Modelling

Interpreting

Executing

Modelling

Interpreting

Executing

LOREM IPSUM DOLOR

Quant-driven and R&D heavy on the back, on the front, we are invisible.

Companies we own to spot anomalies and further incubate and accelerate them as in-house residents on our trading desk, or out-house are Ufunded.com and Campus.Fund.

Our Al, ML and DL deep-tech trinity enables us to not only detect anomalies in real-time, it also allows us to give real-time score ratings to potentials, who in any other scenario might never be discovered.

Plotting Data

LOREM IPSUM DOLOR

Quant-driven and R&D heavy on the back, on the front, we are invisible.

Companies we own to spot anomalies and further incubate and accelerate them as in-house residents on our trading desk, or out-house are Ufunded.com and Campus.Fund.

Our Al, ML and DL deep-tech trinity enables us to not only detect anomalies in real-time, it also allows us to give real-time score ratings to potentials, who in any other scenario might never be discovered.

Plotting Data

Quant-driven, Deep-Tech Trading Institution

Our deep-tech trinity consists of machine learning, deep learning and artificial intelligence. This quantitative trinity enables us to model real-time data derived from our ecosystem where human traders (users) function as indicators, ultimately defining our edge. Cypher executes both discretionary and algorithmic strategies based on our proprietary model's Confidence.

Plotting Data

Building

Building

Quant-driven and R&D heavy on the back, on the front, we are invisible.

Companies we own to spot anomalies and further incubate and accelerate them as in-house residents on our trading desk, or out-house are Ufunded.com and Campus.Fund.

Our Al, ML and DL deep-tech trinity enables us to not only detect anomalies in real-time, it also allows us to give real-time score ratings to potentials, who in any other scenario might never be discovered.

Quant-driven and R&D heavy on the back, on the front, we are invisible.

Companies we own to spot anomalies and further incubate and accelerate them as in-house residents on our trading desk, or out-house are Ufunded.com and Campus.Fund.

Our Al, ML and DL deep-tech trinity enables us to not only detect anomalies in real-time, it also allows us to give real-time score ratings to potentials, who in any other scenario might never be discovered.

Plotting Data

LOREM IPSUM DOLOR

Quant-driven and R&D heavy on the back, on the front, we are invisible.

Companies we own to spot anomalies and further incubate and accelerate them as in-house residents on our trading desk, or out-house are Ufunded.com and Campus.Fund.

Our Al, ML and DL deep-tech trinity enables us to not only detect anomalies in real-time, it also allows us to give real-time score ratings to potentials, who in any other scenario might never be discovered.

Plotting Data

Building

Building

Turning Real-Time Trading
Into Our Real-Time Edge

Quantitative interpretation of real-time data points combined with algorithmic execution.

Subject

Chameleon

Anomaly

{

"tail_risk": "analysing",

"multi_asset": "analysing",

"probability": "unknown",

"model_certainty": "building",

"volatility_index": "unknown"

},

"volatility_index": 18.5,

"moving_average_convergence_divergence": {

"macd_value": 1.2,

"signal_line": 0.9,

"status": "bullish"

},

"relative_strength_index": 62,

"price_to_earnings_ratio": 22.3,

"beta_coefficient": 1.1,

"dividend_yield": 2.5,

"liquidity_risk": "low",

"market_sentiment": "neutral",

"status": "extracted",

"datasource": "real-time",

"execution": "immediate"

}

{

"tail_risk": "analysing",

"multi_asset": "analysing",

"probability": "unknown",

"model_certainty": "building",

"volatility_index": "unknown"

},

"volatility_index": 18.5,

"moving_average_convergence_divergence": {

"macd_value": 1.2,

"signal_line": 0.9,

"status": "bullish"

},

"relative_strength_index": 62,

"price_to_earnings_ratio": 22.3,

"beta_coefficient": 1.1,

"dividend_yield": 2.5,

"liquidity_risk": "low",

"market_sentiment": "neutral",

"status": "extracted",

"datasource": "real-time",

"execution": "immediate"

