{"action":"created","comment":{"url":"https://api.github.com/repos/binary-com/perl-VolSurface-Calibration-Equities/pulls/comments/42203175","id":42203175,"diff_hunk":"@@ -0,0 +1,637 @@\n+package VolSurface::Calibration::Equities;\n+\n+use strict;\n+use warnings;\n+\n+our $VERSION = '0.01';\n+\n+=head1 NAME\n+\n+VolSurface::Calibration::Equities\n+\n+=head1 DESCRIPTION\n+\n+This is a calibration model that is used in volatility surface calibration. This model checks whether a given volatility surface \n+conforms to some specific mathematical equations describing a volatility smile. If not, it will update the surface to fix it.\n+\n+=head1 VERSION\n+\n+Version 0.01\n+\n+=cut\n+\n+use Moose;\n+\n+use Date::Utility;\n+use List::MoreUtils qw(pairwise first_index indexes);\n+use List::Util qw(min max);\n+use Math::Trig qw(tanh);\n+use Try::Tiny;\n+use Format::Util::Numbers qw(roundnear);\n+\n+has surface => (\n+    is       => 'ro',\n+    isa      => 'HashRef',\n+    required => 1,\n+);\n+\n+=head2 term_by_day\n+\n+Get all the terms in a surface in ascending order.\n+\n+=cut\n+\n+has term_by_day => (\n+    is       => 'ro',\n+    isa      => 'ArrayRef',\n+    required => 1,\n+);\n+\n+=head2 parameterization\n+\n+The parameterized (and, thus, smoothed) version of this surface.\n+\n+=cut\n+\n+has parameterization => (\n+    is  => 'rw',\n+    isa => 'Maybe[HashRef]',\n+);\n+\n+=head2 smile_points\n+\n+The points across a smile.\n+\n+It can be delta points, moneyness points or any other points that we might have in the future.\n+\n+=cut\n+\n+has smile_points => (\n+    is       => 'ro',\n+    isa      => 'ArrayRef',\n+    required => 1,\n+);\n+\n+has _max_iteration => (\n+    is      => 'ro',\n+    isa     => 'Int',\n+    default => 500,\n+);\n+\n+has _tolerance_level => (\n+    is      => 'ro',\n+    isa     => 'Num',\n+    default => 1e-05,\n+);\n+\n+has _scale => (\n+    is      => 'ro',\n+    isa     => 'Num',\n+    default => 10,\n+);\n+\n+=head2 function_to_optimize\n+\n+The function that we want to optimize.\n+\n+=cut\n+\n+sub function_to_optimize {\n+    my ($self, $params) = @_;\n+\n+    # this number is returned when the optimization is heading the wrong path\n+    my $error = 1000;\n+\n+    my %params =\n+        pairwise { our $a => our $b } @{$self->calibration_param_names},\n+        @$params;\n+\n+    my @tenors = @{$self->term_by_day};\n+    my @kurtosis =\n+        map { $self->_calculate_kurtosis($_ / 365, \\%params) } @tenors;\n+    my @variance =\n+        map { $self->_calculate_variance($_ / 365, \\%params) } @tenors;\n+    my @skew = map { $self->_calculate_skew($_ / 365, \\%params) } @tenors;\n+\n+    foreach my $param_name (keys %params) {\n+        my $param_value = $params{$param_name};\n+        return $error\n+            if ($param_name =~ /wing(R|L)/i && max(abs($param_value)) > 20.0);\n+        return $error\n+            if ($param_name =~ /growth/i && max(abs($param_value)) > 5.0);\n+        return $error\n+            if ($param_name !~ /wing(R|L)/i\n+            && $param_name !~ /growth/i\n+            && max(abs($param_value)) > 2.0);\n+    }\n+\n+    return $error if (min(@variance) < 0);\n+    my @atmvols            = map { sqrt($_) } @variance;\n+    my $calibrated_surface = $self->get_calibrated_surface(\\%params);\n+    my $actual_surface     = $self->surface;\n+\n+    my $total = 0;\n+    foreach my $day (@{$self->term_by_day}) {\n+        my $sum       = 0;\n+        my $tenorvega = 0;\n+        my $atm_vol   = shift @atmvols;\n+        foreach my $point (@{$self->smile_points}) {\n+            my $atm_check      = log($point / 100) / $atm_vol / sqrt($day / 365);\n+            my $calibrated_vol = $calibrated_surface->{$day}->{$point};\n+            