Package {strategyr}

Backtest Portfolio Target Weights

Description

Evaluates a panel of portfolio target weights with open-price rebalancing and close-price mark-to-market. This is a minimal portfolio-level companion to the single-instrument backtest engine: strategy logic supplies target weights, while this helper applies path-dependent portfolio accounting.

Usage

backtest_portfolio_weights(
  DT,
  date_col = "date",
  asset_col = "asset",
  open_col = "open",
  close_col = "close",
  target_weight_col = "target_weight",
  initial_equity = 1,
  fee_rt = 0,
  rebalance_tol_weight = 0,
  contract_size_col = "contract_size",
  allow_short = TRUE,
  keep_positions = FALSE
)

Arguments

Value

A list with 'equity' and, when requested, 'positions' tables.

Run a Path-Dependent Backtest

Description

Runs the native path-dependent backtest engine over OHLC data and a target position path.

Usage

backtest_rcpp(
  timestamp,
  open,
  high,
  low,
  close,
  tgt_pos,
  pos_strat,
  tol_pos,
  strat,
  asset,
  ctr_size = 1,
  ctr_step = 1,
  lev = 10,
  fee_rt = 0,
  fund_rt = 0,
  rec = FALSE
)

Arguments

Value

A backtest result from the native engine.

Build Portfolio Order Intents

Description

Converts rebalancing deltas into a minimal order-intent table suitable for downstream execution adapters.

Usage

build_order_intents(adjustment_plan, pricing_method = "market")

Arguments

Value

A 'data.table' containing one row per non-zero rebalance intent.

Add Average Directional Index Features

Description

Computes positive and negative directional indicators, directional movement index, and average directional index columns from candle highs, lows, and closes in place.

Usage

calc_ADX(DT, ns = c(14))

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Average True Range Features

Description

Computes Wilder-style ATR columns and log-range ATR columns on a candle 'data.table' in place.

Usage

calc_ATR(DT, ns = c(10, 14, 30), hs = c(12, 24))

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add ATR Quantile Features

Description

Computes rolling quantiles for existing log-range ATR columns on a candle 'data.table' in place.

Usage

calc_ATR_quantile(
  DT,
  hs = c(12, 24),
  window = 300,
  thresholds = c(0.05, 0.1, 0.2, 0.3, 0.7, 0.8, 0.9, 0.95)
)

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Bollinger Band Features

Description

Computes Bollinger band mid, standard deviation, upper, lower, and touch flag columns from the 'close' series of a candle 'data.table' in place.

Usage

calc_BollingerBands(DT, ns = c(20), ks = c(2))

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add CCI Features

Description

Computes Commodity Channel Index columns from candle highs, lows, and closes in place using typical price, its rolling mean, and rolling mean absolute deviation.

Usage

calc_CCI(DT, ns = c(20), constant = 0.015)

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Chaikin Money Flow Features

Description

Computes Chaikin Money Flow columns from candle highs, lows, closes, and traded volume in place.

Usage

calc_CMF(DT, ns = c(20))

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Chande Momentum Oscillator Features

Description

Computes CMO columns from the 'close' series of a candle 'data.table' in place.

Usage

calc_CMO(DT, ns = c(14))

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Double Exponential Moving Average Features

Description

Computes DEMA columns from the 'close' series of a candle 'data.table' in place.

Usage

calc_DEMA(DT, ns = c(10, 20, 50), v = 1)

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Donchian Channel Features

Description

Computes rolling channel highs, lows, and midpoints from 'high' and 'low' price columns on a candle 'data.table' in place.

Usage

calc_DonchianChannels(DT, ns = c(20, 55))

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Exponential Moving Average Features

Description

Computes EMA columns from the 'close' series of a candle 'data.table' in place.

Usage

calc_EMA(DT, ns = c(5, 8, 9, 10, 12, 20, 21, 26, 30, 50, 100, 200))

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add EMA-Cross Strategy Targets

Description

Evaluates a simple EMA-cross trading rule with ATR-based gating and writes either diagnostic columns or a target-position column to a candle 'data.table' in place.

Usage

calc_EMA_cross(
  DT,
  fast = 20,
  slow = 50,
  low_atr_threshold = 5,
  freshness_floor = 18,
  tp_ratio = 0.05,
  sl_ratio = 0.02,
  debug_mode = FALSE
)

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Ease of Movement Features

Description

Computes the raw Ease of Movement series and smoothed moving-average columns from candle highs, lows, and traded volume in place.

Usage

calc_EMV(DT, ns = c(9), vol_divisor = 10000)

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Hull Moving Average Features

Description

Computes HMA columns from the 'close' series of a candle 'data.table' in place using the standard weighted-moving-average construction.

Usage

calc_HMA(DT, ns = c(9, 16, 20, 50))

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Know Sure Thing Features

Description

Computes KST and signal columns from weighted moving averages of multiple rate-of-change series on a candle 'data.table' in place.

Usage

calc_KST(
  DT,
  nss = list(c(10, 10, 10, 15)),
  n_rocss = list(c(10, 15, 20, 30)),
  signal_ns = c(9),
  wtss = list(1:4)
)

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Keltner Channel Features

Description

Computes Keltner channel mid, upper, and lower bands from an EMA centerline and ATR envelope on a candle 'data.table' in place.

Usage

calc_KeltnerChannels(DT, ns = c(20), ks = c(2))

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add MACD Features

Description

Computes Moving Average Convergence Divergence, signal, and histogram columns from the 'close' series of a candle 'data.table' in place.

Usage

calc_MACD(DT, fast = 12, slow = 26, signal = 9)

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Money Flow Index Features

Description

Computes Money Flow Index columns from candle highs, lows, closes, and traded volume in place.

Usage

calc_MFI(DT, ns = c(14))

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add On-Balance Volume Features

Description

Computes the cumulative on-balance volume series from candle closes and traded volume in place.

Usage

calc_OBV(DT)

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Rate of Change Features

Description

Computes rate-of-change columns from the 'close' series of a candle 'data.table' in place.

Usage

calc_ROC(DT, ns = c(5, 10, 20), scale = 100)

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Relative Strength Index Features

Description

Computes both classic Wilder-style RSI columns and strategyr-specific log-return RSI columns on a candle 'data.table' in place.

Usage

calc_RSI(DT, ns = c(9, 14, 21), hs = c(12, 24))

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Parabolic SAR Features

Description

Computes Parabolic SAR columns from candle highs and lows in place using the classic acceleration step and maximum parameters.

Usage

calc_SAR(DT, accels = list(c(0.02, 0.2)))

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Simple Moving Average Features

Description

Computes SMA columns from the 'close' series of a candle 'data.table' in place.

Usage

calc_SMA(DT, ns = c(5, 8, 9, 10, 12, 20, 21, 26, 30, 50, 100, 200))

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Stochastic Momentum Index Features

Description

Computes SMI and signal columns from candle highs, lows, and closes in place using double-smoothed EMA numerators and denominators.

Usage

calc_SMI(DT, n = 13, nFast = 2, nSlow = 25, nSig = 9, bounded = TRUE)

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Stochastic Oscillator Features

Description

Computes fast stochastic '%K' and smoothed '%D' columns from candle highs, lows, and closes in place.

Usage

calc_StochasticOscillator(DT, ns = c(14), d_ns = c(3))

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add TRIX Features

Description

Computes triple-smoothed exponential trend columns and their signal lines from the 'close' series of a candle 'data.table' in place.

Usage

calc_TRIX(DT, ns = c(20), signal_ns = c(9), scale = 100)

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Volume-Weighted Average Price Features

Description

Computes rolling VWAP columns from candle closes and traded volume in place.

Usage

calc_VWAP(DT, ns = c(10))

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Volume-Weighted Moving Average Features

Description

Computes rolling VWMA columns from candle closes and traded volume in place.

Usage

calc_VWMA(DT, ns = c(10))

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Weighted Moving Average Features

Description

Computes linearly weighted moving-average columns from the 'close' series of a candle 'data.table' in place.

Usage

calc_WMA(DT, ns = c(5, 8, 9, 10, 12, 20, 21, 26, 30, 50, 100, 200))

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Williams Percent R Features

Description

Computes Williams percent R columns from candle highs, lows, and closes in place on the same '[0, 1]' scale used by 'TTR::WPR()'.

Usage

calc_WPR(DT, ns = c(14))

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Zero-Lag Exponential Moving Average Features

Description

Computes ZLEMA columns from the 'close' series of a candle 'data.table' in place.