}

{

"tail_risk": “random”,
"multi_asset": “yes”,

"probability": "0,1",
"output": "chameleon",

"volatility_index": "30%"

},

"volatility_index": 18.5,

"moving_average_convergence_divergence": {

"macd_value": 1.2,

"signal_line": 0.9,

"status": "bullish"

},

"relative_strength_index": 62,

"price_to_earnings_ratio": 22.3,

"beta_coefficient": 1.1,

"dividend_yield": 2.5,

"liquidity_risk": "low",

"market_sentiment": "neutral",

"status": "extracted",

"datasource": "real-time",

"execution": "immediate"

}

{

"tail_risk": “random”,
"multi_asset": “yes”,

"probability": "0,1",
"output": "chameleon",

"volatility_index": "30%"

},

"volatility_index": 18.5,

"moving_average_convergence_divergence": {

"macd_value": 1.2,

"signal_line": 0.9,

"status": "bullish"

},

"relative_strength_index": 62,

"price_to_earnings_ratio": 22.3,

"beta_coefficient": 1.1,

"dividend_yield": 2.5,

"liquidity_risk": "low",

"market_sentiment": "neutral",

"status": "extracted",

"datasource": "real-time",

"execution": "immediate"

}

{

"tail_risk": "none",

"multi_asset_correlation": "safe",

"max_drawdown_periodically": {

"probability": 1,

"output": "anomaly",

"model_certainty": 90

},

"volatility_index": 18.5,

"moving_average_convergence_divergence": {

"macd_value": 1.2,

"signal_line": 0.9,

"status": "bullish"

},

"relative_strength_index": 62,

"price_to_earnings_ratio": 22.3,

"beta_coefficient": 1.1,

"dividend_yield": 2.5,

"liquidity_risk": "low",

"market_sentiment": "neutral",

"status": "extracted",

"datasource": "real-time",

"execution": "immediate"

}

{
"tail_risk": "none",
"multi_asset_correlation": "safe",
"max_drawdown_periodically": {
"probability": 1,
"output": "anomaly",
"model_certainty": 90
},
"volatility_index": 18.5,
"moving_average_convergence_divergence": {
"macd_value": 1.2,
"signal_line": 0.9,
"status": "bullish"
},
"relative_strength_index": 62,
"price_to_earnings_ratio": 22.3,
"beta_coefficient": 1.1,
"dividend_yield": 2.5,
"liquidity_risk": "low",
"market_sentiment": "neutral",
"status": "extracted",
"datasource": "real-time",
"execution": "immediate"
}

Subject

Chameleon

Anomaly

{

"tail_risk": "analysing",

"multi_asset": "analysing",

"probability": "unknown",

"model_certainty": "building",

"volatility_index": "unknown"

},

"volatility_index": 18.5,

"moving_average_convergence_divergence": {

"macd_value": 1.2,

"signal_line": 0.9,

"status": "bullish"

},

"relative_strength_index": 62,

"price_to_earnings_ratio": 22.3,

"beta_coefficient": 1.1,

"dividend_yield": 2.5,

"liquidity_risk": "low",

"market_sentiment": "neutral",

"status": "extracted",

"datasource": "real-time",

"execution": "immediate"

}

{

"tail_risk": "analysing",

"multi_asset": "analysing",

"probability": "unknown",

"model_certainty": "building",

"volatility_index": "unknown"

},

"volatility_index": 18.5,

"moving_average_convergence_divergence": {

"macd_value": 1.2,

"signal_line": 0.9,

"status": "bullish"

},

"relative_strength_index": 62,

"price_to_earnings_ratio": 22.3,

"beta_coefficient": 1.1,

"dividend_yield": 2.5,

"liquidity_risk": "low",

"market_sentiment": "neutral",

"status": "extracted",

"datasource": "real-time",

"execution": "immediate"

}

{

"tail_risk": “random”,
"multi_asset": “yes”,

"probability": "0,1",
"output": "chameleon",

"volatility_index": "30%"

},

"volatility_index": 18.5,

"moving_average_convergence_divergence": {

"macd_value": 1.2,

"signal_line": 0.9,

"status": "bullish"

