Federal Deposit Insurance Corporation
US Bank Failures
Introduction
The US Bank Failures dataset by the Federal Deposit Insurance Corporation (FDIC) tracks the failures of FDIC-insured banks, with the assets and deposits of each bank and how the FDIC resolved it. The data covers 4,117 bank failures, starts in April 1934, and is delivered on a daily frequency. This dataset is created by parsing the list of failed banks the FDIC publishes. The data does not include the FDIC's estimated cost of each failure.
For more information about the US Bank Failures dataset, including CLI commands and pricing, see the dataset listing.
About the Provider
The Federal Deposit Insurance Corporation is an independent agency created by Congress in 1933 to maintain stability and public confidence in the nation's financial system. The FDIC insures deposits, examines and supervises financial institutions for safety and soundness and consumer protection, and manages receiverships when banks fail.
Requesting Data
To add US Bank Failures data to your algorithm, call the AddDataadd_data method. Save a reference to the dataset Symbol so you can access the data later in your algorithm.
class FDICBankFailuresDataAlgorithm(QCAlgorithm):
def initialize(self) -> None:
self.set_start_date(2019, 1, 1)
self.set_end_date(2021, 3, 31)
self.set_cash(100000)
self._dataset_symbol = self.add_data(FDICBankFailures, FDIC.FAILURES).symbol public class FDICBankFailuresDataAlgorithm : QCAlgorithm
{
private Symbol _datasetSymbol;
public override void Initialize()
{
SetStartDate(2019, 1, 1);
SetEndDate(2021, 3, 31);
SetCash(100000);
_datasetSymbol = AddData<FDICBankFailures>(FDIC.Failures).Symbol;
}
}
Accessing Data
To get the current US Bank Failures data, index the current Slice with the dataset Symbol. Slice objects deliver unique events to your algorithm as they happen, but the Slice may not contain data for your dataset at every time step. To avoid issues, check if the Slice contains the data you want before you index it.
def on_data(self, slice: Slice) -> None:
failures = slice.get(FDICBankFailures).get(self._dataset_symbol)
if failures:
for failure in failures.data:
self.log(f"{failure.institution_name} ({failure.state}): assets {failure.total_assets}") public override void OnData(Slice slice)
{
if (slice.TryGet<FDICBankFailures>(_datasetSymbol, out var failures))
{
foreach (FDICBankFailure failure in failures.Data)
{
Log($"{failure.InstitutionName} ({failure.State}): assets {failure.TotalAssets}");
}
}
}
Historical Data
To get historical US Bank Failures data, call the Historyhistory method with the dataset Symbol. If there is no data in the period you request, the history result is empty.
history = self.history[FDICBankFailures](self._dataset_symbol, timedelta(days=730), Resolution.DAILY)
var history = History<FDICBankFailures>(_datasetSymbol, TimeSpan.FromDays(730), Resolution.Daily);
For more information about historical data, see History Requests.
Example Applications
The US Bank Failures dataset enables you to follow stress in the US banking system as it happens. Examples include the following strategies:
- Reducing exposure to bank stocks when failures cluster
- Comparing the assets of failed banks against the size of the sector
- Following the states and regions where banks fail
Classic Algorithm Example
The following example algorithm holds SPY and liquidates it for 30 days after an FDIC-insured bank fails.
from AlgorithmImports import *
class FDICBankFailuresDataAlgorithm(QCAlgorithm):
def initialize(self):
self.set_start_date(2019, 1, 1)
self.set_end_date(2021, 3, 31)
self.set_cash(100000)
self.equity = self.add_equity("SPY", Resolution.DAILY).symbol
self.dataset_symbol = self.add_data(FDICBankFailures, FDIC.FAILURES).symbol
self.last_failure = datetime.min
def on_data(self, slice):
failures = slice.get(FDICBankFailures).get(self.dataset_symbol)
if failures:
for failure in failures.data:
self.log(f"{failure.institution_name} ({failure.state}) failed with assets of {failure.total_assets}")
self.last_failure = self.time
# Liquidate SPY for 30 days after a bank fails.
if self.time - self.last_failure < timedelta(days=30):
self.liquidate(self.equity)
elif not self.portfolio.invested:
self.set_holdings(self.equity, 1) using System;
using QuantConnect;
using QuantConnect.Algorithm;
using QuantConnect.Data;
using QuantConnect.DataSource;
public class FDICBankFailuresDataAlgorithm : QCAlgorithm
{
private Symbol _equity, _datasetSymbol;
private DateTime _lastFailure = DateTime.MinValue;
public override void Initialize()
{
SetStartDate(2019, 1, 1);
SetEndDate(2021, 3, 31);
SetCash(100000);
_equity = AddEquity("SPY", Resolution.Daily).Symbol;
_datasetSymbol = AddData<FDICBankFailures>(FDIC.Failures).Symbol;
}
public override void OnData(Slice slice)
{
if (slice.TryGet<FDICBankFailures>(_datasetSymbol, out var failures))
{
foreach (FDICBankFailure failure in failures.Data)
{
Log($"{failure.InstitutionName} ({failure.State}) failed with assets of {failure.TotalAssets}");
}
_lastFailure = Time;
}
// Liquidate SPY for 30 days after a bank fails.