Usage

calc_ZLEMA(DT, ns = c(10, 20, 50))

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Aroon Features

Description

Computes Aroon up, down, and oscillator columns from candle highs and lows in place.

Usage

calc_aroon(DT, ns = c(20))

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Backtest Performance Metrics

Description

Computes compact performance metrics from a path-dependent backtest equity curve. The primary score is Sortino ratio, using log returns and downside deviation below a minimum acceptable annual return.

Usage

calc_backtest_performance(
  equity,
  annualization = 252,
  risk_free_return = 0,
  min_acceptable_return = 0
)

Arguments

Value

A one-row 'data.table' with return, risk, drawdown, and Sortino metrics.

Add Bid-Ask Spread Features

Description

Computes absolute and relative bid-ask spread columns in place.

Usage

calc_bid_ask_spread(DT, bid_col = "bid", ask_col = "ask")

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Compute Bond Accrued Interest

Description

Computes accrued coupon interest for a plain-vanilla fixed-coupon bond using the fraction of the current coupon period that has elapsed.

Usage

calc_bond_accrued_interest(par = 1, c_rate, freq = 2, accrual_frac = 0)

Arguments

Value

Numeric scalar accrued interest.

Compute Bond Carry Return

Description

Computes a simple carry return estimate as coupon accrual earned over the holding horizon minus financing cost, scaled by the opening dirty price.

Usage

calc_bond_carry(
  par = 1,
  c_rate,
  maturity,
  freq = 2,
  ytm,
  accrual_frac = 0,
  holding_years = 1/freq,
  funding_rate = 0
)

Arguments

Value

Numeric scalar carry return.

Decompose Bond Carry And Roll Return

Description

Returns carry, roll-down, and their sum as a compact one-row 'data.table'.

Usage

calc_bond_carry_roll_decomp(carry, roll_down_return)

Arguments

Value

One-row 'data.table' with 'carry', 'roll_down', and 'carry_roll'.

Compute Bond Cash Flows

Description

Generates level-coupon bond cash flows by period.

Usage

calc_bond_cashflows(par = 1, c_rate, maturity, freq = 2)

Arguments

Value

Numeric vector of period cash flows excluding time-zero.

Compute Bond Clean Price

Description

Computes the clean price of a plain-vanilla fixed-coupon bond from yield and bond terms.

Usage

calc_bond_clean_price(
  par = 1,
  c_rate,
  maturity,
  freq = 2,
  ytm,
  accrual_frac = 0
)

Arguments

Value

Numeric scalar clean price.

Compute Bond Convexity

Description

Computes bond convexity in year-squared units from explicit cash flows and rates, or directly from bond terms.

Usage

calc_bond_convexity(
  cashflows = NULL,
  rates = NULL,
  par = NULL,
  c_rate = NULL,
  maturity = NULL,
  freq = 2,
  ytm = NULL
)

Arguments

Value

Numeric scalar convexity.

Compute Bond Current Yield

Description

Computes current yield as annual coupon income divided by clean price.

Usage

calc_bond_current_yield(
  price,
  c_rate,
  par = 1,
  freq = 2,
  price_type = c("clean", "dirty"),
  accrual_frac = 0
)

Arguments

Value

Numeric scalar current yield.

Compute Bond Dirty Price

Description

Computes the dirty price of a plain-vanilla fixed-coupon bond from yield and bond terms. Settlement within the current coupon period is represented by 'accrual_frac'.

Usage

calc_bond_dirty_price(
  par = 1,
  c_rate,
  maturity,
  freq = 2,
  ytm,
  accrual_frac = 0
)

Arguments

Value

Numeric scalar dirty price.

Compute Bond Macaulay Duration

Description

Computes Macaulay duration in years from explicit cash flows and rates, or directly from bond terms.

Usage

calc_bond_duration(
  cashflows = NULL,
  rates = NULL,
  par = NULL,
  c_rate = NULL,
  maturity = NULL,
  freq = 2,
  ytm = NULL
)

Arguments

Value

Numeric scalar duration in years.

Compute Bond DV01

Description

Computes DV01 as the average absolute price change for a one-basis-point annualized yield shock.

Usage

calc_bond_dv01(
  par = 1,
  c_rate,
  maturity,
  freq = 2,
  ytm,
  accrual_frac = 0,
  bases = 1
)

Arguments

Value

Numeric scalar DV01.

Compute Effective Bond Convexity

Description

Computes effective convexity by bumping discount rates up and down by a basis point shock.

Usage

calc_bond_econvexity(
  cashflows = NULL,
  rates = NULL,
  par = NULL,
  c_rate = NULL,
  maturity = NULL,
  freq = 2,
  ytm = NULL,
  bases = 100
)

Arguments

Value

Numeric scalar effective convexity.

Compute Effective Bond Duration

Description

Computes effective duration by bumping discount rates up and down by a basis point shock.

Usage

calc_bond_eduration(
  cashflows = NULL,
  rates = NULL,
  par = NULL,
  c_rate = NULL,
  maturity = NULL,
  freq = 2,
  ytm = NULL,
  bases = 100
)

Arguments

Value

Numeric scalar effective duration.

Compute Bond Holding-Period Return

Description

Computes holding-period return from beginning and ending bond prices plus coupon income received during the holding period.

Usage

calc_bond_holding_period_return(
  begin_price,
  end_price,
  coupon_income = 0,
  price_type = c("dirty", "clean"),
  par = 1,
  c_rate = 0,
  freq = 2,
  begin_accrual_frac = 0,
  end_accrual_frac = 0
)

Arguments

Value

Numeric scalar holding-period return.

Compute Bond Key Rate Duration

Description

Computes key-rate duration by bumping one point on an explicit per-period discount-rate curve at a time.

Usage

calc_bond_key_rate_duration(
  cashflows = NULL,
  rates = NULL,
  par = NULL,
  c_rate = NULL,
  maturity = NULL,
  freq = 2,
  ytm = NULL,
  accrual_frac = 0,
  key_periods = NULL,
  bases = 1
)

Arguments

Value

A 'data.table' with 'key_period' and 'krd'.

Compute Bond Key Rate Duration By Curve Tenor

Description

Computes key-rate duration by bumping one annualized zero-rate tenor on an interpolated curve while holding the rest of the curve fixed.

Usage

calc_bond_key_rate_duration_tenor(
  par = 1,
  c_rate,
  maturity,
  freq = 2,
  tenor,
  zero_rate,
  key_tenor,
  shock_bp = 1,
  accrual_frac = 0,
  method = c("linear")
)

Arguments

Value

Numeric scalar tenor-based key-rate duration.

Compute Bond Modified Duration

Description

Computes modified duration in years from explicit cash flows and rates, or directly from bond terms.

Usage

calc_bond_mduration(
  cashflows = NULL,
  rates = NULL,
  par = NULL,
  c_rate = NULL,
  maturity = NULL,
  freq = 2,
  ytm = NULL
)

Arguments

Value

Numeric scalar modified duration in years.

Compute Next Coupon Date

Description

Returns the next regular coupon date strictly after settlement.

Usage

calc_bond_next_coupon(settle_date, maturity_date, freq = 2, issue_date = NULL)

Arguments

Value

A scalar 'Date', or 'NA' if no future coupon exists within the bounded schedule.

Compute Bond Nominal Spread

Description

Computes the simple nominal spread between a bond yield and a benchmark yield, in annualized decimal units.

Usage

calc_bond_nominal_spread(ytm, benchmark_ytm)

Arguments

Value

Numeric scalar nominal spread.

Compute Bond Net Present Value

Description

Computes bond present value from explicit cash flows and per-period rates, or directly from bond terms.

Usage

calc_bond_npv(
  cashflows = NULL,
  rates = NULL,
  par = NULL,
  c_rate = NULL,
  maturity = NULL,
  freq = 2,
  ytm = NULL
)

Arguments

Value

Numeric scalar present value.

Compute Previous Coupon Date

Description

Returns the most recent regular coupon date on or before settlement.

Usage

calc_bond_prev_coupon(settle_date, maturity_date, freq = 2, issue_date = NULL)

Arguments

Value

A scalar 'Date', or 'NA' if no previous coupon exists within the bounded schedule.

Approximate Bond Price Change From Duration And Convexity

Description

Approximates the absolute bond price change for an annualized yield shock using modified duration and convexity.

Usage

calc_bond_price_change_approx(
  ytm,
  yield_shock,
  par = 1,
  c_rate,
  maturity,
  freq = 2,
  accrual_frac = 0,
  price_type = c("dirty", "clean")
)

Arguments

Value

Numeric scalar approximate absolute price change.