},

"relative_strength_index": 62,

"price_to_earnings_ratio": 22.3,

"beta_coefficient": 1.1,

"dividend_yield": 2.5,

"liquidity_risk": "low",

"market_sentiment": "neutral",

"status": "extracted",

"datasource": "real-time",

"execution": "immediate"

}

{

"tail_risk": “random”,
"multi_asset": “yes”,

"probability": "0,1",
"output": "chameleon",

"volatility_index": "30%"

},

"volatility_index": 18.5,

"moving_average_convergence_divergence": {

"macd_value": 1.2,

"signal_line": 0.9,

"status": "bullish"

},

"relative_strength_index": 62,

"price_to_earnings_ratio": 22.3,

"beta_coefficient": 1.1,

"dividend_yield": 2.5,

"liquidity_risk": "low",

"market_sentiment": "neutral",

"status": "extracted",

"datasource": "real-time",

"execution": "immediate"

}

{

"tail_risk": "none",

"multi_asset_correlation": "safe",

"max_drawdown_periodically": {

"probability": 1,

"output": "anomaly",

"model_certainty": 90

},

"volatility_index": 18.5,

"moving_average_convergence_divergence": {

"macd_value": 1.2,

"signal_line": 0.9,

"status": "bullish"

},

"relative_strength_index": 62,

"price_to_earnings_ratio": 22.3,

"beta_coefficient": 1.1,

"dividend_yield": 2.5,

"liquidity_risk": "low",

"market_sentiment": "neutral",

"status": "extracted",

"datasource": "real-time",

"execution": "immediate"

}

{
"tail_risk": "none",
"multi_asset_correlation": "safe",
"max_drawdown_periodically": {
"probability": 1,
"output": "anomaly",
"model_certainty": 90
},
"volatility_index": 18.5,
"moving_average_convergence_divergence": {
"macd_value": 1.2,
"signal_line": 0.9,
"status": "bullish"
},
"relative_strength_index": 62,
"price_to_earnings_ratio": 22.3,
"beta_coefficient": 1.1,
"dividend_yield": 2.5,
"liquidity_risk": "low",
"market_sentiment": "neutral",
"status": "extracted",
"datasource": "real-time",
"execution": "immediate"
}

Subject

Chameleon

Anomaly

{

"tail_risk": "analysing",

"multi_asset": "analysing",

"probability": "unknown",

"model_certainty": "building",

"volatility_index": "unknown"

},

"volatility_index": 18.5,

"moving_average_convergence_divergence": {

"macd_value": 1.2,

"signal_line": 0.9,

"status": "bullish"

},

"relative_strength_index": 62,

"price_to_earnings_ratio": 22.3,

"beta_coefficient": 1.1,

"dividend_yield": 2.5,

"liquidity_risk": "low",

"market_sentiment": "neutral",

"status": "extracted",

"datasource": "real-time",

"execution": "immediate"

}

{

"tail_risk": "analysing",

"multi_asset": "analysing",

"probability": "unknown",

"model_certainty": "building",

"volatility_index": "unknown"

},

"volatility_index": 18.5,

"moving_average_convergence_divergence": {

"macd_value": 1.2,

"signal_line": 0.9,

"status": "bullish"

},

"relative_strength_index": 62,

"price_to_earnings_ratio": 22.3,

"beta_coefficient": 1.1,

"dividend_yield": 2.5,

"liquidity_risk": "low",

"market_sentiment": "neutral",

"status": "extracted",

"datasource": "real-time",

"execution": "immediate"

}

{

"tail_risk": “random”,

"multi_asset": “yes”,

"probability": "0,1",

"output": "chameleon",

"volatility_index": "30%"

},

"volatility_index": 18.5, "moving_average_convergence_divergence": {

"macd_value": 1.2,

"signal_line": 0.9,

"status": "bullish"

},

"relative_strength_index": 62,

"price_to_earnings_ratio": 22.3,

"beta_coefficient": 1.1,

"dividend_yield": 2.5,

"liquidity_risk": "low",

"market_sentiment": "neutral",

"status": "extracted",

"datasource": "real-time",

"execution": "immediate"

