diff --git a/.flexci/config.pbtxt b/.flexci/config.pbtxt
index 6360c655..b2b706ca 100644
--- a/.flexci/config.pbtxt
+++ b/.flexci/config.pbtxt
@@ -4,7 +4,7 @@ configs {
     requirement {
       cpu: 2
       gpu: 1
-      memory: 20
+      memory: 30
       disk: 10
     }
     time_limit: {
@@ -20,7 +20,7 @@ configs {
     requirement {
       cpu: 2
       gpu: 1
-      memory: 20
+      memory: 30
       disk: 10
     }
     time_limit: {
@@ -36,7 +36,7 @@ configs {
     requirement {
       cpu: 2
       gpu: 1
-      memory: 20
+      memory: 30
       disk: 10
     }
     time_limit: {
diff --git a/Makefile b/Makefile
index 4ee0861c..fd39583e 100644
--- a/Makefile
+++ b/Makefile
@@ -24,7 +24,7 @@ test-cov:
 	$(RUN) pytest --cov=$(PROJECT_NAME) --cov-report=xml -m "not gpu"
 
 .PHONY: lint
-lint: lint-pysen
+lint: lint-black lint-isort flake8 mypy
 
 .PHONY: lint-black
 lint-black:
@@ -40,27 +40,19 @@ mypy:
 
 .PHONY: flake8
 flake8:
-	$(RUN) flake8 $(PROJECT_NAME)
+	$(RUN) pflake8 $(PROJECT_NAME)
 
 .PHONY: format
-format: format-pysen
+format: format-black format-isort
 
 .PHONY: format-black
 format-black:
-	$(RUN) black --quiet --skip-magic-trailing-comma .
+	$(RUN) black --quiet .
 
 .PHONY: format-isort
 format-isort:
 	$(RUN) isort --force-single-line-imports --quiet .
 
-.PHONY: format-pysen
-format-pysen:
-	$(RUN) pysen run format
-
-.PHONY: lint-pysen
-lint-pysen:
-	$(RUN) pysen run lint
-
 .PHONY: doc
 doc:
 	@cd docs && make html
diff --git a/examples/example_hedging_variance_swap.py b/examples/example_hedging_variance_swap.py
index 55cc6e8b..0cc2bea3 100644
--- a/examples/example_hedging_variance_swap.py
+++ b/examples/example_hedging_variance_swap.py
@@ -26,7 +26,7 @@
     total_vega = torch.zeros_like(spot)
     for option, strike in zip(options_list, strikes_list):
         lm = (spot / strike).log()
-        vega = BlackScholes(option).vega(lm, t, v) / (strike**2)
+        vega = BlackScholes(option).vega(lm, t, v) / (strike ** 2)
         total_vega += vega
         if option.call:
             # 2 is for call and put
diff --git a/lint.py b/lint.py
deleted file mode 100644
index 647b5c90..00000000
--- a/lint.py
+++ /dev/null
@@ -1,25 +0,0 @@
-import pathlib
-from typing import Optional
-from typing import Sequence
-
-import pysen
-from pysen import IsortSetting
-from pysen.component import ComponentBase
-from pysen.manifest import Manifest
-from pysen.manifest import ManifestBase
-
-
-def build(
-    components: Sequence[ComponentBase], src_path: Optional[pathlib.Path]
-) -> ManifestBase:
-    isort_setting: IsortSetting = pysen.IsortSetting.default()
-    isort_setting.force_single_line = True
-    isort_setting.known_first_party = {"pfhedge"}
-
-    isort = pysen.Isort(setting=isort_setting.to_black_compatible())
-
-    others = [
-        component for component in components if not isinstance(component, pysen.Isort)
-    ]
-
-    return Manifest([isort, *others])
diff --git a/pfhedge/features/_base.py b/pfhedge/features/_base.py
index ef4a16dc..e13497d0 100644
--- a/pfhedge/features/_base.py
+++ b/pfhedge/features/_base.py
@@ -74,7 +74,7 @@ def is_state_dependent(self) -> bool:
         # If a feature uses the state of a hedger, it is state dependent.
         return getattr(self, "hedger") is not None
 