Compute Bond PV01

Description

Computes PV01 as the average absolute dirty-price change for a one-basis- point annualized yield shock.

Usage

calc_bond_pv01(
  par = 1,
  c_rate,
  maturity,
  freq = 2,
  ytm,
  accrual_frac = 0,
  bases = 1
)

Arguments

Value

Numeric scalar PV01.

Approximate Bond Rate Return

Description

Computes the duration-convexity approximation to bond return from an annualized yield shock.

Usage

calc_bond_rate_return_approx(duration, delta_y, convexity = 0)

Arguments

Value

Numeric scalar approximate rate return.

Compute Bond Risk State

Description

Builds a compact fixed-income risk-state snapshot that can be used by portfolio-adjustment or hedge-planning logic.

Usage

calc_bond_risk_state(
  par = 1,
  c_rate,
  maturity,
  freq = 2,
  ytm,
  accrual_frac = 0,
  tenor = NULL,
  zero_rate = NULL,
  zspread = NULL
)

Arguments

Value

A one-row 'data.table' containing bond valuation and risk measures.

Compute Bond Roll-Down Return

Description

Computes the price return from rolling a bond down the curve over a holding horizon while leaving the annualized yield assumption unchanged.

Usage

calc_bond_roll_down_return(
  par = 1,
  c_rate,
  maturity,
  freq = 2,
  ytm,
  accrual_frac = 0,
  holding_years = 1/freq
)

Arguments

Value

Numeric scalar roll-down return.

Compute Bond Spread Duration

Description

Computes spread duration by bumping an annualized z-spread up and down while holding the zero-rate curve fixed.

Usage

calc_bond_spread_duration(
  par = 1,
  c_rate,
  maturity,
  freq = 2,
  tenor,
  zero_rate,
  zspread,
  shock_bp = 1,
  accrual_frac = 0,
  method = c("linear")
)

Arguments

Value

Numeric scalar spread duration.

Approximate Bond Spread Return

Description

Computes the first-order approximation to bond return from a spread move.

Usage

calc_bond_spread_return_approx(spread_duration, delta_s)

Arguments

Value

Numeric scalar approximate spread return.

Decompose Bond Total Return

Description

Returns the main building blocks of bond total return as a compact one-row 'data.table'.

Usage

calc_bond_total_return_decomp(
  carry,
  roll_down_return = 0,
  rate_return = 0,
  spread_return = 0,
  residual = 0
)

Arguments

Value

One-row 'data.table' with component returns and 'total_return'.

Compute Bond Yield To Maturity

Description

Solves annualized yield-to-maturity from a clean or dirty bond price under a plain-vanilla fixed-coupon schedule.

Usage

calc_bond_yield(
  price,
  par = 1,
  c_rate,
  maturity,
  freq = 2,
  accrual_frac = 0,
  price_type = c("dirty", "clean"),
  interval = NULL
)

Arguments

Value

Numeric scalar annualized yield-to-maturity.

Compute Bond Z-Spread

Description

Solves the constant annualized spread that must be added to a per-period spot rate curve so discounted cash flows match an observed clean or dirty price.

Usage

calc_bond_zspread(
  price,
  spot_rates,
  cashflows = NULL,
  par = NULL,
  c_rate = NULL,
  maturity = NULL,
  freq = 2,
  accrual_frac = 0,
  price_type = c("dirty", "clean"),
  interval = NULL
)

Arguments

Value

Numeric scalar annualized z-spread.

Approximate Bond Z-Spread Return

Description

Computes the first-order approximation to bond return from a z-spread move.

Usage

calc_bond_zspread_return_approx(spread_duration, delta_z)

Arguments

Value

Numeric scalar approximate z-spread return.

Compute Advance-Decline Breadth

Description

Aggregates per-date advancing and declining counts from a cross-sectional asset panel.

Usage

calc_breadth_ad(
  DT,
  date_col = "date",
  asset_col = "asset",
  close_col = "close"
)

Arguments

Value

A 'data.table' with per-date breadth counts and advance-decline difference.

Compute Advance-Decline Line

Description

Builds a cumulative advance-decline line from per-date breadth counts.

Usage

calc_breadth_adl(
  DT,
  date_col = "date",
  asset_col = "asset",
  close_col = "close"
)

Arguments

Value

A 'data.table' with per-date breadth counts, difference, and cumulative advance-decline line.

Compute New-High New-Low Breadth

Description

Aggregates per-date new-high and new-low counts relative to the prior 'n' observations for each asset.

Usage

calc_breadth_high_low(
  DT,
  date_col = "date",
  asset_col = "asset",
  high_col = "high",
  low_col = "low",
  n = 252
)

Arguments

Value

A 'data.table' with per-date new-high/new-low counts and ratios.

Compute Advance-Decline Ratio

Description

Computes the per-date advancing-to-declining ratio from a cross-sectional asset panel.

Usage

calc_breadth_ratio(
  DT,
  date_col = "date",
  asset_col = "asset",
  close_col = "close"
)

Arguments

Value

A 'data.table' with per-date breadth counts and ratio.

Compute TRIN Breadth

Description

Computes per-date TRIN (Arms Index) values from advancing and declining counts and their associated traded volume.

Usage

calc_breadth_trin(
  DT,
  date_col = "date",
  asset_col = "asset",
  close_col = "close",
  volume_col = "volume"
)

Arguments

Value

A 'data.table' with per-date advance/decline counts, volume totals, and TRIN.

Add Chaikin Accumulation Distribution Features

Description

Computes the cumulative Chaikin Accumulation Distribution line from candle highs, lows, closes, and traded volume in place.

Usage

calc_chaikinAD(DT)

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Chaikin Volatility Features

Description

Computes Chaikin Volatility columns from candle highs and lows in place using an EMA of the range followed by a discrete rate of change.

Usage

calc_chaikinVolatility(DT, ns = c(10))

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Compute Contango-Backwardation Regime

Description

Classifies the front-versus-deferred futures curve regime per date as contango ('1'), backwardation ('-1'), or flat ('0').

Usage

calc_contango_backwardation(
  DT,
  date_col = "date",
  rank_col = "contract_rank",
  price_col = "close",
  rank_front = 1L,
  rank_deferred = 2L
)

Arguments

Value

A 'data.table' with one regime code per date.

Compute Coupon Schedule

Description

Generates a regular coupon-payment schedule from issue date to maturity for a plain-vanilla fixed-coupon bond without stub handling.

Usage

calc_coupon_schedule(issue_date, maturity_date, freq = 2)

Arguments

Value

A vector of coupon-payment 'Date's after 'issue_date' and up to 'maturity_date'.

Add Credit-Spread Features

Description

Computes credit-spread columns in place as the difference between an issuer yield and a benchmark yield.

Usage

calc_credit_spread(
  DT,
  yield_col = "ytm",
  benchmark_yield_col = "benchmark_ytm",
  name = NULL
)

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Compute Yield Curve Butterfly

Description

Computes a simple annualized butterfly measure as the belly yield minus the average of wing yields.

Usage

calc_curve_butterfly(short_rate, mid_rate, long_rate)

Arguments

Value

Numeric scalar butterfly measure.

Shock A Zero-Rate Curve

Description

Applies either a parallel or tenor-specific basis-point shock to an annualized zero-rate curve.

Usage

calc_curve_shock(tenor, zero_rate, shock_bp, shock_tenor = NULL)

Arguments

Value

A 'data.table' with 'tenor', 'zero_rate', and 'zero_rate_shocked'.

Compute Yield Curve Slope

Description

Computes the annualized slope between a short and a long point on the yield curve.

Usage

calc_curve_slope(short_rate, long_rate)

Arguments

Value

Numeric scalar curve slope.

Interpolate Zero Rates On A Curve

Description

Interpolates annualized zero rates from an input tenor grid onto requested output tenors.

Usage

calc_curve_zero_rate(tenor_out, tenor, zero_rate, method = c("linear"))

Arguments

Value

Numeric vector of interpolated annualized zero rates.

Compute Day-Count Fraction

Description

Computes the year fraction between two dates under a small set of common fixed-income day-count conventions.

Usage

calc_day_count_frac(
  start_date,
  end_date,
  convention = c("ACT/365", "ACT/360", "30/360")
)

Arguments

Value

Numeric scalar year fraction.

Add Excess-Spread Features

Description

Computes excess-spread columns in place as the difference between a credit spread and a benchmark or sector spread.

Usage

calc_excess_spread(
  DT,
  spread_col = "credit_spread",
  benchmark_spread_col = "benchmark_spread",
  name = NULL
)

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Compute Front-Next Futures Spread

Description

Computes the front-versus-next futures spread per date from a futures curve panel.

