DeepDow
stable
USING DEEPDOW:
Installation
Introduction
Basics
Data Loading
Benchmarks
Layers
Networks
Losses
Experiments
Examples
DEVELOPMENT
Changelog
API Reference:
deepdow package
DeepDow
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Index
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A
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B
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C
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D
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E
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F
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G
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H
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I
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K
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L
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M
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N
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O
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P
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Q
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R
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S
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T
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V
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W
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Z
_
__call__() (Alpha method)
(Benchmark method)
(Compose method)
(CumulativeReturn method)
(Dropout method)
(InverseVolatility method)
(KeynesNet method)
(LargestWeight method)
(Loss method)
(MaximumDrawdown method)
(MaximumReturn method)
(MeanReturns method)
(MinimumVariance method)
(Multiply method)
(Noise method)
(OneOverN method)
(Quantile method)
(Random method)
(RiskParity method)
(Scale method)
(SharpeRatio method)
(Singleton method)
(Softmax method)
(SortinoRatio method)
(SquaredWeights method)
(StandardDeviation method)
(TargetMeanReturn method)
(TargetStandardDeviation method)
(WorstReturn method)
_previous (ChangeWorkingDirectory attribute)
A
add_entry() (History method)
affine (AttentionCollapse attribute)
allocate_layer (LinearNet attribute)
(MinimalNet attribute)
alpha (BachelierNet attribute)
Alpha (class in deepdow.losses)
alpha (ThorpNet attribute)
AnalyticalMarkowitz (class in deepdow.layers.allocate)
AttentionCollapse (class in deepdow.layers.collapse)
AverageCollapse (class in deepdow.layers.collapse)
B
BachelierNet (class in deepdow.nn)
bar (ProgressBarCallback attribute)
batch_size (FlexibleDataLoader attribute)
(RigidDataLoader attribute)
Benchmark (class in deepdow.benchmarks)
BenchmarkCallback (class in deepdow.callbacks)
C
Callback (class in deepdow.callbacks)
callbacks (Run attribute)
ChangeWorkingDirectory (class in deepdow.utils)
channel_collapse_layer (BachelierNet attribute)
check_indices_agree() (PandasChecks static method)
check_no_gaps() (PandasChecks static method)
check_valid_entries() (PandasChecks static method)
collate_uniform() (in module deepdow.data.load)
Compose (class in deepdow.data.augment)
compute_covariance() (CovarianceMatrix static method)
compute_distances() (KMeans static method)
compute_sqrt() (CovarianceMatrix static method)
context_vector (AttentionCollapse attribute)
Conv (class in deepdow.layers.transform)
Cov2Corr (class in deepdow.layers.misc)
covariance() (in module deepdow.losses)
covariance_layer (BachelierNet attribute)
(RiskParity attribute)
CovarianceMatrix (class in deepdow.layers.misc)
create_custom_postfix_str() (ProgressBarCallback static method)
CumulativeReturn (class in deepdow.losses)
cvxpylayer (NumericalMarkowitz attribute)
(NumericalRiskBudgeting attribute)
D
database (History attribute)
dataset (FlexibleDataLoader attribute)
(RigidDataLoader attribute)
deepdow.benchmarks
module
