Apply dimensionality reduction techniques to see patterns in data and identify profit opportunities in real time. Visualize embeddings in the data and pick coloring criteria to see groupings.

Apply dimensionality reduction to extract patterns in the data. One point is one day. More exactly the 2D embedding of the market context related to that day. A market context is a multi-dimensional characteristic regrouping info about vol surface, long-short term past market trends in terms of spot, volatility, etc. ... Relative positioning of points in the graphic gives info about how similar market context are between each other. Mapping a PnL criteria as a colormap gives insights on how a particular product performed in similar market contexts.

Currencies: Select cryptocurrency.

Texp: Select time to expiration (in days).

Color scheme: assign color scheme to differentiate based on time, clustering, term regime (contango or backwardation), profitability of a long risk reversal, and profitability of a long straddle.

PnL RR: Backtested performance for risk reversal strategy (can select Buy/Sell).

PnL Straddle: Backtested performance for straddle/strangle strategy (can select Buy/Sell).

Moneyness (% change): Change in strike price (negative for the put and positive for the call) as a percentage relative to spot/ATM strike (i.e. the current value of the underlier). Relevant for risk reversal and straddle/strangle.

Direction: Select buy or sell from PnL RR and PnL Straddle.

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