Usage

calc_front_next_spread(
  DT,
  date_col = "date",
  rank_col = "contract_rank",
  price_col = "close",
  rank_front = 1L,
  rank_next = 2L
)

Arguments

Value

A 'data.table' with front price, next price, and absolute/relative spread per date.

Compute Futures Curve Butterfly

Description

Computes a simple three-point butterfly from selected futures-curve ranks.

Usage

calc_futures_curve_butterfly(
  DT,
  date_col = "date",
  rank_col = "contract_rank",
  price_col = "close",
  ranks = c(1L, 2L, 3L)
)

Arguments

Value

A 'data.table' with one butterfly value per date.

Compute Futures Curve Slope

Description

Computes the per-date linear slope of log futures price against time to expiry.

Usage

calc_futures_curve_slope(
  DT,
  date_col = "date",
  time_to_expiry_col = "time_to_expiry",
  price_col = "close"
)

Arguments

Value

A 'data.table' with one slope estimate per date.

Add FX Basis Features

Description

Computes FX basis columns as the gap between observed forward points and covered-interest-parity-implied forward points.

Usage

calc_fx_basis(
  DT,
  spot_col = "spot",
  forward_col = "forward",
  domestic_rate_col = "r_domestic",
  foreign_rate_col = "r_foreign",
  tenor_col = "tenor_years",
  tenor_tag = "1m"
)

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add FX Carry Features

Description

Computes FX carry columns from domestic and foreign interest rates in place.

Usage

calc_fx_carry(
  DT,
  domestic_rate_col = "r_domestic",
  foreign_rate_col = "r_foreign",
  tenor_col = NULL,
  tenor_tag = "1m"
)

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add FX Forward-Points Features

Description

Computes forward-points columns from spot and forward FX rates in place.

Usage

calc_fx_forward_points(
  DT,
  spot_col = "spot",
  forward_col = "forward",
  tenor_tag = "1m"
)

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add FX Realized-Carry Features

Description

Computes realized-carry columns from spot return plus accrual carry over the selected horizon.

Usage

calc_fx_realized_carry(
  DT,
  spot_col = "spot",
  domestic_rate_col = "r_domestic",
  foreign_rate_col = "r_foreign",
  tenor_col = NULL,
  annualization = 252,
  tenor_tag = "1m"
)

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Rolling Kurtosis Features

Description

Computes rolling excess-kurtosis columns in place for the selected input columns.

Usage

calc_kurtosis(DT, cols = "close", ns = c(20, 60))

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Signed Fibonacci Ladder Indices

Description

Detects recent pivot cycles and maps each bar's close to a signed Fibonacci ladder index. Positive and negative signs encode cycle direction, while the absolute value encodes the ladder level selected by the native engine.

Usage

calc_ladder_index(
  DT,
  span = 3,
  latest_n = NULL,
  refined = TRUE,
  min_swing = 0.05,
  cycle_N = 360L,
  cycle_prefix = NULL,
  center_idx = 9L,
  detailed_report = FALSE
)

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Log-Spread Features

Description

Computes log-price spread columns between two positive numeric input columns in place.

Usage

calc_log_spread(DT, x_col = "close", y_col = "benchmark_close", name = NULL)

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Microprice Features

Description

Computes microprice columns from bid/ask quotes and queue sizes in place.

Usage

calc_microprice(
  DT,
  bid_col = "bid",
  ask_col = "ask",
  bid_size_col = "bid_size",
  ask_size_col = "ask_size"
)

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Mid-Price Features

Description

Computes mid-price columns from bid and ask quotes in place.

Usage

calc_mid_price(DT, bid_col = "bid", ask_col = "ask")

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Min-Max Normalization Features

Description

Computes rolling min-max normalized columns in place for the selected input columns.

Usage

calc_normalize(DT, cols = "close", ns = c(20, 60))

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Compute Option Delta

Description

Computes Black-Scholes delta for a European call or put with continuous dividend yield.

Usage

calc_option_delta(
  S,
  K,
  time_to_expiry,
  r,
  sigma,
  type = c("call", "put"),
  q = 0
)

Arguments

Value

Numeric scalar delta.

Add Option Forward-Moneyness Features

Description

Computes forward-based option moneyness columns in place from spot, strike, time to expiry, rates, and dividend yield.

Usage

calc_option_forward_moneyness(
  DT,
  spot_col = "S",
  strike_col = "K",
  expiry_col = "time_to_expiry",
  rate_col = "r",
  dividend_col = "q"
)

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Compute Option Gamma

Description

Computes Black-Scholes gamma for a European option with continuous dividend yield.

Usage

calc_option_gamma(S, K, time_to_expiry, r, sigma, q = 0)

Arguments

Value

Numeric scalar gamma.

Compute Option Greeks

Description

Computes Black-Scholes price and Greeks for a European call or put with continuous dividend yield.

Usage

calc_option_greeks(
  S,
  K,
  time_to_expiry,
  r,
  sigma,
  type = c("call", "put"),
  q = 0,
  theta_scale = c("annual", "daily")
)

Arguments

Value

A one-row 'data.table' with 'price', 'delta', 'gamma', 'vega', 'theta', and 'rho'.

Compute Option Implied Volatility

Description

Solves Black-Scholes implied volatility from an observed European option price with continuous dividend yield.

Usage

calc_option_iv(
  price,
  S,
  K,
  time_to_expiry,
  r,
  type = c("call", "put"),
  q = 0,
  interval = c(1e-06, 5)
)

Arguments

Value

Numeric scalar implied volatility.

Compute Option Implied-Volatility Skew

Description

Computes per-date and per-expiry put-minus-call IV skew using strikes nearest to a target absolute forward-moneyness level.

Usage

calc_option_iv_skew(
  DT,
  date_col = "date",
  expiry_col = "time_to_expiry",
  type_col = "type",
  moneyness_col = "option_log_forward_moneyness",
  iv_col = "iv",
  target_abs_moneyness = 0.1
)

Arguments

Value

A 'data.table' with IV skew per date and expiry.

Compute Option Implied-Volatility Term Structure

Description

Computes per-date ATM IV term-structure slope using the nearest-to-ATM option at each expiry.

Usage

calc_option_iv_term_structure(
  DT,
  date_col = "date",
  expiry_col = "time_to_expiry",
  moneyness_col = "option_log_forward_moneyness",
  iv_col = "iv"
)

Arguments

Value

A 'data.table' with ATM-front, ATM-back, and ATM-term-structure slope per date.

Add Option Moneyness Features

Description

Computes spot-based option moneyness columns in place from underlying spot and strike.

Usage

calc_option_moneyness(DT, spot_col = "S", strike_col = "K")

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Compute Option Put-Call IV Spread

Description

Computes per-date and per-expiry put-minus-call ATM IV spread using the nearest-to-ATM option of each type.

Usage

calc_option_put_call_iv_spread(
  DT,
  date_col = "date",
  expiry_col = "time_to_expiry",
  type_col = "type",
  moneyness_col = "option_log_forward_moneyness",
  iv_col = "iv"
)

Arguments

Value

A 'data.table' with ATM put-call IV spread per date and expiry.

Compute Option Rho

Description

Computes Black-Scholes rho for a European call or put with continuous dividend yield.

Usage

calc_option_rho(S, K, time_to_expiry, r, sigma, type = c("call", "put"), q = 0)

Arguments

Value

Numeric scalar rho per 1.00 rate change.

Compute Option Risk State

Description

Builds a compact option risk-state snapshot from Black-Scholes price, implied volatility, and Greeks.

Usage

calc_option_risk_state(
  S,
  K,
  time_to_expiry,
  r,
  sigma = NULL,
  type = c("call", "put"),
  q = 0,
  price = NULL
)

Arguments

Value

A one-row 'data.table' with observed/model price, implied volatility, IV source, and Greeks.

Compute Option Smile Slope

Description

Computes per-date and per-expiry smile slope from a linear fit of implied volatility on absolute forward log-moneyness.

Usage

calc_option_smile_slope(
  DT,
  date_col = "date",
  expiry_col = "time_to_expiry",
  moneyness_col = "option_log_forward_moneyness",
  iv_col = "iv"
)

Arguments

Value

A 'data.table' with smile slope per date and expiry.

Compute Option Theta

Description

Computes Black-Scholes theta for a European call or put with continuous dividend yield.

Usage

calc_option_theta(
  S,
  K,
  time_to_expiry,
  r,
  sigma,
  type = c("call", "put"),
  q = 0,
  scale = c("annual", "daily")
)

Arguments

Value

Numeric scalar theta.