-    def __str__(self):
+    def __str__(self) -> str:
         return self.name
 
     # TODO(simaki) Remove later
diff --git a/pfhedge/features/_getter.py b/pfhedge/features/_getter.py
index 66995316..9f64ceb3 100644
--- a/pfhedge/features/_getter.py
+++ b/pfhedge/features/_getter.py
@@ -14,7 +14,7 @@ class FeatureFactory:
     _features: Dict[str, Type[Feature]]
 
     # singleton
-    def __new__(cls, *args, **kwargs):
+    def __new__(cls, *args: Any, **kwargs: Any) -> "FeatureFactory":
         if not hasattr(cls, "_instance"):
             cls._instance = super().__new__(cls)
             cls._instance._features = OrderedDict()
diff --git a/pfhedge/features/features.py b/pfhedge/features/features.py
index 69935b73..e6b0d59d 100644
--- a/pfhedge/features/features.py
+++ b/pfhedge/features/features.py
@@ -134,7 +134,7 @@ def __str__(self) -> str:
 
     def get(self, time_step: Optional[int] = None) -> Tensor:
         index = [time_step] if isinstance(time_step, int) else ...
-        output = self.derivative.ul().spot[:, index].unsqueeze(-1)
+        output = self.derivative.ul().spot[:, index].unsqueeze(-1)  # type: ignore
         if self.log:
             output.log_()
         return output
@@ -147,7 +147,7 @@ class UnderlierLogSpot(UnderlierSpot):
         ``'underlier_log_spot'``
     """
 
-    def __init__(self):
+    def __init__(self) -> None:
         super().__init__(log=True)
 
 
@@ -167,7 +167,7 @@ def __str__(self) -> str:
 
     def get(self, time_step: Optional[int] = None) -> Tensor:
         index = [time_step] if isinstance(time_step, int) else ...
-        output = self.derivative.spot[:, index].unsqueeze(-1)
+        output = self.derivative.spot[:, index].unsqueeze(-1)  # type: ignore
         if self.log:
             output.log_()
         return output
@@ -186,7 +186,7 @@ class Volatility(StateIndependentFeature):
 
     def get(self, time_step: Optional[int] = None) -> Tensor:
         index = [time_step] if isinstance(time_step, int) else ...
-        return self.derivative.ul().volatility[:, index].unsqueeze(-1)
+        return self.derivative.ul().volatility[:, index].unsqueeze(-1)  # type: ignore
 
 
 class Variance(StateIndependentFeature):
@@ -200,7 +200,7 @@ class Variance(StateIndependentFeature):
 
     def get(self, time_step: Optional[int]) -> Tensor:
         index = [time_step] if isinstance(time_step, int) else ...
-        return self.derivative.ul().variance[:, index].unsqueeze(-1)
+        return self.derivative.ul().variance[:, index].unsqueeze(-1)  # type: ignore
 
 
 class PrevHedge(Feature):
@@ -305,7 +305,7 @@ class Zeros(StateIndependentFeature):
 
     def get(self, time_step: Optional[int] = None) -> Tensor:
         index = [time_step] if time_step is not None else ...
-        return torch.zeros_like(self.derivative.ul().spot[..., index]).unsqueeze(-1)
+        return torch.zeros_like(self.derivative.ul().spot[..., index]).unsqueeze(-1)  # type: ignore
 
 
 class Ones(StateIndependentFeature):
@@ -335,7 +335,7 @@ class Ones(StateIndependentFeature):
 
     def get(self, time_step: Optional[int] = None) -> Tensor:
         index = [time_step] if time_step is not None else ...
-        return torch.ones_like(self.derivative.ul().spot[..., index]).unsqueeze(-1)
+        return torch.ones_like(self.derivative.ul().spot[..., index]).unsqueeze(-1)  # type: ignore
 
 
 class Empty(StateIndependentFeature):
@@ -365,7 +365,7 @@ class Empty(StateIndependentFeature):
 
     def get(self, time_step: Optional[int] = None) -> Tensor:
         index = [time_step] if time_step is not None else ...
-        return torch.empty_like(self.derivative.ul().spot[..., index]).unsqueeze(-1)
+        return torch.empty_like(self.derivative.ul().spot[..., index]).unsqueeze(-1)  # type: ignore
 