if (Time - _lastFailure < TimeSpan.FromDays(30))
{
Liquidate(_equity);
}
else if (!Portfolio.Invested)
{
SetHoldings(_equity, 1);
}
}
}
Framework Algorithm Example
The following example algorithm emits a flat insight for SPY when an FDIC-insured bank failed in the last 30 days. Otherwise, it emits an up insight.
from AlgorithmImports import *
class FDICBankFailuresFrameworkAlgorithm(QCAlgorithm):
def initialize(self):
self.set_start_date(2019, 1, 1)
self.set_end_date(2021, 3, 31)
self.set_cash(100000)
self.universe_settings.resolution = Resolution.DAILY
self.set_universe_selection(ManualUniverseSelectionModel(
[Symbol.create("SPY", SecurityType.EQUITY, Market.USA)]))
self.add_alpha(BankFailureAlphaModel(self))
self.set_portfolio_construction(EqualWeightingPortfolioConstructionModel())
self.set_execution(ImmediateExecutionModel())
class BankFailureAlphaModel(AlphaModel):
def __init__(self, algorithm):
self._dataset_symbol = algorithm.add_data(FDICBankFailures, FDIC.FAILURES).symbol
self._last_failure = datetime.min
self._symbols = set()
def update(self, algorithm, data):
if data.get(FDICBankFailures).get(self._dataset_symbol):
self._last_failure = algorithm.time
# Emit a flat insight within 30 days of a bank failure, otherwise an up insight.
failed_recently = algorithm.time - self._last_failure < timedelta(days=30)
direction = InsightDirection.FLAT if failed_recently else InsightDirection.UP
return [Insight.price(symbol, timedelta(days=1), direction) for symbol in self._symbols]
def on_securities_changed(self, algorithm, changes):
for security in changes.added_securities:
self._symbols.add(security.symbol)
for security in changes.removed_securities:
self._symbols.discard(security.symbol) using System;
using System.Collections.Generic;
using System.Linq;
using QuantConnect;
using QuantConnect.Algorithm;
using QuantConnect.Algorithm.Framework.Alphas;
using QuantConnect.Algorithm.Framework.Execution;
using QuantConnect.Algorithm.Framework.Portfolio;
using QuantConnect.Algorithm.Framework.Selection;
using QuantConnect.Data;
using QuantConnect.Data.UniverseSelection;
using QuantConnect.DataSource;
public class FDICBankFailuresFrameworkAlgorithm : QCAlgorithm
{
public override void Initialize()
{
SetStartDate(2019, 1, 1);
SetEndDate(2021, 3, 31);
SetCash(100000);
UniverseSettings.Resolution = Resolution.Daily;
SetUniverseSelection(new ManualUniverseSelectionModel(
QuantConnect.Symbol.Create("SPY", SecurityType.Equity, Market.USA)));
AddAlpha(new BankFailureAlphaModel(this));
SetPortfolioConstruction(new EqualWeightingPortfolioConstructionModel());
SetExecution(new ImmediateExecutionModel());
}
}
public class BankFailureAlphaModel : AlphaModel
{
private readonly Symbol _datasetSymbol;
private readonly HashSet<Symbol> _symbols = new();
private DateTime _lastFailure = DateTime.MinValue;
public BankFailureAlphaModel(QCAlgorithm algorithm)
{
_datasetSymbol = algorithm.AddData<FDICBankFailures>(FDIC.Failures).Symbol;
}
public override IEnumerable<Insight> Update(QCAlgorithm algorithm, Slice data)
{
if (data.ContainsKey(_datasetSymbol))
{
_lastFailure = algorithm.Time;
}
// Emit a flat insight within 30 days of a bank failure, otherwise an up insight.
var failedRecently = algorithm.Time - _lastFailure < TimeSpan.FromDays(30);
var direction = failedRecently ? InsightDirection.Flat : InsightDirection.Up;
return _symbols.Select(symbol => Insight.Price(symbol, TimeSpan.FromDays(1), direction)).ToList();
}
public override void OnSecuritiesChanged(QCAlgorithm algorithm, SecurityChanges changes)
{
foreach (var security in changes.AddedSecurities)
{
_symbols.Add(security.Symbol);
}
foreach (var security in changes.RemovedSecurities)
{
_symbols.Remove(security.Symbol);
}
}
}
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