Compute Option Vega

Description

Computes Black-Scholes vega for a European option with continuous dividend yield.

Usage

calc_option_vega(S, K, time_to_expiry, r, sigma, q = 0)

Arguments

Value

Numeric scalar vega per 1.00 volatility change.

Add Order-Imbalance Features

Description

Computes normalized order-imbalance columns from bid and ask queue sizes in place.

Usage

calc_order_imbalance(DT, bid_size_col = "bid_size", ask_size_col = "ask_size")

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Rolling Percent-Rank Features

Description

Computes rolling percent-rank columns in place for the selected input columns. The current observation is ranked against the most recent 'n' values, including itself.

Usage

calc_percent_rank(DT, cols = "close", ns = c(20, 60))

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Compute Per-Period Yield Rates

Description

Converts annualized yield-to-maturity values into per-period rates.

Usage

calc_period_rate(ytm, freq = 2)

Arguments

Value

Numeric vector of per-period rates.

Compute Position Greeks

Description

Computes Black-Scholes Greeks per row and scales them by position size and contract size so the result is ready for portfolio aggregation.

Usage

calc_position_greeks(
  option_state,
  contract_size_col = "contract_size",
  units_col = "units"
)

Arguments

Value

A 'data.table' with per-contract and position-scaled Greek columns.

Add Price-Impact Proxy Features

Description

Computes an Amihud-style price-impact proxy from absolute returns and dollar volume in place.

Usage

calc_price_impact_proxy(
  DT,
  close_col = "close",
  volume_col = "volume",
  use_log = TRUE
)

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Ratio Features

Description

Computes arithmetic ratio columns between two numeric input columns in place.

Usage

calc_ratio(DT, x_col = "close", y_col = "benchmark_close", name = NULL)

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Realized Volatility Features

Description

Computes annualized rolling realized-volatility columns from close-to-close log returns in place.

Usage

calc_realized_vol(DT, ns = c(10, 20, 60), annualization = 252)

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Relative-Strength Features

Description

Computes rolling relative-strength columns as the ratio of cumulative asset return to cumulative benchmark return over each lookback window.

Usage

calc_relative_strength(
  DT,
  x_col = "close",
  y_col = "benchmark_close",
  ns = c(20, 60),
  use_log = TRUE
)

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Compute Annualized Roll Yield

Description

Computes the annualized front-versus-deferred roll yield from a futures curve panel. Positive values indicate backwardation and negative values indicate contango under the selected pair.

Usage

calc_roll_yield(
  DT,
  date_col = "date",
  rank_col = "contract_rank",
  price_col = "close",
  time_to_expiry_col = "time_to_expiry",
  rank_front = 1L,
  rank_deferred = 2L
)

Arguments

Value

A 'data.table' with annualized roll yield per date.

Add Rolling Beta Features

Description

Computes rolling beta columns from asset and benchmark return series.

Usage

calc_rolling_beta(
  DT,
  x_col = "close",
  y_col = "benchmark_close",
  ns = c(20, 60),
  use_log = TRUE
)

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Rolling Correlation Features

Description

Computes rolling correlation columns from asset and benchmark return series.

Usage

calc_rolling_corr(
  DT,
  x_col = "close",
  y_col = "benchmark_close",
  ns = c(20, 60),
  use_log = TRUE
)

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Rolling Quantile Features

Description

Computes rolling quantile columns in place for the selected input columns.

Usage

calc_rolling_quantile(
  DT,
  cols = "close",
  ns = c(20, 60),
  probs = c(0.25, 0.5, 0.75)
)

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Rolling Skewness Features

Description

Computes rolling skewness columns in place for the selected input columns.

Usage

calc_skewness(DT, cols = "close", ns = c(20, 60))

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Slippage-Proxy Features

Description

Computes a simple execution slippage proxy from intrabar range and close price in place.

Usage

calc_slippage_proxy(
  DT,
  high_col = "high",
  low_col = "low",
  close_col = "close"
)

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Spread Features

Description

Computes arithmetic spread columns between two numeric input columns in place.

Usage

calc_spread(DT, x_col = "close", y_col = "benchmark_close", name = NULL)

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Compute Spread-Curve Butterfly

Description

Computes a three-point spread-curve butterfly per date using the nearest available tenors.

Usage

calc_spread_curve_butterfly(
  DT,
  date_col = "date",
  tenor_col = "tenor",
  spread_col = "credit_spread",
  tenors = c(2, 5, 10)
)

Arguments

Value

A 'data.table' with one spread-curve butterfly value per date.

Compute Spread-Curve Slope

Description

Computes the per-date linear slope of credit spread against tenor.

Usage

calc_spread_curve_slope(
  DT,
  date_col = "date",
  tenor_col = "tenor",
  spread_col = "credit_spread"
)

Arguments

Value

A 'data.table' with one spread-curve slope estimate per date.

Standard Backtest Performance Summary

Description

Computes a broader one-row performance summary from a path-dependent backtest equity curve and, optionally, the strategy target-position path. This is intended for strategy comparison reports and examples where Sortino alone is too narrow.

Usage

calc_strategy_performance_summary(
  equity,
  tgt_pos = NULL,
  annualization = 252,
  risk_free_return = 0,
  min_acceptable_return = 0,
  fee_paid = NULL,
  funding_paid = NULL,
  leverage = NULL,
  recorder = attr(equity, "recorder", exact = TRUE),
  fee_rt = NULL,
  recorder_contract_size = 1,
  turnover_tol = 0
)

Arguments

Value

A one-row 'data.table' with return, risk, drawdown, exposure, turnover, trade-count, and optional cost metrics.

Compute Term-Structure Carry

Description

Computes a simple annualized term-structure carry approximation from the front-versus-deferred futures pair. Positive values indicate positive carry from curve roll-down under backwardation.

Usage

calc_term_structure_carry(
  DT,
  date_col = "date",
  rank_col = "contract_rank",
  price_col = "close",
  time_to_expiry_col = "time_to_expiry",
  rank_front = 1L,
  rank_deferred = 2L
)

Arguments

Value

A 'data.table' with annualized term-structure carry per date.

Add Rolling Tracking-Error Features

Description

Computes rolling tracking-error columns from the return difference between an asset and benchmark series.

Usage

calc_tracking_error(
  DT,
  x_col = "close",
  y_col = "benchmark_close",
  ns = c(20, 60),
  annualization = 252,
  use_log = TRUE
)

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Turnover Features

Description

Computes traded-value turnover and optional float-normalized turnover ratio in place.

Usage

calc_turnover(DT, price_col = "close", volume_col = "volume", float_col = NULL)

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Ultimate Oscillator Features

Description

Computes Ultimate Oscillator columns from candle highs, lows, and closes in place using weighted buy-pressure to true-range ratios across three windows.

Usage

calc_ultimateOscillator(DT, nss = list(c(7, 14, 28)), wtss = list(c(4, 2, 1)))

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Add Z-Score Features

Description

Computes rolling z-score columns in place for the selected input columns.

Usage

calc_zscore(DT, cols = "close", ns = c(20, 60), sample = TRUE)

Arguments

Value

The input 'DT', modified by reference and returned invisibly.

Compare Strategy Backtests

Description

Runs multiple 'strat_*_tgt_pos()' functions over the same market data and execution assumptions, summarizes each path, and ranks the results by a selected metric.

Usage

compare_strategy_backtests(
  DT,
  strategies,
  from = NULL,
  to = NULL,
  score_col = "sortino",
  keep_paths = FALSE,
  ctr_size = 1,
  ctr_step = 1,
  lev = 10,
  fee_rt = 0,
  fund_rt = 0,
  tol_pos = 0.1,
  rec = FALSE,
  annualization = 252,
  risk_free_return = 0,
  min_acceptable_return = 0,
  turnover_tol = 0
)

Arguments

Value

A ranked 'data.table' containing strategy labels, identifiers, and performance summary metrics.

Filter Walk-Forward Results for Overfit Risk

Description

Applies simple out-of-sample robustness gates to walk-forward mining results. This helper is intentionally conservative: it filters on realized test-window summaries rather than on in-sample fit quality.

Usage

filter_walk_forward_results(
  x,
  score_col = "sortino",
  group_cols = NULL,
  min_windows = 3L,
  min_positive_return_rate = 0.5,
  min_avg_score = -Inf,
  max_avg_score_decay = Inf,
  max_warmup_insufficient_rate = 0,
  min_avg_total_return = -Inf
)

Arguments

Value

A ranked 'data.table' of groups that pass the robustness filters, with filter thresholds recorded as columns.