 
 class MaxMoneyness(StateIndependentFeature):
diff --git a/pfhedge/instruments/derivative/base.py b/pfhedge/instruments/derivative/base.py
index 18785da3..4477c507 100644
--- a/pfhedge/instruments/derivative/base.py
+++ b/pfhedge/instruments/derivative/base.py
@@ -305,7 +305,7 @@ def moneyness(self, time_step: Optional[int] = None, log: bool = False) -> Tenso
             torch.Tensor
         """
         index = ... if time_step is None else [time_step]
-        output = self.underlier.spot[..., index] / self.strike
+        output = self.underlier.spot[..., index] / self.strike  # type: ignore
         if log:
             output = output.log()
         return output
@@ -389,7 +389,7 @@ def max_log_moneyness(self, time_step: Optional[int] = None) -> Tensor:
 class BaseOption(BaseDerivative, OptionMixin):
     """(deprecated) Base class for options."""
 
-    def __init__(self):
+    def __init__(self) -> None:
         super().__init__()
         raise DeprecationWarning(
             "BaseOption is deprecated. Inherit `BaseDerivative` and `OptionMixin` instead."
diff --git a/pfhedge/nn/modules/bs/american_binary.py b/pfhedge/nn/modules/bs/american_binary.py
index 0eec3d0b..066a4953 100644
--- a/pfhedge/nn/modules/bs/american_binary.py
+++ b/pfhedge/nn/modules/bs/american_binary.py
@@ -82,7 +82,9 @@ def __init__(
         self.derivative = derivative
 
     @classmethod
-    def from_derivative(cls, derivative):
+    def from_derivative(
+        cls, derivative: AmericanBinaryOption
+    ) -> "BSAmericanBinaryOption":
         """Initialize a module from a derivative.
 
         Args:
diff --git a/pfhedge/nn/modules/bs/black_scholes.py b/pfhedge/nn/modules/bs/black_scholes.py
index c78c386d..9fafd4dc 100644
--- a/pfhedge/nn/modules/bs/black_scholes.py
+++ b/pfhedge/nn/modules/bs/black_scholes.py
@@ -1,4 +1,5 @@
 from collections import OrderedDict
+from typing import Any
 from typing import Callable
 from typing import Dict
 from typing import Iterator
@@ -17,7 +18,7 @@ class BlackScholesModuleFactory:
     _modules: Dict[str, Type[Module]]
 
     # singleton
-    def __new__(cls, *args, **kwargs):
+    def __new__(cls, *args: Any, **kwargs: Any) -> "BlackScholesModuleFactory":
         if not hasattr(cls, "_instance"):
             cls._instance = super().__new__(cls)
             cls._instance._modules = OrderedDict()
@@ -97,5 +98,5 @@ class BlackScholes(Module):
     vega: Callable[..., Tensor]  # vega(self, ...) -> Tensor
     theta: Callable[..., Tensor]  # theta(self, ...) -> Tensor
 
-    def __new__(cls, derivative):
-        return BlackScholesModuleFactory().get_class_from_derivative(derivative)
+    def __new__(cls, derivative: "Derivative") -> "BlackScholes":
+        return BlackScholesModuleFactory().get_class_from_derivative(derivative)  # type: ignore
diff --git a/pfhedge/nn/modules/bs/european.py b/pfhedge/nn/modules/bs/european.py
index 1c9fb002..c38b52d6 100644
--- a/pfhedge/nn/modules/bs/european.py
+++ b/pfhedge/nn/modules/bs/european.py
@@ -73,7 +73,7 @@ def __init__(
         self.derivative = derivative
 
     @classmethod
-    def from_derivative(cls, derivative):
+    def from_derivative(cls, derivative: EuropeanOption) -> "BSEuropeanOption":
         """Initialize a module from a derivative.
 
         Args:
diff --git a/pfhedge/nn/modules/bs/european_binary.py b/pfhedge/nn/modules/bs/european_binary.py
index 350deb7b..459c51a5 100644
--- a/pfhedge/nn/modules/bs/european_binary.py
+++ b/pfhedge/nn/modules/bs/european_binary.py
@@ -75,7 +75,9 @@ def __init__(
         self.derivative = derivative
 
     @classmethod
-    def from_derivative(cls, derivative):
+    def from_derivative(
+        cls, derivative: EuropeanBinaryOption
+    ) -> "BSEuropeanBinaryOption":
         """Initialize a module from a derivative.
 