deepdow.callbacks
module
deepdow.data.augment
module
deepdow.data.load
module
deepdow.data.synthetic
module
deepdow.experiments
module
deepdow.explain
module
deepdow.layers.allocate
module
deepdow.layers.collapse
module
deepdow.layers.misc
module
deepdow.layers.transform
module
deepdow.losses
module
deepdow.nn
module
deepdow.utils
module
drop_last (FlexibleDataLoader attribute)
(RigidDataLoader attribute)
Dropout (class in deepdow.data.augment)
dropout_layer (BachelierNet attribute)
(LinearNet attribute)
DummyNet (class in deepdow.nn)
E
EarlyStoppingCallback (class in deepdow.callbacks)
EarlyStoppingException
ElementCollapse (class in deepdow.layers.collapse)
exp_returns (ThorpNet attribute)
ExponentialCollapse (class in deepdow.layers.collapse)
F
FlexibleDataLoader (class in deepdow.data.load)
forward() (AnalyticalMarkowitz method)
(AttentionCollapse method)
(AverageCollapse method)
(BachelierNet method)
(Conv method)
(Cov2Corr method)
(CovarianceMatrix method)
(DummyNet method)
(ElementCollapse method)
(ExponentialCollapse method)
(KMeans method)
(LinearNet method)
(MaxCollapse method)
(MinimalNet method)
(MultiplyByConstant method)
(NCO method)
(NumericalMarkowitz method)
(NumericalRiskBudgeting method)
(Resample method)
(RNN method)
(SoftmaxAllocator method)
(SparsemaxAllocator method)
(SumCollapse method)
(ThorpNet method)
(Warp method)
(WeightNorm method)
(Zoom method)
G
gamma (BachelierNet attribute)
gamma_sqrt (ThorpNet attribute)
gradient_wrt_input() (in module deepdow.explain)
H
History (class in deepdow.experiments)
hparams() (BachelierNet property)
(Benchmark property)
(DummyNet property)
(FlexibleDataLoader property)
(InverseVolatility property)
(KeynesNet property)
(LinearNet property)
(MaximumReturn property)
(MinimalNet property)
(MinimumVariance property)
(RigidDataLoader property)
(Run property)
(Singleton property)
(ThorpNet property)
I
initialize() (KMeans method)
InRAMDataset (class in deepdow.data.load)
InverseVolatility (class in deepdow.benchmarks)
K
KeynesNet (class in deepdow.nn)
KMeans (class in deepdow.layers.misc)
L
LargestWeight (class in deepdow.losses)
launch() (Run method)
linear (LinearNet attribute)
LinearNet (class in deepdow.nn)
log2simple() (in module deepdow.losses)
Loss (class in deepdow.losses)
M
matrix (ThorpNet attribute)
MaxCollapse (class in deepdow.layers.collapse)
MaximumDrawdown (class in deepdow.losses)
MaximumReturn (class in deepdow.benchmarks)
MeanReturns (class in deepdow.losses)
metrics (ProgressBarCallback attribute)
(Run attribute)
metrics() (History property)
metrics_per_epoch() (History method)
min (EarlyStoppingCallback attribute)
(ModelCheckpointCallback attribute)
MinimalNet (class in deepdow.nn)
MinimumVariance (class in deepdow.benchmarks)
MLFlowCallback (class in deepdow.callbacks)
ModelCheckpointCallback (class in deepdow.callbacks)
models (Run attribute)
module
deepdow.benchmarks
deepdow.callbacks
deepdow.data.augment
deepdow.data.load
deepdow.data.synthetic
deepdow.experiments
deepdow.explain
deepdow.layers.allocate
deepdow.layers.collapse
deepdow.layers.misc
deepdow.layers.transform
deepdow.losses
deepdow.nn
deepdow.utils
Multiply (class in deepdow.data.augment)
MultiplyByConstant (class in deepdow.layers.misc)
N
n_epochs_no_improvement (EarlyStoppingCallback attribute)
NCO (class in deepdow.layers.allocate)
Noise (class in deepdow.data.augment)
norm_layer (BachelierNet attribute)
(LinearNet attribute)
norm_layer_1 (KeynesNet attribute)
norm_layer_2 (KeynesNet attribute)
num_workers (FlexibleDataLoader attribute)
(RigidDataLoader attribute)
NumericalMarkowitz (class in deepdow.layers.allocate)
NumericalRiskBudgeting (class in deepdow.layers.allocate)
O
on_batch_begin() (Callback method)
(Run method)
(TensorBoardCallback method)
on_batch_end() (Callback method)
(ProgressBarCallback method)
(Run method)
(TensorBoardCallback method)