Generate a Market-Order Action Plan

Description

Translates current account state and a target position into an executable market-order action plan.

Usage

gen_action_plan_rcpp(
  ctr_size,
  ctr_step,
  lev,
  last_px,
  ctr_unit,
  avg_price,
  cash,
  tgt_pos,
  tol_pos,
  strat_id,
  pos_dir = 0L
)

Arguments

Value

A list describing the action plan required to move toward 'tgt_pos'.

Mine Strategy Parameters Across Asset-Year Pairs

Description

First mines the best parameter rows on selected seed assets over the full period. It then evaluates the unique selected parameter rows across every valid asset-year pair, keeps only pairs where strategy total return beats a simple buy-and-hold return, and ranks the survivors by Sortino ratio.

Usage

mine_strategy_asset_years(
  market_data_list,
  strategy_fun,
  param_grid,
  seed_assets = c("SPY", "AGG", "IAU", "IBIT", "USO", "UUP"),
  seed_n_best = 1L,
  asset_names = NULL,
  years = NULL,
  from = NULL,
  to = NULL,
  min_year_rows = 200L,
  warmup_days = 365L,
  warmup_years = NULL,
  score_col = "sortino",
  keep_paths = FALSE,
  strat_id = 0L,
  asset_id = 0L,
  ctr_size = 1,
  ctr_step = 1,
  lev = 10,
  fee_rt = 0,
  fund_rt = 0,
  tol_pos = 0.1,
  rec = FALSE,
  annualization = 252,
  risk_free_return = 0,
  min_acceptable_return = 0
)

Arguments

Details

Asset-year strategy signals are computed on a wider signal window that can include warmup history before the trade year. The reported performance is always computed on the trade/evaluation asset-year slice only.

Value

A list with 'seed_params', 'candidate_params', and 'asset_year_results' 'data.table's.

Mine Strategy Assets

Description

Loops over a list of assets for one fixed strategy parameter set and backtesting period, then ranks assets by Sortino ratio by default.

Usage

mine_strategy_assets(
  market_data_list,
  strategy_fun,
  strategy_params = list(),
  asset_names = NULL,
  from = NULL,
  to = NULL,
  score_col = "sortino",
  keep_paths = FALSE,
  strat_id = 0L,
  asset_id = 0L,
  ctr_size = 1,
  ctr_step = 1,
  lev = 10,
  fee_rt = 0,
  fund_rt = 0,
  tol_pos = 0.1,
  rec = FALSE,
  annualization = 252,
  risk_free_return = 0,
  min_acceptable_return = 0
)

Arguments

Value

A ranked 'data.table' containing asset labels and performance metrics.

Mine Strategy Parameters

Description

Loops over a strategy parameter grid for one fixed asset and backtesting period, then ranks parameter sets by Sortino ratio by default.

Usage

mine_strategy_params(
  DT,
  strategy_fun,
  param_grid,
  from = NULL,
  to = NULL,
  score_col = "sortino",
  keep_paths = FALSE,
  strat_id = 0L,
  asset_id = 0L,
  ctr_size = 1,
  ctr_step = 1,
  lev = 10,
  fee_rt = 0,
  fund_rt = 0,
  tol_pos = 0.1,
  rec = FALSE,
  annualization = 252,
  risk_free_return = 0,
  min_acceptable_return = 0
)

Arguments

Value

A ranked 'data.table' containing parameter values and performance metrics.

Walk-Forward Strategy Mining

Description

Performs rolling train/test strategy mining. For each window, parameter rows are ranked on the training slice, the best rows are evaluated on the following test slice, and test signals are computed on a wider window that can include warmup history.

Usage

mine_strategy_walk_forward(
  DT,
  strategy_fun,
  param_grid,
  train_years = 3,
  test_years = 1,
  step_years = 1,
  n_best = 1L,
  from = NULL,
  to = NULL,
  min_train_rows = 200L,
  min_test_rows = 50L,
  warmup_days = 365L,
  warmup_years = NULL,
  score_col = "sortino",
  keep_paths = FALSE,
  strat_id = 0L,
  asset_id = 0L,
  ctr_size = 1,
  ctr_step = 1,
  lev = 10,
  fee_rt = 0,
  fund_rt = 0,
  tol_pos = 0.1,
  rec = FALSE,
  annualization = 252,
  risk_free_return = 0,
  min_acceptable_return = 0,
  turnover_tol = 0
)

Arguments

Value

A list with 'windows', 'train_results', and ranked 'test_results' 'data.table's.

Plan Curve Trade Adjustment

Description

Computes hedge units that move current key-rate exposure toward target key-rate exposure.

Usage

plan_curve_trade_adjustment(current_krd, target_krd, hedge_krd)

Arguments

Value

A 'data.table' with tenor, current, target, gap, hedge exposure, and hedge units.

Plan Delta-Neutral Adjustment

Description

Computes hedge units needed to move current delta toward a target delta.

Usage

plan_delta_neutral_adjustment(current_delta, target_delta = 0, hedge_delta)

Arguments

Value

A one-row 'data.table' with current, target, gap, hedge exposure, hedge units, absolute hedge units, and hedge action.

Plan Duration-Neutral Adjustment

Description

Computes the hedge units needed to move current DV01 toward a target DV01.

Usage

plan_duration_neutral_adjustment(current_dv01, target_dv01 = 0, hedge_dv01)

Arguments

Value

A one-row 'data.table' with current, target, gap, and hedge units.

Plan Portfolio Adjustments

Description

Converts target portfolio weights into per-asset rebalancing deltas using the current portfolio state. This is a minimal multi-asset bridge between quantitative allocation outputs and executable portfolio adjustments.

Usage

plan_portfolio_adjustment(
  portfolio_state,
  equity,
  contract_size_col = "contract_size",
  lot_step_col = "lot_step"
)

Arguments

Value

A 'data.table' with current, target, and delta notional/unit columns.

Plan Vega Target Adjustment

Description

Computes hedge units needed to move current vega toward a target vega.

Usage

plan_vega_target_adjustment(current_vega, target_vega = 0, hedge_vega)

Arguments

Value

A one-row 'data.table' with current, target, gap, hedge exposure, hedge units, absolute hedge units, and hedge action.

Rank Strategy Results

Description

Orders a strategy result table by a selected score column and adds a 'rank' column. This helper is shared by comparison workflows and can also be used on custom result tables.

Usage

rank_strategy_results(result_dt, score_col = "sortino", decreasing = TRUE)

Arguments

Value

A ranked 'data.table'.

Select Strategy Parameter Candidates

Description

Extracts reusable parameter rows from a ranked mining result. This is useful after parameter, asset-year, or walk-forward mining when the next step is to rerun a strategy with the best discovered settings.

Usage

select_strategy_params(
  x,
  n = 1L,
  param_cols = NULL,
  score_col = "sortino",
  decreasing = TRUE,
  unique_params = TRUE,
  include_metrics = FALSE,
  table = c("auto", "seed_params", "candidate_params", "asset_year_results",
    "train_results", "test_results"),
  rerank = FALSE
)

Arguments

Value

A 'data.table' containing selected parameter rows.

ATR-Breakout Action Plan

Description

Applies the ATR breakout rule to the latest bar and translates the resulting target exposure into an executable action plan.

Usage

strat_atr_breakout_action_plan(
  DT,
  state,
  n = 14L,
  atr_mult = 1,
  target_size = 1,
  compute_features = TRUE,
  strat_id = 401L,
  tol_pos = 0.1,
  debug = FALSE
)

Arguments

Value

A list produced by 'gen_action_plan_rcpp()'.

ATR-Breakout Target Positions

Description

Generates a simple breakout target-position path from close-to-close moves measured against prior ATR. Upside moves larger than 'atr_mult * ATR' target a long exposure, while downside moves larger than the same threshold target a short exposure.

Usage

strat_atr_breakout_tgt_pos(
  DT,
  n = 14L,
  atr_mult = 1,
  target_size = 1,
  compute_features = TRUE,
  debug = FALSE
)

Arguments

Value

A numeric vector of target positions, or a list when 'debug = TRUE'.

ATR-Breakout-Trailing-Stop Action Plan

Description

Applies the ATR breakout with trailing-stop rule to the latest bar and translates the resulting target exposure into an executable action plan.

Usage

strat_atr_breakout_trailing_stop_action_plan(
  DT,
  state,
  n = 14L,
  atr_mult = 1,
  trail_mult = 2,
  target_size = 1,
  compute_features = TRUE,
  strat_id = 405L,
  tol_pos = 0.1,
  debug = FALSE
)

Arguments

Value

A list produced by 'gen_action_plan_rcpp()'.