         Args:
diff --git a/pfhedge/nn/modules/bs/lookback.py b/pfhedge/nn/modules/bs/lookback.py
index a64429f5..b82992be 100644
--- a/pfhedge/nn/modules/bs/lookback.py
+++ b/pfhedge/nn/modules/bs/lookback.py
@@ -83,7 +83,7 @@ def __init__(
         self.derivative = derivative
 
     @classmethod
-    def from_derivative(cls, derivative):
+    def from_derivative(cls, derivative: LookbackOption) -> "BSLookbackOption":
         """Initialize a module from a derivative.
 
         Args:
diff --git a/pfhedge/nn/modules/hedger.py b/pfhedge/nn/modules/hedger.py
index 75883212..9cd1fc88 100644
--- a/pfhedge/nn/modules/hedger.py
+++ b/pfhedge/nn/modules/hedger.py
@@ -475,7 +475,7 @@ def compute_loss(
         """
         with torch.set_grad_enabled(enable_grad):
 
-            def _get_loss():
+            def _get_loss() -> Tensor:
                 derivative.simulate(n_paths=n_paths, init_state=init_state)
                 portfolio = self.compute_portfolio(derivative, hedge=hedge)
                 return self.criterion(portfolio, derivative.payoff())
@@ -666,7 +666,7 @@ def price(
         """
         with torch.set_grad_enabled(enable_grad):
 
-            def _get_price():
+            def _get_price() -> Tensor:
                 derivative.simulate(n_paths=n_paths, init_state=init_state)
                 portfolio = self.compute_portfolio(derivative, hedge)
                 # Negative because selling
diff --git a/pfhedge/nn/modules/loss.py b/pfhedge/nn/modules/loss.py
index 99b2f11e..7e1eb63e 100644
--- a/pfhedge/nn/modules/loss.py
+++ b/pfhedge/nn/modules/loss.py
@@ -1,4 +1,5 @@
 from abc import ABC
+from abc import abstractmethod
 from typing import Callable
 
 import torch
@@ -20,6 +21,7 @@
 class HedgeLoss(Module, ABC):
     """Base class for hedging criteria."""
 
+    @abstractmethod
     def forward(self, input: Tensor, target: TensorOrScalar = 0.0) -> Tensor:
         """Returns the loss of the profit-loss distribution.
 
@@ -39,6 +41,7 @@ def forward(self, input: Tensor, target: TensorOrScalar = 0.0) -> Tensor:
         Returns:
             torch.Tensor
         """
+        pass
 
     def cash(self, input: Tensor, target: TensorOrScalar = 0.0) -> Tensor:
         """Returns the cash amount which is as preferable as
diff --git a/pfhedge/stochastic/rough_bergomi.py b/pfhedge/stochastic/rough_bergomi.py
index 9176e440..5fa694a0 100644
--- a/pfhedge/stochastic/rough_bergomi.py
+++ b/pfhedge/stochastic/rough_bergomi.py
@@ -122,9 +122,7 @@ def discrete_TBSS_fn(k: torch.Tensor, a: TensorOrScalar) -> torch.Tensor:
     _gamma = torch.cat([torch.zeros(2, dtype=dtype, device=device), _gamma], dim=0)
     _Xi = dW1[:, :, 0]
     _GXi_convolve = torch.nn.functional.conv1d(
-        _gamma.flip(0)[None, None, :],
-        _Xi[:, None, :],
-        padding=_Xi.size(1) - 1,
+        _gamma.flip(0)[None, None, :], _Xi[:, None, :], padding=_Xi.size(1) - 1
     )[0, :, :]
     _Y2 = _GXi_convolve[:, -n_steps:].flip(1)
     Y = torch.sqrt(2 * alpha_tensor + 1) * (_Y1 + _Y2)
diff --git a/poetry.toml b/poetry.toml
deleted file mode 100644
index bb621ad4..00000000
--- a/poetry.toml
+++ /dev/null
@@ -1,4 +0,0 @@
-[installer]
-# TODO(masanorihirano): Remove this after the bugs happenning after poetry version 1.4.1 are fixed in some packages
-# issue #609, avoiding invalid hash (c.f., https://github.com/python-poetry/poetry/issues/7691).
-modern-installation = false
diff --git a/pyproject.toml b/pyproject.toml
index d5a9c78a..20e17934 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -7,25 +7,25 @@ license = "MIT"
 repository = "https://github.com/pfnet-research/pfhedge"
 