}

{

"tail_risk": “random”,

"multi_asset": “yes”,

"probability": "0,1",

"output": "chameleon",

"volatility_index": "30%"

},

"volatility_index": 18.5, "moving_average_convergence_divergence": {

"macd_value": 1.2,

"signal_line": 0.9,

"status": "bullish"

},

"relative_strength_index": 62,

"price_to_earnings_ratio": 22.3,

"beta_coefficient": 1.1,

"dividend_yield": 2.5,

"liquidity_risk": "low",

"market_sentiment": "neutral",

"status": "extracted",

"datasource": "real-time",

"execution": "immediate"

}

{

"tail_risk": "none",

"multi_asset_correlation": "safe",

"max_drawdown_periodically": {

"probability": 1,

"output": "anomaly",

"model_certainty": 90

},

"volatility_index": 18.5,

"moving_average_convergence_divergence": {

"macd_value": 1.2,

"signal_line": 0.9,

"status": "bullish"

},

"relative_strength_index": 62,

"price_to_earnings_ratio": 22.3,

"beta_coefficient": 1.1,

"dividend_yield": 2.5,

"liquidity_risk": "low",

"market_sentiment": "neutral",

"status": "extracted",

"datasource": "real-time",

"execution": "immediate"

}

{

"tail_risk": "none",

"multi_asset_correlation": "safe",

"max_drawdown_periodically": {

"probability": 1,

"output": "anomaly",

"model_certainty": 90

},

"volatility_index": 18.5,

"moving_average_convergence_divergence": {

"macd_value": 1.2,

"signal_line": 0.9,

"status": "bullish"

},

"relative_strength_index": 62,

"price_to_earnings_ratio": 22.3,

"beta_coefficient": 1.1,

"dividend_yield": 2.5,

"liquidity_risk": "low",

"market_sentiment": "neutral",

"status": "extracted",

"datasource": "real-time",

"execution": "immediate"

}

Subject

Chameleon

Anomaly

{

"tail_risk": "analysing",

"multi_asset": "analysing",

"probability": "unknown",

"model_certainty": "building",

"volatility_index": "unknown"

},

"volatility_index": 18.5,

"moving_average_convergence_divergence": {

"macd_value": 1.2,

"signal_line": 0.9,

"status": "bullish"

},

"relative_strength_index": 62,

"price_to_earnings_ratio": 22.3,

"beta_coefficient": 1.1,

"dividend_yield": 2.5,

"liquidity_risk": "low",

"market_sentiment": "neutral",

"status": "extracted",

"datasource": "real-time",

"execution": "immediate"

}

{

"tail_risk": "analysing",

"multi_asset": "analysing",

"probability": "unknown",

"model_certainty": "building",

"volatility_index": "unknown"

},

"volatility_index": 18.5,

"moving_average_convergence_divergence": {

"macd_value": 1.2,

"signal_line": 0.9,

"status": "bullish"

},

"relative_strength_index": 62,

"price_to_earnings_ratio": 22.3,

"beta_coefficient": 1.1,

"dividend_yield": 2.5,

"liquidity_risk": "low",

"market_sentiment": "neutral",

"status": "extracted",

"datasource": "real-time",

"execution": "immediate"

}

{

"tail_risk": “random”,

"multi_asset": “yes”,

"probability": "0,1",

"output": "chameleon",

"volatility_index": "30%"

},

"volatility_index": 18.5, "moving_average_convergence_divergence": {

"macd_value": 1.2,

"signal_line": 0.9,

"status": "bullish"

},

"relative_strength_index": 62,

"price_to_earnings_ratio": 22.3,

"beta_coefficient": 1.1,

"dividend_yield": 2.5,

"liquidity_risk": "low",

"market_sentiment": "neutral",

"status": "extracted",

"datasource": "real-time",

"execution": "immediate"

}

{

"tail_risk": “random”,

"multi_asset": “yes”,

"probability": "0,1",

"output": "chameleon",

"volatility_index": "30%"

},

"volatility_index": 18.5, "moving_average_convergence_divergence": {

"macd_value": 1.2,

"signal_line": 0.9,

"status": "bullish"