ATR-Breakout-Trailing-Stop Target Positions

Description

Generates a breakout target-position path from ATR moves with an ATR-based trailing stop. Entries use the current ATR breakout rule, and exits trail the most favorable close by a multiple of current ATR.

Usage

strat_atr_breakout_trailing_stop_tgt_pos(
  DT,
  n = 14L,
  atr_mult = 1,
  trail_mult = 2,
  target_size = 1,
  compute_features = TRUE,
  debug = FALSE
)

Arguments

Value

A numeric vector of target positions, or a list when 'debug = TRUE'.

Bollinger-Low-ADX-Reversion Action Plan

Description

Applies the low-ADX Bollinger reversion rule to the latest bar and translates the resulting target exposure into an executable action plan.

Usage

strat_bollinger_low_adx_revert_action_plan(
  DT,
  state,
  n = 20L,
  k = 2,
  adx_n = 14L,
  adx_max = 18,
  target_size = 1,
  compute_features = TRUE,
  strat_id = 312L,
  tol_pos = 0.1,
  debug = FALSE
)

Arguments

Value

A list produced by 'gen_action_plan_rcpp()'.

Bollinger-Low-ADX-Reversion Target Positions

Description

Generates a Bollinger-band mean-reversion target-position path that is only active in low-ADX regimes. Open reversion positions are also flattened if ADX rises above the permitted regime threshold.

Usage

strat_bollinger_low_adx_revert_tgt_pos(
  DT,
  n = 20L,
  k = 2,
  adx_n = 14L,
  adx_max = 18,
  target_size = 1,
  compute_features = TRUE,
  debug = FALSE
)

Arguments

Value

A numeric vector of target positions, or a list when 'debug = TRUE'.

Bollinger-Reversion Action Plan

Description

Applies the Bollinger-band mean-reversion rule to the latest bar and translates the resulting target exposure into an executable action plan.

Usage

strat_bollinger_revert_action_plan(
  DT,
  state,
  n = 20L,
  k = 2,
  target_size = 1,
  compute_features = TRUE,
  strat_id = 301L,
  tol_pos = 0.1,
  debug = FALSE
)

Arguments

Value

A list produced by 'gen_action_plan_rcpp()'.

Bollinger-Reversion-RSI Action Plan

Description

Applies the Bollinger-band-plus-RSI mean-reversion rule to the latest bar and translates the resulting target exposure into an executable action plan.

Usage

strat_bollinger_revert_rsi_action_plan(
  DT,
  state,
  bb_n = 20L,
  bb_k = 2,
  rsi_n = 14L,
  oversold = 30,
  overbought = 70,
  exit_level = 50,
  target_size = 1,
  compute_features = TRUE,
  strat_id = 308L,
  tol_pos = 0.1,
  debug = FALSE
)

Arguments

Value

A list produced by 'gen_action_plan_rcpp()'.

Bollinger-Reversion-RSI Target Positions

Description

Generates a Bollinger-band mean-reversion target-position path that requires RSI confirmation before opening long or short reversion trades.

Usage

strat_bollinger_revert_rsi_tgt_pos(
  DT,
  bb_n = 20L,
  bb_k = 2,
  rsi_n = 14L,
  oversold = 30,
  overbought = 70,
  exit_level = 50,
  target_size = 1,
  compute_features = TRUE,
  debug = FALSE
)

Arguments

Value

A numeric vector of target positions, or a list when 'debug = TRUE'.

Bollinger-Reversion Target Positions

Description

Generates a simple mean-reversion target-position path from Bollinger band touches. Touching the lower band opens a long target, touching the upper band opens a short target, and open targets are closed when price returns to the mid band.

Usage

strat_bollinger_revert_tgt_pos(
  DT,
  n = 20L,
  k = 2,
  target_size = 1,
  compute_features = TRUE,
  debug = FALSE
)

Arguments

Value

A numeric vector of target positions, or a list when 'debug = TRUE'.

Bollinger-Squeeze-Breakout Action Plan

Description

Applies the squeeze-breakout rule to the latest bar and translates the resulting target exposure into an executable action plan.

Usage

strat_bollinger_squeeze_breakout_action_plan(
  DT,
  state,
  bb_n = 20L,
  bb_k = 2,
  squeeze_width = 0.05,
  target_size = 1,
  compute_features = TRUE,
  strat_id = 309L,
  tol_pos = 0.1,
  debug = FALSE
)

Arguments

Value

A list produced by 'gen_action_plan_rcpp()'.

Bollinger-Squeeze-Breakout Target Positions

Description

Generates a volatility-compression breakout target-position path. The strategy arms when Bollinger-band width falls below a squeeze threshold, then enters in the breakout direction when price breaches the outer band during width expansion. Open positions are closed on a return to the mid band.

Usage

strat_bollinger_squeeze_breakout_tgt_pos(
  DT,
  bb_n = 20L,
  bb_k = 2,
  squeeze_width = 0.05,
  target_size = 1,
  compute_features = TRUE,
  debug = FALSE
)

Arguments

Value

A numeric vector of target positions, or a list when 'debug = TRUE'.

Bond-Carry-and-Roll Action Plan

Description

Applies the bond carry-and-roll rule to the latest row and translates the resulting target exposure into an executable action plan.

Usage

strat_bond_carry_roll_action_plan(
  DT,
  state,
  par_col = "par",
  c_rate_col = "c_rate",
  maturity_col = "maturity",
  freq_col = "freq",
  ytm_col = "ytm",
  accrual_frac_col = NULL,
  holding_years_col = NULL,
  funding_rate_col = NULL,
  long_threshold = 0,
  short_threshold = 0,
  target_size = 1,
  compute_features = TRUE,
  strat_id = 602L,
  tol_pos = 0.1,
  debug = FALSE
)

Arguments

Value

A list produced by 'gen_action_plan_rcpp()'.

Bond-Carry-and-Roll-Duration-Cap Action Plan

Description

Applies the duration-capped bond carry-and-roll rule to the latest row and translates the resulting target exposure into an executable action plan.

Usage

strat_bond_carry_roll_duration_cap_action_plan(
  DT,
  state,
  par_col = "par",
  c_rate_col = "c_rate",
  maturity_col = "maturity",
  freq_col = "freq",
  ytm_col = "ytm",
  duration_col = NULL,
  duration_max = NULL,
  duration_min = NULL,
  accrual_frac_col = NULL,
  holding_years_col = NULL,
  funding_rate_col = NULL,
  long_threshold = 0,
  short_threshold = 0,
  target_size = 1,
  compute_features = TRUE,
  strat_id = 613L,
  tol_pos = 0.1,
  debug = FALSE
)

Arguments

Value

A list produced by 'gen_action_plan_rcpp()'.

Bond-Carry-and-Roll-Duration-Cap Target Positions

Description

Generates a bond carry-and-roll target-position path with an optional duration bucket or cap. The base signal is carry plus roll-down return, but positions are only allowed when modified duration remains within the requested range.

Usage

strat_bond_carry_roll_duration_cap_tgt_pos(
  DT,
  par_col = "par",
  c_rate_col = "c_rate",
  maturity_col = "maturity",
  freq_col = "freq",
  ytm_col = "ytm",
  duration_col = NULL,
  duration_max = NULL,
  duration_min = NULL,
  accrual_frac_col = NULL,
  holding_years_col = NULL,
  funding_rate_col = NULL,
  long_threshold = 0,
  short_threshold = 0,
  target_size = 1,
  compute_features = TRUE,
  debug = FALSE
)

Arguments

Value

A numeric vector of target positions, or a list when 'debug = TRUE'.

Bond-Carry-and-Roll-Spread-Filter Action Plan

Description

Applies the bond carry-and-roll rule with optional spread filters to the latest row and translates the resulting target exposure into an executable action plan.

Usage

strat_bond_carry_roll_spread_filter_action_plan(
  DT,
  state,
  par_col = "par",
  c_rate_col = "c_rate",
  maturity_col = "maturity",
  freq_col = "freq",
  ytm_col = "ytm",
  spread_col = "credit_spread",
  accrual_frac_col = NULL,
  holding_years_col = NULL,
  funding_rate_col = NULL,
  long_threshold = 0,
  short_threshold = 0,
  min_long_spread = NULL,
  max_short_spread = NULL,
  target_size = 1,
  compute_features = TRUE,
  strat_id = 606L,
  tol_pos = 0.1,
  debug = FALSE
)

Arguments

Value

A list produced by 'gen_action_plan_rcpp()'.