my $actual_vol     = $actual_surface->{$day}->{smile}->{$point};\n+            my $d1             = (log(100 / $point) + (0.5 * $actual_vol**2) * ($day / 365)) / ($actual_vol * ($day / 365)**0.5);\n+            my $nd1            = (1 / (2 * 3.1416)**0.5) * exp(-$d1 * $d1 / 2);\n+            my $vega           = $nd1 * ($day / 365)**0.5;\n+            $sum += $vega * abs($calibrated_vol - $actual_vol);\n+            $tenorvega += $vega;\n+        }\n+        $total += $sum / $tenorvega;\n+    }\n+\n+    return $total;\n+}\n+\n+=head2 calibration_param_names\n+\n+Calibration parameter names.\n+It is hard-coded here because it needs to be in this sequence\n+\n+=cut\n+\n+has calibration_param_names => (\n+    is      => 'ro',\n+    isa     => 'ArrayRef',\n+    default => sub {\n+        [qw(\n+                atmvolshort\n+                atmvol1year\n+                atmvolLong\n+                atmWingL\n+                atmWingR\n+                skewshort\n+                skew1year\n+                skewlong\n+                skewwingL\n+                skewwingR\n+                kurtosisshort\n+                kurtosislong\n+                kurtosisgrowth\n+                )];\n+    },\n+);\n+\n+=head2 default_initial_guess\n+\n+Initial guess for parameters. We need to start with something.\n+\n+=cut\n+\n+has default_initial_guess => (\n+    is      => 'ro',\n+    isa     => 'HashRef',\n+    default => sub {\n+        {\n+            atmvolshort    => 0.13,\n+            atmvol1year    => 0.19,\n+            atmvolLong     => 0.12,\n+            atmWingL       => 1.27,\n+            atmWingR       => 1.56,\n+            skewshort      => -0.27,\n+            skew1year      => -0.08,\n+            skewlong       => -0.03,\n+            skewwingL      => 2.01,\n+            skewwingR      => 2.03,\n+            kurtosisshort  => 0.001,\n+            kurtosislong   => 0.001,\n+            kurtosisgrowth => 0.001\n+        };\n+    },\n+);\n+\n+=head2 strike_ratio\n+\n+=cut\n+\n+has strike_ratio => (\n+    is      => 'ro',\n+    isa     => 'HashRef',\n+    default => sub {\n+        {\n+            lower  => 0.60,\n+            higher => 1.30,\n+        };\n+    },\n+);\n+\n+=head2 compute_parameterization\n+\n+    Returns a hash reference with new parameterization and calibration_error.\n+    These new parameters are calculated using the current parameterization values saved in cache if present,\n+    else it would use default parameterization.\n+\n+    my $new_values = $self->compute_parameterization;\n+    my $new_params = $new_values->{values};\n+    my $new_calibration_error = $new_values->{calibration_error};\n+\n+=cut\n+\n+sub compute_parameterization {\n+    my $self = shift;\n+\n+    my $opt_using_params_from_cache;\n+    if ($self->parameterization) {\n+        my $params_from_cache = $self->_get_params_from($self->parameterization->{values});\n+        $opt_using_params_from_cache = try { $self->_optimize($params_from_cache) };\n+    }\n+\n+    my $initial_params           = $self->_get_params_from($self->default_initial_guess);\n+    my $opt_using_initial_params = $self->_optimize($initial_params);\n+\n+    my $new_values;\n+    if ($opt_using_params_from_cache) {\n+        $new_values =\n+            ($opt_using_params_from_cache->{calibration_error} < $opt_using_initial_params->{calibration_error})\n+            ? $opt_using_params_from_cache\n+            : $opt_using_initial_params;\n+    } else {\n+        $new_values = $opt_using_initial_params;\n+    }\n+\n+    # we expect the params to be passed in the correct order\n+    my %calib_params =\n+        pairwise { $a => $b } @{$self->calibration_param_names},\n+        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