 [tool.poetry.dependencies]
-python = "^3.8,<3.12"
+python = "^3.8.1,<3.12"
 torch = ">=1.9.0,<3.0.0"
 tqdm = "^4.62.3"
 
 [tool.poetry.dev-dependencies]
 pytest = "^6.2.5"
 black = "21.9b0"
-isort = "^5.9.3"
-mypy = "0.920"
+isort = "5.9.3"
 pytest-cov = "^3.0.0"
 Sphinx = "^4.2.0"
 sphinx-autobuild = "^2021.3.14"
 sphinx-copybutton = "^0.4.0"
 furo = "^2021.9.22"
 codecov = "^2.1.12"
-pysen = "^0.10.3"
 click = "8.0.4"
 flake8 = "4.0.1"
 scipy = "^1.10.1"
+mypy = "^1.11.1"
+pyproject-flake8 = "4.0.1"
 
 [build-system]
 requires = ["poetry-core>=1.0.0"]
@@ -34,39 +34,53 @@ build-backend = "poetry.core.masonry.api"
 [tool.pytest.ini_options]
 markers = ["gpu: tests using gpu"]
 
-[tool.pysen]
-version = "0.10"
-builder = "lint.py"
-
-[tool.pysen.lint]
-enable_black = true
-enable_flake8 = true
-enable_isort = true
-enable_mypy = true
-mypy_preset = "entry"
-line_length = 88
-py_version = "py37"
-#isort_known_first_party = ["pfhedge"]
-
-[[tool.pysen.lint.mypy_targets]]
-  paths = ["pfhedge"]
-
-[tool.pysen.lint.source]
-  includes = ["."]
-  excludes = ["examples/", "docs/"]
-
-[tool.black] # automatically generated by pysen
-# pysen ignores and overwrites any modifications
+[tool.black]
 line-length = 88
-target-version = ["py37"]
+exclude = '/(__pycache__|__init__\.py|\.git|\.cache|\.mypy_cache|docs|build|dist|\.venv)/'
 
-[tool.isort] # automatically generated by pysen
-# pysen ignores and overwrites any modifications
+[tool.isort]
+profile = 'black'
 ensure_newline_before_comments = true
 force_grid_wrap = 0
 force_single_line = true
 include_trailing_comma = true
 known_first_party = ["pfhedge"]
+skip = [
+    ".cache",
+    ".git",
+    "__pycache__",
+    "docs",
+    "build",
+    "dist",
+    ".venv"]
 line_length = 88
 multi_line_output = 3
 use_parentheses = true
+
+[tool.mypy]
+disallow_untyped_defs = true
+ignore_missing_imports = true
+exclude = [
+    ".cache",
+    ".git",
+    "__pycache__",
+    "docs",
+    "build",
+    "dist",
+    ".venv"]
+
+[tool.flake8]
+ignore = "E203,E231,E501,W503"
+max-line-length = 88
+exclude = [
+    ".cache",
+    ".git",
+    "__pycache__",
+    "docs",
+    "build",
+    "dist",
+    ".venv",
+    "__init__.py",
+    "qfeval",
+    ]
+select = "B,B950,C,E,F,W"
diff --git a/setup.cfg b/setup.cfg
deleted file mode 100644
index 387ff191..00000000
--- a/setup.cfg
+++ /dev/null
@@ -1,30 +0,0 @@
-[flake8]
-ignore = E203,E231,E501,W503
-max-line-length = 88
-select = B,B950,C,E,F,W
-
-[mypy]
-# automatically generated by pysen
-# pysen ignores and overwrites any modifications
-check_untyped_defs = True
-disallow_any_decorated = False
-disallow_any_generics = False
-disallow_any_unimported = False
-disallow_incomplete_defs = True
-disallow_subclassing_any = True
-disallow_untyped_calls = False
-disallow_untyped_decorators = False
-disallow_untyped_defs = False
-ignore_errors = False
-ignore_missing_imports = True
-no_implicit_optional = True
-python_version = 3.7
-show_error_codes = True
-strict_equality = True
-strict_optional = True
-warn_redundant_casts = True
-warn_return_any = False
-warn_unreachable = True
-warn_unused_configs = True
-warn_unused_ignores = False
-
diff --git a/tests/features/test_features.py b/tests/features/test_features.py
index 5dda2af2..147a7a8f 100644
--- a/tests/features/test_features.py
+++ b/tests/features/test_features.py
@@ -27,13 +27,7 @@
 