Bond-Carry-and-Roll-Spread-Filter Target Positions

Description

Generates a bond carry-and-roll target-position path that applies optional spread filters before allowing long or short exposure.

Usage

strat_bond_carry_roll_spread_filter_tgt_pos(
  DT,
  par_col = "par",
  c_rate_col = "c_rate",
  maturity_col = "maturity",
  freq_col = "freq",
  ytm_col = "ytm",
  spread_col = "credit_spread",
  accrual_frac_col = NULL,
  holding_years_col = NULL,
  funding_rate_col = NULL,
  long_threshold = 0,
  short_threshold = 0,
  min_long_spread = NULL,
  max_short_spread = NULL,
  target_size = 1,
  compute_features = TRUE,
  debug = FALSE
)

Arguments

Value

A numeric vector of target positions, or a list when 'debug = TRUE'.

Bond-Carry-and-Roll Target Positions

Description

Generates a simple bond target-position path from carry plus roll-down return. Positive carry-and-roll targets a long exposure and negative carry-and-roll targets a short exposure.

Usage

strat_bond_carry_roll_tgt_pos(
  DT,
  par_col = "par",
  c_rate_col = "c_rate",
  maturity_col = "maturity",
  freq_col = "freq",
  ytm_col = "ytm",
  accrual_frac_col = NULL,
  holding_years_col = NULL,
  funding_rate_col = NULL,
  long_threshold = 0,
  short_threshold = 0,
  target_size = 1,
  compute_features = TRUE,
  debug = FALSE
)

Arguments

Value

A numeric vector of target positions, or a list when 'debug = TRUE'.

Buy-And-Hold Action Plan

Description

Applies the buy-and-hold target rule to the latest bar and translates the resulting target exposure into an executable action plan.

Usage

strat_buy_and_hold_action_plan(
  DT,
  state,
  value = 1,
  strat_id = 1L,
  tol_pos = 0
)

Arguments

Value

A list produced by 'gen_action_plan_rcpp()'.

Buy-And-Hold Target Positions

Description

Generates a constant target exposure path for a simple buy-and-hold strategy.

Usage

strat_buy_and_hold_tgt_pos(DT, value = 1)

Arguments

Value

A numeric vector of target positions with length 'nrow(DT)'.

Credit-Spread-Momentum Action Plan

Description

Applies the credit-spread momentum rule to the latest row and translates the resulting target exposure into an executable action plan.

Usage

strat_credit_spread_momentum_action_plan(
  DT,
  state,
  spread_col = "credit_spread",
  n = 20L,
  yield_col = "ytm",
  benchmark_yield_col = "benchmark_ytm",
  momentum_col = NULL,
  long_threshold = 0,
  short_threshold = 0,
  target_size = 1,
  compute_features = TRUE,
  strat_id = 609L,
  tol_pos = 0.1,
  debug = FALSE
)

Arguments

Value

A list produced by 'gen_action_plan_rcpp()'.

Credit-Spread-Momentum Target Positions

Description

Generates a target-position path from momentum in credit spreads. Positive spread momentum targets a long widener exposure and negative spread momentum targets a short or tightening exposure.

Usage

strat_credit_spread_momentum_tgt_pos(
  DT,
  spread_col = "credit_spread",
  n = 20L,
  yield_col = "ytm",
  benchmark_yield_col = "benchmark_ytm",
  momentum_col = NULL,
  long_threshold = 0,
  short_threshold = 0,
  target_size = 1,
  compute_features = TRUE,
  debug = FALSE
)

Arguments

Value

A numeric vector of target positions, or a list when 'debug = TRUE'.

Credit-Spread-Reversion Action Plan

Description

Applies the credit-spread mean-reversion rule to the latest row and translates the resulting target exposure into an executable action plan.

Usage

strat_credit_spread_revert_action_plan(
  DT,
  state,
  signal_col = "excess_spread",
  z_n = 20L,
  entry_z = 2,
  exit_z = 0.5,
  spread_col = "credit_spread",
  benchmark_spread_col = "benchmark_spread",
  yield_col = "ytm",
  benchmark_yield_col = "benchmark_ytm",
  target_size = 1,
  compute_features = TRUE,
  sample = TRUE,
  strat_id = 610L,
  tol_pos = 0.1,
  debug = FALSE
)

Arguments

Value

A list produced by 'gen_action_plan_rcpp()'.

Credit-Spread-Reversion Target Positions

Description

Generates a mean-reversion target-position path from standardized credit spread or excess-spread signals. Wide positive excess spread targets a long tightening exposure, while strongly negative excess spread targets a short exposure.

Usage

strat_credit_spread_revert_tgt_pos(
  DT,
  signal_col = "excess_spread",
  z_n = 20L,
  entry_z = 2,
  exit_z = 0.5,
  spread_col = "credit_spread",
  benchmark_spread_col = "benchmark_spread",
  yield_col = "ytm",
  benchmark_yield_col = "benchmark_ytm",
  target_size = 1,
  compute_features = TRUE,
  sample = TRUE,
  debug = FALSE
)

Arguments

Value

A numeric vector of target positions, or a list when 'debug = TRUE'.

Cross-Sectional-Rank-Allocator Action Plan

Description

Applies the latest cross-sectional target weights to a portfolio state and converts them into a portfolio-adjustment table plus order intents.

Usage

strat_cross_sectional_rank_allocator_action_plan(
  DT,
  portfolio_state,
  equity,
  date_col = "date",
  asset_col = "asset",
  signal_col = "score",
  long_n = 1L,
  short_n = 0L,
  gross_exposure = 1,
  strat_id = 507L,
  pricing_method = "market",
  debug = FALSE
)

Arguments

Value

A list with 'adjustment_plan', 'order_intents', and the latest target weights.

Cross-Sectional-Rank-Allocator Target Positions

Description

Generates per-row target weights from cross-sectional signal ranks within each date. Top-ranked assets receive positive target weights and optionally bottom-ranked assets receive negative target weights.

Usage

strat_cross_sectional_rank_allocator_tgt_pos(
  DT,
  date_col = "date",
  asset_col = "asset",
  signal_col = "score",
  long_n = 1L,
  short_n = 0L,
  gross_exposure = 1,
  debug = FALSE
)

Arguments

Value

A numeric vector of target weights aligned with 'DT', or a list when 'debug = TRUE'.

Curve-Butterfly Action Plan

Description

Applies the curve-butterfly rule to the latest row and translates the resulting target exposure into an executable action plan.

Usage

strat_curve_butterfly_action_plan(
  DT,
  state,
  short_rate_col = "short_rate",
  mid_rate_col = "mid_rate",
  long_rate_col = "long_rate",
  long_threshold = 0,
  short_threshold = 0,
  target_size = 1,
  compute_features = TRUE,
  strat_id = 608L,
  tol_pos = 0.1,
  debug = FALSE
)

Arguments

Value

A list produced by 'gen_action_plan_rcpp()'.

Curve-Butterfly Target Positions

Description

Generates a target-position path from a simple yield-curve butterfly measure. Positive butterfly values target a long-butterfly exposure and negative values target a short-butterfly exposure.

Usage

strat_curve_butterfly_tgt_pos(
  DT,
  short_rate_col = "short_rate",
  mid_rate_col = "mid_rate",
  long_rate_col = "long_rate",
  long_threshold = 0,
  short_threshold = 0,
  target_size = 1,
  compute_features = TRUE,
  debug = FALSE
)

Arguments

Value

A numeric vector of target positions, or a list when 'debug = TRUE'.

Curve-Steepener Action Plan

Description

Applies the curve-steepener rule to the latest row and translates the resulting target exposure into an executable action plan.

Usage

strat_curve_steepener_action_plan(
  DT,
  state,
  short_rate_col = "short_rate",
  long_rate_col = "long_rate",
  long_threshold = 0,
  short_threshold = 0,
  target_size = 1,
  compute_features = TRUE,
  strat_id = 603L,
  tol_pos = 0.1,
  debug = FALSE
)

Arguments

Value

A list produced by 'gen_action_plan_rcpp()'.

Curve-Steepener Target Positions

Description

Generates a simple curve-steepener target-position path from yield-curve slope. Positive slope targets a steepener exposure and negative slope targets a flattener exposure.

Usage

strat_curve_steepener_tgt_pos(
  DT,
  short_rate_col = "short_rate",
  long_rate_col = "long_rate",
  long_threshold = 0,
  short_threshold = 0,
  target_size = 1,
  compute_features = TRUE,
  debug = FALSE
)

Arguments