price stability and liquidity for
positioning.
3) Continuation or reversal of the initial move from re-pricing based on the true value of the new
information.
Entries and exits must be based on at least one other factor in addition to price.
Proprietary multi-purpose Python-based suite with functionality including:
Signal generation and strategy backtesting: Pandas, sk-learn
Data terminal GUI including index composition download through custom API: tkinter,
selenium, pythoncom (threading), GIT (version control)
Historical and fundamental data download and storage: IBKR and Yahoo Finance APIs.
Historical, descriptive, index composition and symbol mapping data database maintainance:
xlwings (csv)
Website development for easy resource accesibility and maintenance: HTML, CSS, JavaScript