},

"relative_strength_index": 62,

"price_to_earnings_ratio": 22.3,

"beta_coefficient": 1.1,

"dividend_yield": 2.5,

"liquidity_risk": "low",

"market_sentiment": "neutral",

"status": "extracted",

"datasource": "real-time",

"execution": "immediate"

}

{

"tail_risk": "none",

"multi_asset_correlation": "safe",

"max_drawdown_periodically": {

"probability": 1,

"output": "anomaly",

"model_certainty": 90

},

"volatility_index": 18.5,

"moving_average_convergence_divergence": {

"macd_value": 1.2,

"signal_line": 0.9,

"status": "bullish"

},

"relative_strength_index": 62,

"price_to_earnings_ratio": 22.3,

"beta_coefficient": 1.1,

"dividend_yield": 2.5,

"liquidity_risk": "low",

"market_sentiment": "neutral",

"status": "extracted",

"datasource": "real-time",

"execution": "immediate"

}

{

"tail_risk": "none",

"multi_asset_correlation": "safe",

"max_drawdown_periodically": {

"probability": 1,

"output": "anomaly",

"model_certainty": 90

},

"volatility_index": 18.5,

"moving_average_convergence_divergence": {

"macd_value": 1.2,

"signal_line": 0.9,

"status": "bullish"

},

"relative_strength_index": 62,

"price_to_earnings_ratio": 22.3,

"beta_coefficient": 1.1,

"dividend_yield": 2.5,

"liquidity_risk": "low",

"market_sentiment": "neutral",

"status": "extracted",

"datasource": "real-time",

"execution": "immediate"

}

Real-Time Data Interpretation & Real-Time Execution

Seamlessly Executing Our Statistical Edge.

Executional Strategies

Cypher executes a variety of proprietary discretionary and systematic strategies.

  • ID 234224

    Range

    Performance: +23%

    Anomaly

  • ID 432549

    Volatility

    Performance: +14%

    Anomaly

  • ID 981343

    Sector

    Performance: +11%

    Anomaly

  • ID 281029

    Pattern

    Performance: +18%

    Anomaly

  • ID 290521

    Swing

    Performance: +9%

    Anomaly

  • ID 969764

    Contrarian

    Performance: +33%

    Anomaly

  • ID 303101

    Mean

    Performance: +16%

    Anomaly

  • ID 328436

    Momentum

    Performance: +15%

    Anomaly

  • ID 836441

    Scalping

    Performance: +27%

    Anomaly

Conformance

Total Exposure

$49,745,882.62

Last Quarter

Total Profit

$3,233,942.22

Avg. Monthly

+6.5%

Best Performing

> Quantitative

Code Owner

Allocation

KEY FACTORS - BIAS REMOVED

Sentiment

Seasonality

55%

Quantitative

Trading

33%

Dealing Desk

12%

Discretionary

Conformance

Total Exposure

$49,745,882.62

Last Quarter

Total Profit

$3,233,942.22

Avg. Monthly

+6.5%

Best Performing

> Quantitative

Code Owner

Allocation

KEY FACTORS - BIAS REMOVED

Sentiment

Seasonality

55%

Quantitative

Trading

33%

Dealing Desk

12%

Discretionary

Conformance

Total Exposure

$49,745,882.62

Last Quarter

Total Profit

$3,233,942.22

Avg. Monthly

+6.5%

Best Performing

> Quantitative

Code Owner

Allocation

KEY FACTORS - BIAS REMOVED

Sentiment

Seasonality

55%

Quantitative

Trading

33%

Dealing Desk

12%

Discretionary

Modelling

Modelling

Modelling

Cypher LLC, Nevis, West Indies

  • tail risk

    alpha

    sharpe ratio

    AON order

  • arbitrageur

    null hypothesis

    Dickey Fuller

    ADTV

  • Brownian Motion

    Butterfly spread

    Decision trees

    ECN

  • Generalized Autoregressive Conditional Heteroskedasticity

    Γ(y)

    Granger Causality

  • market microstructure

    z-score