 
 class _TestFeature:
-    def assert_same_dtype(
-        self,
-        feature,
-        derivative,
-        dtype,
-        device: str = "cpu",
-    ):
+    def assert_same_dtype(self, feature, derivative, dtype, device: str = "cpu"):
         derivative.to(dtype=dtype, device=device).simulate()
         f = feature.of(derivative)
         assert f.get(0).dtype == dtype
diff --git a/tests/instruments/derivative/test_european.py b/tests/instruments/derivative/test_european.py
index a6cfebbe..8e1df8f7 100644
--- a/tests/instruments/derivative/test_european.py
+++ b/tests/instruments/derivative/test_european.py
@@ -35,13 +35,7 @@ def test_payoff_gpu(self):
     @pytest.mark.parametrize("n_paths", [100])
     @pytest.mark.parametrize("init_spot", [1.0, 1.1, 0.9])
     def test_put_call_parity(
-        self,
-        volatility,
-        strike,
-        maturity,
-        n_paths,
-        init_spot,
-        device: str = "cpu",
+        self, volatility, strike, maturity, n_paths, init_spot, device: str = "cpu"
     ):
         stock = BrownianStock(volatility).to(device)
         co = EuropeanOption(stock, strike=strike, maturity=maturity, call=True).to(
diff --git a/tests/instruments/derivative/test_european_binary.py b/tests/instruments/derivative/test_european_binary.py
index 9089e102..5a6fb3b9 100644
--- a/tests/instruments/derivative/test_european_binary.py
+++ b/tests/instruments/derivative/test_european_binary.py
@@ -37,13 +37,7 @@ def test_payoff_gpu(self):
     @pytest.mark.parametrize("n_paths", [100])
     @pytest.mark.parametrize("init_spot", [1.0, 1.1, 0.9])
     def test_parity(
-        self,
-        volatility,
-        strike,
-        maturity,
-        n_paths,
-        init_spot,
-        device: str = "cpu",
+        self, volatility, strike, maturity, n_paths, init_spot, device: str = "cpu"
     ):
         """
         Test put-call parity.
diff --git a/tests/nn/modules/test_mlp.py b/tests/nn/modules/test_mlp.py
index f8fbe59f..ce5ffd4d 100644
--- a/tests/nn/modules/test_mlp.py
+++ b/tests/nn/modules/test_mlp.py
@@ -32,13 +32,7 @@ def test_n_layers_gpu(self, n_layers):
     @pytest.mark.parametrize("n_units", [2, 8, 32])
     @pytest.mark.parametrize("in_features", [1, 2])
     @pytest.mark.parametrize("out_features", [1, 2])
-    def test_n_units(
-        self,
-        n_units,
-        in_features,
-        out_features,
-        device: str = "cpu",
-    ):
+    def test_n_units(self, n_units, in_features, out_features, device: str = "cpu"):
         n_layers = 4
         m = MultiLayerPerceptron(
             n_layers=n_layers, n_units=n_units, out_features=out_features
@@ -61,12 +55,7 @@ def test_n_units_gpu(self, n_units, in_features, out_features):
 
     @pytest.mark.parametrize("activation", [torch.nn.ELU(), torch.nn.CELU()])
     @pytest.mark.parametrize("out_activation", [torch.nn.ELU(), torch.nn.CELU()])
-    def test_activation(
-        self,
-        activation,
-        out_activation,
-        device: str = "cpu",
-    ):
+    def test_activation(self, activation, out_activation, device: str = "cpu"):
         n_layers = 4
         m = MultiLayerPerceptron(
             n_layers=n_layers, activation=activation, out_activation=out_activation