on_epoch_begin() (Callback method)
(ProgressBarCallback method)
(Run method)
on_epoch_end() (Callback method)
(EarlyStoppingCallback method)
(MLFlowCallback method)
(ModelCheckpointCallback method)
(ProgressBarCallback method)
(Run method)
(TensorBoardCallback method)
(ValidationCallback method)
on_train_begin() (BenchmarkCallback method)
(Callback method)
(EarlyStoppingCallback method)
(MLFlowCallback method)
(ModelCheckpointCallback method)
(Run method)
(TensorBoardCallback method)
on_train_end() (Callback method)
(Run method)
on_train_interrupt() (Callback method)
(EarlyStoppingCallback method)
(Run method)
OneOverN (class in deepdow.benchmarks)
optlayer (MaximumReturn attribute)
(MinimumVariance attribute)
output (ProgressBarCallback attribute)
P
PandasChecks (class in deepdow.utils)
pin_memory (FlexibleDataLoader attribute)
(RigidDataLoader attribute)
portfolio_cumulative_returns() (in module deepdow.losses)
portfolio_opt_layer (BachelierNet attribute)
(KeynesNet attribute)
portfolio_returns() (in module deepdow.losses)
prefetch_factor (FlexibleDataLoader attribute)
(RigidDataLoader attribute)
prepare_robust_scaler() (in module deepdow.data.augment)
prepare_standard_scaler() (in module deepdow.data.augment)
pretty_print() (History method)
prices_to_returns() (in module deepdow.utils)
ProgressBarCallback (class in deepdow.callbacks)
Q
Quantile (class in deepdow.losses)
R
Random (class in deepdow.benchmarks)
raw_to_Xy() (in module deepdow.utils)
Resample (class in deepdow.layers.allocate)
returns_to_Xy() (in module deepdow.utils)
RigidDataLoader (class in deepdow.data.load)
RiskParity (class in deepdow.losses)
RNN (class in deepdow.layers.transform)
run (BenchmarkCallback attribute)
Run (class in deepdow.experiments)
run (MLFlowCallback attribute)
(ProgressBarCallback attribute)
(TensorBoardCallback attribute)
(ValidationCallback attribute)
S
sampler (FlexibleDataLoader attribute)
(RigidDataLoader attribute)
Scale (class in deepdow.data.augment)
SharpeRatio (class in deepdow.losses)
simple2log() (in module deepdow.losses)
sin_single() (in module deepdow.data.synthetic)
Singleton (class in deepdow.benchmarks)
Softmax (class in deepdow.losses)
SoftmaxAllocator (class in deepdow.layers.allocate)
SortinoRatio (class in deepdow.losses)
SparsemaxAllocator (class in deepdow.layers.allocate)
SquaredWeights (class in deepdow.losses)
StandardDeviation (class in deepdow.losses)
SumCollapse (class in deepdow.layers.collapse)
T
TargetMeanReturn (class in deepdow.losses)
TargetStandardDeviation (class in deepdow.losses)
temperature (KeynesNet attribute)
(LinearNet attribute)
TensorBoardCallback (class in deepdow.callbacks)
ThorpNet (class in deepdow.nn)
time_collapse_layer (BachelierNet attribute)
timeout (FlexibleDataLoader attribute)
(RigidDataLoader attribute)
training (AnalyticalMarkowitz attribute)
(AttentionCollapse attribute)
(AverageCollapse attribute)
(BachelierNet attribute)
(Conv attribute)
(Cov2Corr attribute)
(CovarianceMatrix attribute)
(DummyNet attribute)
(ElementCollapse attribute)
(ExponentialCollapse attribute)
(KeynesNet attribute)
(KMeans attribute)
(LinearNet attribute)
(MaxCollapse attribute)
(MinimalNet attribute)
(MultiplyByConstant attribute)
(NCO attribute)
(NumericalMarkowitz attribute)
(NumericalRiskBudgeting attribute)
(Resample attribute)
(RNN attribute)
(SoftmaxAllocator attribute)
(SparsemaxAllocator attribute)
(SumCollapse attribute)
(ThorpNet attribute)
(Warp attribute)
(WeightNorm attribute)
(Zoom attribute)
transform_layer (BachelierNet attribute)
(KeynesNet attribute)
V
val_dataloaders (Run attribute)
ValidationCallback (class in deepdow.callbacks)
W
Warp (class in deepdow.layers.transform)
WeightNorm (class in deepdow.layers.allocate)
WorstReturn (class in deepdow.losses)
Z
Zoom (class in deepdow.layers.transform)
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